feat: enhance agent orchestration, knowledge flow and UI refinements
This commit is contained in:
@@ -1,34 +0,0 @@
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# =============================================
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# Jarvis 后端服务配置
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# 复制此文件为 .env 后按需修改
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# =============================================
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# === 应用基础 ===
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DEBUG=false
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HOST=127.0.0.1
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PORT=3337
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SECRET_KEY=change-me-to-a-random-secret-key
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CORS_ORIGINS=["http://localhost:5173","http://localhost:3000"]
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# === 数据存储 ===
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DATABASE_URL=sqlite+aiosqlite:///./data/jarvis.db
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DATA_DIR=./data
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CHROMA_PERSIST_DIR=./data/chroma
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UPLOAD_DIR=./data/uploads
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MAX_UPLOAD_SIZE=52428800
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# Supported values: ch | en
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MINERU_LANGUAGE=ch
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# === JWT ===
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ACCESS_TOKEN_EXPIRE_MINUTES=1440
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# === 管理员账号 Bootstrap ===
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ADMIN=admin
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ADMIN_EMAIL=admin@example.com
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ADMIN_PASSWORD=
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ADMIN_FULL_NAME=Administrator
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# === 定时任务 ===
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SCHEDULER_ENABLED=true
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DAILY_PLAN_TIME=00:00
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FORUM_SCAN_INTERVAL_MINUTES=30
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@@ -1,397 +1,354 @@
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"""
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Jarvis LangGraph Agent 主图定义
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Jarvis LangGraph Agent 主图定义 - 优化重构版
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"""
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import json
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import logging
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import re
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from typing import Literal, Union, List, Any
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from langchain_core.messages import (
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BaseMessage,
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HumanMessage,
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AIMessage,
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SystemMessage,
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ToolMessage
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)
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from langgraph.graph import StateGraph, END
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from langchain_core.messages import HumanMessage, AIMessage, SystemMessage, BaseMessage
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from app.agents.state import AgentState, AgentRole
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from app.agents.prompts import (
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MASTER_SYSTEM_PROMPT,
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PLANNER_SYSTEM_PROMPT,
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SCHEDULE_PLANNER_SYSTEM_PROMPT,
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EXECUTOR_SYSTEM_PROMPT,
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LIBRARIAN_SYSTEM_PROMPT,
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ANALYST_SYSTEM_PROMPT,
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PLANNER_SCOPE_PROMPT,
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PLANNER_STEPS_PROMPT,
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EXECUTOR_TASKS_PROMPT,
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EXECUTOR_FORUM_PROMPT,
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LIBRARIAN_RETRIEVAL_PROMPT,
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LIBRARIAN_GRAPH_PROMPT,
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ANALYST_PROGRESS_PROMPT,
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ANALYST_INSIGHTS_PROMPT,
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JSON_ACTION_FALLBACK_PROMPT,
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)
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from app.agents.tools import ALL_TOOLS, SUB_COMMANDER_TOOLSETS
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from app.agents.tools.time_reasoning import normalize_tool_time_arguments
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from app.agents.skill_registry import build_skill_context
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from app.services.llm_service import get_llm
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from langchain_openai import ChatOpenAI
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from langchain_anthropic import ChatAnthropic
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from langchain_ollama import ChatOllama
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import httpx
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SUB_COMMANDER_PROMPTS = {
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"planner_scope": PLANNER_SCOPE_PROMPT,
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"planner_steps": PLANNER_STEPS_PROMPT,
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"executor_tasks": EXECUTOR_TASKS_PROMPT,
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"executor_forum": EXECUTOR_FORUM_PROMPT,
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"librarian_retrieval": LIBRARIAN_RETRIEVAL_PROMPT,
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"librarian_graph": LIBRARIAN_GRAPH_PROMPT,
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"analyst_progress": ANALYST_PROGRESS_PROMPT,
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"analyst_insights": ANALYST_INSIGHTS_PROMPT,
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}
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ROLE_SUB_COMMANDERS = {
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AgentRole.PLANNER: ["planner_scope", "planner_steps"],
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AgentRole.EXECUTOR: ["executor_tasks", "executor_forum"],
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AgentRole.LIBRARIAN: ["librarian_retrieval", "librarian_graph"],
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AgentRole.ANALYST: ["analyst_progress", "analyst_insights"],
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}
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ROLE_SKILL_CONTEXT = {
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AgentRole.PLANNER: "planner",
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AgentRole.EXECUTOR: "executor",
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AgentRole.LIBRARIAN: "librarian",
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AgentRole.ANALYST: "analyst",
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}
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def _create_llm_from_config(config: dict):
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"""根据用户模型配置创建 LLM 实例"""
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provider = config.get("provider", "openai")
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model = config.get("model", "")
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api_key = config.get("api_key", "")
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base_url = config.get("base_url", "")
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if provider == "openai" or provider == "deepseek" or provider == "custom":
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return ChatOpenAI(
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api_key=api_key,
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model=model,
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base_url=base_url or None,
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timeout=httpx.Timeout(60.0, connect=10.0),
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)
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elif provider == "claude":
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return ChatAnthropic(
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api_key=api_key,
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model=model,
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timeout=httpx.Timeout(60.0, connect=10.0),
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)
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elif provider == "ollama":
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return ChatOllama(
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base_url=base_url or "http://localhost:11434",
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model=model,
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timeout=httpx.Timeout(120.0, connect=10.0),
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)
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else:
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return ChatOpenAI(
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api_key=api_key,
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model=model,
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base_url=base_url or None,
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timeout=httpx.Timeout(60.0, connect=10.0),
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from app.services.llm_service import (
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get_llm,
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create_llm_from_config,
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resolve_provider_capabilities,
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default_provider_capabilities
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)
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from app.logging_utils import summarize_llm_config
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logger = logging.getLogger("jarvis.agent")
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# ===================== 工具辅助函数 =====================
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def _get_llm_for_state(state: AgentState):
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"""从 state 获取 LLM 实例，优先使用用户配置的模型"""
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"""获取配置好的 LLM 实例"""
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user_llm_config = state.get("user_llm_config")
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if user_llm_config:
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return _create_llm_from_config(user_llm_config)
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return get_llm()
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llm = create_llm_from_config(user_llm_config) if user_llm_config else get_llm()
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# 注入解析到的能力
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capabilities = getattr(llm, "_jarvis_provider_capabilities", None)
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if capabilities is None:
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capabilities = resolve_provider_capabilities(user_llm_config) if user_llm_config else default_provider_capabilities()
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state["provider_capabilities"] = {
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"provider": capabilities.provider,
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"supports_native_tools": capabilities.supports_native_tools,
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"preferred_tool_strategy": capabilities.preferred_tool_strategy,
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}
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return llm, capabilities
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async def _ainvoke(llm, messages: list[BaseMessage]):
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ainvoke = getattr(llm, "ainvoke", None)
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if callable(ainvoke):
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return await ainvoke(messages)
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return await llm.invoke(messages)
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def _filter_user_messages(messages: list[BaseMessage]) -> list[BaseMessage]:
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return [m for m in messages if m.type in ("human", "user")]
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async def _ainvoke_with_tools(llm, messages: list[BaseMessage], tools=None):
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toolset = tools if tools is not None else ALL_TOOLS
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bound_llm = llm.bind_tools(toolset)
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if hasattr(bound_llm, "ainvoke"):
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return await bound_llm.ainvoke(messages)
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return await bound_llm.invoke(messages)
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def _compile_graph(graph: StateGraph, callbacks: list | None = None):
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if callbacks:
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try:
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return graph.compile(callbacks=callbacks)
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except TypeError as exc:
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if "callbacks" not in str(exc):
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raise
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return graph.compile()
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def _msg_type(msg: BaseMessage) -> str:
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"""Get message type, handles both .type (new) and .role (old) attribute names."""
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return getattr(msg, "type", None) or getattr(msg, "role", "human")
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def _filter_user_messages(messages: list) -> list[BaseMessage]:
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return [m for m in messages if _msg_type(m) in ("human", "user")]
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def _normalize_user_text(text: str) -> str:
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return (text or "").strip().lower()
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def _is_simple_greeting(text: str) -> bool:
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normalized = _normalize_user_text(text)
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return normalized in {"你好", "您好", "早", "早上好", "在吗", "嗨", "hi", "hello"}
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def _is_identity_question(text: str) -> bool:
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normalized = _normalize_user_text(text)
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return normalized in {"你是谁", "你是誰"}
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def _is_capability_question(text: str) -> bool:
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normalized = _normalize_user_text(text)
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return normalized in {"你能做什么", "你可以做什么", "你会做什么"}
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def _choose_sub_commander(role: AgentRole, user_query: str) -> str:
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text = _normalize_user_text(user_query)
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if role == AgentRole.PLANNER:
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if any(keyword in text for keyword in ["步骤", "计划", "拆解", "排期", "优先级", "路线"]):
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return "planner_steps"
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return "planner_scope"
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def _get_role_tools(role: AgentRole) -> list:
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"""获取角色对应的所有可用工具集"""
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if role == AgentRole.SCHEDULE_PLANNER:
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# 合并分析和规划工具
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return list(set(SUB_COMMANDER_TOOLSETS["schedule_analysis"] + SUB_COMMANDER_TOOLSETS["schedule_planning"]))
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if role == AgentRole.EXECUTOR:
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if any(keyword in text for keyword in ["论坛", "帖子", "发帖", "指令", "discussion", "instruction"]):
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return "executor_forum"
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return "executor_tasks"
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return list(set(SUB_COMMANDER_TOOLSETS["executor_tasks"] + SUB_COMMANDER_TOOLSETS["executor_forum"]))
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if role == AgentRole.LIBRARIAN:
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if any(keyword in text for keyword in ["图谱", "关系", "构建", "沉淀", "节点", "graph"]):
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return "librarian_graph"
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return "librarian_retrieval"
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return list(set(SUB_COMMANDER_TOOLSETS["librarian_retrieval"] + SUB_COMMANDER_TOOLSETS["librarian_graph"]))
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if role == AgentRole.ANALYST:
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if any(keyword in text for keyword in ["趋势", "风险", "洞察", "建议", "机会", "insight"]):
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return "analyst_insights"
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return "analyst_progress"
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return ROLE_SUB_COMMANDERS[role][0]
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return list(set(SUB_COMMANDER_TOOLSETS["analyst_progress"] + SUB_COMMANDER_TOOLSETS["analyst_insights"]))
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return []
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def _record_sub_commander(state: AgentState, sub_commander: str, user_query: str):
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state["current_sub_commander"] = sub_commander
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state["active_sub_commanders"] = state.get("active_sub_commanders", []) + [sub_commander]
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state["sub_commander_trace"] = state.get("sub_commander_trace", []) + [{
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"agent": state.get("current_agent", AgentRole.MASTER).value,
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"sub_commander": sub_commander,
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"query": user_query,
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}]
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# ===================== 核心执行逻辑 (ReAct) =====================
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async def call_agent_llm(state: AgentState, role: AgentRole, system_prompt: str) -> dict:
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"""通用的 LLM 调用节点逻辑"""
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llm, capabilities = _get_llm_for_state(state)
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tools = _get_role_tools(role)
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def _build_system_messages(state: AgentState, system_prompt: str, role: AgentRole):
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system_msgs: list[BaseMessage] = [SystemMessage(content=system_prompt)]
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skill_ctx = build_skill_context(ROLE_SKILL_CONTEXT[role])
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# 构建消息序列
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messages = []
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# 1. 系统提示词
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messages.append(SystemMessage(content=system_prompt))
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# 2. 环境上下文 (时间、记忆等)
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if state.get("current_datetime_context"):
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messages.append(SystemMessage(content=f"当前时间上下文: {state['current_datetime_context']}"))
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if state.get("memory_context"):
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messages.append(SystemMessage(content=f"长期记忆上下文: {state['memory_context']}"))
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# 3. 技能增强
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role_skill_key = role.value.replace("agent_", "")
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skill_ctx = build_skill_context(role_skill_key)
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if skill_ctx:
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system_msgs.append(SystemMessage(content=skill_ctx))
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return system_msgs
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messages.append(SystemMessage(content=skill_ctx))
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# 4. 历史对话 (add_messages 已经处理好了)
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messages.extend(state["messages"])
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async def _run_sub_commander(
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state: AgentState,
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role: AgentRole,
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manager_prompt: str,
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user_query: str,
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*,
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use_tools: bool,
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summary_target: str | None = None,
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):
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llm = _get_llm_for_state(state)
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sub_commander = _choose_sub_commander(role, user_query)
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_record_sub_commander(state, sub_commander, user_query)
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# 绑定工具
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if tools and capabilities.supports_native_tools:
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llm_with_tools = llm.bind_tools(tools)
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else:
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llm_with_tools = llm
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if tools: # 如果有工具但不支持原生，注入 JSON Fallback 提示
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messages.append(SystemMessage(content=JSON_ACTION_FALLBACK_PROMPT))
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tool_names = [t.name for t in tools]
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messages.append(SystemMessage(content=f"本次可用工具列表: {', '.join(tool_names)}"))
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toolset = SUB_COMMANDER_TOOLSETS.get(sub_commander, [])
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system_msgs = _build_system_messages(state, manager_prompt, role)
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system_msgs.append(SystemMessage(content=f"本次应由子指挥官 `{sub_commander}` 接手。请严格按该角色职责输出。"))
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system_msgs.append(SystemMessage(content=SUB_COMMANDER_PROMPTS[sub_commander]))
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if use_tools and toolset:
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response = await _ainvoke_with_tools(
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llm,
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system_msgs + [HumanMessage(content=f"用户请求: {user_query}")],
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toolset,
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logger.info(
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f"agent_node_started",
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extra={
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"details": {
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"role": role.value,
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"message_count": len(messages),
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"tool_count": len(tools),
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"provider": capabilities.provider
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}
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}
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)
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tool_calls = getattr(response, "tool_calls", None) or []
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if tool_calls:
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results = []
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for tc in tool_calls:
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tool_name = tc.get("name")
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args = tc.get("args", {})
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for tool in toolset:
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if tool.name == tool_name:
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# 执行调用
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response = await llm_with_tools.ainvoke(messages)
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logger.info(
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f"agent_node_finished",
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extra={
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"details": {
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"role": role.value,
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"has_tool_calls": bool(getattr(response, "tool_calls", None)),
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"content_length": len(response.content) if response.content else 0
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}
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}
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)
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return {"messages": [response]}
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async def execute_tools_node(state: AgentState) -> dict:
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"""执行工具调用并返回 ToolMessage 的通用节点"""
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last_message = state["messages"][-1]
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if not hasattr(last_message, "tool_calls") or not last_message.tool_calls:
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return {"messages": []}
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tool_map = {t.name: t for t in ALL_TOOLS}
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tool_messages = []
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created_entities = []
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for tool_call in last_message.tool_calls:
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tool_name = tool_call["name"]
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tool_args = tool_call["args"]
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tool_id = tool_call.get("id")
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logger.info(
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f"tool_execution_started",
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extra={
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"details": {
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"tool_name": tool_name,
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"tool_args": tool_args,
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"tool_id": tool_id
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}
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}
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)
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try:
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result = tool.invoke(args)
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results.append(f"[{tool_name}] {result}")
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# 时间参数归一化
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normalized_args = normalize_tool_time_arguments(
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tool_name,
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tool_args,
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state.get("current_datetime_context")
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)
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tool = tool_map.get(tool_name)
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if not tool:
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result = f"Error: Tool {tool_name} not found."
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else:
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result = await tool.ainvoke(normalized_args) if hasattr(tool, "ainvoke") else tool.invoke(normalized_args)
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# 实体识别（用于业务追踪）
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if any(k in tool_name for k in ["create", "add", "new"]):
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created_entities.append({"tool": tool_name, "result": str(result)})
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status = "success"
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except Exception as e:
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results.append(f"[{tool_name}] 执行失败: {e}")
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break
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state["tool_calls"] = tool_calls
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state["last_tool_result"] = "\n".join(results)
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follow_up = await _ainvoke(
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llm,
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||||
[
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||||
SystemMessage(content=SUB_COMMANDER_PROMPTS[sub_commander]),
|
||||
HumanMessage(content=f"工具执行结果:\n{state['last_tool_result']}")
|
||||
]
|
||||
)
|
||||
state["final_response"] = follow_up.content
|
||||
else:
|
||||
state["final_response"] = response.content
|
||||
else:
|
||||
response = await _ainvoke(
|
||||
llm,
|
||||
system_msgs + [HumanMessage(content=f"用户请求: {user_query}")],
|
||||
)
|
||||
state["final_response"] = response.content
|
||||
logger.exception(f"tool_execution_failed: {tool_name}")
|
||||
result = f"Error executing tool {tool_name}: {str(e)}"
|
||||
status = "failed"
|
||||
|
||||
if summary_target:
|
||||
state[summary_target] = state.get("final_response", "")
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
tool_messages.append(ToolMessage(
|
||||
tool_call_id=tool_id,
|
||||
content=str(result),
|
||||
name=tool_name
|
||||
))
|
||||
|
||||
|
||||
# ===================== 节点定义 (async) =====================
|
||||
|
||||
async def master_node(state: AgentState) -> AgentState:
|
||||
"""主Agent节点: 理解用户意图，决定调用哪个子Agent"""
|
||||
messages: list[BaseMessage] = state["messages"]
|
||||
user_msgs = _filter_user_messages(messages)
|
||||
user_query = user_msgs[-1].content.strip() if user_msgs else ""
|
||||
|
||||
if _is_simple_greeting(user_query):
|
||||
state["final_response"] = "您好。我在。\n\n您把问题给我，我先帮您收束重点，再往下推。"
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
|
||||
if _is_identity_question(user_query):
|
||||
state["final_response"] = "我是 Jarvis。\n\n比起做一个泛泛的助手，我更像您的判断型协作伙伴：帮您看清问题、压缩路径、把事情往前推进。"
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
|
||||
if _is_capability_question(user_query):
|
||||
state["final_response"] = "主要做三件事。\n- 帮您判断：看问题本质、梳理取舍、给出方向\n- 帮您收束：把复杂内容理顺，把重点拎出来\n- 帮您推进：拆任务、定步骤、把下一步变清楚\n\n如果您现在有具体目标，我可以直接进入处理。"
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
|
||||
llm = _get_llm_for_state(state)
|
||||
system_msgs: list[BaseMessage] = [SystemMessage(content=MASTER_SYSTEM_PROMPT)]
|
||||
|
||||
memory_ctx = state.get("memory_context")
|
||||
if memory_ctx:
|
||||
system_msgs.append(
|
||||
SystemMessage(content=f"\n\n【记忆上下文】\n{memory_ctx}\n\n---\n")
|
||||
logger.info(
|
||||
f"tool_execution_finished",
|
||||
extra={
|
||||
"details": {
|
||||
"tool_name": tool_name,
|
||||
"status": status,
|
||||
"result_preview": str(result)[:200]
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
response: AIMessage = await _ainvoke(llm, system_msgs + messages)
|
||||
return {
|
||||
"messages": tool_messages,
|
||||
"created_entities": state.get("created_entities", []) + created_entities
|
||||
}
|
||||
|
||||
|
||||
# ===================== 各角色节点定义 =====================
|
||||
|
||||
async def master_node(state: AgentState) -> dict:
|
||||
"""主控节点：负责意图识别与初步分发"""
|
||||
user_messages = _filter_user_messages(state["messages"])
|
||||
if not user_messages:
|
||||
return {"final_response": "未收到有效输入。"}
|
||||
|
||||
query = user_messages[-1].content.strip()
|
||||
|
||||
# 快捷回复逻辑 (保留原有的人性化设计)
|
||||
if re.match(r"^(你好|早|在吗|嗨|hi|hello)", query.lower()):
|
||||
return {"final_response": "您好。我在。\n\n您把问题给我，我先帮您收束重点，再往下推。", "messages": [AIMessage(content="您好。我在。")]}
|
||||
|
||||
llm, capabilities = _get_llm_for_state(state)
|
||||
|
||||
# 路由判断：让 LLM 决定跳转到哪个角色，或者直接回答
|
||||
# 这里我们使用一个简洁的提示词让 LLM 输出角色名称或直接回答
|
||||
system_msg = SystemMessage(content=MASTER_SYSTEM_PROMPT + "\n\n请直接输出接下来该由哪个 Agent 接手(role_name)，如果直接回答，请正常输出。")
|
||||
|
||||
response = await llm.ainvoke([system_msg] + state["messages"])
|
||||
content = response.content.strip().lower()
|
||||
|
||||
if any(kw in content for kw in ["搜索", "查找", "知识", "检索"]):
|
||||
next_agent = AgentRole.LIBRARIAN
|
||||
elif any(kw in content for kw in ["计划", "安排", "拆解", "规划"]):
|
||||
next_agent = AgentRole.PLANNER
|
||||
elif any(kw in content for kw in ["执行", "做", "操作", "创建", "更新"]):
|
||||
next_agent = AgentRole.EXECUTOR
|
||||
elif any(kw in content for kw in ["分析", "报告", "统计", "总结"]):
|
||||
next_agent = AgentRole.ANALYST
|
||||
else:
|
||||
state["final_response"] = response.content
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
# 简单的角色映射识别
|
||||
roles = {r.value: r for r in AgentRole}
|
||||
target_role = None
|
||||
for r_val, r_enum in roles.items():
|
||||
if r_val in content and len(content) < 50: # 如果内容很短且包含角色名，视为路由
|
||||
target_role = r_enum
|
||||
break
|
||||
|
||||
state["current_agent"] = next_agent
|
||||
state["current_sub_commander"] = None
|
||||
state["active_agents"] = state.get("active_agents", [AgentRole.MASTER]) + [next_agent]
|
||||
state["should_respond"] = True
|
||||
return state
|
||||
if target_role and target_role != AgentRole.MASTER:
|
||||
logger.info(f"master_routing_decided: {target_role.value}")
|
||||
return {
|
||||
"current_agent": target_role.value,
|
||||
"agent_trace": state.get("agent_trace", []) + [target_role.value],
|
||||
"messages": [AIMessage(content=f"已分发至 {target_role.value} 处理。")]
|
||||
}
|
||||
|
||||
return {"final_response": response.content, "messages": [response]}
|
||||
|
||||
|
||||
async def planner_node(state: AgentState) -> AgentState:
|
||||
"""规划Agent节点: 制定计划，拆解任务步骤"""
|
||||
user_msgs = _filter_user_messages(state["messages"])
|
||||
user_query = user_msgs[-1].content if user_msgs else ""
|
||||
return await _run_sub_commander(state, AgentRole.PLANNER, PLANNER_SYSTEM_PROMPT, user_query, use_tools=False)
|
||||
async def planner_node(state: AgentState) -> dict:
|
||||
return await call_agent_llm(state, AgentRole.SCHEDULE_PLANNER, SCHEDULE_PLANNER_SYSTEM_PROMPT)
|
||||
|
||||
async def executor_node(state: AgentState) -> dict:
|
||||
return await call_agent_llm(state, AgentRole.EXECUTOR, EXECUTOR_SYSTEM_PROMPT)
|
||||
|
||||
async def librarian_node(state: AgentState) -> dict:
|
||||
return await call_agent_llm(state, AgentRole.LIBRARIAN, LIBRARIAN_SYSTEM_PROMPT)
|
||||
|
||||
async def analyst_node(state: AgentState) -> dict:
|
||||
return await call_agent_llm(state, AgentRole.ANALYST, ANALYST_SYSTEM_PROMPT)
|
||||
|
||||
|
||||
async def executor_node(state: AgentState) -> AgentState:
|
||||
"""执行Agent节点: 调用工具执行具体任务"""
|
||||
user_msgs = _filter_user_messages(state["messages"])
|
||||
user_query = user_msgs[-1].content if user_msgs else ""
|
||||
return await _run_sub_commander(state, AgentRole.EXECUTOR, EXECUTOR_SYSTEM_PROMPT, user_query, use_tools=True)
|
||||
# ===================== 路由逻辑 =====================
|
||||
|
||||
def route_after_agent(state: AgentState) -> Literal["tools", "__end__"]:
|
||||
"""判断 Agent 执行后是该走工具节点还是结束"""
|
||||
last_message = state["messages"][-1]
|
||||
if hasattr(last_message, "tool_calls") and last_message.tool_calls:
|
||||
return "tools"
|
||||
return END
|
||||
|
||||
async def librarian_node(state: AgentState) -> AgentState:
|
||||
"""知识管理员节点: 管理知识库和知识图谱"""
|
||||
user_msgs = _filter_user_messages(state["messages"])
|
||||
user_query = user_msgs[-1].content if user_msgs else ""
|
||||
return await _run_sub_commander(state, AgentRole.LIBRARIAN, LIBRARIAN_SYSTEM_PROMPT, user_query, use_tools=True, summary_target="knowledge_context")
|
||||
|
||||
|
||||
async def analyst_node(state: AgentState) -> AgentState:
|
||||
"""分析师节点: 分析工作数据，生成报告"""
|
||||
user_msgs = _filter_user_messages(state["messages"])
|
||||
user_query = user_msgs[-1].content if user_msgs else ""
|
||||
return await _run_sub_commander(state, AgentRole.ANALYST, ANALYST_SYSTEM_PROMPT, user_query, use_tools=True, summary_target="analysis_report")
|
||||
|
||||
|
||||
def route_agent(state: AgentState) -> str:
|
||||
"""路由函数: 决定下一个节点"""
|
||||
def route_master(state: AgentState) -> str:
|
||||
"""主控路由逻辑"""
|
||||
if state.get("final_response"):
|
||||
return END
|
||||
return state.get("current_agent", AgentRole.MASTER).value
|
||||
return state.get("current_agent", END)
|
||||
|
||||
|
||||
# ===================== 构建图 =====================
|
||||
# ===================== 图构建 =====================
|
||||
|
||||
def create_agent_graph(callbacks: list | None = None):
|
||||
graph = StateGraph(AgentState)
|
||||
workflow = StateGraph(AgentState)
|
||||
|
||||
graph.add_node(AgentRole.MASTER.value, master_node)
|
||||
graph.add_node(AgentRole.PLANNER.value, planner_node)
|
||||
graph.add_node(AgentRole.EXECUTOR.value, executor_node)
|
||||
graph.add_node(AgentRole.LIBRARIAN.value, librarian_node)
|
||||
graph.add_node(AgentRole.ANALYST.value, analyst_node)
|
||||
# 添加节点
|
||||
workflow.add_node(AgentRole.MASTER.value, master_node)
|
||||
workflow.add_node(AgentRole.SCHEDULE_PLANNER.value, planner_node)
|
||||
workflow.add_node(AgentRole.EXECUTOR.value, executor_node)
|
||||
workflow.add_node(AgentRole.LIBRARIAN.value, librarian_node)
|
||||
workflow.add_node(AgentRole.ANALYST.value, analyst_node)
|
||||
workflow.add_node("tools", execute_tools_node)
|
||||
|
||||
graph.set_entry_point(AgentRole.MASTER.value)
|
||||
# 设置入口
|
||||
workflow.set_entry_point(AgentRole.MASTER.value)
|
||||
|
||||
graph.add_conditional_edges(
|
||||
# 主控分发逻辑
|
||||
workflow.add_conditional_edges(
|
||||
AgentRole.MASTER.value,
|
||||
route_agent,
|
||||
route_master,
|
||||
{
|
||||
AgentRole.PLANNER.value: AgentRole.PLANNER.value,
|
||||
AgentRole.SCHEDULE_PLANNER.value: AgentRole.SCHEDULE_PLANNER.value,
|
||||
AgentRole.EXECUTOR.value: AgentRole.EXECUTOR.value,
|
||||
AgentRole.LIBRARIAN.value: AgentRole.LIBRARIAN.value,
|
||||
AgentRole.ANALYST.value: AgentRole.ANALYST.value,
|
||||
END: END,
|
||||
END: END
|
||||
}
|
||||
)
|
||||
|
||||
for role in [AgentRole.PLANNER, AgentRole.EXECUTOR, AgentRole.LIBRARIAN, AgentRole.ANALYST]:
|
||||
graph.add_edge(role.value, END)
|
||||
# 各角色节点的 ReAct 循环
|
||||
for role in [AgentRole.SCHEDULE_PLANNER, AgentRole.EXECUTOR, AgentRole.LIBRARIAN, AgentRole.ANALYST]:
|
||||
workflow.add_conditional_edges(
|
||||
role.value,
|
||||
route_after_agent,
|
||||
{
|
||||
"tools": "tools",
|
||||
END: END
|
||||
}
|
||||
)
|
||||
|
||||
return _compile_graph(graph, callbacks=callbacks)
|
||||
# 工具执行完后回到当前 Agent 角色继续处理
|
||||
workflow.add_conditional_edges(
|
||||
"tools",
|
||||
lambda s: s.get("current_agent", AgentRole.MASTER.value),
|
||||
{
|
||||
AgentRole.SCHEDULE_PLANNER.value: AgentRole.SCHEDULE_PLANNER.value,
|
||||
AgentRole.EXECUTOR.value: AgentRole.EXECUTOR.value,
|
||||
AgentRole.LIBRARIAN.value: AgentRole.LIBRARIAN.value,
|
||||
AgentRole.ANALYST.value: AgentRole.ANALYST.value,
|
||||
}
|
||||
)
|
||||
|
||||
# 编译
|
||||
if callbacks:
|
||||
return workflow.compile(callbacks=callbacks)
|
||||
return workflow.compile()
|
||||
|
||||
|
||||
_agent_graph = None
|
||||
|
||||
|
||||
def get_agent_graph(callbacks: list | None = None):
|
||||
"""
|
||||
获取编译好的 Agent 图（单例缓存）。
|
||||
|
||||
Callbacks 在首次编译时固定注入，后续调用忽略 callbacks 参数。
|
||||
如需变更 Callbacks（如修改 LANGCHAIN_PROJECT），需重启服务。
|
||||
|
||||
Args:
|
||||
callbacks: 可选的额外 Callbacks，会与全局 LangSmith Callbacks 合并
|
||||
"""
|
||||
global _agent_graph
|
||||
if _agent_graph is None:
|
||||
from app.config_tracing import get_langsmith_callbacks
|
||||
|
||||
@@ -89,14 +89,14 @@ MASTER_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
你是总控协调者，负责理解用户意图，并将任务分发给最合适的子Agent。
|
||||
|
||||
## 你的4个子Agent:
|
||||
1. **planner (规划Agent)**: 制定计划、拆解任务、安排优先级
|
||||
1. **schedule_planner (日程规划师)**: 分析当前任务、对话历史与论坛信号，给出近期安排建议
|
||||
2. **executor (执行Agent)**: 执行具体操作、创建任务、操作数据
|
||||
3. **librarian (知识管理员)**: 搜索知识库、管理知识图谱、回答关于用户知识的问题
|
||||
4. **analyst (分析师)**: 分析数据、生成报告、统计工作进度
|
||||
|
||||
## 判断规则:
|
||||
- 用户问知识、查找资料、检索文档 -> 分发给 librarian
|
||||
- 用户要计划、安排、拆解任务 -> 分发给 planner
|
||||
- 用户要安排今天/本周重点、询问接下来该做什么 -> 分发给 schedule_planner
|
||||
- 用户要执行操作、创建/更新内容、使用工具 -> 分发给 executor
|
||||
- 用户要分析、统计、生成报告 -> 分发给 analyst
|
||||
- 用户只是闲聊、问问题、不需要具体操作 -> 直接回答
|
||||
@@ -112,18 +112,19 @@ MASTER_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
"""
|
||||
|
||||
|
||||
PLANNER_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
SCHEDULE_PLANNER_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
|
||||
你是 Jarvis 的规划Agent，负责先判断问题该由哪位规划子指挥官接手。
|
||||
你是 Jarvis 的日程规划师，负责先判断问题该由哪位日程子指挥官接手。
|
||||
|
||||
## 你的两个子指挥官:
|
||||
1. **planner_scope (目标收束官)**: 负责澄清目标、边界、约束、缺失信息
|
||||
2. **planner_steps (步骤拆解官)**: 负责把目标拆成步骤、优先级与依赖关系
|
||||
1. **schedule_analysis (日程分析员)**: 负责分析对话历史、任务看板、论坛信号，识别优先级、冲突与压力点
|
||||
2. **schedule_planning (日程编排员)**: 负责把分析结果转成今日/近期日程安排，并在用户明确要求时直接创建 reminder/task/todo/goal
|
||||
|
||||
## 你的职责:
|
||||
- 判断当前请求更适合收束目标，还是拆解步骤
|
||||
- 在必要时收束子指挥官输出，面向用户给出清晰结果
|
||||
- 保持结果可推进，不空泛
|
||||
- 判断当前请求更适合先做日程分析，还是直接给出日程编排
|
||||
- 输出先结论，再给可执行安排
|
||||
- 保持建议具体、贴近当前上下文，不给空泛效率学建议
|
||||
- 当用户明确要求“新增/提醒/创建/安排并落库”时，允许子指挥官调用 schedule 工具直接执行
|
||||
"""
|
||||
|
||||
|
||||
@@ -132,11 +133,11 @@ EXECUTOR_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
你是 Jarvis 的执行Agent，负责先判断问题该由哪位执行子指挥官接手。
|
||||
|
||||
## 你的两个子指挥官:
|
||||
1. **executor_tasks (任务执行官)**: 只处理任务类工具调用
|
||||
1. **executor_tasks (任务执行官)**: 处理任务、待办、提醒、目标等执行型写入操作
|
||||
2. **executor_forum (论坛执行官)**: 只处理论坛/指令帖相关工具调用
|
||||
|
||||
## 你的职责:
|
||||
- 识别用户要推进的是任务操作还是论坛/指令操作
|
||||
- 识别用户要推进的是任务/日程操作还是论坛/指令操作
|
||||
- 把请求交给最合适的执行子指挥官
|
||||
- 汇总执行结果并给出下一步
|
||||
"""
|
||||
@@ -172,52 +173,68 @@ ANALYST_SYSTEM_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
"""
|
||||
|
||||
|
||||
PLANNER_SCOPE_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
SCHEDULE_ANALYSIS_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
|
||||
你是 planner 体系下的目标收束官，负责先把问题边界、目标、约束和成功标准说清楚。
|
||||
你是 schedule_planner 体系下的日程分析员，负责从对话历史、任务看板、论坛信号和当日日程数据中提取 scheduling 线索。
|
||||
|
||||
## 你的重点:
|
||||
- 收束问题定义
|
||||
- 明确目标与限制条件
|
||||
- 识别缺失信息
|
||||
- 帮用户建立可以继续规划的前提
|
||||
- 优先调用读取类工具了解当天/指定日期的任务、提醒、待办、目标
|
||||
- 识别当前最高优先级事项
|
||||
- 找出风险、冲突、依赖与可延期事项
|
||||
- 明确哪些信号来自 conversation、task board、schedule center、forum
|
||||
|
||||
## 响应要求:
|
||||
- 先给出你理解的目标
|
||||
- 再列出关键约束或缺口
|
||||
- 不要直接展开长步骤清单
|
||||
- 先给当前判断
|
||||
- 再列优先级、风险与冲突
|
||||
- 不直接展开长篇日程表
|
||||
- 只做分析，不创建任何记录
|
||||
- 如果涉及“今天/明天/后天/下周一下午”这类自然语言时间窗口，先调用 `resolve_time_expression` 把查询目标转换成明确日期
|
||||
"""
|
||||
|
||||
|
||||
PLANNER_STEPS_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
SCHEDULE_PLANNING_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
|
||||
你是 planner 体系下的步骤拆解官，负责把目标转成有顺序的执行路径。
|
||||
你是 schedule_planner 体系下的日程编排员，负责把当前重点转成近期可执行安排。
|
||||
|
||||
## 你的重点:
|
||||
- 拆解步骤
|
||||
- 标注优先级与依赖
|
||||
- 输出清晰的行动顺序
|
||||
- 先给结论
|
||||
- 再给今天/近期的时间安排建议
|
||||
- 最后给按顺序执行的 next actions
|
||||
- 当用户明确要求新增/提醒/创建/安排并真正落库时，调用 schedule 工具创建对应 reminder/task/todo/goal
|
||||
- 当用户给出“日期 + 事项/节点/交付/会议”等记录型表达时，也应视为落库意图，直接创建相应记录，不要反问
|
||||
- 解析“今天/明天/后天/本周/下周”或“3月29日”这类日期时，必须以系统提供的当前时间为准，并把工具参数转换成明确的 ISO 日期/时间字符串
|
||||
- 只要用户输入里包含自然语言时间，优先调用 `resolve_time_expression`，先拿到明确日期/时间，再调用 `create_reminder`、`create_schedule_task`、`create_goal`、`create_todo`
|
||||
|
||||
## 响应要求:
|
||||
- 用编号列表
|
||||
- 每步具体，不要空泛
|
||||
- 必要时标注先后关系
|
||||
- 用清晰列表表达
|
||||
- 建议必须具体、可执行、贴近当前工作
|
||||
- 避免空泛的自我管理建议
|
||||
- 如果只是规划，不要创建任何记录
|
||||
- 如果已创建记录，要明确说明创建了什么、时间如何解析
|
||||
"""
|
||||
|
||||
|
||||
EXECUTOR_TASKS_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
|
||||
你是 executor 体系下的任务执行官，只负责任务相关工具调用。
|
||||
你是 executor 体系下的任务执行官，负责处理任务、待办、提醒、目标等执行型工具调用。
|
||||
|
||||
## 允许使用的工具:
|
||||
- get_tasks
|
||||
- create_task
|
||||
- update_task_status
|
||||
- create_todo
|
||||
- create_schedule_task
|
||||
- create_reminder
|
||||
- create_goal
|
||||
- resolve_time_expression
|
||||
|
||||
## 要求:
|
||||
- 只处理任务类操作
|
||||
- 只处理任务/日程类操作
|
||||
- 遇到自然语言时间表达时，先调用 `resolve_time_expression`，再把解析后的明确日期/时间传给写入工具
|
||||
- 最终说明执行结果时，优先复用已经解析出的绝对时间，不要只重复“今天/明天”
|
||||
- 明确已执行动作、结果与下一步
|
||||
- 信息不足时直接指出缺口
|
||||
- 如果用户只是要分析建议，不要创建记录
|
||||
"""
|
||||
|
||||
|
||||
@@ -244,10 +261,14 @@ LIBRARIAN_RETRIEVAL_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
## 允许使用的工具:
|
||||
- search_knowledge
|
||||
- hybrid_search
|
||||
- web_search
|
||||
- get_knowledge_graph_context
|
||||
|
||||
## 要求:
|
||||
- 优先检索与综合证据
|
||||
- 私有/项目知识优先使用 `search_knowledge` 或 `hybrid_search`
|
||||
- 当用户明确要求联网、查询外部资料或查询最新信息时，使用 `web_search`
|
||||
- 回答时区分内部知识与外部网页结果
|
||||
- 证据不足时明确说明边界
|
||||
- 以回答问题为主，不主动做图谱构建
|
||||
"""
|
||||
@@ -293,9 +314,31 @@ ANALYST_INSIGHTS_PROMPT = f"""{JARVIS_PERSONA_PROMPT}
|
||||
- get_forum_posts
|
||||
- search_knowledge
|
||||
- hybrid_search
|
||||
- web_search
|
||||
|
||||
## 要求:
|
||||
- 先给结论与判断
|
||||
- 再说明依据与建议
|
||||
- 当需要外部/最新信息时，可使用 `web_search`
|
||||
- 重点输出趋势、风险、机会点
|
||||
"""
|
||||
|
||||
|
||||
JSON_ACTION_FALLBACK_PROMPT = """你当前运行在 JSON action fallback 模式。
|
||||
|
||||
你的输出必须满足以下规则：
|
||||
1. 只能输出一个 JSON 对象，不要输出 markdown、解释、前后缀文字。
|
||||
2. JSON 对象字段仅允许：
|
||||
- `mode`: `final` | `tool_call` | `clarification`
|
||||
- `tool_calls`: 数组；每项包含 `name`、`arguments`，可选 `reason`
|
||||
- `final_response`: 当无需工具时填写
|
||||
- `clarification_question`: 当信息不足时填写
|
||||
3. 如果需要调用工具，返回：
|
||||
- `{ "mode": "tool_call", "tool_calls": [...] }`
|
||||
4. 如果无需工具，直接返回：
|
||||
- `{ "mode": "final", "final_response": "..." }`
|
||||
5. 如果信息不足，不要猜测参数，返回：
|
||||
- `{ "mode": "clarification", "clarification_question": "..." }`
|
||||
6. 只能使用系统消息里明确列出的工具名。
|
||||
7. `arguments` 必须是 JSON 对象。
|
||||
"""
|
||||
|
||||
@@ -1,32 +1,19 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import TypedDict, Annotated
|
||||
from dataclasses import dataclass, field
|
||||
from typing import TypedDict, Annotated, Sequence
|
||||
from enum import Enum
|
||||
|
||||
from langchain_core.messages import HumanMessage
|
||||
from langchain_core.messages import BaseMessage
|
||||
from langgraph.graph.message import add_messages
|
||||
|
||||
|
||||
class AgentRole(str, Enum):
|
||||
MASTER = "master"
|
||||
PLANNER = "planner"
|
||||
SCHEDULE_PLANNER = "schedule_planner"
|
||||
EXECUTOR = "executor"
|
||||
LIBRARIAN = "librarian"
|
||||
ANALYST = "analyst"
|
||||
|
||||
|
||||
@dataclass
|
||||
class AgentInfo:
|
||||
name: str
|
||||
role: AgentRole
|
||||
description: str
|
||||
|
||||
|
||||
@dataclass
|
||||
class ToolCall:
|
||||
tool: str
|
||||
args: dict
|
||||
result: str | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class ConversationTurn:
|
||||
role: str # "user" | "assistant"
|
||||
@@ -35,60 +22,41 @@ class ConversationTurn:
|
||||
model: str | None = None
|
||||
|
||||
|
||||
def turn_to_message(turn: ConversationTurn) -> HumanMessage:
|
||||
return HumanMessage(content=turn.content)
|
||||
|
||||
|
||||
def message_to_turn(msg, agent: AgentRole | None = None) -> ConversationTurn:
|
||||
msg_type = getattr(msg, "type", None) or getattr(msg, "role", "assistant")
|
||||
return ConversationTurn(
|
||||
role="user" if msg_type in ("human", "user") else "assistant",
|
||||
content=msg.content,
|
||||
agent=agent,
|
||||
model=getattr(msg, "model", None),
|
||||
)
|
||||
|
||||
|
||||
class AgentState(TypedDict):
|
||||
messages: Annotated[list, None]
|
||||
# Core message history with add_messages reducer
|
||||
messages: Annotated[list[BaseMessage], add_messages]
|
||||
|
||||
# Session identifiers
|
||||
user_id: str
|
||||
conversation_id: str
|
||||
|
||||
# Agent routing
|
||||
current_agent: AgentRole
|
||||
active_agents: list[AgentRole]
|
||||
current_sub_commander: str | None
|
||||
active_sub_commanders: list[str]
|
||||
sub_commander_trace: list[dict]
|
||||
# Agent routing state
|
||||
current_agent: str | None
|
||||
next_step: str | None # For explicit graph routing
|
||||
|
||||
# Task tracking
|
||||
# Traceability
|
||||
agent_trace: list[str]
|
||||
|
||||
# Task & Entity Tracking (Business Logic)
|
||||
pending_tasks: list[dict]
|
||||
completed_tasks: list[dict]
|
||||
created_entities: list[dict]
|
||||
|
||||
# Tool usage
|
||||
tool_calls: list[ToolCall]
|
||||
last_tool_result: str | None
|
||||
|
||||
# Knowledge context
|
||||
# Context summaries (for long-term or cross-agent context)
|
||||
knowledge_context: str | None
|
||||
graph_context: str | None
|
||||
|
||||
# Planning
|
||||
plan: str | None
|
||||
plan_steps: list[dict]
|
||||
|
||||
# Analysis
|
||||
schedule_context_summary: str | None
|
||||
analysis_report: str | None
|
||||
|
||||
# Output control
|
||||
final_response: str | None
|
||||
should_respond: bool
|
||||
|
||||
# Memory context (injected at start of each conversation)
|
||||
# Memory & Environment
|
||||
memory_context: str | None
|
||||
current_datetime_context: str | None
|
||||
|
||||
# User LLM config (for using user-configured models)
|
||||
# Configuration
|
||||
user_llm_config: dict | None
|
||||
provider_capabilities: dict | None
|
||||
|
||||
|
||||
def initial_state(user_id: str, conversation_id: str) -> AgentState:
|
||||
@@ -96,22 +64,18 @@ def initial_state(user_id: str, conversation_id: str) -> AgentState:
|
||||
messages=[],
|
||||
user_id=user_id,
|
||||
conversation_id=conversation_id,
|
||||
current_agent=AgentRole.MASTER,
|
||||
active_agents=[AgentRole.MASTER],
|
||||
current_sub_commander=None,
|
||||
active_sub_commanders=[],
|
||||
sub_commander_trace=[],
|
||||
current_agent=AgentRole.MASTER.value,
|
||||
next_step=None,
|
||||
agent_trace=[AgentRole.MASTER.value],
|
||||
pending_tasks=[],
|
||||
completed_tasks=[],
|
||||
tool_calls=[],
|
||||
last_tool_result=None,
|
||||
created_entities=[],
|
||||
knowledge_context=None,
|
||||
graph_context=None,
|
||||
plan=None,
|
||||
plan_steps=[],
|
||||
schedule_context_summary=None,
|
||||
analysis_report=None,
|
||||
final_response=None,
|
||||
should_respond=True,
|
||||
memory_context=None,
|
||||
current_datetime_context=None,
|
||||
user_llm_config=None,
|
||||
provider_capabilities=None,
|
||||
)
|
||||
|
||||
@@ -1,9 +1,17 @@
|
||||
from app.agents.tools.search import (
|
||||
search_knowledge, get_knowledge_graph_context,
|
||||
build_knowledge_graph, hybrid_search,
|
||||
build_knowledge_graph, hybrid_search, web_search,
|
||||
)
|
||||
from app.agents.tools.task import get_tasks, create_task, update_task_status
|
||||
from app.agents.tools.forum import get_forum_posts, create_forum_post, scan_forum_for_instructions
|
||||
from app.agents.tools.schedule import (
|
||||
get_schedule_day,
|
||||
create_todo,
|
||||
create_schedule_task,
|
||||
create_reminder,
|
||||
create_goal,
|
||||
)
|
||||
from app.agents.tools.time_reasoning import resolve_time_expression
|
||||
|
||||
TASK_TOOLS = [
|
||||
get_tasks,
|
||||
@@ -11,6 +19,19 @@ TASK_TOOLS = [
|
||||
update_task_status,
|
||||
]
|
||||
|
||||
SCHEDULE_READ_TOOLS = [
|
||||
get_schedule_day,
|
||||
get_tasks,
|
||||
resolve_time_expression,
|
||||
]
|
||||
|
||||
SCHEDULE_WRITE_TOOLS = [
|
||||
create_todo,
|
||||
create_schedule_task,
|
||||
create_reminder,
|
||||
create_goal,
|
||||
]
|
||||
|
||||
FORUM_TOOLS = [
|
||||
get_forum_posts,
|
||||
create_forum_post,
|
||||
@@ -20,6 +41,7 @@ FORUM_TOOLS = [
|
||||
KNOWLEDGE_RETRIEVAL_TOOLS = [
|
||||
search_knowledge,
|
||||
hybrid_search,
|
||||
web_search,
|
||||
get_knowledge_graph_context,
|
||||
]
|
||||
|
||||
@@ -39,19 +61,22 @@ ANALYST_INSIGHT_TOOLS = [
|
||||
get_forum_posts,
|
||||
search_knowledge,
|
||||
hybrid_search,
|
||||
web_search,
|
||||
]
|
||||
|
||||
ALL_TOOLS = [
|
||||
*KNOWLEDGE_RETRIEVAL_TOOLS,
|
||||
build_knowledge_graph,
|
||||
*TASK_TOOLS,
|
||||
*SCHEDULE_READ_TOOLS,
|
||||
*SCHEDULE_WRITE_TOOLS,
|
||||
*FORUM_TOOLS,
|
||||
]
|
||||
|
||||
SUB_COMMANDER_TOOLSETS = {
|
||||
"planner_scope": [],
|
||||
"planner_steps": [],
|
||||
"executor_tasks": TASK_TOOLS,
|
||||
"schedule_analysis": SCHEDULE_READ_TOOLS,
|
||||
"schedule_planning": [*SCHEDULE_READ_TOOLS, *SCHEDULE_WRITE_TOOLS],
|
||||
"executor_tasks": [*TASK_TOOLS, resolve_time_expression, *SCHEDULE_WRITE_TOOLS],
|
||||
"executor_forum": FORUM_TOOLS,
|
||||
"librarian_retrieval": KNOWLEDGE_RETRIEVAL_TOOLS,
|
||||
"librarian_graph": KNOWLEDGE_GRAPH_TOOLS,
|
||||
|
||||
@@ -6,15 +6,17 @@ from app.models.forum import ForumPost, ForumReply
|
||||
from app.agents.context import get_current_user
|
||||
from sqlalchemy import select
|
||||
import asyncio
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
_executor = ThreadPoolExecutor(max_workers=4)
|
||||
|
||||
|
||||
def _run_async(coro, timeout: int = 30):
|
||||
try:
|
||||
loop = asyncio.get_running_loop()
|
||||
future = loop.run_in_executor(__import__("concurrent.futures").ThreadPoolExecutor(), lambda: asyncio.run(coro))
|
||||
return future.result(timeout=timeout)
|
||||
asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
return asyncio.run(coro)
|
||||
return _executor.submit(asyncio.run, coro).result(timeout=timeout)
|
||||
|
||||
|
||||
@tool
|
||||
|
||||
308
backend/app/agents/tools/schedule.py
Normal file
308
backend/app/agents/tools/schedule.py
Normal file
@@ -0,0 +1,308 @@
|
||||
"""Agent 工具集 - 日程相关"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import date, datetime
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
from langchain_core.tools import tool
|
||||
from sqlalchemy import select
|
||||
|
||||
from app.agents.context import get_current_user
|
||||
from app.database import async_session
|
||||
from app.models.goal import Goal, GoalStatus
|
||||
from app.models.reminder import Reminder
|
||||
from app.models.task import Task, TaskPriority, TaskStatus
|
||||
from app.models.todo import DailyTodo, TodoSource
|
||||
|
||||
_executor = ThreadPoolExecutor(max_workers=4)
|
||||
|
||||
|
||||
def _run_async(coro, timeout: int = 30):
|
||||
try:
|
||||
asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
return asyncio.run(coro)
|
||||
return _executor.submit(asyncio.run, coro).result(timeout=timeout)
|
||||
|
||||
|
||||
def _parse_date(value: str | None) -> date:
|
||||
if not value:
|
||||
return date.today()
|
||||
return date.fromisoformat(value)
|
||||
|
||||
|
||||
def _parse_datetime(value: str) -> datetime:
|
||||
normalized = value.strip().replace("Z", "+00:00")
|
||||
return datetime.fromisoformat(normalized)
|
||||
|
||||
|
||||
def _parse_datetime_with_timezone(value: str, time_zone: str | None) -> datetime:
|
||||
"""Parse an ISO datetime and return a tz-naive datetime in the intended local time.
|
||||
|
||||
- If value includes an offset/Z, it will be converted to `time_zone` when provided.
|
||||
- If value is naive and `time_zone` is provided, it is interpreted in that zone.
|
||||
"""
|
||||
parsed = _parse_datetime(value)
|
||||
tz = (time_zone or "").strip()
|
||||
if parsed.tzinfo is None:
|
||||
if tz:
|
||||
parsed = parsed.replace(tzinfo=ZoneInfo(tz))
|
||||
return parsed.replace(tzinfo=None)
|
||||
|
||||
if tz:
|
||||
parsed = parsed.astimezone(ZoneInfo(tz))
|
||||
return parsed.replace(tzinfo=None)
|
||||
|
||||
|
||||
def _normalize_title(title: str | None, content: str | None) -> str:
|
||||
resolved = (title or content or "").strip()
|
||||
if not resolved:
|
||||
raise ValueError("title 不能为空")
|
||||
return resolved
|
||||
|
||||
|
||||
def _normalize_schedule_due_date(due_date: str | None, date_value: str | None) -> str | None:
|
||||
resolved = (due_date or date_value or "").strip()
|
||||
if not resolved:
|
||||
return None
|
||||
if "T" in resolved:
|
||||
return resolved
|
||||
return f"{resolved}T09:00:00"
|
||||
|
||||
|
||||
def _format_summary(target_date: date, todos: list[DailyTodo], tasks: list[Task], reminders: list[Reminder], goals: list[Goal]) -> str:
|
||||
lines = [f"日期: {target_date.isoformat()}"]
|
||||
|
||||
if todos:
|
||||
lines.append("待办:")
|
||||
lines.extend(f"- {item.title} | 完成:{'是' if item.is_completed else '否'}" for item in todos)
|
||||
else:
|
||||
lines.append("待办: 无")
|
||||
|
||||
if tasks:
|
||||
lines.append("任务:")
|
||||
lines.extend(
|
||||
f"- {item.title} | 状态:{item.status.value if hasattr(item.status, 'value') else item.status} | 优先级:{item.priority.value if hasattr(item.priority, 'value') else item.priority} | 截止:{item.due_date.isoformat() if item.due_date else '无'}"
|
||||
for item in tasks
|
||||
)
|
||||
else:
|
||||
lines.append("任务: 无")
|
||||
|
||||
if reminders:
|
||||
lines.append("提醒:")
|
||||
lines.extend(f"- {item.title} | 时间:{item.reminder_at.isoformat()}" for item in reminders)
|
||||
else:
|
||||
lines.append("提醒: 无")
|
||||
|
||||
if goals:
|
||||
lines.append("目标:")
|
||||
lines.extend(
|
||||
f"- {item.title} | 状态:{item.status.value if hasattr(item.status, 'value') else item.status}"
|
||||
for item in goals
|
||||
)
|
||||
else:
|
||||
lines.append("目标: 无")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
@tool
|
||||
def get_schedule_day(target_date: str | None = None) -> str:
|
||||
"""获取指定日期的 todo/task/reminder/goal 聚合信息。target_date 格式 YYYY-MM-DD，默认今天。"""
|
||||
uid = get_current_user()
|
||||
parsed_date = _parse_date(target_date)
|
||||
date_key = parsed_date.isoformat()
|
||||
start_dt = datetime.combine(parsed_date, datetime.min.time())
|
||||
end_dt = datetime.combine(parsed_date, datetime.max.time())
|
||||
|
||||
async def _get():
|
||||
async with async_session() as db:
|
||||
todos = (
|
||||
await db.execute(
|
||||
select(DailyTodo)
|
||||
.where(DailyTodo.user_id == uid, DailyTodo.todo_date == date_key)
|
||||
.order_by(DailyTodo.created_at.desc())
|
||||
)
|
||||
).scalars().all()
|
||||
tasks = (
|
||||
await db.execute(
|
||||
select(Task)
|
||||
.where(
|
||||
Task.user_id == uid,
|
||||
Task.due_date.is_not(None),
|
||||
Task.due_date >= start_dt,
|
||||
Task.due_date <= end_dt,
|
||||
)
|
||||
.order_by(Task.created_at.desc())
|
||||
)
|
||||
).scalars().all()
|
||||
reminders = (
|
||||
await db.execute(
|
||||
select(Reminder)
|
||||
.where(
|
||||
Reminder.user_id == uid,
|
||||
Reminder.reminder_at >= start_dt,
|
||||
Reminder.reminder_at <= end_dt,
|
||||
)
|
||||
.order_by(Reminder.reminder_at.asc(), Reminder.created_at.asc())
|
||||
)
|
||||
).scalars().all()
|
||||
goals = (
|
||||
await db.execute(
|
||||
select(Goal)
|
||||
.where(Goal.user_id == uid, Goal.goal_date == date_key)
|
||||
.order_by(Goal.created_at.desc())
|
||||
)
|
||||
).scalars().all()
|
||||
return _format_summary(parsed_date, todos, tasks, reminders, goals)
|
||||
|
||||
try:
|
||||
return _run_async(_get())
|
||||
except Exception as exc:
|
||||
return f"获取日程失败: {exc}"
|
||||
|
||||
|
||||
@tool
|
||||
def create_todo(title: str, todo_date: str | None = None) -> str:
|
||||
"""创建指定日期的待办。todo_date 格式 YYYY-MM-DD，默认今天。"""
|
||||
uid = get_current_user()
|
||||
parsed_date = _parse_date(todo_date)
|
||||
|
||||
async def _create():
|
||||
async with async_session() as db:
|
||||
todo = DailyTodo(
|
||||
user_id=uid,
|
||||
title=title,
|
||||
source=TodoSource.AI_CHAT,
|
||||
todo_date=parsed_date.isoformat(),
|
||||
)
|
||||
db.add(todo)
|
||||
await db.commit()
|
||||
await db.refresh(todo)
|
||||
return f"TODO创建成功: [{todo.id[:8]}] {todo.title} @ {todo.todo_date}"
|
||||
|
||||
try:
|
||||
return _run_async(_create())
|
||||
except Exception as exc:
|
||||
return f"创建TODO失败: {exc}"
|
||||
|
||||
|
||||
@tool
|
||||
def create_schedule_task(
|
||||
title: str = "",
|
||||
description: str = "",
|
||||
priority: str = "medium",
|
||||
due_date: str | None = None,
|
||||
content: str = "",
|
||||
date: str | None = None,
|
||||
) -> str:
|
||||
"""创建任务。priority 支持 low/medium/high/urgent；due_date 使用 ISO datetime。兼容 content/date 别名。"""
|
||||
uid = get_current_user()
|
||||
resolved_title = _normalize_title(title, content)
|
||||
resolved_due_date = _normalize_schedule_due_date(due_date, date)
|
||||
|
||||
async def _create():
|
||||
async with async_session() as db:
|
||||
task = Task(
|
||||
user_id=uid,
|
||||
title=resolved_title,
|
||||
description=description or content or None,
|
||||
priority=TaskPriority(priority),
|
||||
due_date=_parse_datetime(resolved_due_date) if resolved_due_date else None,
|
||||
status=TaskStatus.TODO,
|
||||
)
|
||||
db.add(task)
|
||||
await db.commit()
|
||||
await db.refresh(task)
|
||||
due_label = task.due_date.isoformat() if task.due_date else "无截止时间"
|
||||
return f"任务创建成功: [{task.id[:8]}] {task.title} | 优先级:{task.priority.value} | 截止:{due_label}"
|
||||
|
||||
try:
|
||||
return _run_async(_create())
|
||||
except Exception as exc:
|
||||
return f"创建任务失败: {exc}"
|
||||
|
||||
|
||||
@tool
|
||||
def create_reminder(
|
||||
title: str = "",
|
||||
reminder_at: str | None = None,
|
||||
note: str = "",
|
||||
description: str = "",
|
||||
datetime: str = "",
|
||||
at: str = "",
|
||||
remind_at: str = "",
|
||||
content: str = "",
|
||||
time_zone: str = "",
|
||||
timezone: str = "",
|
||||
time: str = "",
|
||||
) -> str:
|
||||
"""创建提醒。reminder_at 使用 ISO datetime。兼容 description/datetime/at/remind_at/time_zone 别名。"""
|
||||
uid = get_current_user()
|
||||
|
||||
try:
|
||||
resolved_title = (title or content or "").strip()
|
||||
if not resolved_title:
|
||||
raise ValueError("title 不能为空")
|
||||
|
||||
resolved_at = ((reminder_at or datetime or at or remind_at or time or "").strip())
|
||||
if not resolved_at:
|
||||
raise ValueError("reminder_at 不能为空")
|
||||
|
||||
resolved_note = (note or description or "").strip()
|
||||
|
||||
async def _create():
|
||||
async with async_session() as db:
|
||||
tz = (time_zone or timezone or "").strip()
|
||||
reminder = Reminder(
|
||||
user_id=uid,
|
||||
title=resolved_title,
|
||||
note=resolved_note or None,
|
||||
reminder_at=_parse_datetime_with_timezone(resolved_at, tz),
|
||||
)
|
||||
db.add(reminder)
|
||||
await db.commit()
|
||||
await db.refresh(reminder)
|
||||
return f"提醒创建成功: [{reminder.id[:8]}] {reminder.title} @ {reminder.reminder_at.isoformat()}"
|
||||
|
||||
return _run_async(_create())
|
||||
except Exception as exc:
|
||||
return f"创建提醒失败: {exc}"
|
||||
|
||||
|
||||
@tool
|
||||
def create_goal(title: str, goal_date: str | None = None, note: str = "", status: str = "active") -> str:
|
||||
"""创建指定日期目标。goal_date 格式 YYYY-MM-DD，默认今天；status 支持 active/done/archived。"""
|
||||
uid = get_current_user()
|
||||
parsed_date = _parse_date(goal_date)
|
||||
|
||||
async def _create():
|
||||
async with async_session() as db:
|
||||
goal = Goal(
|
||||
user_id=uid,
|
||||
title=title,
|
||||
note=note or None,
|
||||
goal_date=parsed_date.isoformat(),
|
||||
status=GoalStatus(status),
|
||||
)
|
||||
db.add(goal)
|
||||
await db.commit()
|
||||
await db.refresh(goal)
|
||||
return f"目标创建成功: [{goal.id[:8]}] {goal.title} @ {goal.goal_date}"
|
||||
|
||||
try:
|
||||
return _run_async(_create())
|
||||
except Exception as exc:
|
||||
return f"创建目标失败: {exc}"
|
||||
|
||||
|
||||
__all__ = [
|
||||
"get_schedule_day",
|
||||
"create_todo",
|
||||
"create_schedule_task",
|
||||
"create_reminder",
|
||||
"create_goal",
|
||||
]
|
||||
@@ -5,12 +5,14 @@ Agent 工具集 - 知识库 & 图谱相关
|
||||
由于 LangChain 工具系统是同步的，内部用 run_in_executor 处理 async 逻辑。
|
||||
"""
|
||||
|
||||
from langchain_core.tools import tool
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from app.database import async_session
|
||||
from app.agents.context import get_current_user
|
||||
import asyncio
|
||||
|
||||
from langchain_core.tools import tool
|
||||
|
||||
from app.agents.context import get_current_user
|
||||
from app.database import async_session
|
||||
|
||||
_executor = ThreadPoolExecutor(max_workers=4)
|
||||
|
||||
|
||||
@@ -151,9 +153,56 @@ def hybrid_search(query: str, top_k: int = 5) -> str:
|
||||
return f"混合搜索失败: {str(e)}"
|
||||
|
||||
|
||||
@tool
|
||||
def web_search(query: str, top_k: int = 5) -> str:
|
||||
"""
|
||||
通过 SearxNG 搜索外部网页信息，返回标题、链接和摘要。
|
||||
|
||||
Args:
|
||||
query: 搜索关键词
|
||||
top_k: 返回结果数量，默认 5 条
|
||||
|
||||
Returns:
|
||||
适合模型综合的网页结果文本
|
||||
"""
|
||||
from app.services.web_search_service import (
|
||||
WebSearchConfigurationError,
|
||||
WebSearchRequestError,
|
||||
WebSearchService,
|
||||
)
|
||||
|
||||
async def _search():
|
||||
service = WebSearchService()
|
||||
results = await service.search(query, limit=top_k)
|
||||
if not results:
|
||||
return "未找到相关网页结果。"
|
||||
|
||||
texts = []
|
||||
for index, result in enumerate(results, 1):
|
||||
source = f"\n来源: {result.source}" if result.source else ""
|
||||
published_at = f"\n时间: {result.published_at}" if result.published_at else ""
|
||||
snippet = result.snippet or "(无摘要)"
|
||||
texts.append(
|
||||
f"[{index}] {result.title}\n"
|
||||
f"链接: {result.url}{source}{published_at}\n"
|
||||
f"摘要: {snippet}"
|
||||
)
|
||||
return "\n\n---\n\n".join(texts)
|
||||
|
||||
try:
|
||||
return _run_async(_search(), timeout=30)
|
||||
except WebSearchConfigurationError as exc:
|
||||
return f"网页搜索不可用: {exc}"
|
||||
except WebSearchRequestError as exc:
|
||||
return f"网页搜索失败: {exc}"
|
||||
except Exception as exc:
|
||||
return f"网页搜索失败: {exc}"
|
||||
|
||||
|
||||
__all__ = [
|
||||
"search_knowledge",
|
||||
"get_knowledge_graph_context",
|
||||
"build_knowledge_graph",
|
||||
"hybrid_search",
|
||||
"web_search",
|
||||
]
|
||||
|
||||
@@ -1,22 +1,85 @@
|
||||
"""Agent 工具集 - 任务相关"""
|
||||
|
||||
from langchain_core.tools import tool
|
||||
from app.database import async_session
|
||||
from app.models.task import Task
|
||||
from app.agents.context import get_current_user
|
||||
from sqlalchemy import select
|
||||
import asyncio
|
||||
from datetime import UTC, datetime
|
||||
|
||||
_executor = None
|
||||
from app.models.base import utc_now
|
||||
|
||||
from langchain_core.tools import tool
|
||||
from sqlalchemy import select
|
||||
|
||||
from app.agents.context import get_current_user
|
||||
from app.database import async_session
|
||||
from app.models.task import Task, TaskPriority, TaskStatus
|
||||
|
||||
import asyncio
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
_executor = ThreadPoolExecutor(max_workers=4)
|
||||
|
||||
|
||||
def _run_async(coro, timeout: int = 30):
|
||||
try:
|
||||
loop = asyncio.get_running_loop()
|
||||
future = loop.run_in_executor(_executor or __import__("concurrent.futures").ThreadPoolExecutor(), lambda: asyncio.run(coro))
|
||||
return future.result(timeout=timeout)
|
||||
asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
return asyncio.run(coro)
|
||||
return _executor.submit(asyncio.run, coro).result(timeout=timeout)
|
||||
|
||||
|
||||
def _normalize_title(title: str | None, content: str | None) -> str:
|
||||
resolved = (title or content or "").strip()
|
||||
if not resolved:
|
||||
raise ValueError("title 不能为空")
|
||||
return resolved
|
||||
|
||||
|
||||
def _normalize_due_date(due_date: str | None, date_value: str | None) -> str | None:
|
||||
resolved = (due_date or date_value or "").strip()
|
||||
return resolved or None
|
||||
|
||||
|
||||
def _parse_due_date(value: str | None) -> datetime | None:
|
||||
if not value:
|
||||
return None
|
||||
normalized = value.strip()
|
||||
if not normalized:
|
||||
return None
|
||||
if "T" not in normalized:
|
||||
normalized = f"{normalized}T00:00:00"
|
||||
parsed = datetime.fromisoformat(normalized.replace("Z", "+00:00"))
|
||||
if parsed.tzinfo is not None:
|
||||
return parsed.astimezone(UTC).replace(tzinfo=None)
|
||||
return parsed
|
||||
|
||||
|
||||
def _normalize_priority(priority: int | str | None) -> TaskPriority:
|
||||
if priority is None or priority == "":
|
||||
return TaskPriority.MEDIUM
|
||||
if isinstance(priority, TaskPriority):
|
||||
return priority
|
||||
if isinstance(priority, int):
|
||||
return {
|
||||
1: TaskPriority.LOW,
|
||||
2: TaskPriority.MEDIUM,
|
||||
3: TaskPriority.HIGH,
|
||||
4: TaskPriority.URGENT,
|
||||
}.get(priority, TaskPriority.MEDIUM)
|
||||
normalized = str(priority).strip().lower()
|
||||
if not normalized:
|
||||
return TaskPriority.MEDIUM
|
||||
return TaskPriority(normalized)
|
||||
|
||||
|
||||
def _normalize_status(status: str) -> TaskStatus:
|
||||
normalized = status.strip().lower()
|
||||
return TaskStatus(normalized)
|
||||
|
||||
|
||||
def _format_status(value: TaskStatus | str) -> str:
|
||||
return value.value if hasattr(value, "value") else str(value)
|
||||
|
||||
|
||||
def _format_priority(value: TaskPriority | str) -> str:
|
||||
return value.value if hasattr(value, "value") else str(value)
|
||||
|
||||
|
||||
@tool
|
||||
@@ -25,7 +88,7 @@ def get_tasks(status: str | None = None, limit: int = 20) -> str:
|
||||
获取用户当前的任务列表。
|
||||
|
||||
Args:
|
||||
status: 可选，筛选任务状态 (todo/in_progress/done/blocked)
|
||||
status: 可选，筛选任务状态 (todo/in_progress/done/cancelled)
|
||||
limit: 返回数量，默认20
|
||||
|
||||
Returns:
|
||||
@@ -33,6 +96,9 @@ def get_tasks(status: str | None = None, limit: int = 20) -> str:
|
||||
"""
|
||||
uid = get_current_user()
|
||||
|
||||
try:
|
||||
resolved_status = _normalize_status(status) if status else None
|
||||
|
||||
async def _get():
|
||||
async with async_session() as db:
|
||||
from app.models.user import User
|
||||
@@ -41,8 +107,8 @@ def get_tasks(status: str | None = None, limit: int = 20) -> str:
|
||||
.join(User, User.id == Task.user_id)
|
||||
.where(User.id == uid)
|
||||
)
|
||||
if status:
|
||||
query = query.where(Task.status == status)
|
||||
if resolved_status:
|
||||
query = query.where(Task.status == resolved_status)
|
||||
query = query.order_by(Task.priority.desc(), Task.updated_at.desc()).limit(limit)
|
||||
result = await db.execute(query)
|
||||
tasks = result.scalars().all()
|
||||
@@ -52,48 +118,60 @@ def get_tasks(status: str | None = None, limit: int = 20) -> str:
|
||||
for t in tasks:
|
||||
lines.append(
|
||||
f"- [{t.id[:8]}] {t.title} | "
|
||||
f"状态:{t.status} | 优先级:{t.priority} | 截止:{t.due_date or '无'}"
|
||||
f"状态:{_format_status(t.status)} | 优先级:{_format_priority(t.priority)} | 截止:{t.due_date or '无'}"
|
||||
)
|
||||
return "\n".join(lines)
|
||||
|
||||
try:
|
||||
return _run_async(_get())
|
||||
except Exception as e:
|
||||
return f"获取任务失败: {str(e)}"
|
||||
|
||||
|
||||
@tool
|
||||
def create_task(title: str, description: str = "", priority: int = 2, due_date: str | None = None) -> str:
|
||||
def create_task(
|
||||
title: str = "",
|
||||
description: str = "",
|
||||
priority: int | str = 2,
|
||||
due_date: str | None = None,
|
||||
content: str = "",
|
||||
date: str | None = None,
|
||||
) -> str:
|
||||
"""
|
||||
创建新任务。
|
||||
|
||||
Args:
|
||||
title: 任务标题（必填）
|
||||
title: 任务标题（必填，兼容 content 作为别名）
|
||||
description: 任务描述
|
||||
priority: 优先级 1-4，数字越大优先级越高，默认2
|
||||
due_date: 截止日期，格式 YYYY-MM-DD
|
||||
priority: 优先级，支持 1-4 或 low/medium/high/urgent，默认2
|
||||
due_date: 截止日期，格式 YYYY-MM-DD 或 ISO datetime
|
||||
content: title 的兼容别名
|
||||
date: due_date 的兼容别名
|
||||
|
||||
Returns:
|
||||
创建结果
|
||||
"""
|
||||
uid = get_current_user()
|
||||
|
||||
try:
|
||||
resolved_title = _normalize_title(title, content)
|
||||
resolved_due_date = _normalize_due_date(due_date, date)
|
||||
resolved_priority = _normalize_priority(priority)
|
||||
|
||||
async def _create():
|
||||
async with async_session() as db:
|
||||
task = Task(
|
||||
user_id=uid,
|
||||
title=title,
|
||||
description=description,
|
||||
priority=priority,
|
||||
due_date=due_date,
|
||||
status="todo",
|
||||
title=resolved_title,
|
||||
description=description or content or None,
|
||||
priority=resolved_priority,
|
||||
due_date=_parse_due_date(resolved_due_date),
|
||||
status=TaskStatus.TODO,
|
||||
)
|
||||
db.add(task)
|
||||
await db.commit()
|
||||
await db.refresh(task)
|
||||
return f"任务创建成功: [{task.id[:8]}] {title}"
|
||||
return f"任务创建成功: [{task.id[:8]}] {resolved_title}"
|
||||
|
||||
try:
|
||||
return _run_async(_create())
|
||||
except Exception as e:
|
||||
return f"创建任务失败: {str(e)}"
|
||||
@@ -106,13 +184,16 @@ def update_task_status(task_id: str, status: str) -> str:
|
||||
|
||||
Args:
|
||||
task_id: 任务ID（完整ID或前8位）
|
||||
status: 新状态 (todo/in_progress/done/blocked)
|
||||
status: 新状态 (todo/in_progress/done/cancelled)
|
||||
|
||||
Returns:
|
||||
更新结果
|
||||
"""
|
||||
uid = get_current_user()
|
||||
|
||||
try:
|
||||
resolved_status = _normalize_status(status)
|
||||
|
||||
async def _update():
|
||||
async with async_session() as db:
|
||||
from app.models.user import User
|
||||
@@ -129,11 +210,11 @@ def update_task_status(task_id: str, status: str) -> str:
|
||||
task = result.scalar_one_or_none()
|
||||
if not task:
|
||||
return f"任务不存在: {task_id}"
|
||||
task.status = status
|
||||
task.status = resolved_status
|
||||
task.completed_at = utc_now() if resolved_status == TaskStatus.DONE else None
|
||||
await db.commit()
|
||||
return f"任务状态已更新: {task.title} -> {status}"
|
||||
return f"任务状态已更新: {task.title} -> {resolved_status.value}"
|
||||
|
||||
try:
|
||||
return _run_async(_update())
|
||||
except Exception as e:
|
||||
return f"更新任务失败: {str(e)}"
|
||||
|
||||
269
backend/app/agents/tools/time_reasoning.py
Normal file
269
backend/app/agents/tools/time_reasoning.py
Normal file
@@ -0,0 +1,269 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import re
|
||||
from datetime import UTC, date, datetime, time, timedelta
|
||||
|
||||
from langchain_core.tools import tool
|
||||
|
||||
_WEEKDAY_MAP = {"一": 0, "二": 1, "三": 2, "四": 3, "五": 4, "六": 5, "日": 6, "天": 6}
|
||||
_DEFAULT_HOUR_BY_PERIOD = {
|
||||
"morning": 9,
|
||||
"noon": 12,
|
||||
"afternoon": 15,
|
||||
"evening": 20,
|
||||
}
|
||||
_TIME_KEYWORDS = ("今天", "明天", "后天", "本周", "这周", "下周", "周", "星期", "月", "日", "早上", "上午", "中午", "下午", "晚上", "今晚", "点", ":", "：")
|
||||
|
||||
|
||||
def _parse_datetime(value: str) -> datetime:
|
||||
normalized = value.strip().replace("Z", "+00:00")
|
||||
return datetime.fromisoformat(normalized)
|
||||
|
||||
|
||||
def extract_reference_datetime(current_datetime_context: str | None) -> datetime:
|
||||
context = (current_datetime_context or "").strip()
|
||||
if context:
|
||||
for pattern in (r"current_time_utc:\s*(\S+)", r"CURRENT_TIME:\s*(\S+)", r"(\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(?:\.\d+)?(?:Z|[+-]\d{2}:\d{2}))"):
|
||||
match = re.search(pattern, context)
|
||||
if match:
|
||||
return _parse_datetime(match.group(1))
|
||||
return datetime.now(UTC)
|
||||
|
||||
|
||||
def _normalize_local_iso(value: datetime) -> str:
|
||||
return value.replace(tzinfo=None).isoformat(timespec="seconds")
|
||||
|
||||
|
||||
def _normalize_datetime_iso(value: datetime) -> str:
|
||||
if value.tzinfo is not None:
|
||||
return value.isoformat(timespec="seconds")
|
||||
return _normalize_local_iso(value)
|
||||
|
||||
|
||||
def _normalize_date_iso(value: date) -> str:
|
||||
return value.isoformat()
|
||||
|
||||
|
||||
def _is_iso_datetime(value: str) -> bool:
|
||||
try:
|
||||
parsed = _parse_datetime(value)
|
||||
except ValueError:
|
||||
return False
|
||||
return isinstance(parsed, datetime)
|
||||
|
||||
|
||||
def _is_iso_date(value: str) -> bool:
|
||||
try:
|
||||
date.fromisoformat(value.strip())
|
||||
return True
|
||||
except ValueError:
|
||||
return False
|
||||
|
||||
|
||||
def _has_explicit_time(text: str) -> bool:
|
||||
return bool(
|
||||
re.search(r"\d{1,2}[:：]\d{2}", text)
|
||||
or re.search(r"\d{1,2}点(?:半|(?:\d{1,2})分?)?", text)
|
||||
or any(keyword in text for keyword in ("早上", "上午", "中午", "下午", "晚上", "今晚"))
|
||||
)
|
||||
|
||||
|
||||
def _detect_period(text: str) -> str | None:
|
||||
if any(keyword in text for keyword in ("晚上", "今晚")):
|
||||
return "evening"
|
||||
if "下午" in text:
|
||||
return "afternoon"
|
||||
if "中午" in text:
|
||||
return "noon"
|
||||
if any(keyword in text for keyword in ("早上", "上午", "早晨", "清晨")):
|
||||
return "morning"
|
||||
return None
|
||||
|
||||
|
||||
def _resolve_time(text: str) -> tuple[time, bool, str | None]:
|
||||
period = _detect_period(text)
|
||||
colon_match = re.search(r"(\d{1,2})[:：](\d{2})", text)
|
||||
if colon_match:
|
||||
hour = int(colon_match.group(1))
|
||||
minute = int(colon_match.group(2))
|
||||
if period in {"afternoon", "evening"} and hour < 12:
|
||||
hour += 12
|
||||
return time(hour=hour, minute=minute), False, period
|
||||
|
||||
half_match = re.search(r"(\d{1,2})点半", text)
|
||||
if half_match:
|
||||
hour = int(half_match.group(1))
|
||||
if period in {"afternoon", "evening"} and hour < 12:
|
||||
hour += 12
|
||||
return time(hour=hour, minute=30), False, period
|
||||
|
||||
dot_match = re.search(r"(\d{1,2})点(?:(\d{1,2})分?)?", text)
|
||||
if dot_match:
|
||||
hour = int(dot_match.group(1))
|
||||
minute = int(dot_match.group(2) or 0)
|
||||
if period in {"afternoon", "evening"} and hour < 12:
|
||||
hour += 12
|
||||
if period == "noon" and hour < 11:
|
||||
hour += 12
|
||||
return time(hour=hour, minute=minute), False, period
|
||||
|
||||
if period:
|
||||
return time(hour=_DEFAULT_HOUR_BY_PERIOD[period], minute=0), True, period
|
||||
return time(hour=9, minute=0), True, None
|
||||
|
||||
|
||||
def _resolve_date(text: str, reference: datetime) -> tuple[date, str]:
|
||||
stripped = text.strip()
|
||||
if _is_iso_date(stripped):
|
||||
return date.fromisoformat(stripped), "explicit_date"
|
||||
|
||||
month_day_match = re.search(r"(\d{1,2})月(\d{1,2})日", stripped)
|
||||
if month_day_match:
|
||||
month = int(month_day_match.group(1))
|
||||
day = int(month_day_match.group(2))
|
||||
candidate = date(reference.year, month, day)
|
||||
if candidate < reference.date() - timedelta(days=1):
|
||||
candidate = date(reference.year + 1, month, day)
|
||||
return candidate, "explicit_month_day"
|
||||
|
||||
if "后天" in stripped:
|
||||
return reference.date() + timedelta(days=2), "relative_day"
|
||||
if "明天" in stripped:
|
||||
return reference.date() + timedelta(days=1), "relative_day"
|
||||
if "今天" in stripped:
|
||||
return reference.date(), "relative_day"
|
||||
|
||||
weekday_match = re.search(r"((?:本周|这周|下周)?)(?:周|星期)([一二三四五六日天])", stripped)
|
||||
if weekday_match:
|
||||
prefix = weekday_match.group(1)
|
||||
weekday = _WEEKDAY_MAP[weekday_match.group(2)]
|
||||
current_weekday = reference.date().weekday()
|
||||
delta = weekday - current_weekday
|
||||
if prefix == "下周":
|
||||
delta += 7 if delta <= 0 else 7
|
||||
elif prefix in {"本周", "这周"}:
|
||||
if delta < 0:
|
||||
delta += 7
|
||||
elif delta < 0:
|
||||
delta += 7
|
||||
return reference.date() + timedelta(days=delta), "relative_weekday"
|
||||
|
||||
return reference.date(), "reference_day"
|
||||
|
||||
|
||||
def resolve_time_expression_data(
|
||||
expression: str,
|
||||
*,
|
||||
current_datetime_context: str | None = None,
|
||||
prefer: str = "datetime",
|
||||
) -> dict:
|
||||
text = (expression or "").strip()
|
||||
if not text:
|
||||
raise ValueError("expression 不能为空")
|
||||
|
||||
reference = extract_reference_datetime(current_datetime_context)
|
||||
|
||||
if _is_iso_datetime(text):
|
||||
parsed = _parse_datetime(text)
|
||||
return {
|
||||
"expression": text,
|
||||
"reference_time": reference.isoformat(),
|
||||
"grain": "datetime",
|
||||
"resolved_date": _normalize_date_iso(parsed.date()),
|
||||
"resolved_datetime": _normalize_datetime_iso(parsed),
|
||||
"assumed_time": False,
|
||||
"reason": "explicit_datetime",
|
||||
}
|
||||
|
||||
if _is_iso_date(text):
|
||||
parsed_date = date.fromisoformat(text)
|
||||
return {
|
||||
"expression": text,
|
||||
"reference_time": reference.isoformat(),
|
||||
"grain": "date",
|
||||
"resolved_date": _normalize_date_iso(parsed_date),
|
||||
"resolved_datetime": None,
|
||||
"assumed_time": False,
|
||||
"reason": "explicit_date",
|
||||
}
|
||||
|
||||
resolved_date, date_reason = _resolve_date(text, reference)
|
||||
resolved_time, assumed_time, period = _resolve_time(text)
|
||||
has_explicit_time = _has_explicit_time(text)
|
||||
grain = "date" if prefer == "date" and not has_explicit_time else "datetime"
|
||||
resolved_dt = datetime.combine(resolved_date, resolved_time)
|
||||
note = date_reason
|
||||
if period:
|
||||
note = f"{note}:{period}"
|
||||
if assumed_time:
|
||||
note = f"{note}:assumed_time"
|
||||
return {
|
||||
"expression": text,
|
||||
"reference_time": reference.isoformat(),
|
||||
"grain": grain,
|
||||
"resolved_date": _normalize_date_iso(resolved_date),
|
||||
"resolved_datetime": None if grain == "date" else _normalize_local_iso(resolved_dt),
|
||||
"assumed_time": assumed_time,
|
||||
"reason": note,
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def resolve_time_expression(
|
||||
expression: str,
|
||||
current_datetime_context: str = "",
|
||||
prefer: str = "datetime",
|
||||
) -> str:
|
||||
"""解析中文自然语言时间表达，基于当前参考时间返回明确的日期或 datetime。prefer 支持 datetime/date。"""
|
||||
try:
|
||||
payload = resolve_time_expression_data(
|
||||
expression,
|
||||
current_datetime_context=current_datetime_context or None,
|
||||
prefer=prefer,
|
||||
)
|
||||
return json.dumps(payload, ensure_ascii=False)
|
||||
except Exception as exc:
|
||||
return json.dumps(
|
||||
{
|
||||
"expression": expression,
|
||||
"error": str(exc),
|
||||
},
|
||||
ensure_ascii=False,
|
||||
)
|
||||
|
||||
|
||||
def normalize_tool_time_arguments(tool_name: str, args: dict, current_datetime_context: str | None) -> dict:
|
||||
normalized = dict(args)
|
||||
|
||||
if tool_name == "create_reminder":
|
||||
raw_value = next((normalized.get(key) for key in ("reminder_at", "datetime", "at", "remind_at", "time") if isinstance(normalized.get(key), str) and normalized.get(key).strip()), None)
|
||||
if raw_value and not _is_iso_datetime(raw_value):
|
||||
payload = resolve_time_expression_data(raw_value, current_datetime_context=current_datetime_context, prefer="datetime")
|
||||
normalized["reminder_at"] = payload["resolved_datetime"]
|
||||
return normalized
|
||||
|
||||
if tool_name in {"create_schedule_task", "create_task"}:
|
||||
raw_value = next((normalized.get(key) for key in ("due_date", "date") if isinstance(normalized.get(key), str) and normalized.get(key).strip()), None)
|
||||
if raw_value and not _is_iso_datetime(raw_value) and not _is_iso_date(raw_value):
|
||||
prefer = "datetime" if tool_name == "create_schedule_task" or _has_explicit_time(raw_value) else "date"
|
||||
payload = resolve_time_expression_data(raw_value, current_datetime_context=current_datetime_context, prefer=prefer)
|
||||
normalized["due_date"] = payload["resolved_datetime"] or payload["resolved_date"]
|
||||
return normalized
|
||||
|
||||
if tool_name in {"create_todo", "create_goal", "get_schedule_day"}:
|
||||
field_name = {
|
||||
"create_todo": "todo_date",
|
||||
"create_goal": "goal_date",
|
||||
"get_schedule_day": "target_date",
|
||||
}[tool_name]
|
||||
raw_value = normalized.get(field_name)
|
||||
if isinstance(raw_value, str) and raw_value.strip() and not _is_iso_date(raw_value):
|
||||
payload = resolve_time_expression_data(raw_value, current_datetime_context=current_datetime_context, prefer="date")
|
||||
normalized[field_name] = payload["resolved_date"]
|
||||
return normalized
|
||||
|
||||
return normalized
|
||||
|
||||
|
||||
__all__ = ["resolve_time_expression", "resolve_time_expression_data", "normalize_tool_time_arguments", "extract_reference_datetime"]
|
||||
@@ -15,7 +15,9 @@ def _resolve_path(value: str) -> str:
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
model_config = SettingsConfigDict(env_file=str(ENV_FILE), env_file_encoding="utf-8", extra="ignore")
|
||||
model_config = SettingsConfigDict(
|
||||
env_file=str(ENV_FILE), env_file_encoding="utf-8", extra="ignore"
|
||||
)
|
||||
|
||||
# === 应用基础 ===
|
||||
APP_NAME: str = "Jarvis"
|
||||
@@ -75,6 +77,8 @@ class Settings(BaseSettings):
|
||||
|
||||
# === 向量化 ===
|
||||
EMBEDDING_MODEL: str = "text-embedding-3-small"
|
||||
EMBEDDING_BASE_URL: str = "https://api.openai.com/v1"
|
||||
EMBEDDING_API_KEY: str = ""
|
||||
CHUNK_SIZE: int = 500
|
||||
CHUNK_OVERLAP: int = 50
|
||||
|
||||
@@ -86,6 +90,17 @@ class Settings(BaseSettings):
|
||||
# === NAS 部署 ===
|
||||
NAS_DATA_ROOT: str = "/data/jarvis"
|
||||
|
||||
# === Web Search / SearxNG ===
|
||||
WEB_SEARCH_ENABLED: bool = False
|
||||
WEB_SEARCH_PROVIDER: str = "searxng"
|
||||
SEARXNG_BASE_URL: str = ""
|
||||
SEARXNG_AUTH_TYPE: Literal["none", "bearer", "basic"] = "none"
|
||||
SEARXNG_AUTH_TOKEN: str = ""
|
||||
SEARXNG_BASIC_USER: str = ""
|
||||
SEARXNG_BASIC_PASSWORD: str = ""
|
||||
WEB_SEARCH_DEFAULT_LIMIT: int = 5
|
||||
WEB_SEARCH_TIMEOUT_SECONDS: int = 10
|
||||
|
||||
|
||||
settings = Settings()
|
||||
settings.DATABASE_URL = settings.DATABASE_URL.replace("./data", _resolve_path("./data"), 1)
|
||||
|
||||
@@ -40,6 +40,8 @@ async def init_db():
|
||||
await ensure_document_columns(conn)
|
||||
await ensure_user_columns(conn)
|
||||
await ensure_forum_columns(conn)
|
||||
await ensure_agent_columns(conn)
|
||||
await ensure_skill_columns(conn)
|
||||
|
||||
|
||||
async def ensure_log_columns(conn):
|
||||
@@ -139,6 +141,55 @@ async def ensure_forum_columns(conn):
|
||||
await conn.execute(text("CREATE INDEX IF NOT EXISTS ix_forum_posts_board ON forum_posts (board)"))
|
||||
|
||||
|
||||
async def ensure_agent_columns(conn):
|
||||
rows = await _get_table_info(conn, 'agents')
|
||||
if not rows:
|
||||
return
|
||||
|
||||
columns = {row[1] for row in rows}
|
||||
required_columns = {
|
||||
'selected_skill_ids': "ALTER TABLE agents ADD COLUMN selected_skill_ids JSON DEFAULT '[]' NOT NULL",
|
||||
}
|
||||
for column, ddl in required_columns.items():
|
||||
if column not in columns:
|
||||
await conn.execute(text(ddl))
|
||||
|
||||
|
||||
async def ensure_skill_columns(conn):
|
||||
rows = await _get_table_info(conn, 'skills')
|
||||
if not rows:
|
||||
return
|
||||
|
||||
columns = {row[1] for row in rows}
|
||||
required_columns = {
|
||||
'required_context': "ALTER TABLE skills ADD COLUMN required_context JSON DEFAULT '[]' NOT NULL",
|
||||
'output_format': "ALTER TABLE skills ADD COLUMN output_format TEXT",
|
||||
'is_builtin': "ALTER TABLE skills ADD COLUMN is_builtin BOOLEAN DEFAULT 0 NOT NULL",
|
||||
'team_id': "ALTER TABLE skills ADD COLUMN team_id VARCHAR(36)",
|
||||
}
|
||||
for column, ddl in required_columns.items():
|
||||
if column not in columns:
|
||||
await conn.execute(text(ddl))
|
||||
|
||||
await conn.execute(text("UPDATE skills SET agent_type = 'schedule_planner' WHERE agent_type = 'planner'"))
|
||||
builtin_names = [
|
||||
'今日重点拆解',
|
||||
'周计划编排',
|
||||
'时间冲突分析',
|
||||
'任务执行 SOP',
|
||||
'外部交互推进',
|
||||
'知识检索摘要',
|
||||
'图谱沉淀策略',
|
||||
'风险识别模板',
|
||||
'趋势洞察模板',
|
||||
]
|
||||
for name in builtin_names:
|
||||
await conn.execute(
|
||||
text("UPDATE skills SET is_builtin = 1 WHERE name = :name"),
|
||||
{'name': name},
|
||||
)
|
||||
|
||||
|
||||
async def _backfill_usernames(conn):
|
||||
result = await conn.execute(text("SELECT id, email, username FROM users ORDER BY created_at, id"))
|
||||
users = result.fetchall()
|
||||
|
||||
@@ -14,6 +14,9 @@ from app.routers import (
|
||||
graph_router,
|
||||
agent_router,
|
||||
todo_router,
|
||||
reminder_router,
|
||||
goal_router,
|
||||
schedule_center_router,
|
||||
settings_router,
|
||||
folder_router,
|
||||
skill_router,
|
||||
@@ -23,7 +26,7 @@ from app.routers import (
|
||||
)
|
||||
from app.routers.scheduler import router as scheduler_router
|
||||
from app.services.scheduler_service import start_scheduler, stop_scheduler, get_scheduler_status
|
||||
from app.services.admin_bootstrap_service import ensure_admin_user
|
||||
from app.services.admin_bootstrap_service import ensure_admin_user, ensure_builtin_skills
|
||||
from app.config import settings
|
||||
from app.logging_utils import (
|
||||
setup_logging,
|
||||
@@ -53,6 +56,7 @@ async def run_startup() -> None:
|
||||
await init_db()
|
||||
async with async_session() as session:
|
||||
await ensure_admin_user(session, settings)
|
||||
await ensure_builtin_skills(session)
|
||||
await persist_system_log(
|
||||
message="application_started",
|
||||
source="app",
|
||||
@@ -103,6 +107,9 @@ app.include_router(forum_router)
|
||||
app.include_router(graph_router)
|
||||
app.include_router(agent_router)
|
||||
app.include_router(todo_router)
|
||||
app.include_router(reminder_router)
|
||||
app.include_router(goal_router)
|
||||
app.include_router(schedule_center_router)
|
||||
app.include_router(settings_router)
|
||||
app.include_router(folder_router)
|
||||
app.include_router(skill_router)
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
from app.models.base import Base
|
||||
from app.models.user import User
|
||||
from app.models.folder import Folder
|
||||
from app.models.document import Document, DocumentChunk
|
||||
from app.models.task import Task, TaskHistory
|
||||
from app.models.forum import ForumPost, ForumReply
|
||||
@@ -17,11 +18,14 @@ from app.models.brain import (
|
||||
brain_memory_sources,
|
||||
)
|
||||
from app.models.todo import DailyTodo, TodoSource
|
||||
from app.models.reminder import Reminder, ReminderStatus
|
||||
from app.models.goal import Goal, GoalStatus
|
||||
from app.models.log import Log, LogType, LogLevel
|
||||
|
||||
__all__ = [
|
||||
"Base",
|
||||
"User",
|
||||
"Folder",
|
||||
"Document",
|
||||
"DocumentChunk",
|
||||
"Task",
|
||||
@@ -45,6 +49,10 @@ __all__ = [
|
||||
"brain_memory_sources",
|
||||
"DailyTodo",
|
||||
"TodoSource",
|
||||
"Reminder",
|
||||
"ReminderStatus",
|
||||
"Goal",
|
||||
"GoalStatus",
|
||||
"Log",
|
||||
"LogType",
|
||||
"LogLevel",
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
from sqlalchemy import Column, String, Text, Boolean, ForeignKey, Integer
|
||||
from sqlalchemy import Column, String, Text, Boolean, ForeignKey, Integer, JSON
|
||||
from sqlalchemy.orm import relationship
|
||||
from app.models.base import BaseModel
|
||||
|
||||
@@ -7,9 +7,10 @@ class Agent(BaseModel):
|
||||
__tablename__ = "agents"
|
||||
|
||||
name = Column(String(100), nullable=False)
|
||||
role = Column(String(100), nullable=False) # master, planner, executor, librarian, analyst
|
||||
role = Column(String(100), nullable=False) # master, schedule_planner, executor, librarian, analyst
|
||||
description = Column(Text, nullable=True)
|
||||
system_prompt = Column(Text, nullable=False)
|
||||
selected_skill_ids = Column(JSON, default=list, nullable=False)
|
||||
is_active = Column(Boolean, default=True)
|
||||
is_default = Column(Boolean, default=False)
|
||||
|
||||
|
||||
21
backend/app/models/goal.py
Normal file
21
backend/app/models/goal.py
Normal file
@@ -0,0 +1,21 @@
|
||||
from enum import Enum as PyEnum
|
||||
|
||||
from sqlalchemy import Column, Enum, ForeignKey, String, Text
|
||||
|
||||
from app.models.base import BaseModel
|
||||
|
||||
|
||||
class GoalStatus(str, PyEnum):
|
||||
ACTIVE = "active"
|
||||
DONE = "done"
|
||||
ARCHIVED = "archived"
|
||||
|
||||
|
||||
class Goal(BaseModel):
|
||||
__tablename__ = "goals"
|
||||
|
||||
user_id = Column(String(36), ForeignKey("users.id"), nullable=False, index=True)
|
||||
title = Column(String(255), nullable=False)
|
||||
note = Column(Text, nullable=True)
|
||||
goal_date = Column(String(10), nullable=False, index=True)
|
||||
status = Column(Enum(GoalStatus), default=GoalStatus.ACTIVE, nullable=False)
|
||||
21
backend/app/models/reminder.py
Normal file
21
backend/app/models/reminder.py
Normal file
@@ -0,0 +1,21 @@
|
||||
from enum import Enum as PyEnum
|
||||
|
||||
from sqlalchemy import Boolean, Column, DateTime, Enum, ForeignKey, String, Text
|
||||
|
||||
from app.models.base import BaseModel
|
||||
|
||||
|
||||
class ReminderStatus(str, PyEnum):
|
||||
PENDING = "pending"
|
||||
DONE = "done"
|
||||
|
||||
|
||||
class Reminder(BaseModel):
|
||||
__tablename__ = "reminders"
|
||||
|
||||
user_id = Column(String(36), ForeignKey("users.id"), nullable=False, index=True)
|
||||
title = Column(String(255), nullable=False)
|
||||
note = Column(Text, nullable=True)
|
||||
reminder_at = Column(DateTime, nullable=False, index=True)
|
||||
status = Column(Enum(ReminderStatus), default=ReminderStatus.PENDING, nullable=False)
|
||||
is_dismissed = Column(Boolean, default=False, nullable=False)
|
||||
@@ -9,11 +9,12 @@ class Skill(BaseModel):
|
||||
name = Column(String(100), nullable=False, unique=True, index=True)
|
||||
description = Column(Text, nullable=True) # 供 LLM 理解用途
|
||||
instructions = Column(Text, nullable=False) # Agent 执行时的指令模板
|
||||
agent_type = Column(String(50), nullable=False, index=True) # master/planner/executor/librarian/analyst
|
||||
agent_type = Column(String(50), nullable=False, index=True) # master/schedule_planner/executor/librarian/analyst
|
||||
tools = Column(JSON, default=list) # 引用的工具名称列表
|
||||
required_context = Column(JSON, default=list) # 需要的前置数据
|
||||
output_format = Column(Text, nullable=True) # 输出格式要求
|
||||
visibility = Column(String(20), default="private") # private/team/market
|
||||
is_builtin = Column(Boolean, default=False, nullable=False)
|
||||
team_id = Column(String(36), ForeignKey("users.id"), nullable=True)
|
||||
is_active = Column(Boolean, default=True)
|
||||
owner_id = Column(String(36), ForeignKey("users.id"), nullable=False)
|
||||
|
||||
@@ -6,6 +6,9 @@ from app.routers.forum import router as forum_router
|
||||
from app.routers.graph import router as graph_router
|
||||
from app.routers.agent import router as agent_router
|
||||
from app.routers.todo import router as todo_router
|
||||
from app.routers.reminder import router as reminder_router
|
||||
from app.routers.goal import router as goal_router
|
||||
from app.routers.schedule_center import router as schedule_center_router
|
||||
from app.routers.settings import router as settings_router
|
||||
from app.routers.folder import router as folder_router
|
||||
from app.routers.skill import router as skill_router
|
||||
|
||||
@@ -3,6 +3,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select
|
||||
from app.database import get_db
|
||||
from app.models.agent import Agent
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.schemas.agent import AgentCreate, AgentOut, AgentStats, AgentConfigUpdate, AgentConfigOut
|
||||
@@ -13,9 +14,9 @@ _agent_call_counts: dict[str, int] = {}
|
||||
_agent_current_tasks: dict[str, str | None] = {}
|
||||
_agent_statuses: dict[str, str] = {}
|
||||
|
||||
DEFAULT_AGENT_ROLES = ["master", "planner", "executor", "librarian", "analyst"]
|
||||
DEFAULT_AGENT_ROLES = ["master", "schedule_planner", "executor", "librarian", "analyst"]
|
||||
SUB_COMMANDERS_BY_ROLE = {
|
||||
"planner": ["planner_scope", "planner_steps"],
|
||||
"schedule_planner": ["schedule_analysis", "schedule_planning"],
|
||||
"executor": ["executor_tasks", "executor_forum"],
|
||||
"librarian": ["librarian_retrieval", "librarian_graph"],
|
||||
"analyst": ["analyst_progress", "analyst_insights"],
|
||||
@@ -88,10 +89,10 @@ async def get_agent_config(
|
||||
agent = result.scalar_one_or_none()
|
||||
|
||||
if not agent:
|
||||
from app.agents.prompts import MASTER_SYSTEM_PROMPT, PLANNER_SYSTEM_PROMPT, EXECUTOR_SYSTEM_PROMPT, LIBRARIAN_SYSTEM_PROMPT, ANALYST_SYSTEM_PROMPT
|
||||
from app.agents.prompts import MASTER_SYSTEM_PROMPT, SCHEDULE_PLANNER_SYSTEM_PROMPT, EXECUTOR_SYSTEM_PROMPT, LIBRARIAN_SYSTEM_PROMPT, ANALYST_SYSTEM_PROMPT
|
||||
defaults = {
|
||||
"master": ("JARVIS", "主控制核心", MASTER_SYSTEM_PROMPT),
|
||||
"planner": ("PLANNER", "规划专家", PLANNER_SYSTEM_PROMPT),
|
||||
"schedule_planner": ("SCHEDULE PLANNER", "日程规划师", SCHEDULE_PLANNER_SYSTEM_PROMPT),
|
||||
"executor": ("EXECUTOR", "执行专家", EXECUTOR_SYSTEM_PROMPT),
|
||||
"librarian": ("LIBRARIAN", "知识管理员", LIBRARIAN_SYSTEM_PROMPT),
|
||||
"analyst": ("ANALYST", "数据分析师", ANALYST_SYSTEM_PROMPT),
|
||||
@@ -107,6 +108,7 @@ async def get_agent_config(
|
||||
system_prompt=prompt,
|
||||
enabled=True,
|
||||
is_active=True,
|
||||
selected_skill_ids=[],
|
||||
)
|
||||
return AgentConfigOut(
|
||||
id=agent.role,
|
||||
@@ -116,6 +118,7 @@ async def get_agent_config(
|
||||
system_prompt=agent.system_prompt,
|
||||
enabled=agent.is_active,
|
||||
is_active=agent.is_active,
|
||||
selected_skill_ids=agent.selected_skill_ids or [],
|
||||
)
|
||||
|
||||
|
||||
@@ -141,6 +144,19 @@ async def update_agent_config(
|
||||
if data.enabled is not None:
|
||||
agent.is_active = data.enabled
|
||||
_agent_statuses[agent_id] = "disabled" if not data.enabled else "idle"
|
||||
if data.selected_skill_ids is not None:
|
||||
if data.selected_skill_ids:
|
||||
result = await db.execute(
|
||||
select(Skill.id).where(
|
||||
Skill.id.in_(data.selected_skill_ids),
|
||||
Skill.owner_id == current_user.id,
|
||||
)
|
||||
)
|
||||
allowed_skill_ids = set(result.scalars().all())
|
||||
invalid_skill_ids = [skill_id for skill_id in data.selected_skill_ids if skill_id not in allowed_skill_ids]
|
||||
if invalid_skill_ids:
|
||||
raise HTTPException(status_code=400, detail="存在无效的技能绑定")
|
||||
agent.selected_skill_ids = data.selected_skill_ids
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(agent)
|
||||
@@ -152,6 +168,7 @@ async def update_agent_config(
|
||||
system_prompt=agent.system_prompt,
|
||||
enabled=agent.is_active,
|
||||
is_active=agent.is_active,
|
||||
selected_skill_ids=agent.selected_skill_ids or [],
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -6,6 +6,7 @@ from sqlalchemy.exc import IntegrityError
|
||||
from app.database import get_db
|
||||
from app.models.user import User
|
||||
from app.schemas.auth import UserCreate, UserOut, Token
|
||||
from app.services.admin_bootstrap_service import ensure_builtin_skills
|
||||
from app.services.auth_service import verify_password, get_password_hash, create_access_token, decode_token
|
||||
from app.config import settings
|
||||
|
||||
@@ -58,6 +59,7 @@ async def register(user_data: UserCreate, db: AsyncSession = Depends(get_db)):
|
||||
await db.rollback()
|
||||
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="用户名或邮箱已被注册")
|
||||
await db.refresh(user)
|
||||
await ensure_builtin_skills(db)
|
||||
return user
|
||||
|
||||
|
||||
@@ -97,10 +99,12 @@ async def login(form_data: OAuth2PasswordRequestForm = Depends(), db: AsyncSessi
|
||||
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="用户名、邮箱或密码错误")
|
||||
if not user.is_active:
|
||||
raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="用户已被禁用")
|
||||
await ensure_builtin_skills(db)
|
||||
access_token = create_access_token(data={"sub": user.id})
|
||||
return Token(access_token=access_token)
|
||||
|
||||
|
||||
@router.get("/me", response_model=UserOut)
|
||||
async def get_me(current_user: User = Depends(get_current_user)):
|
||||
async def get_me(current_user: User = Depends(get_current_user), db: AsyncSession = Depends(get_db)):
|
||||
await ensure_builtin_skills(db)
|
||||
return current_user
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketDisconnect
|
||||
|
||||
from fastapi.responses import StreamingResponse
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select, desc
|
||||
@@ -92,6 +93,7 @@ async def chat(
|
||||
):
|
||||
"""简单版对话（非流式）"""
|
||||
agent_svc = AgentService(db)
|
||||
try:
|
||||
conv_id, msg_id, content, model_name = await agent_svc.chat_simple(
|
||||
user_id=current_user.id,
|
||||
message=data.message,
|
||||
@@ -99,6 +101,8 @@ async def chat(
|
||||
file_ids=data.file_ids,
|
||||
model_name=data.model_name,
|
||||
)
|
||||
except ValueError as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc))
|
||||
|
||||
# 更新对话消息计数
|
||||
result = await db.execute(select(Conversation).where(Conversation.id == conv_id))
|
||||
@@ -126,6 +130,7 @@ async def chat_stream(
|
||||
agent_svc = AgentService(db)
|
||||
|
||||
async def stream_generator():
|
||||
try:
|
||||
conv_id, msg_id, stream = await agent_svc.chat(
|
||||
user_id=current_user.id,
|
||||
message=data.message,
|
||||
@@ -133,6 +138,9 @@ async def chat_stream(
|
||||
file_ids=data.file_ids,
|
||||
model_name=data.model_name,
|
||||
)
|
||||
except ValueError as exc:
|
||||
yield f"event: error\ndata: {json.dumps({'error': str(exc)}, ensure_ascii=False)}\n\n"
|
||||
return
|
||||
|
||||
yield f"event: metadata\ndata: {json.dumps({'conversation_id': conv_id, 'message_id': msg_id})}\n\n"
|
||||
|
||||
|
||||
92
backend/app/routers/goal.py
Normal file
92
backend/app/routers/goal.py
Normal file
@@ -0,0 +1,92 @@
|
||||
from datetime import date
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.database import get_db
|
||||
from app.models.goal import Goal
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.schemas.goal import GoalCreate, GoalListOut, GoalOut, GoalUpdate
|
||||
|
||||
router = APIRouter(prefix="/api/goals", tags=["目标"])
|
||||
|
||||
|
||||
@router.get("", response_model=GoalListOut)
|
||||
async def list_goals(
|
||||
date_str: str = Query(...),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
target_date = date.fromisoformat(date_str).isoformat()
|
||||
query = (
|
||||
select(Goal)
|
||||
.where(Goal.user_id == current_user.id)
|
||||
.where(Goal.goal_date == target_date)
|
||||
.order_by(Goal.created_at.desc())
|
||||
)
|
||||
items = (await db.execute(query)).scalars().all()
|
||||
return GoalListOut(items=items)
|
||||
|
||||
|
||||
@router.post("", response_model=GoalOut, status_code=201)
|
||||
async def create_goal(
|
||||
data: GoalCreate,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
goal = Goal(
|
||||
user_id=current_user.id,
|
||||
title=data.title,
|
||||
note=data.note,
|
||||
goal_date=data.goal_date.isoformat(),
|
||||
status=data.status,
|
||||
)
|
||||
db.add(goal)
|
||||
await db.commit()
|
||||
await db.refresh(goal)
|
||||
return goal
|
||||
|
||||
|
||||
@router.patch("/{goal_id}", response_model=GoalOut)
|
||||
async def update_goal(
|
||||
goal_id: str,
|
||||
data: GoalUpdate,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
result = await db.execute(
|
||||
select(Goal).where(Goal.id == goal_id, Goal.user_id == current_user.id)
|
||||
)
|
||||
goal = result.scalar_one_or_none()
|
||||
if not goal:
|
||||
raise HTTPException(status_code=404, detail="目标不存在")
|
||||
|
||||
payload = data.model_dump(exclude_none=True)
|
||||
if "goal_date" in payload:
|
||||
payload["goal_date"] = payload["goal_date"].isoformat()
|
||||
|
||||
for field, value in payload.items():
|
||||
setattr(goal, field, value)
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(goal)
|
||||
return goal
|
||||
|
||||
|
||||
@router.delete("/{goal_id}", status_code=204)
|
||||
async def delete_goal(
|
||||
goal_id: str,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
result = await db.execute(
|
||||
select(Goal).where(Goal.id == goal_id, Goal.user_id == current_user.id)
|
||||
)
|
||||
goal = result.scalar_one_or_none()
|
||||
if not goal:
|
||||
raise HTTPException(status_code=404, detail="目标不存在")
|
||||
|
||||
await db.delete(goal)
|
||||
await db.commit()
|
||||
90
backend/app/routers/reminder.py
Normal file
90
backend/app/routers/reminder.py
Normal file
@@ -0,0 +1,90 @@
|
||||
from datetime import date, datetime
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.database import get_db
|
||||
from app.models.reminder import Reminder
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.schemas.reminder import ReminderCreate, ReminderListOut, ReminderOut, ReminderUpdate
|
||||
|
||||
router = APIRouter(prefix="/api/reminders", tags=["提醒"])
|
||||
|
||||
|
||||
@router.get("", response_model=ReminderListOut)
|
||||
async def list_reminders(
|
||||
date_str: str = Query(...),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
target_date = date.fromisoformat(date_str)
|
||||
start = datetime.combine(target_date, datetime.min.time())
|
||||
end = datetime.combine(target_date, datetime.max.time())
|
||||
query = (
|
||||
select(Reminder)
|
||||
.where(Reminder.user_id == current_user.id)
|
||||
.where(Reminder.reminder_at >= start)
|
||||
.where(Reminder.reminder_at <= end)
|
||||
.order_by(Reminder.reminder_at.asc(), Reminder.created_at.asc())
|
||||
)
|
||||
items = (await db.execute(query)).scalars().all()
|
||||
return ReminderListOut(items=items)
|
||||
|
||||
|
||||
@router.post("", response_model=ReminderOut, status_code=201)
|
||||
async def create_reminder(
|
||||
data: ReminderCreate,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
reminder = Reminder(
|
||||
user_id=current_user.id,
|
||||
title=data.title,
|
||||
note=data.note,
|
||||
reminder_at=data.reminder_at,
|
||||
)
|
||||
db.add(reminder)
|
||||
await db.commit()
|
||||
await db.refresh(reminder)
|
||||
return reminder
|
||||
|
||||
|
||||
@router.patch("/{reminder_id}", response_model=ReminderOut)
|
||||
async def update_reminder(
|
||||
reminder_id: str,
|
||||
data: ReminderUpdate,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
result = await db.execute(
|
||||
select(Reminder).where(Reminder.id == reminder_id, Reminder.user_id == current_user.id)
|
||||
)
|
||||
reminder = result.scalar_one_or_none()
|
||||
if not reminder:
|
||||
raise HTTPException(status_code=404, detail="提醒不存在")
|
||||
|
||||
for field, value in data.model_dump(exclude_none=True).items():
|
||||
setattr(reminder, field, value)
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(reminder)
|
||||
return reminder
|
||||
|
||||
|
||||
@router.delete("/{reminder_id}", status_code=204)
|
||||
async def delete_reminder(
|
||||
reminder_id: str,
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
result = await db.execute(
|
||||
select(Reminder).where(Reminder.id == reminder_id, Reminder.user_id == current_user.id)
|
||||
)
|
||||
reminder = result.scalar_one_or_none()
|
||||
if not reminder:
|
||||
raise HTTPException(status_code=404, detail="提醒不存在")
|
||||
|
||||
await db.delete(reminder)
|
||||
await db.commit()
|
||||
160
backend/app/routers/schedule_center.py
Normal file
160
backend/app/routers/schedule_center.py
Normal file
@@ -0,0 +1,160 @@
|
||||
from calendar import monthrange
|
||||
from datetime import UTC, date, datetime
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.database import get_db
|
||||
from app.models.goal import Goal
|
||||
from app.models.reminder import Reminder
|
||||
from app.models.task import Task, TaskPriority
|
||||
from app.models.todo import DailyTodo
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.schemas.schedule_center import (
|
||||
ScheduleCenterDateOut,
|
||||
ScheduleCenterDaySummary,
|
||||
ScheduleCenterMonthOut,
|
||||
)
|
||||
|
||||
router = APIRouter(prefix="/api/schedule-center", tags=["调度中心"])
|
||||
|
||||
|
||||
def _build_summary(
|
||||
target_date: str,
|
||||
todos: list[DailyTodo],
|
||||
tasks: list[Task],
|
||||
reminders: list[Reminder],
|
||||
goals: list[Goal],
|
||||
) -> ScheduleCenterDaySummary:
|
||||
return ScheduleCenterDaySummary(
|
||||
date=target_date,
|
||||
todo_total=len(todos),
|
||||
todo_completed=sum(1 for item in todos if item.is_completed),
|
||||
task_due_total=len(tasks),
|
||||
high_priority_total=sum(1 for item in tasks if item.priority in {TaskPriority.HIGH, TaskPriority.URGENT}),
|
||||
reminder_total=len(reminders),
|
||||
goal_total=len(goals),
|
||||
)
|
||||
|
||||
|
||||
@router.get("/month", response_model=ScheduleCenterMonthOut)
|
||||
async def get_month_schedule(
|
||||
year: int = Query(..., ge=2000, le=2100),
|
||||
month: int = Query(..., ge=1, le=12),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
month_start = date(year, month, 1)
|
||||
days_in_month = monthrange(month_start.year, month_start.month)[1]
|
||||
start_key = month_start.isoformat()
|
||||
end_key = month_start.replace(day=days_in_month).isoformat()
|
||||
start_dt = datetime.combine(month_start, datetime.min.time())
|
||||
end_dt = datetime.combine(month_start.replace(day=days_in_month), datetime.max.time())
|
||||
|
||||
todos = (await db.execute(
|
||||
select(DailyTodo).where(DailyTodo.user_id == current_user.id, DailyTodo.todo_date >= start_key, DailyTodo.todo_date <= end_key)
|
||||
)).scalars().all()
|
||||
tasks = (await db.execute(
|
||||
select(Task).where(
|
||||
Task.user_id == current_user.id,
|
||||
Task.due_date.is_not(None),
|
||||
Task.due_date >= start_dt,
|
||||
Task.due_date <= end_dt,
|
||||
)
|
||||
)).scalars().all()
|
||||
reminders = (await db.execute(
|
||||
select(Reminder).where(
|
||||
Reminder.user_id == current_user.id,
|
||||
Reminder.reminder_at >= start_dt,
|
||||
Reminder.reminder_at <= end_dt,
|
||||
)
|
||||
)).scalars().all()
|
||||
goals = (await db.execute(
|
||||
select(Goal).where(Goal.user_id == current_user.id, Goal.goal_date >= start_key, Goal.goal_date <= end_key)
|
||||
)).scalars().all()
|
||||
|
||||
todo_map: dict[str, list[DailyTodo]] = {}
|
||||
for item in todos:
|
||||
todo_map.setdefault(item.todo_date, []).append(item)
|
||||
|
||||
task_map: dict[str, list[Task]] = {}
|
||||
for item in tasks:
|
||||
key = item.due_date.date().isoformat()
|
||||
task_map.setdefault(key, []).append(item)
|
||||
|
||||
reminder_map: dict[str, list[Reminder]] = {}
|
||||
for item in reminders:
|
||||
key = item.reminder_at.date().isoformat()
|
||||
reminder_map.setdefault(key, []).append(item)
|
||||
|
||||
goal_map: dict[str, list[Goal]] = {}
|
||||
for item in goals:
|
||||
goal_map.setdefault(item.goal_date, []).append(item)
|
||||
|
||||
days = []
|
||||
for day in range(1, days_in_month + 1):
|
||||
date_key = month_start.replace(day=day).isoformat()
|
||||
days.append(_build_summary(
|
||||
date_key,
|
||||
todo_map.get(date_key, []),
|
||||
task_map.get(date_key, []),
|
||||
reminder_map.get(date_key, []),
|
||||
goal_map.get(date_key, []),
|
||||
))
|
||||
|
||||
return ScheduleCenterMonthOut(month=f"{year:04d}-{month:02d}", days=days)
|
||||
|
||||
|
||||
@router.get("/date", response_model=ScheduleCenterDateOut)
|
||||
async def get_date_schedule(
|
||||
date_str: date = Query(...),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
target_date = date_str
|
||||
start_dt = datetime.combine(target_date, datetime.min.time())
|
||||
end_dt = datetime.combine(target_date, datetime.max.time())
|
||||
date_key = target_date.isoformat()
|
||||
|
||||
todos = (await db.execute(
|
||||
select(DailyTodo)
|
||||
.where(DailyTodo.user_id == current_user.id, DailyTodo.todo_date == date_key)
|
||||
.order_by(DailyTodo.created_at.desc())
|
||||
)).scalars().all()
|
||||
tasks = (await db.execute(
|
||||
select(Task)
|
||||
.where(
|
||||
Task.user_id == current_user.id,
|
||||
Task.due_date.is_not(None),
|
||||
Task.due_date >= start_dt,
|
||||
Task.due_date <= end_dt,
|
||||
)
|
||||
.order_by(Task.created_at.desc())
|
||||
)).scalars().all()
|
||||
reminders = (await db.execute(
|
||||
select(Reminder)
|
||||
.where(
|
||||
Reminder.user_id == current_user.id,
|
||||
Reminder.reminder_at >= start_dt,
|
||||
Reminder.reminder_at <= end_dt,
|
||||
)
|
||||
.order_by(Reminder.reminder_at.asc(), Reminder.created_at.asc())
|
||||
)).scalars().all()
|
||||
goals = (await db.execute(
|
||||
select(Goal)
|
||||
.where(Goal.user_id == current_user.id, Goal.goal_date == date_key)
|
||||
.order_by(Goal.created_at.desc())
|
||||
)).scalars().all()
|
||||
|
||||
summary = _build_summary(date_key, todos, tasks, reminders, goals)
|
||||
return ScheduleCenterDateOut(
|
||||
date=date_key,
|
||||
todos=todos,
|
||||
tasks=tasks,
|
||||
reminders=reminders,
|
||||
goals=goals,
|
||||
summary=summary,
|
||||
generated_at=datetime.now(UTC),
|
||||
)
|
||||
@@ -1,11 +1,13 @@
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from app.database import get_db
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.schemas.skill import SkillCreate, SkillOut, SkillUpdate
|
||||
from app.services.admin_bootstrap_service import ensure_builtin_skills
|
||||
from app.services.skill_service import SkillService
|
||||
|
||||
router = APIRouter(prefix="/api/skills", tags=["Skill"])
|
||||
|
||||
@@ -37,13 +39,23 @@ async def create_skill(
|
||||
|
||||
@router.get("", response_model=list[SkillOut])
|
||||
async def list_skills(
|
||||
agent_type: str | None = Query(default=None),
|
||||
visibility: str | None = Query(default=None),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
result = await db.execute(
|
||||
select(Skill).where(Skill.owner_id == current_user.id).order_by(Skill.created_at.desc())
|
||||
)
|
||||
return result.scalars().all()
|
||||
service = SkillService(db)
|
||||
return await service.list_for_user(current_user.id, agent_type=agent_type, visibility=visibility)
|
||||
|
||||
|
||||
@router.post("/bootstrap-builtin", response_model=list[SkillOut])
|
||||
async def bootstrap_builtin_skills(
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
await ensure_builtin_skills(db, preferred_owner_id=current_user.id)
|
||||
service = SkillService(db)
|
||||
return await service.list_for_user(current_user.id)
|
||||
|
||||
|
||||
@router.get("/{skill_id}", response_model=SkillOut)
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from datetime import UTC, date, datetime
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import desc, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select, desc
|
||||
from app.database import get_db
|
||||
from app.models.task import Task, TaskStatus
|
||||
from app.models.user import User
|
||||
@@ -13,12 +15,28 @@ router = APIRouter(prefix="/api/tasks", tags=["看板"])
|
||||
@router.get("", response_model=list[TaskOut])
|
||||
async def list_tasks(
|
||||
status: TaskStatus | None = None,
|
||||
due_date: date | None = Query(default=None),
|
||||
date_from: date | None = Query(default=None),
|
||||
date_to: date | None = Query(default=None),
|
||||
current_user: User = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
):
|
||||
query = select(Task).where(Task.user_id == current_user.id)
|
||||
if status:
|
||||
query = query.where(Task.status == status)
|
||||
if due_date:
|
||||
start = datetime.combine(due_date, datetime.min.time())
|
||||
end = datetime.combine(due_date, datetime.max.time())
|
||||
query = query.where(Task.due_date.is_not(None), Task.due_date >= start, Task.due_date <= end)
|
||||
else:
|
||||
start = datetime.combine(date_from, datetime.min.time()) if date_from else None
|
||||
end = datetime.combine(date_to, datetime.max.time()) if date_to else None
|
||||
if start and end and start > end:
|
||||
raise HTTPException(status_code=400, detail="开始日期不能晚于结束日期")
|
||||
if start is not None:
|
||||
query = query.where(Task.due_date.is_not(None), Task.due_date >= start)
|
||||
if end is not None:
|
||||
query = query.where(Task.due_date.is_not(None), Task.due_date <= end)
|
||||
query = query.order_by(desc(Task.created_at))
|
||||
result = await db.execute(query)
|
||||
return result.scalars().all()
|
||||
@@ -64,10 +82,10 @@ async def update_task(
|
||||
if field == "tags":
|
||||
setattr(task, field, json.dumps(value))
|
||||
elif field == "status" and value == TaskStatus.DONE:
|
||||
from datetime import UTC, datetime
|
||||
task.completed_at = datetime.now(UTC)
|
||||
setattr(task, field, value)
|
||||
else:
|
||||
elif field == "status":
|
||||
task.completed_at = None
|
||||
setattr(task, field, value)
|
||||
|
||||
await db.commit()
|
||||
|
||||
@@ -1,7 +1,8 @@
|
||||
from datetime import UTC, date, datetime
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from sqlalchemy import func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select, func
|
||||
from datetime import date
|
||||
from app.database import get_db
|
||||
from app.models.todo import DailyTodo, TodoSource
|
||||
from app.models.user import User
|
||||
@@ -52,7 +53,7 @@ async def create_todo(
|
||||
user_id=current_user.id,
|
||||
title=data.title,
|
||||
source=TodoSource.MANUAL,
|
||||
todo_date=date.today().isoformat(),
|
||||
todo_date=(data.todo_date or date.today()).isoformat(),
|
||||
)
|
||||
db.add(todo)
|
||||
await db.commit()
|
||||
@@ -74,14 +75,11 @@ async def update_todo(
|
||||
if not todo:
|
||||
raise HTTPException(status_code=404, detail="待办不存在")
|
||||
|
||||
# 历史日期不允许修改
|
||||
if todo.todo_date != date.today().isoformat():
|
||||
raise HTTPException(status_code=403, detail="历史待办不可修改")
|
||||
|
||||
if data.title is not None:
|
||||
todo.title = data.title
|
||||
if data.todo_date is not None:
|
||||
todo.todo_date = data.todo_date.isoformat()
|
||||
if data.is_completed is not None:
|
||||
from datetime import UTC, datetime
|
||||
todo.is_completed = data.is_completed
|
||||
todo.completed_at = datetime.now(UTC) if data.is_completed else None
|
||||
|
||||
@@ -102,9 +100,6 @@ async def delete_todo(
|
||||
todo = result.scalar_one_or_none()
|
||||
if not todo:
|
||||
raise HTTPException(status_code=404, detail="待办不存在")
|
||||
if todo.todo_date != date.today().isoformat():
|
||||
raise HTTPException(status_code=403, detail="历史待办不可删除")
|
||||
|
||||
await db.delete(todo)
|
||||
await db.commit()
|
||||
|
||||
|
||||
@@ -41,6 +41,7 @@ class AgentConfigUpdate(BaseModel):
|
||||
description: str | None = None
|
||||
system_prompt: str | None = None
|
||||
enabled: bool | None = None
|
||||
selected_skill_ids: list[str] | None = None
|
||||
|
||||
|
||||
class AgentConfigOut(BaseModel):
|
||||
@@ -51,5 +52,6 @@ class AgentConfigOut(BaseModel):
|
||||
system_prompt: str
|
||||
enabled: bool
|
||||
is_active: bool
|
||||
selected_skill_ids: list[str]
|
||||
|
||||
model_config = {"from_attributes": True}
|
||||
|
||||
35
backend/app/schemas/goal.py
Normal file
35
backend/app/schemas/goal.py
Normal file
@@ -0,0 +1,35 @@
|
||||
from datetime import date, datetime
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.models.goal import GoalStatus
|
||||
|
||||
|
||||
class GoalCreate(BaseModel):
|
||||
title: str
|
||||
goal_date: date
|
||||
note: str | None = None
|
||||
status: GoalStatus = GoalStatus.ACTIVE
|
||||
|
||||
|
||||
class GoalUpdate(BaseModel):
|
||||
title: str | None = None
|
||||
goal_date: date | None = None
|
||||
note: str | None = None
|
||||
status: GoalStatus | None = None
|
||||
|
||||
|
||||
class GoalOut(BaseModel):
|
||||
id: str
|
||||
title: str
|
||||
note: str | None
|
||||
goal_date: str
|
||||
status: GoalStatus
|
||||
created_at: datetime
|
||||
updated_at: datetime
|
||||
|
||||
model_config = {"from_attributes": True}
|
||||
|
||||
|
||||
class GoalListOut(BaseModel):
|
||||
items: list[GoalOut]
|
||||
40
backend/app/schemas/reminder.py
Normal file
40
backend/app/schemas/reminder.py
Normal file
@@ -0,0 +1,40 @@
|
||||
from datetime import date, datetime
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.models.reminder import ReminderStatus
|
||||
|
||||
|
||||
class ReminderCreate(BaseModel):
|
||||
title: str
|
||||
reminder_at: datetime
|
||||
note: str | None = None
|
||||
|
||||
|
||||
class ReminderUpdate(BaseModel):
|
||||
title: str | None = None
|
||||
reminder_at: datetime | None = None
|
||||
note: str | None = None
|
||||
status: ReminderStatus | None = None
|
||||
is_dismissed: bool | None = None
|
||||
|
||||
|
||||
class ReminderOut(BaseModel):
|
||||
id: str
|
||||
title: str
|
||||
note: str | None
|
||||
reminder_at: datetime
|
||||
status: ReminderStatus
|
||||
is_dismissed: bool
|
||||
created_at: datetime
|
||||
updated_at: datetime
|
||||
|
||||
model_config = {"from_attributes": True}
|
||||
|
||||
|
||||
class ReminderListOut(BaseModel):
|
||||
items: list[ReminderOut]
|
||||
|
||||
|
||||
class ReminderDateQuery(BaseModel):
|
||||
date: date
|
||||
33
backend/app/schemas/schedule_center.py
Normal file
33
backend/app/schemas/schedule_center.py
Normal file
@@ -0,0 +1,33 @@
|
||||
from datetime import datetime
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.schemas.goal import GoalOut
|
||||
from app.schemas.reminder import ReminderOut
|
||||
from app.schemas.task import TaskOut
|
||||
from app.schemas.todo import TodoOut
|
||||
|
||||
|
||||
class ScheduleCenterDaySummary(BaseModel):
|
||||
date: str
|
||||
todo_total: int
|
||||
todo_completed: int
|
||||
task_due_total: int
|
||||
high_priority_total: int
|
||||
reminder_total: int
|
||||
goal_total: int
|
||||
|
||||
|
||||
class ScheduleCenterMonthOut(BaseModel):
|
||||
month: str
|
||||
days: list[ScheduleCenterDaySummary]
|
||||
|
||||
|
||||
class ScheduleCenterDateOut(BaseModel):
|
||||
date: str
|
||||
todos: list[TodoOut]
|
||||
tasks: list[TaskOut]
|
||||
reminders: list[ReminderOut]
|
||||
goals: list[GoalOut]
|
||||
summary: ScheduleCenterDaySummary
|
||||
generated_at: datetime
|
||||
@@ -10,7 +10,8 @@ LLMType = Literal["chat", "vlm", "embedding", "rerank"]
|
||||
# 单个模型配置
|
||||
class LLMModelConfig(BaseModel):
|
||||
name: str = "" # 模型名称/别名，用于标识
|
||||
provider: LLMProviderType = "openai"
|
||||
# provider 已废弃为必填字段：优先通过 base_url + model 推断。
|
||||
provider: Optional[LLMProviderType] = None
|
||||
model: str = ""
|
||||
base_url: str = ""
|
||||
api_key: str = ""
|
||||
@@ -52,7 +53,8 @@ class SettingsOut(BaseModel):
|
||||
# 测试 LLM 连接请求
|
||||
class LLMTestIn(BaseModel):
|
||||
type: LLMType
|
||||
provider: LLMProviderType
|
||||
# provider 已废弃为必填字段：优先通过 base_url + model 推断。
|
||||
provider: Optional[LLMProviderType] = None
|
||||
model: str
|
||||
base_url: str
|
||||
api_key: str
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
from datetime import datetime
|
||||
from pydantic import BaseModel
|
||||
from typing import Optional
|
||||
|
||||
@@ -6,7 +7,7 @@ class SkillCreate(BaseModel):
|
||||
name: str
|
||||
description: Optional[str] = None
|
||||
instructions: str
|
||||
agent_type: str # master/planner/executor/librarian/analyst
|
||||
agent_type: str # master/schedule_planner/executor/librarian/analyst
|
||||
tools: list[str] = []
|
||||
required_context: list[str] = []
|
||||
output_format: Optional[str] = None
|
||||
@@ -39,10 +40,11 @@ class SkillOut(BaseModel):
|
||||
required_context: list[str]
|
||||
output_format: Optional[str]
|
||||
visibility: str
|
||||
is_builtin: bool
|
||||
team_id: Optional[str]
|
||||
is_active: bool
|
||||
owner_id: str
|
||||
created_at: str
|
||||
updated_at: str
|
||||
created_at: datetime
|
||||
updated_at: datetime
|
||||
|
||||
model_config = {"from_attributes": True}
|
||||
|
||||
@@ -1,15 +1,19 @@
|
||||
from datetime import date, datetime
|
||||
|
||||
from pydantic import BaseModel
|
||||
from datetime import datetime
|
||||
|
||||
from app.models.todo import TodoSource
|
||||
|
||||
|
||||
class TodoCreate(BaseModel):
|
||||
title: str
|
||||
todo_date: date | None = None
|
||||
|
||||
|
||||
class TodoUpdate(BaseModel):
|
||||
title: str | None = None
|
||||
is_completed: bool | None = None
|
||||
todo_date: date | None = None
|
||||
|
||||
|
||||
class TodoOut(BaseModel):
|
||||
|
||||
@@ -2,10 +2,87 @@ from sqlalchemy import or_, select
|
||||
from sqlalchemy.exc import IntegrityError
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
BUILTIN_SKILLS = [
|
||||
{
|
||||
'name': '今日重点拆解',
|
||||
'description': '帮助日程规划师从上下文中提炼今天最值得推进的事项。',
|
||||
'instructions': '优先识别今天最关键的 1-3 个重点，说明原因，并给出可执行顺序。',
|
||||
'agent_type': 'schedule_planner',
|
||||
'tools': ['calendar', 'tasks'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '周计划编排',
|
||||
'description': '把本周目标整理成可落地的节奏与时间块。',
|
||||
'instructions': '将目标拆成周内节奏安排，明确先后顺序、时间块与缓冲。',
|
||||
'agent_type': 'schedule_planner',
|
||||
'tools': ['calendar'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '时间冲突分析',
|
||||
'description': '识别任务、日程与优先级之间的冲突。',
|
||||
'instructions': '分析冲突来源、影响和推荐取舍，必要时给出替代方案。',
|
||||
'agent_type': 'schedule_planner',
|
||||
'tools': ['calendar', 'tasks'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '任务执行 SOP',
|
||||
'description': '为执行角色提供标准执行步骤和结果回报格式。',
|
||||
'instructions': '执行前先确认目标与边界，执行中记录关键动作，执行后输出结果、风险与下一步。',
|
||||
'agent_type': 'executor',
|
||||
'tools': ['shell', 'api_calls'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '外部交互推进',
|
||||
'description': '支持论坛、外部接口或内容发布类动作。',
|
||||
'instructions': '围绕外部交互任务，优先保证动作完整、结果清晰、反馈及时。',
|
||||
'agent_type': 'executor',
|
||||
'tools': ['api_calls', 'git'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '知识检索摘要',
|
||||
'description': '从知识中枢中提炼与当前问题最相关的信息。',
|
||||
'instructions': '检索后只保留当前决策需要的内容，输出摘要、来源与缺口。',
|
||||
'agent_type': 'librarian',
|
||||
'tools': ['web_search', 'database'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '图谱沉淀策略',
|
||||
'description': '帮助知识管理员把零散信息沉淀为结构化关系。',
|
||||
'instructions': '识别应沉淀的实体、关系与后续可检索维度。',
|
||||
'agent_type': 'librarian',
|
||||
'tools': ['database'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '风险识别模板',
|
||||
'description': '帮助分析师快速识别当前推进中的风险点。',
|
||||
'instructions': '从进度、依赖、资源与外部信号中提炼风险，并按严重度排序。',
|
||||
'agent_type': 'analyst',
|
||||
'tools': ['database', 'api_calls'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
{
|
||||
'name': '趋势洞察模板',
|
||||
'description': '把多源状态汇总为趋势与判断。',
|
||||
'instructions': '对比近期变化，输出趋势、证据、判断与建议动作。',
|
||||
'agent_type': 'analyst',
|
||||
'tools': ['database', 'code_execution'],
|
||||
'visibility': 'market',
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
def _is_bootstrap_enabled(settings) -> bool:
|
||||
return bool(settings.ADMIN.strip() and settings.ADMIN_EMAIL.strip() and settings.ADMIN_PASSWORD.strip())
|
||||
|
||||
@@ -58,3 +135,49 @@ async def ensure_admin_user(db: AsyncSession, settings) -> None:
|
||||
return
|
||||
raise
|
||||
await db.refresh(admin_user)
|
||||
|
||||
|
||||
async def ensure_builtin_skills(db: AsyncSession, preferred_owner_id: str | None = None) -> None:
|
||||
owner = None
|
||||
if preferred_owner_id:
|
||||
owner_result = await db.execute(
|
||||
select(User).where(User.id == preferred_owner_id, User.is_active == True)
|
||||
)
|
||||
owner = owner_result.scalar_one_or_none()
|
||||
|
||||
if not owner:
|
||||
owner_result = await db.execute(
|
||||
select(User).where(User.is_active == True).order_by(User.is_superuser.desc(), User.created_at.asc())
|
||||
)
|
||||
owner = owner_result.scalars().first()
|
||||
|
||||
if not owner:
|
||||
return
|
||||
|
||||
existing_result = await db.execute(select(Skill.name))
|
||||
existing_names = set(existing_result.scalars().all())
|
||||
|
||||
missing_skills = [
|
||||
Skill(
|
||||
owner_id=owner.id,
|
||||
name=item['name'],
|
||||
description=item['description'],
|
||||
instructions=item['instructions'],
|
||||
agent_type=item['agent_type'],
|
||||
tools=item['tools'],
|
||||
required_context=[],
|
||||
output_format=None,
|
||||
visibility=item['visibility'],
|
||||
is_builtin=True,
|
||||
team_id=None,
|
||||
is_active=True,
|
||||
)
|
||||
for item in BUILTIN_SKILLS
|
||||
if item['name'] not in existing_names
|
||||
]
|
||||
|
||||
if not missing_skills:
|
||||
return
|
||||
|
||||
db.add_all(missing_skills)
|
||||
await db.commit()
|
||||
|
||||
@@ -5,18 +5,17 @@ Jarvis Agent 服务层
|
||||
|
||||
import json
|
||||
import uuid
|
||||
from datetime import datetime
|
||||
import logging
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any, AsyncGenerator
|
||||
import asyncio
|
||||
from openai import BadRequestError
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy import select
|
||||
from langchain_core.messages import HumanMessage, AIMessage
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langchain_anthropic import ChatAnthropic
|
||||
from langchain_ollama import ChatOllama
|
||||
import httpx
|
||||
|
||||
from app.database import async_session
|
||||
from app.logging_utils import summarize_llm_config
|
||||
|
||||
from app.models.conversation import Conversation, Message
|
||||
from app.models.user import User
|
||||
@@ -24,43 +23,35 @@ from app.agents.graph import get_agent_graph
|
||||
from app.agents.context import set_current_user, clear_current_user
|
||||
from app.services import memory_service
|
||||
from app.services.brain_service import BrainService
|
||||
from app.services.llm_service import create_llm_from_config, resolve_provider_capabilities
|
||||
from app.agents.tools.time_reasoning import extract_reference_datetime
|
||||
from app.agents.state import initial_state
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _create_llm_from_config(config: dict):
|
||||
"""根据用户模型配置创建 LLM 实例"""
|
||||
provider = config.get("provider", "openai")
|
||||
model = config.get("model", "")
|
||||
api_key = config.get("api_key", "")
|
||||
base_url = config.get("base_url", "")
|
||||
def _is_streaming_rejection_error(error: Exception, user_llm_config: dict | None) -> bool:
|
||||
capabilities = resolve_provider_capabilities(user_llm_config)
|
||||
error_text = str(error).lower()
|
||||
markers = [
|
||||
"invalid chat setting",
|
||||
"invalid params",
|
||||
"stream",
|
||||
"streaming",
|
||||
"unsupported",
|
||||
"bad_request_error",
|
||||
"http 400",
|
||||
"error code: 400",
|
||||
]
|
||||
|
||||
if provider == "openai" or provider == "deepseek" or provider == "custom":
|
||||
return ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or None,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
)
|
||||
elif provider == "claude":
|
||||
return ChatAnthropic(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
)
|
||||
elif provider == "ollama":
|
||||
return ChatOllama(
|
||||
base_url=base_url or "http://localhost:11434",
|
||||
model=model,
|
||||
timeout=httpx.Timeout(120.0, connect=10.0),
|
||||
)
|
||||
else:
|
||||
# 默认使用 OpenAI
|
||||
return ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or None,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
if isinstance(error, BadRequestError):
|
||||
return (
|
||||
getattr(capabilities, "provider", None) not in {"openai", "claude"}
|
||||
and any(marker in error_text for marker in markers)
|
||||
)
|
||||
|
||||
return any(marker in error_text for marker in markers)
|
||||
|
||||
|
||||
class AgentService:
|
||||
"""对话 Agent 服务"""
|
||||
@@ -101,27 +92,18 @@ class AgentService:
|
||||
|
||||
llm_config = user.llm_config
|
||||
|
||||
# 如果指定了模型名称，查找对应的配置
|
||||
if model_name:
|
||||
for model_type in ["chat", "vlm"]:
|
||||
models = llm_config.get(model_type, [])
|
||||
models = llm_config.get("chat", [])
|
||||
for m in models:
|
||||
if m.get("name") == model_name:
|
||||
return m
|
||||
# 没找到，返回 None 让调用方知道配置不存在
|
||||
return None
|
||||
|
||||
# 如果没指定模型名，返回默认启用的 chat 模型
|
||||
chat_models = llm_config.get("chat", [])
|
||||
for m in chat_models:
|
||||
if m.get("enabled"):
|
||||
return m
|
||||
|
||||
vlm_models = llm_config.get("vlm", [])
|
||||
for m in vlm_models:
|
||||
if m.get("enabled"):
|
||||
return m
|
||||
|
||||
return None
|
||||
|
||||
async def chat(
|
||||
@@ -134,11 +116,26 @@ class AgentService:
|
||||
) -> tuple[str, str, AsyncGenerator[dict[str, Any], None]]:
|
||||
"""
|
||||
处理对话请求（流式）
|
||||
|
||||
Returns:
|
||||
(conversation_id, message_id, response_stream)
|
||||
"""
|
||||
# 获取或创建对话
|
||||
user_llm_config = await self._get_user_llm_config(user_id, model_name)
|
||||
model_name_used = model_name
|
||||
if model_name and not user_llm_config:
|
||||
raise ValueError("所选模型不可用于聊天，请切换到聊天模型")
|
||||
if user_llm_config:
|
||||
model_name_used = user_llm_config.get("name", model_name)
|
||||
|
||||
logger.info(
|
||||
"agent_chat_started",
|
||||
extra={
|
||||
"details": {
|
||||
"mode": "stream",
|
||||
"requested_model_name": model_name,
|
||||
"resolved_model_name": model_name_used,
|
||||
"message_length": len(message or ""),
|
||||
}
|
||||
},
|
||||
)
|
||||
|
||||
if conversation_id:
|
||||
result = await self.db.execute(
|
||||
select(Conversation).where(Conversation.id == conversation_id)
|
||||
@@ -156,7 +153,6 @@ class AgentService:
|
||||
else:
|
||||
conversation_id = conv.id
|
||||
|
||||
# 如果有文件，读取内容作为上下文
|
||||
file_context = ""
|
||||
if file_ids:
|
||||
from app.services.document_service import DocumentService
|
||||
@@ -168,7 +164,6 @@ class AgentService:
|
||||
|
||||
full_message = f"{message}\n{file_context}" if file_context else message
|
||||
|
||||
# 存储用户消息
|
||||
user_msg = Message(
|
||||
conversation_id=conversation_id,
|
||||
role="user",
|
||||
@@ -193,156 +188,133 @@ class AgentService:
|
||||
)
|
||||
await self.db.commit()
|
||||
|
||||
# 预创建助手消息（后续更新内容）
|
||||
user_llm_config = await self._get_user_llm_config(user_id, model_name)
|
||||
model_name_used = model_name
|
||||
if user_llm_config:
|
||||
model_name_used = user_llm_config.get("name", model_name)
|
||||
memory_ctx = await memory_service.build_memory_context(
|
||||
self.db, user_id, conversation_id, message
|
||||
)
|
||||
|
||||
assistant_msg = Message(
|
||||
conversation_id=conversation_id,
|
||||
role="assistant",
|
||||
content="",
|
||||
model=model_name_used or "jarvis",
|
||||
attachments=None,
|
||||
)
|
||||
self.db.add(assistant_msg)
|
||||
await self.db.commit()
|
||||
await self.db.refresh(assistant_msg)
|
||||
|
||||
# 加载记忆上下文
|
||||
memory_ctx = await memory_service.build_memory_context(
|
||||
self.db, user_id, conversation_id, message
|
||||
def _build_current_datetime_context() -> str:
|
||||
now_utc = datetime.now(UTC)
|
||||
return (
|
||||
"【当前时间】\n"
|
||||
f"- current_time_utc: {now_utc.isoformat()}\n"
|
||||
f"- current_date_utc: {now_utc.date().isoformat()}\n"
|
||||
"说明：解析‘今天/明天/后天/本周/下周’等相对时间时，请以 current_time_utc 为准。"
|
||||
)
|
||||
|
||||
# 调用 LangGraph Agent
|
||||
async def run_agent():
|
||||
set_current_user(user_id)
|
||||
try:
|
||||
graph = get_agent_graph()
|
||||
langgraph_state = {
|
||||
"messages": [HumanMessage(content=full_message)], # type: ignore[arg-type]
|
||||
"user_id": user_id,
|
||||
"conversation_id": conversation_id,
|
||||
"current_agent": "master",
|
||||
"active_agents": ["master"],
|
||||
"current_sub_commander": None,
|
||||
"active_sub_commanders": [],
|
||||
"sub_commander_trace": [],
|
||||
"pending_tasks": [],
|
||||
"completed_tasks": [],
|
||||
"tool_calls": [],
|
||||
"last_tool_result": None,
|
||||
"knowledge_context": None,
|
||||
"graph_context": None,
|
||||
"plan": None,
|
||||
"plan_steps": [],
|
||||
"analysis_report": None,
|
||||
"final_response": None,
|
||||
"should_respond": True,
|
||||
current_datetime_context = _build_current_datetime_context()
|
||||
|
||||
# 使用 initial_state 构建状态
|
||||
state = initial_state(user_id, conversation_id)
|
||||
state.update({
|
||||
"messages": [HumanMessage(content=full_message)],
|
||||
"memory_context": memory_ctx,
|
||||
"current_datetime_context": current_datetime_context,
|
||||
"user_llm_config": user_llm_config,
|
||||
}
|
||||
})
|
||||
|
||||
yield self._build_progress_event("thinking", "Jarvis 正在分析请求", agent="master", step="理解你的问题")
|
||||
|
||||
collected = ""
|
||||
async for event in graph.astream_events(langgraph_state, version="v2"):
|
||||
try:
|
||||
async for event in graph.astream_events(state, version="v2"):
|
||||
kind = event.get("event")
|
||||
event_name = event.get("name", "")
|
||||
metadata = event.get("metadata", {})
|
||||
data = event.get("data", {})
|
||||
|
||||
if kind == "on_chain_start" and event_name in {"master", "planner", "executor", "librarian", "analyst"}:
|
||||
if kind == "on_chain_start" and event_name in {"master", "schedule_planner", "executor", "librarian", "analyst"}:
|
||||
stage_map = {
|
||||
"master": ("thinking", "Jarvis 正在理解请求"),
|
||||
"planner": ("planning", "Jarvis 正在拆解步骤"),
|
||||
"schedule_planner": ("planning", "Jarvis 正在编排日程"),
|
||||
"executor": ("tool", "Jarvis 正在执行操作"),
|
||||
"librarian": ("tool", "Jarvis 正在检索知识"),
|
||||
"analyst": ("thinking", "Jarvis 正在分析信息"),
|
||||
}
|
||||
stage, label = stage_map[event_name]
|
||||
stage, label = stage_map.get(event_name, ("thinking", "Jarvis 正在思考"))
|
||||
yield self._build_progress_event(stage, label, agent=event_name, step=label)
|
||||
|
||||
elif kind == "on_tool_start":
|
||||
tool_input = data.get("input")
|
||||
step = None
|
||||
if isinstance(tool_input, dict) and tool_input:
|
||||
step = f"调用工具 {event_name}"
|
||||
yield self._build_progress_event("tool", f"Jarvis 正在调用工具 {event_name}", agent="executor", tool_name=event_name, step=step)
|
||||
yield self._build_progress_event(
|
||||
"tool",
|
||||
f"Jarvis 正在调用工具 {event_name}",
|
||||
agent="executor",
|
||||
tool_name=event_name,
|
||||
step=f"正在执行 {event_name}",
|
||||
)
|
||||
|
||||
elif kind == "on_tool_end":
|
||||
yield self._build_progress_event("tool", f"工具 {event_name} 已完成", agent="executor", tool_name=event_name, step=f"已获得 {event_name} 结果")
|
||||
elif kind == "on_chain_end" and event_name == "planner":
|
||||
output = data.get("output") or {}
|
||||
plan_steps = output.get("plan_steps") or []
|
||||
steps = [item.get("description", "") for item in plan_steps if item.get("description")]
|
||||
yield self._build_progress_event("planning", "Jarvis 已生成处理步骤", agent="planner", step=steps[0] if steps else "正在整理计划", steps=steps[:4])
|
||||
tool_result = data.get("output")
|
||||
step = f"已完成 {event_name}"
|
||||
if isinstance(tool_result, str) and len(tool_result) > 0:
|
||||
step = tool_result[:100]
|
||||
yield self._build_progress_event(
|
||||
"tool",
|
||||
f"工具 {event_name} 已完成",
|
||||
agent="executor",
|
||||
tool_name=event_name,
|
||||
step=step,
|
||||
)
|
||||
|
||||
elif kind == "on_chat_model_stream":
|
||||
chunk = data.get("chunk")
|
||||
content = getattr(chunk, "content", "") if chunk else ""
|
||||
if isinstance(content, list):
|
||||
text_parts = []
|
||||
for item in content:
|
||||
if isinstance(item, dict):
|
||||
text_parts.append(item.get("text", ""))
|
||||
else:
|
||||
text_parts.append(str(item))
|
||||
content = "".join(text_parts)
|
||||
if content:
|
||||
collected += content
|
||||
yield {"type": "chunk", "content": content}
|
||||
elif kind == "on_chat_model_end" and not collected:
|
||||
|
||||
elif kind == "on_chain_end" and event_name == "create_agent_graph":
|
||||
# 最终输出通常在这里
|
||||
output = data.get("output")
|
||||
content = getattr(output, "content", "") if output else ""
|
||||
if isinstance(content, list):
|
||||
text_parts = []
|
||||
for item in content:
|
||||
if isinstance(item, dict):
|
||||
text_parts.append(item.get("text", ""))
|
||||
else:
|
||||
text_parts.append(str(item))
|
||||
content = "".join(text_parts)
|
||||
if content:
|
||||
collected = content
|
||||
yield {"type": "chunk", "content": content}
|
||||
elif kind == "on_chain_end" and event_name in {"executor", "librarian", "analyst"}:
|
||||
yield self._build_progress_event("responding", "Jarvis 正在整理最终回答", agent=event_name, step="生成回复")
|
||||
if isinstance(output, dict) and "final_response" in output:
|
||||
final_resp = output["final_response"]
|
||||
# 如果还没流式输出完整，补全它
|
||||
if final_resp and not collected:
|
||||
collected = final_resp
|
||||
yield {"type": "chunk", "content": collected}
|
||||
|
||||
except Exception as e:
|
||||
fallback = f"抱歉，发生错误: {str(e)}"
|
||||
collected = fallback
|
||||
if _is_streaming_rejection_error(e, user_llm_config) and not collected:
|
||||
yield self._build_progress_event("responding", "Jarvis 正在生成回复", agent="master", step="fallback")
|
||||
try:
|
||||
result_state = await graph.ainvoke(state)
|
||||
fallback_content = result_state.get("final_response") or str(result_state.get("messages", [AIMessage(content="")])[-1].content)
|
||||
collected = str(fallback_content)
|
||||
yield {"type": "chunk", "content": collected}
|
||||
except Exception as fallback_error:
|
||||
logger.exception("llm_sync_fallback_failed")
|
||||
yield {"type": "error", "error": "模型服务暂不可用。"}
|
||||
else:
|
||||
logger.exception("agent_streaming_failed")
|
||||
yield {"type": "error", "error": str(e)}
|
||||
yield {"type": "chunk", "content": fallback}
|
||||
finally:
|
||||
clear_current_user()
|
||||
try:
|
||||
asyncio.get_running_loop().create_task(
|
||||
self._try_auto_summarize_background(user_id, conversation_id)
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
asyncio.create_task(self._try_auto_summarize_background(user_id, conversation_id))
|
||||
|
||||
# 最终更新数据库中的消息内容
|
||||
if collected:
|
||||
try:
|
||||
result2 = await self.db.execute(
|
||||
select(Message).where(Message.id == assistant_msg.id)
|
||||
)
|
||||
async with async_session() as session:
|
||||
result2 = await session.execute(select(Message).where(Message.id == assistant_msg.id))
|
||||
msg = result2.scalar_one_or_none()
|
||||
if msg:
|
||||
msg.content = collected
|
||||
await self.db.commit()
|
||||
await brain_service.create_event(
|
||||
user_id,
|
||||
source_type="conversation",
|
||||
source_id=conversation_id,
|
||||
event_type="message_created",
|
||||
title="Assistant message",
|
||||
content_summary=collected[:500],
|
||||
raw_excerpt=collected[:2000],
|
||||
metadata_={"role": "assistant"},
|
||||
importance_signal=1.0,
|
||||
)
|
||||
await self.db.commit()
|
||||
await session.commit()
|
||||
except Exception:
|
||||
pass
|
||||
logger.exception("save_assistant_message_failed")
|
||||
|
||||
return conversation_id, assistant_msg.id, run_agent()
|
||||
|
||||
@@ -355,117 +327,44 @@ class AgentService:
|
||||
model_name: str | None = None,
|
||||
) -> tuple[str, str, str, str | None]:
|
||||
"""
|
||||
简单同步版对话（无流式）
|
||||
|
||||
Returns:
|
||||
(conversation_id, message_id, response_content, model_name_used)
|
||||
简单同步版对话
|
||||
"""
|
||||
# 获取或创建对话
|
||||
if conversation_id:
|
||||
result = await self.db.execute(
|
||||
select(Conversation).where(Conversation.id == conversation_id)
|
||||
)
|
||||
conv = result.scalar_one_or_none()
|
||||
else:
|
||||
conv = None
|
||||
|
||||
if not conv:
|
||||
conv = Conversation(user_id=user_id, title=message[:50])
|
||||
self.db.add(conv)
|
||||
await self.db.commit()
|
||||
await self.db.refresh(conv)
|
||||
conversation_id = conv.id
|
||||
else:
|
||||
conversation_id = conv.id
|
||||
|
||||
# 如果有文件，读取内容作为上下文
|
||||
file_context = ""
|
||||
if file_ids:
|
||||
from app.services.document_service import DocumentService
|
||||
doc_svc = DocumentService(self.db)
|
||||
for file_id in file_ids:
|
||||
content = await doc_svc.get_document_content(user_id, file_id)
|
||||
if content:
|
||||
file_context += f"\n\n[用户上传文件内容]\n{content}\n[/文件内容]"
|
||||
|
||||
# 将文件上下文添加到消息
|
||||
full_message = f"{message}\n{file_context}" if file_context else message
|
||||
|
||||
# 存储用户消息
|
||||
user_msg = Message(
|
||||
conversation_id=conversation_id,
|
||||
role="user",
|
||||
content=message,
|
||||
attachments=[{"file_ids": file_ids}] if file_ids else None,
|
||||
)
|
||||
self.db.add(user_msg)
|
||||
await self.db.commit()
|
||||
await self.db.refresh(user_msg)
|
||||
|
||||
brain_service = BrainService(self.db)
|
||||
await brain_service.create_event(
|
||||
user_id,
|
||||
source_type="conversation",
|
||||
source_id=conversation_id,
|
||||
event_type="message_created",
|
||||
title="User message",
|
||||
content_summary=message[:500],
|
||||
raw_excerpt=message[:2000],
|
||||
metadata_={"role": "user"},
|
||||
importance_signal=1.0,
|
||||
)
|
||||
await self.db.commit()
|
||||
|
||||
# 加载记忆上下文
|
||||
memory_ctx = await memory_service.build_memory_context(
|
||||
self.db, user_id, conversation_id, message
|
||||
)
|
||||
|
||||
# 获取用户配置的 LLM
|
||||
user_llm_config = await self._get_user_llm_config(user_id, model_name)
|
||||
model_name_used = model_name
|
||||
if user_llm_config:
|
||||
model_name_used = user_llm_config.get("name", model_name)
|
||||
|
||||
# 调用 LangGraph Agent
|
||||
set_current_user(user_id)
|
||||
graph = get_agent_graph()
|
||||
langgraph_state = {
|
||||
"messages": [HumanMessage(content=full_message)], # type: ignore[arg-type]
|
||||
"user_id": user_id,
|
||||
"conversation_id": conversation_id,
|
||||
"current_agent": "master",
|
||||
"active_agents": ["master"],
|
||||
"pending_tasks": [],
|
||||
"completed_tasks": [],
|
||||
"tool_calls": [],
|
||||
"last_tool_result": None,
|
||||
"knowledge_context": None,
|
||||
"graph_context": None,
|
||||
"plan": None,
|
||||
"plan_steps": [],
|
||||
"analysis_report": None,
|
||||
"final_response": None,
|
||||
"should_respond": True,
|
||||
"memory_context": memory_ctx,
|
||||
"user_llm_config": user_llm_config, # 传递用户 LLM 配置
|
||||
}
|
||||
if not conversation_id:
|
||||
conv = Conversation(user_id=user_id, title=message[:50])
|
||||
self.db.add(conv)
|
||||
await self.db.commit()
|
||||
await self.db.refresh(conv)
|
||||
conversation_id = conv.id
|
||||
|
||||
user_msg = Message(conversation_id=conversation_id, role="user", content=message)
|
||||
self.db.add(user_msg)
|
||||
|
||||
memory_ctx = await memory_service.build_memory_context(self.db, user_id, conversation_id, message)
|
||||
|
||||
set_current_user(user_id)
|
||||
try:
|
||||
result_state = await graph.ainvoke(langgraph_state)
|
||||
response_content = result_state.get("final_response", "抱歉，我无法处理这个请求。")
|
||||
graph = get_agent_graph()
|
||||
state = initial_state(user_id, conversation_id)
|
||||
state.update({
|
||||
"messages": [HumanMessage(content=message)],
|
||||
"memory_context": memory_ctx,
|
||||
"current_datetime_context": datetime.now(UTC).isoformat(),
|
||||
"user_llm_config": user_llm_config,
|
||||
})
|
||||
|
||||
result_state = await graph.ainvoke(state)
|
||||
response_content = result_state.get("final_response") or str(result_state.get("messages", [AIMessage(content="")])[-1].content)
|
||||
except Exception as e:
|
||||
response_content = f"抱歉，发生错误: {str(e)}"
|
||||
logger.exception("agent_chat_simple_failed")
|
||||
response_content = "抱歉，发生错误。"
|
||||
finally:
|
||||
clear_current_user()
|
||||
try:
|
||||
asyncio.get_running_loop().create_task(
|
||||
self._try_auto_summarize_background(user_id, conversation_id)
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# 保存助手消息
|
||||
assistant_msg = Message(
|
||||
conversation_id=conversation_id,
|
||||
role="assistant",
|
||||
@@ -474,19 +373,5 @@ class AgentService:
|
||||
)
|
||||
self.db.add(assistant_msg)
|
||||
await self.db.commit()
|
||||
await self.db.refresh(assistant_msg)
|
||||
|
||||
await brain_service.create_event(
|
||||
user_id,
|
||||
source_type="conversation",
|
||||
source_id=conversation_id,
|
||||
event_type="message_created",
|
||||
title="Assistant message",
|
||||
content_summary=response_content[:500],
|
||||
raw_excerpt=response_content[:2000],
|
||||
metadata_={"role": "assistant"},
|
||||
importance_signal=1.0,
|
||||
)
|
||||
await self.db.commit()
|
||||
|
||||
return conversation_id, assistant_msg.id, response_content, model_name_used
|
||||
|
||||
@@ -4,7 +4,8 @@ OpenAI / Claude / Ollama / DeepSeek / 任意 OpenAI 兼容接口
|
||||
"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import AsyncIterator
|
||||
from dataclasses import dataclass
|
||||
from typing import AsyncIterator, Literal
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from langchain_core.messages import BaseMessage, AIMessage
|
||||
@@ -16,8 +17,131 @@ from app.models.user import User
|
||||
import httpx
|
||||
import os
|
||||
|
||||
os.makedirs(settings.DATA_DIR, exist_ok=True)
|
||||
os.makedirs(settings.CHROMA_PERSIST_DIR, exist_ok=True)
|
||||
|
||||
|
||||
ToolStrategy = Literal["native", "json_fallback"]
|
||||
|
||||
|
||||
def _resolve_effective_base_url(config: dict | None) -> str:
|
||||
provider = str((config or {}).get("provider") or settings.LLM_PROVIDER or "openai").strip().lower()
|
||||
base_url = str((config or {}).get("base_url") or "").strip()
|
||||
if base_url:
|
||||
return base_url
|
||||
if provider in {"openai", "custom", "deepseek"}:
|
||||
return settings.OPENAI_BASE_URL
|
||||
if provider == "ollama":
|
||||
return settings.OLLAMA_BASE_URL
|
||||
return ""
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class ProviderCapabilities:
|
||||
provider: str
|
||||
supports_native_tools: bool
|
||||
preferred_tool_strategy: ToolStrategy
|
||||
|
||||
|
||||
def default_provider_capabilities() -> ProviderCapabilities:
|
||||
return resolve_provider_capabilities({"provider": settings.LLM_PROVIDER})
|
||||
|
||||
|
||||
def normalize_provider_name(config: dict | None) -> str:
|
||||
provider_raw = str((config or {}).get("provider") or "").strip().lower()
|
||||
provider = provider_raw or str(settings.LLM_PROVIDER or "openai").strip().lower()
|
||||
model = str((config or {}).get("model") or "").strip().lower()
|
||||
base_url = _resolve_effective_base_url(config).strip().lower()
|
||||
|
||||
# base_url-first inference (provider may be omitted in user config)
|
||||
if base_url:
|
||||
if any(key in base_url for key in {"localhost:11434", "127.0.0.1:11434"}):
|
||||
return "ollama"
|
||||
if any(key in base_url for key in {"api.anthropic.com", "anthropic"}):
|
||||
return "claude"
|
||||
if "api.deepseek.com" in base_url:
|
||||
return "deepseek"
|
||||
|
||||
# Many "openai-compatible" endpoints are configured as provider=openai.
|
||||
# We treat them as distinct providers so capability routing can stay conservative.
|
||||
if provider in {"openai", "custom"}:
|
||||
if any(key in model or key in base_url for key in {"minimax", "abab"}):
|
||||
return "minimax"
|
||||
if any(key in model or key in base_url for key in {"kimi", "moonshot"}):
|
||||
return "kimi"
|
||||
if any(key in model or key in base_url for key in {"qwen", "dashscope", "aliyuncs"}):
|
||||
return "qwen"
|
||||
|
||||
return provider
|
||||
|
||||
|
||||
def resolve_provider_capabilities(config: dict | None) -> ProviderCapabilities:
|
||||
provider = normalize_provider_name(config)
|
||||
|
||||
# Conservative default: only treat official OpenAI + DeepSeek + Claude as reliable native tool providers.
|
||||
# Many OpenAI-compatible endpoints reject tool / response_format / other chat params.
|
||||
native_tool_providers = {"openai", "deepseek", "claude"}
|
||||
|
||||
base_url = _resolve_effective_base_url(config).strip().lower()
|
||||
is_official_openai = (
|
||||
provider != "openai"
|
||||
or not base_url
|
||||
or "api.openai.com" in base_url
|
||||
or "openai.azure.com" in base_url
|
||||
)
|
||||
|
||||
if provider in native_tool_providers and is_official_openai:
|
||||
return ProviderCapabilities(
|
||||
provider=provider,
|
||||
supports_native_tools=True,
|
||||
preferred_tool_strategy="native",
|
||||
)
|
||||
|
||||
return ProviderCapabilities(
|
||||
provider=provider,
|
||||
supports_native_tools=False,
|
||||
preferred_tool_strategy="json_fallback",
|
||||
)
|
||||
|
||||
|
||||
def create_llm_from_config(config: dict | None):
|
||||
"""根据用户模型配置创建底层 LangChain LLM 实例"""
|
||||
if not config:
|
||||
return get_llm()
|
||||
|
||||
provider = normalize_provider_name(config)
|
||||
model = config.get("model", "")
|
||||
api_key = config.get("api_key", "")
|
||||
base_url = config.get("base_url", "")
|
||||
|
||||
if provider in {"openai", "deepseek", "custom", "minimax", "kimi", "qwen"}:
|
||||
llm = ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or None,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
)
|
||||
elif provider == "claude":
|
||||
llm = ChatAnthropic(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
)
|
||||
elif provider == "ollama":
|
||||
llm = ChatOllama(
|
||||
base_url=base_url or "http://localhost:11434",
|
||||
model=model,
|
||||
timeout=httpx.Timeout(120.0, connect=10.0),
|
||||
)
|
||||
else:
|
||||
llm = ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or None,
|
||||
timeout=httpx.Timeout(60.0, connect=10.0),
|
||||
)
|
||||
|
||||
setattr(llm, "_jarvis_user_llm_config", config)
|
||||
setattr(llm, "_jarvis_provider_capabilities", resolve_provider_capabilities(config))
|
||||
return llm
|
||||
|
||||
|
||||
class LLMService(ABC):
|
||||
@@ -145,4 +269,7 @@ def get_llm() -> LLMService:
|
||||
_llm_instance = OllamaService()
|
||||
else:
|
||||
raise ValueError(f"Unknown LLM provider: {provider}")
|
||||
setattr(_llm_instance, "_jarvis_provider_capabilities", default_provider_capabilities())
|
||||
return _llm_instance
|
||||
|
||||
|
||||
|
||||
@@ -1,23 +1,154 @@
|
||||
"""
|
||||
Jarvis 记忆系统
|
||||
Jarvis 记忆系统 (基于 Mem0)
|
||||
三层记忆: 短期(对话历史) → 中期(摘要) → 长期(用户画像)
|
||||
底层使用 Mem0 实现事实提取、时间线、矛盾解决和遗忘机制
|
||||
"""
|
||||
|
||||
import json
|
||||
import re
|
||||
import os
|
||||
from datetime import datetime
|
||||
from typing import Optional
|
||||
from typing import Optional, Any
|
||||
from sqlalchemy import select, desc, func
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from app.models.memory import MemorySummary, UserMemory
|
||||
from app.models.conversation import Conversation, Message
|
||||
from app.models.user import User
|
||||
from app.services.brain_service import BrainService
|
||||
from app.services.llm_service import get_llm
|
||||
from app.agents.context import get_current_user
|
||||
from app.config import settings as _settings
|
||||
|
||||
try:
|
||||
from mem0 import Memory
|
||||
|
||||
MEM0_AVAILABLE = True
|
||||
except ImportError:
|
||||
MEM0_AVAILABLE = False
|
||||
Memory = None
|
||||
|
||||
|
||||
async def _get_user_embedding_config(db: AsyncSession, user_id: str) -> dict | None:
|
||||
"""从用户配置中获取 embedding 模型配置"""
|
||||
result = await db.execute(select(User).where(User.id == user_id))
|
||||
user = result.scalar_one_or_none()
|
||||
if not user or not user.llm_config:
|
||||
return None
|
||||
|
||||
embedding_models = user.llm_config.get("embedding", [])
|
||||
for model in embedding_models:
|
||||
if model.get("enabled") and model.get("model"):
|
||||
return {
|
||||
"model": model.get("model"),
|
||||
"base_url": model.get("base_url") or _settings.EMBEDDING_BASE_URL,
|
||||
"api_key": model.get("api_key")
|
||||
or _settings.EMBEDDING_API_KEY
|
||||
or _settings.OPENAI_API_KEY,
|
||||
}
|
||||
return None
|
||||
|
||||
|
||||
async def _get_user_chat_config(db: AsyncSession, user_id: str) -> dict | None:
|
||||
"""从用户配置中获取 chat 模型配置"""
|
||||
result = await db.execute(select(User).where(User.id == user_id))
|
||||
user = result.scalar_one_or_none()
|
||||
if not user or not user.llm_config:
|
||||
return None
|
||||
|
||||
chat_models = user.llm_config.get("chat", [])
|
||||
for model in chat_models:
|
||||
if model.get("enabled") and model.get("model"):
|
||||
return {
|
||||
"model": model.get("model"),
|
||||
"base_url": model.get("base_url") or _settings.OPENAI_BASE_URL,
|
||||
"api_key": model.get("api_key") or _settings.OPENAI_API_KEY,
|
||||
}
|
||||
return None
|
||||
|
||||
|
||||
class Mem0Client:
|
||||
"""Mem0 客户端 - 按用户隔离"""
|
||||
|
||||
_instances: dict[str, Memory] = {}
|
||||
_persist_dir: str = "./data/mem0"
|
||||
|
||||
async def get_memory(self, db: AsyncSession, user_id: str) -> Memory:
|
||||
"""获取指定用户的 Mem0 实例"""
|
||||
cache_key = user_id
|
||||
|
||||
if cache_key not in self._instances:
|
||||
self._instances[cache_key] = await self._init_memory(db, user_id)
|
||||
|
||||
return self._instances[cache_key]
|
||||
|
||||
async def _init_memory(self, db: AsyncSession, user_id: str) -> Memory:
|
||||
if not MEM0_AVAILABLE:
|
||||
raise RuntimeError("mem0ai 未安装，请运行: pip install mem0ai")
|
||||
|
||||
os.makedirs(self._persist_dir, exist_ok=True)
|
||||
|
||||
llm_config = {
|
||||
"model": _settings.OPENAI_MODEL,
|
||||
"base_url": _settings.OPENAI_BASE_URL,
|
||||
"api_key": _settings.OPENAI_API_KEY,
|
||||
}
|
||||
|
||||
embed_config = _settings.EMBEDDING_MODEL
|
||||
embed_base_url = _settings.EMBEDDING_BASE_URL
|
||||
embed_api_key = _settings.EMBEDDING_API_KEY or _settings.OPENAI_API_KEY
|
||||
|
||||
if db and user_id:
|
||||
try:
|
||||
user_chat = await _get_user_chat_config(db, user_id)
|
||||
if user_chat:
|
||||
llm_config = user_chat
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
try:
|
||||
user_embed = await _get_user_embedding_config(db, user_id)
|
||||
if user_embed:
|
||||
embed_config = user_embed["model"]
|
||||
embed_base_url = user_embed["base_url"]
|
||||
embed_api_key = user_embed["api_key"]
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
config = {
|
||||
"vector_store": {
|
||||
"provider": "chroma",
|
||||
"config": {
|
||||
"collection_name": f"jarvis_memory_{user_id}",
|
||||
"path": self._persist_dir,
|
||||
},
|
||||
},
|
||||
"llm": {
|
||||
"provider": "openai",
|
||||
"config": {
|
||||
"model": llm_config["model"],
|
||||
"api_key": llm_config["api_key"],
|
||||
"base_url": llm_config["base_url"],
|
||||
},
|
||||
},
|
||||
"embedder": {
|
||||
"provider": "openai",
|
||||
"config": {
|
||||
"model": embed_config,
|
||||
"api_key": embed_api_key,
|
||||
"base_url": embed_base_url,
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
return Memory.from_config(config)
|
||||
|
||||
|
||||
_mem0_client = Mem0Client()
|
||||
|
||||
|
||||
async def get_mem0(db: AsyncSession, user_id: str) -> Memory:
|
||||
"""获取指定用户的 Mem0 实例"""
|
||||
return await _mem0_client.get_memory(db, user_id)
|
||||
|
||||
|
||||
# ———— 短期记忆: 对话历史 ————
|
||||
|
||||
|
||||
async def load_conversation_history(
|
||||
db: AsyncSession,
|
||||
conversation_id: str,
|
||||
@@ -36,8 +167,7 @@ async def load_conversation_history(
|
||||
async def get_conversation_turn_count(db: AsyncSession, conversation_id: str) -> int:
|
||||
"""获取对话轮数（用户消息数）"""
|
||||
result = await db.execute(
|
||||
select(func.count(Message.id))
|
||||
.where(
|
||||
select(func.count(Message.id)).where(
|
||||
Message.conversation_id == conversation_id,
|
||||
Message.role == "user",
|
||||
)
|
||||
@@ -47,14 +177,15 @@ async def get_conversation_turn_count(db: AsyncSession, conversation_id: str) ->
|
||||
|
||||
# ———— 中期记忆: 对话摘要 ————
|
||||
|
||||
SUMMARIZE_THRESHOLD = 8 # 超过此轮数则摘要
|
||||
MAX_HISTORY_TURNS = 10 # Agent 最多看到的对话历史轮数
|
||||
SUMMARIZE_THRESHOLD = 8
|
||||
MAX_HISTORY_TURNS = 10
|
||||
|
||||
|
||||
async def should_summarize(db: AsyncSession, conversation_id: str) -> bool:
|
||||
"""判断当前对话是否需要摘要"""
|
||||
from app.models.memory import MemorySummary
|
||||
|
||||
turn_count = await get_conversation_turn_count(db, conversation_id)
|
||||
# 检查是否已有摘要覆盖到当前轮数
|
||||
result = await db.execute(
|
||||
select(MemorySummary)
|
||||
.where(MemorySummary.conversation_id == conversation_id)
|
||||
@@ -72,17 +203,21 @@ async def generate_summary(
|
||||
conversation_id: str,
|
||||
messages: list[Message],
|
||||
) -> str:
|
||||
"""调用 LLM 生成对话摘要"""
|
||||
history_text = "\n".join(
|
||||
f"[{m.role}] {m.content}" for m in messages
|
||||
)
|
||||
llm = get_llm()
|
||||
"""生成对话摘要"""
|
||||
from app.services.llm_service import get_llm
|
||||
from langchain_core.messages import HumanMessage, SystemMessage
|
||||
response = await llm.invoke([
|
||||
SystemMessage(content="你是一个记忆助手。请用简洁的中文总结以下对话的核心内容，"
|
||||
"提取关键信息、用户偏好、待办事项等。不超过150字。"),
|
||||
|
||||
history_text = "\n".join(f"[{m.role}] {m.content}" for m in messages)
|
||||
llm = get_llm()
|
||||
response = await llm.invoke(
|
||||
[
|
||||
SystemMessage(
|
||||
content="你是一个记忆助手。请用简洁的中文总结以下对话的核心内容，"
|
||||
"提取关键信息、用户偏好、待办事项等。不超过150字。"
|
||||
),
|
||||
HumanMessage(content=history_text),
|
||||
])
|
||||
]
|
||||
)
|
||||
return response.content.strip()
|
||||
|
||||
|
||||
@@ -92,8 +227,10 @@ async def save_summary(
|
||||
conversation_id: str,
|
||||
summary_text: str,
|
||||
turn_count: int,
|
||||
) -> MemorySummary:
|
||||
"""保存对话摘要"""
|
||||
) -> Any:
|
||||
"""保存对话摘要到数据库"""
|
||||
from app.models.memory import MemorySummary
|
||||
|
||||
summary = MemorySummary(
|
||||
user_id=user_id,
|
||||
conversation_id=conversation_id,
|
||||
@@ -109,8 +246,10 @@ async def save_summary(
|
||||
async def get_summaries(
|
||||
db: AsyncSession,
|
||||
conversation_id: str,
|
||||
) -> list[MemorySummary]:
|
||||
) -> list[Any]:
|
||||
"""获取某对话的所有历史摘要"""
|
||||
from app.models.memory import MemorySummary
|
||||
|
||||
result = await db.execute(
|
||||
select(MemorySummary)
|
||||
.where(MemorySummary.conversation_id == conversation_id)
|
||||
@@ -119,31 +258,7 @@ async def get_summaries(
|
||||
return list(result.scalars().all())
|
||||
|
||||
|
||||
# ———— 长期记忆: 用户画像 ————
|
||||
|
||||
EXTRACTION_PROMPT = """从以下对话中提取关于用户的关键信息。
|
||||
只提取事实性的、可能对未来对话有帮助的信息，如：
|
||||
- 用户的身份/职业/背景
|
||||
- 用户的偏好和习惯
|
||||
- 用户的目标和计划
|
||||
- 重要的事件和日期
|
||||
- 用户的观点和态度
|
||||
|
||||
每条记忆格式: [类型] 内容
|
||||
类型: fact(事实) | preference(偏好) | goal(目标) | habit(习惯)
|
||||
|
||||
如果没有提取到任何记忆，回复"无"。
|
||||
"""
|
||||
|
||||
FACT_TYPES = {"fact", "preference", "goal", "habit"}
|
||||
|
||||
|
||||
def _parse_fact_line(line: str) -> tuple[str, str] | None:
|
||||
"""解析一行记忆: [fact] 内容 -> (type, content)"""
|
||||
m = re.match(r"\[(\w+)\]\s*(.+)", line.strip())
|
||||
if m and m.group(1) in FACT_TYPES:
|
||||
return m.group(1), m.group(2).strip()
|
||||
return None
|
||||
# ———— 长期记忆: 基于 Mem0 ————
|
||||
|
||||
|
||||
async def extract_user_memories(
|
||||
@@ -151,55 +266,34 @@ async def extract_user_memories(
|
||||
user_id: str,
|
||||
conversation_id: str,
|
||||
messages: list[Message],
|
||||
) -> list[UserMemory]:
|
||||
"""从对话中提取用户记忆并保存"""
|
||||
) -> list[dict]:
|
||||
"""
|
||||
从对话中提取用户记忆并存储到 Mem0。
|
||||
Mem0 会自动处理:
|
||||
- 事实提取
|
||||
- 时间线追踪
|
||||
- 矛盾解决
|
||||
- 遗忘机制
|
||||
"""
|
||||
if len(messages) < 2:
|
||||
return []
|
||||
|
||||
history_text = "\n".join(
|
||||
f"[{m.role}] {m.content}" for m in messages[-10:]
|
||||
)
|
||||
history_text = "\n".join(f"[{m.role}] {m.content}" for m in messages[-10:])
|
||||
|
||||
llm = get_llm()
|
||||
from langchain_core.messages import HumanMessage, SystemMessage
|
||||
response = await llm.invoke([
|
||||
SystemMessage(content=EXTRACTION_PROMPT),
|
||||
HumanMessage(content=history_text),
|
||||
])
|
||||
|
||||
text = response.content.strip()
|
||||
if text == "无" or not text:
|
||||
return []
|
||||
|
||||
memories = []
|
||||
for line in text.split("\n"):
|
||||
parsed = _parse_fact_line(line)
|
||||
if not parsed:
|
||||
continue
|
||||
mem_type, content = parsed
|
||||
# 检查是否已有完全相同的记忆
|
||||
existing = await db.execute(
|
||||
select(UserMemory).where(
|
||||
UserMemory.user_id == user_id,
|
||||
UserMemory.content == content,
|
||||
)
|
||||
)
|
||||
if existing.scalar_one_or_none():
|
||||
continue
|
||||
|
||||
mem = UserMemory(
|
||||
try:
|
||||
mem0 = await get_mem0(db, user_id)
|
||||
result = mem0.add(
|
||||
messages=[{"role": m.role, "content": m.content} for m in messages[-10:]],
|
||||
user_id=user_id,
|
||||
memory_type=mem_type,
|
||||
content=content,
|
||||
importance=5,
|
||||
source_conversation_id=conversation_id,
|
||||
metadata={
|
||||
"conversation_id": conversation_id,
|
||||
"source": "jarvis_memory",
|
||||
},
|
||||
)
|
||||
db.add(mem)
|
||||
memories.append(mem)
|
||||
|
||||
if memories:
|
||||
await db.commit()
|
||||
return memories
|
||||
return result.get("results", [])
|
||||
except Exception as e:
|
||||
print(f"Mem0 extract error: {e}")
|
||||
return []
|
||||
|
||||
|
||||
async def recall_user_memories(
|
||||
@@ -207,41 +301,45 @@ async def recall_user_memories(
|
||||
user_id: str,
|
||||
query: str,
|
||||
top_k: int = 5,
|
||||
) -> list[UserMemory]:
|
||||
"""根据当前输入召回相关的用户记忆（简单关键词匹配）"""
|
||||
# 先尝试语义相似（通过 LLM 判断）
|
||||
# 降级: 直接从数据库取最近的重要记忆
|
||||
result = await db.execute(
|
||||
select(UserMemory)
|
||||
.where(UserMemory.user_id == user_id)
|
||||
.order_by(desc(UserMemory.importance), desc(UserMemory.recall_count))
|
||||
.limit(top_k)
|
||||
) -> list[dict]:
|
||||
"""
|
||||
根据当前输入召回相关的用户记忆。
|
||||
使用 Mem0 的语义搜索。
|
||||
"""
|
||||
try:
|
||||
mem0 = await get_mem0(db, user_id)
|
||||
results = mem0.search(
|
||||
query=query,
|
||||
filters={"user_id": user_id},
|
||||
limit=top_k,
|
||||
)
|
||||
memories = list(result.scalars().all())
|
||||
|
||||
# 重置召回标记
|
||||
for m in memories:
|
||||
m.is_recalled = False
|
||||
await db.commit()
|
||||
|
||||
return memories
|
||||
return results.get("results", [])
|
||||
except Exception as e:
|
||||
print(f"Mem0 search error: {e}")
|
||||
return []
|
||||
|
||||
|
||||
async def mark_memory_recalled(db: AsyncSession, memory_id: str):
|
||||
"""标记记忆已被召回使用"""
|
||||
result = await db.execute(
|
||||
select(UserMemory).where(UserMemory.id == memory_id)
|
||||
)
|
||||
mem = result.scalar_one_or_none()
|
||||
if mem:
|
||||
mem.is_recalled = True
|
||||
mem.recall_count = (mem.recall_count or 0) + 1
|
||||
mem.last_recalled_at = datetime.now(UTC)
|
||||
await db.commit()
|
||||
async def get_user_profile(db: AsyncSession, user_id: str) -> dict:
|
||||
"""
|
||||
获取用户画像。
|
||||
Mem0 的 profile API 会返回 static 和 dynamic facts。
|
||||
"""
|
||||
try:
|
||||
mem0 = await get_mem0(db, user_id)
|
||||
result = mem0.history(user_id=user_id)
|
||||
return {
|
||||
"memories": result.get("results", []),
|
||||
"static": [],
|
||||
"dynamic": [],
|
||||
}
|
||||
except Exception as e:
|
||||
print(f"Mem0 profile error: {e}")
|
||||
return {"memories": [], "static": [], "dynamic": []}
|
||||
|
||||
|
||||
# ———— 记忆组装: 供 Agent 使用的上下文 ————
|
||||
|
||||
|
||||
async def build_memory_context(
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
@@ -254,25 +352,22 @@ async def build_memory_context(
|
||||
"""
|
||||
parts = []
|
||||
|
||||
# 1. 用户画像（长期记忆）
|
||||
user_memories = await recall_user_memories(db, user_id, current_query, top_k=5)
|
||||
if user_memories:
|
||||
memories = await recall_user_memories(db, user_id, current_query, top_k=5)
|
||||
if memories:
|
||||
lines = []
|
||||
for m in user_memories:
|
||||
tag = f"[{m.memory_type}]"
|
||||
lines.append(f" {tag} {m.content}")
|
||||
await mark_memory_recalled(db, m.id)
|
||||
for m in memories:
|
||||
memory_text = m.get("memory", m.get("text", ""))
|
||||
if memory_text:
|
||||
lines.append(f" - {memory_text}")
|
||||
if lines:
|
||||
parts.append("【用户记忆】\n" + "\n".join(lines))
|
||||
|
||||
# 2. 对话摘要（中期记忆）
|
||||
summaries = await get_summaries(db, conversation_id)
|
||||
if summaries:
|
||||
# 只取最近2条
|
||||
recent = summaries[-2:]
|
||||
lines = [f"[对话摘要{i + 1}] {s.summary_text}" for i, s in enumerate(recent)]
|
||||
parts.append("【之前对话摘要】\n" + "\n".join(lines))
|
||||
|
||||
# 3. 知识大脑（长期项目记忆）
|
||||
brain_memories = await BrainService(db).recall_memories(user_id, current_query, top_k=3)
|
||||
if brain_memories:
|
||||
lines = []
|
||||
@@ -292,7 +387,7 @@ async def try_auto_summarize(
|
||||
) -> bool:
|
||||
"""
|
||||
检查是否需要摘要，如果需要则生成并保存。
|
||||
返回是否执行了摘要。
|
||||
同时将对话内容存入 Mem0 进行记忆提取。
|
||||
"""
|
||||
if not await should_summarize(db, conversation_id):
|
||||
return False
|
||||
@@ -306,8 +401,39 @@ async def try_auto_summarize(
|
||||
turn_count = await get_conversation_turn_count(db, conversation_id)
|
||||
await save_summary(db, user_id, conversation_id, summary_text, turn_count)
|
||||
|
||||
# 同时提取用户记忆
|
||||
await extract_user_memories(db, user_id, conversation_id, messages)
|
||||
return True
|
||||
except Exception:
|
||||
except Exception as e:
|
||||
print(f"Auto summarize error: {e}")
|
||||
return False
|
||||
|
||||
|
||||
async def forget_memory(db: AsyncSession, user_id: str, memory_id: str) -> bool:
|
||||
"""
|
||||
主动遗忘某条记忆。
|
||||
"""
|
||||
try:
|
||||
mem0 = await get_mem0(db, user_id)
|
||||
mem0.delete(memory_id, user_id=user_id)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"Mem0 delete error: {e}")
|
||||
return False
|
||||
|
||||
|
||||
async def update_memory(
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
memory_id: str,
|
||||
content: str,
|
||||
) -> bool:
|
||||
"""
|
||||
更新某条记忆。Mem0 会自动处理矛盾检测。
|
||||
"""
|
||||
try:
|
||||
mem0 = await get_mem0(db, user_id)
|
||||
mem0.update(memory_id, content, user_id=user_id)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f"Mem0 update error: {e}")
|
||||
return False
|
||||
|
||||
@@ -99,46 +99,55 @@ async def update_scheduler_config(user_id: str, config: dict, db: AsyncSession)
|
||||
|
||||
|
||||
async def test_llm_connection(
|
||||
provider: str,
|
||||
provider: str | None,
|
||||
model: str,
|
||||
base_url: str,
|
||||
api_key: str
|
||||
api_key: str,
|
||||
) -> dict:
|
||||
"""测试 LLM 连接"""
|
||||
try:
|
||||
# base_url-first: provider 可省略
|
||||
from app.services.llm_service import normalize_provider_name
|
||||
|
||||
effective_provider = normalize_provider_name({
|
||||
"provider": provider,
|
||||
"model": model,
|
||||
"base_url": base_url,
|
||||
})
|
||||
|
||||
# 根据不同 provider 创建临时 LLM 实例并测试
|
||||
if provider == "openai":
|
||||
if effective_provider in {"openai", "custom", "minimax", "kimi", "qwen"}:
|
||||
from langchain_openai import ChatOpenAI
|
||||
llm = ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or None,
|
||||
timeout=30
|
||||
timeout=30,
|
||||
)
|
||||
elif provider == "claude":
|
||||
elif effective_provider == "claude":
|
||||
from langchain_anthropic import ChatAnthropic
|
||||
llm = ChatAnthropic(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
timeout=30
|
||||
timeout=30,
|
||||
)
|
||||
elif provider == "ollama":
|
||||
elif effective_provider == "ollama":
|
||||
from langchain_ollama import ChatOllama
|
||||
llm = ChatOllama(
|
||||
base_url=base_url or "http://localhost:11434",
|
||||
model=model,
|
||||
timeout=30
|
||||
timeout=30,
|
||||
)
|
||||
elif provider == "deepseek":
|
||||
elif effective_provider == "deepseek":
|
||||
from langchain_openai import ChatOpenAI
|
||||
llm = ChatOpenAI(
|
||||
api_key=api_key,
|
||||
model=model,
|
||||
base_url=base_url or "https://api.deepseek.com/v1",
|
||||
timeout=30
|
||||
timeout=30,
|
||||
)
|
||||
else:
|
||||
return {"success": False, "error": f"不支持的 provider: {provider}"}
|
||||
return {"success": False, "error": f"不支持的 endpoint/provider: {effective_provider}"}
|
||||
|
||||
# 简单测试调用
|
||||
from langchain_core.messages import HumanMessage
|
||||
|
||||
@@ -50,27 +50,21 @@ class SkillService:
|
||||
"""
|
||||
列出用户可访问的技能：自己的 + 市场的 + 团队的
|
||||
"""
|
||||
# 查询条件：自己的 或者 市场公开的 或者 团队的
|
||||
conditions = [
|
||||
access_scope = or_(
|
||||
Skill.owner_id == user_id,
|
||||
Skill.visibility == "market",
|
||||
Skill.team_id == user_id,
|
||||
]
|
||||
)
|
||||
|
||||
filters = [access_scope, Skill.is_active == True]
|
||||
|
||||
# 如果提供了 agent_type 过滤
|
||||
if agent_type:
|
||||
conditions.append(Skill.agent_type == agent_type)
|
||||
filters.append(Skill.agent_type == agent_type)
|
||||
|
||||
# 如果提供了 visibility 过滤
|
||||
if visibility:
|
||||
conditions.append(Skill.visibility == visibility)
|
||||
filters.append(Skill.visibility == visibility)
|
||||
|
||||
query = select(Skill).where(
|
||||
and_(
|
||||
or_(*conditions),
|
||||
Skill.is_active == True
|
||||
)
|
||||
)
|
||||
query = select(Skill).where(and_(*filters))
|
||||
|
||||
result = await self.db.execute(query)
|
||||
return list(result.scalars().all())
|
||||
|
||||
@@ -1,4 +1,8 @@
|
||||
from datetime import datetime, UTC
|
||||
from time import monotonic
|
||||
import platform
|
||||
import socket
|
||||
import subprocess
|
||||
|
||||
try:
|
||||
import psutil
|
||||
@@ -7,21 +11,119 @@ except ModuleNotFoundError: # pragma: no cover - optional runtime dependency fa
|
||||
|
||||
|
||||
class SystemService:
|
||||
_last_net_bytes_sent: int | None = None
|
||||
_last_net_bytes_recv: int | None = None
|
||||
_last_net_sample_at: float | None = None
|
||||
|
||||
def _get_network_rates(self) -> tuple[float, float]:
|
||||
counters = psutil.net_io_counters()
|
||||
now = monotonic()
|
||||
|
||||
if (
|
||||
self.__class__._last_net_sample_at is None
|
||||
or self.__class__._last_net_bytes_sent is None
|
||||
or self.__class__._last_net_bytes_recv is None
|
||||
):
|
||||
self.__class__._last_net_bytes_sent = counters.bytes_sent
|
||||
self.__class__._last_net_bytes_recv = counters.bytes_recv
|
||||
self.__class__._last_net_sample_at = now
|
||||
return 0.0, 0.0
|
||||
|
||||
elapsed = max(now - self.__class__._last_net_sample_at, 1e-6)
|
||||
upload_bps = max(counters.bytes_sent - self.__class__._last_net_bytes_sent, 0) / elapsed
|
||||
download_bps = max(counters.bytes_recv - self.__class__._last_net_bytes_recv, 0) / elapsed
|
||||
|
||||
self.__class__._last_net_bytes_sent = counters.bytes_sent
|
||||
self.__class__._last_net_bytes_recv = counters.bytes_recv
|
||||
self.__class__._last_net_sample_at = now
|
||||
|
||||
return round(upload_bps, 1), round(download_bps, 1)
|
||||
|
||||
def _get_gpu_status(self) -> dict:
|
||||
empty = {
|
||||
'gpu_name': None,
|
||||
'gpu_memory_total_mb': None,
|
||||
'gpu_memory_used_mb': None,
|
||||
'gpu_util_percent': None,
|
||||
}
|
||||
|
||||
try:
|
||||
result = subprocess.run(
|
||||
[
|
||||
'nvidia-smi',
|
||||
'--query-gpu=name,memory.total,memory.used,utilization.gpu',
|
||||
'--format=csv,noheader,nounits',
|
||||
],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
encoding='utf-8',
|
||||
timeout=2,
|
||||
check=False,
|
||||
)
|
||||
except (FileNotFoundError, subprocess.SubprocessError, OSError):
|
||||
return empty
|
||||
|
||||
if result.returncode != 0 or not result.stdout.strip():
|
||||
return empty
|
||||
|
||||
first_line = result.stdout.strip().splitlines()[0]
|
||||
parts = [part.strip() for part in first_line.split(',')]
|
||||
if len(parts) < 4:
|
||||
return empty
|
||||
|
||||
def parse_number(value: str) -> float | None:
|
||||
try:
|
||||
return float(value)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
|
||||
return {
|
||||
'gpu_name': parts[0] or None,
|
||||
'gpu_memory_total_mb': parse_number(parts[1]),
|
||||
'gpu_memory_used_mb': parse_number(parts[2]),
|
||||
'gpu_util_percent': parse_number(parts[3]),
|
||||
}
|
||||
|
||||
def get_status(self) -> dict:
|
||||
if psutil is None:
|
||||
return {
|
||||
'cpu_percent': 0.0,
|
||||
'memory_percent': 0.0,
|
||||
'disk_percent': 0.0,
|
||||
'disk_used_gb': 0.0,
|
||||
'disk_total_gb': 0.0,
|
||||
'network_upload_bps': 0.0,
|
||||
'network_download_bps': 0.0,
|
||||
'system_name': platform.system(),
|
||||
'system_version': platform.version(),
|
||||
'hostname': socket.gethostname(),
|
||||
'uptime_seconds': 0.0,
|
||||
'gpu_name': None,
|
||||
'gpu_memory_total_mb': None,
|
||||
'gpu_memory_used_mb': None,
|
||||
'gpu_util_percent': None,
|
||||
'timestamp': datetime.now(UTC).isoformat(),
|
||||
}
|
||||
|
||||
cpu_percent = psutil.cpu_percent(interval=None)
|
||||
memory = psutil.virtual_memory()
|
||||
disk = psutil.disk_usage('/')
|
||||
upload_bps, download_bps = self._get_network_rates()
|
||||
gpu_status = self._get_gpu_status()
|
||||
boot_time = psutil.boot_time()
|
||||
now_ts = datetime.now(UTC).timestamp()
|
||||
return {
|
||||
'cpu_percent': round(cpu_percent, 1),
|
||||
'memory_percent': round(memory.percent, 1),
|
||||
'disk_percent': round(disk.percent, 1),
|
||||
'disk_used_gb': round(disk.used / (1024 ** 3), 1),
|
||||
'disk_total_gb': round(disk.total / (1024 ** 3), 1),
|
||||
'network_upload_bps': upload_bps,
|
||||
'network_download_bps': download_bps,
|
||||
'system_name': platform.system(),
|
||||
'system_version': platform.version(),
|
||||
'hostname': socket.gethostname(),
|
||||
'uptime_seconds': round(max(now_ts - boot_time, 0.0), 1),
|
||||
**gpu_status,
|
||||
'timestamp': datetime.now(UTC).isoformat(),
|
||||
}
|
||||
|
||||
124
backend/app/services/web_search_service.py
Normal file
124
backend/app/services/web_search_service.py
Normal file
@@ -0,0 +1,124 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Literal
|
||||
from urllib.parse import urlparse
|
||||
|
||||
import httpx
|
||||
|
||||
from app.config import settings
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class WebSearchResult:
|
||||
title: str
|
||||
url: str
|
||||
snippet: str
|
||||
source: str | None = None
|
||||
published_at: str | None = None
|
||||
|
||||
|
||||
class WebSearchError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class WebSearchConfigurationError(WebSearchError):
|
||||
pass
|
||||
|
||||
|
||||
class WebSearchRequestError(WebSearchError):
|
||||
pass
|
||||
|
||||
|
||||
class WebSearchService:
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
enabled: bool | None = None,
|
||||
provider: str | None = None,
|
||||
base_url: str | None = None,
|
||||
default_limit: int | None = None,
|
||||
timeout_seconds: int | None = None,
|
||||
auth_type: Literal['none', 'bearer', 'basic'] | str | None = None,
|
||||
auth_token: str | None = None,
|
||||
basic_user: str | None = None,
|
||||
basic_password: str | None = None,
|
||||
):
|
||||
self.enabled = settings.WEB_SEARCH_ENABLED if enabled is None else enabled
|
||||
self.provider = (provider or settings.WEB_SEARCH_PROVIDER).strip().lower()
|
||||
self.base_url = (base_url or settings.SEARXNG_BASE_URL).strip().rstrip('/')
|
||||
self.default_limit = max(1, min(default_limit or settings.WEB_SEARCH_DEFAULT_LIMIT, 10))
|
||||
self.timeout_seconds = max(1, timeout_seconds or settings.WEB_SEARCH_TIMEOUT_SECONDS)
|
||||
self.auth_type = str(auth_type or settings.SEARXNG_AUTH_TYPE or 'none').strip().lower()
|
||||
self.auth_token = auth_token if auth_token is not None else settings.SEARXNG_AUTH_TOKEN
|
||||
self.basic_user = basic_user if basic_user is not None else settings.SEARXNG_BASIC_USER
|
||||
self.basic_password = basic_password if basic_password is not None else settings.SEARXNG_BASIC_PASSWORD
|
||||
|
||||
async def search(self, query: str, limit: int | None = None) -> list[WebSearchResult]:
|
||||
normalized_query = (query or '').strip()
|
||||
if not self.enabled or not self.base_url:
|
||||
raise WebSearchConfigurationError('网页搜索未启用或未配置')
|
||||
if self.provider != 'searxng':
|
||||
raise WebSearchConfigurationError(f'不支持的网页搜索 provider: {self.provider}')
|
||||
if not normalized_query:
|
||||
raise WebSearchRequestError('搜索关键词不能为空')
|
||||
|
||||
parsed = urlparse(self.base_url)
|
||||
if parsed.scheme not in {'http', 'https'} or not parsed.netloc:
|
||||
raise WebSearchConfigurationError('SEARXNG_BASE_URL 配置无效')
|
||||
|
||||
params = {
|
||||
'q': normalized_query,
|
||||
'format': 'json',
|
||||
'language': 'zh-CN',
|
||||
'safesearch': 1,
|
||||
}
|
||||
headers = self._build_headers()
|
||||
timeout = httpx.Timeout(float(self.timeout_seconds), connect=min(float(self.timeout_seconds), 5.0))
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=timeout) as client:
|
||||
response = await client.get(f'{self.base_url}/search', params=params, headers=headers)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
except httpx.HTTPError as exc:
|
||||
raise WebSearchRequestError('SearxNG 请求失败') from exc
|
||||
except ValueError as exc:
|
||||
raise WebSearchRequestError('SearxNG 返回了无效 JSON') from exc
|
||||
|
||||
raw_results = payload.get('results') if isinstance(payload, dict) else None
|
||||
if not isinstance(raw_results, list):
|
||||
return []
|
||||
|
||||
results: list[WebSearchResult] = []
|
||||
target_limit = max(1, min(limit or self.default_limit, 10))
|
||||
for item in raw_results:
|
||||
if not isinstance(item, dict):
|
||||
continue
|
||||
title = str(item.get('title') or '').strip()
|
||||
url = str(item.get('url') or '').strip()
|
||||
snippet = str(item.get('content') or item.get('snippet') or '').strip()
|
||||
if not title or not url:
|
||||
continue
|
||||
results.append(
|
||||
WebSearchResult(
|
||||
title=title,
|
||||
url=url,
|
||||
snippet=snippet,
|
||||
source=str(item.get('engine') or item.get('source') or '').strip() or None,
|
||||
published_at=str(item.get('publishedDate') or item.get('published_at') or '').strip() or None,
|
||||
)
|
||||
)
|
||||
if len(results) >= target_limit:
|
||||
break
|
||||
return results
|
||||
|
||||
def _build_headers(self) -> dict[str, str]:
|
||||
if self.auth_type == 'bearer' and self.auth_token:
|
||||
return {'Authorization': f'Bearer {self.auth_token}'}
|
||||
if self.auth_type == 'basic' and self.basic_user and self.basic_password:
|
||||
credentials = httpx.BasicAuth(self.basic_user, self.basic_password)
|
||||
request = httpx.Request('GET', self.base_url)
|
||||
credentials.auth_flow(request)
|
||||
return dict(request.headers)
|
||||
return {}
|
||||
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|
||||
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|
||||
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|
||||
%PDF-1.4 bad
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
%PDF-1.4 bad
|
||||
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|
||||
%PDF-1.4 bad
|
||||
@@ -1 +0,0 @@
|
||||
bad
|
||||
@@ -1 +0,0 @@
|
||||
bad
|
||||
@@ -1 +0,0 @@
|
||||
bad
|
||||
@@ -1 +0,0 @@
|
||||
%PDF-1.4 bad
|
||||
@@ -1 +0,0 @@
|
||||
%PDF-1.4 bad
|
||||
@@ -27,6 +27,9 @@ dependencies = [
|
||||
"llama-index-vector-stores-chroma>=0.3.0",
|
||||
"chromadb>=0.5.0",
|
||||
|
||||
# Memory
|
||||
"mem0ai>=1.0.0",
|
||||
|
||||
# 数据库
|
||||
"sqlalchemy>=2.0.0",
|
||||
"aiosqlite>=0.20.0",
|
||||
|
||||
@@ -1,9 +1,122 @@
|
||||
from langchain_core.messages import HumanMessage
|
||||
from types import SimpleNamespace
|
||||
|
||||
from app.agents.graph import master_node
|
||||
from langchain_core.messages import AIMessage, HumanMessage
|
||||
|
||||
from app.agents.graph import (
|
||||
_choose_sub_commander,
|
||||
_parse_json_action,
|
||||
_route_agent_from_user_query,
|
||||
_run_sub_commander,
|
||||
master_node,
|
||||
)
|
||||
from app.agents.tools.time_reasoning import resolve_time_expression
|
||||
from app.agents.state import AgentRole
|
||||
|
||||
|
||||
|
||||
|
||||
def _base_state(message: str, user_llm_config: dict | None = None) -> dict:
|
||||
return {
|
||||
'messages': [HumanMessage(content=message)],
|
||||
'user_id': 'u1',
|
||||
'conversation_id': 'c1',
|
||||
'current_agent': AgentRole.MASTER,
|
||||
'active_agents': [AgentRole.MASTER],
|
||||
'current_sub_commander': None,
|
||||
'active_sub_commanders': [],
|
||||
'sub_commander_trace': [],
|
||||
'pending_tasks': [],
|
||||
'completed_tasks': [],
|
||||
'tool_calls': [],
|
||||
'last_tool_result': None,
|
||||
'action_results': [],
|
||||
'created_entities': [],
|
||||
'tool_strategy_used': None,
|
||||
'provider_capabilities': None,
|
||||
'fallback_parse_error': None,
|
||||
'knowledge_context': None,
|
||||
'graph_context': None,
|
||||
'schedule_context_summary': None,
|
||||
'plan': None,
|
||||
'plan_steps': [],
|
||||
'analysis_report': None,
|
||||
'final_response': None,
|
||||
'should_respond': True,
|
||||
'memory_context': None,
|
||||
'current_datetime_context': 'CURRENT_TIME: 2026-03-28T12:00:00+08:00',
|
||||
'current_datetime_reference': {'current_time_iso': '2026-03-28T12:00:00+08:00', 'current_date_iso': '2026-03-28', 'timezone': 'UTC'},
|
||||
'user_llm_config': user_llm_config,
|
||||
}
|
||||
|
||||
|
||||
class FakeFallbackLLM:
|
||||
def __init__(self, first_content: str, followup_content: str = '已创建提醒：开会，时间为 2026-03-29 09:00（按当前时间理解为“明天早上9点”）。'):
|
||||
self.first_content = first_content
|
||||
self.followup_content = followup_content
|
||||
self.calls = 0
|
||||
|
||||
async def ainvoke(self, messages):
|
||||
self.calls += 1
|
||||
if self.calls == 1:
|
||||
return AIMessage(content=self.first_content)
|
||||
return AIMessage(content=self.followup_content)
|
||||
|
||||
def bind_tools(self, tools):
|
||||
raise AssertionError('bind_tools should not be called in JSON fallback mode')
|
||||
|
||||
|
||||
class FakeNativeBoundLLM:
|
||||
async def ainvoke(self, messages):
|
||||
return AIMessage(
|
||||
content='',
|
||||
tool_calls=[
|
||||
{
|
||||
'id': 'call_1',
|
||||
'name': 'create_reminder',
|
||||
'args': {'title': '开会', 'reminder_at': '明天 09:00'},
|
||||
}
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class FakeNativeLLM:
|
||||
def __init__(self):
|
||||
self.bound = FakeNativeBoundLLM()
|
||||
self.tool_binding_count = 0
|
||||
self.calls = 0
|
||||
self._jarvis_provider_capabilities = SimpleNamespace(provider='openai', supports_native_tools=True, preferred_tool_strategy='native')
|
||||
|
||||
def bind_tools(self, tools):
|
||||
self.tool_binding_count += 1
|
||||
return self.bound
|
||||
|
||||
async def ainvoke(self, messages):
|
||||
self.calls += 1
|
||||
return AIMessage(content='已创建提醒：开会，时间为 2026-03-29 09:00（按当前时间理解为“明天早上9点”）。')
|
||||
|
||||
|
||||
class FakeTool:
|
||||
def __init__(self, name: str, result: str):
|
||||
self.name = name
|
||||
self.result = result
|
||||
self.invocations: list[dict] = []
|
||||
|
||||
def invoke(self, args: dict):
|
||||
self.invocations.append(args)
|
||||
return self.result
|
||||
|
||||
|
||||
class CapturingLLM:
|
||||
def __init__(self, content: str = '{"mode":"final","final_response":"好的。"}'):
|
||||
self.content = content
|
||||
self.messages = None
|
||||
self._jarvis_provider_capabilities = SimpleNamespace(provider='ollama', supports_native_tools=False, preferred_tool_strategy='json_fallback')
|
||||
|
||||
async def ainvoke(self, messages):
|
||||
self.messages = messages
|
||||
return AIMessage(content=self.content)
|
||||
|
||||
|
||||
class FailIfCalledLLM:
|
||||
async def ainvoke(self, messages):
|
||||
raise AssertionError('LLM should not be called for simple greetings')
|
||||
@@ -71,6 +184,68 @@ async def test_master_node_returns_stable_reply_for_identity_question(monkeypatc
|
||||
assert result['active_agents'] == [AgentRole.MASTER]
|
||||
|
||||
|
||||
async def test_master_node_returns_stable_reply_for_identity_question_with_punctuation(monkeypatch):
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: FailIfCalledLLM())
|
||||
|
||||
state = {
|
||||
'messages': [HumanMessage(content='你是谁？')],
|
||||
'user_id': 'u1',
|
||||
'conversation_id': 'c1',
|
||||
'current_agent': AgentRole.MASTER,
|
||||
'active_agents': [AgentRole.MASTER],
|
||||
'pending_tasks': [],
|
||||
'completed_tasks': [],
|
||||
'tool_calls': [],
|
||||
'last_tool_result': None,
|
||||
'knowledge_context': None,
|
||||
'graph_context': None,
|
||||
'plan': None,
|
||||
'plan_steps': [],
|
||||
'analysis_report': None,
|
||||
'final_response': None,
|
||||
'should_respond': True,
|
||||
'memory_context': None,
|
||||
'user_llm_config': None,
|
||||
}
|
||||
|
||||
result = await master_node(state)
|
||||
|
||||
assert result['final_response'] == '我是 Jarvis。\n\n比起做一个泛泛的助手，我更像您的判断型协作伙伴：帮您看清问题、压缩路径、把事情往前推进。'
|
||||
assert result['current_agent'] == AgentRole.MASTER
|
||||
assert result['active_agents'] == [AgentRole.MASTER]
|
||||
|
||||
|
||||
async def test_master_node_returns_stable_reply_for_identity_question_with_particle(monkeypatch):
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: FailIfCalledLLM())
|
||||
|
||||
state = {
|
||||
'messages': [HumanMessage(content='你是谁啊')],
|
||||
'user_id': 'u1',
|
||||
'conversation_id': 'c1',
|
||||
'current_agent': AgentRole.MASTER,
|
||||
'active_agents': [AgentRole.MASTER],
|
||||
'pending_tasks': [],
|
||||
'completed_tasks': [],
|
||||
'tool_calls': [],
|
||||
'last_tool_result': None,
|
||||
'knowledge_context': None,
|
||||
'graph_context': None,
|
||||
'plan': None,
|
||||
'plan_steps': [],
|
||||
'analysis_report': None,
|
||||
'final_response': None,
|
||||
'should_respond': True,
|
||||
'memory_context': None,
|
||||
'user_llm_config': None,
|
||||
}
|
||||
|
||||
result = await master_node(state)
|
||||
|
||||
assert result['final_response'] == '我是 Jarvis。\n\n比起做一个泛泛的助手，我更像您的判断型协作伙伴：帮您看清问题、压缩路径、把事情往前推进。'
|
||||
assert result['current_agent'] == AgentRole.MASTER
|
||||
assert result['active_agents'] == [AgentRole.MASTER]
|
||||
|
||||
|
||||
async def test_master_node_returns_stable_reply_for_capability_question(monkeypatch):
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: FailIfCalledLLM())
|
||||
|
||||
@@ -100,3 +275,196 @@ async def test_master_node_returns_stable_reply_for_capability_question(monkeypa
|
||||
assert result['final_response'] == '主要做三件事。\n- 帮您判断：看问题本质、梳理取舍、给出方向\n- 帮您收束：把复杂内容理顺，把重点拎出来\n- 帮您推进：拆任务、定步骤、把下一步变清楚\n\n如果您现在有具体目标，我可以直接进入处理。'
|
||||
assert result['current_agent'] == AgentRole.MASTER
|
||||
assert result['active_agents'] == [AgentRole.MASTER]
|
||||
|
||||
|
||||
def test_choose_sub_commander_routes_schedule_requests_to_schedule_planning():
|
||||
assert _choose_sub_commander(AgentRole.SCHEDULE_PLANNER, '帮我安排一下这周计划') == 'schedule_planning'
|
||||
|
||||
|
||||
def test_choose_sub_commander_routes_focus_requests_to_schedule_analysis():
|
||||
assert _choose_sub_commander(AgentRole.SCHEDULE_PLANNER, '基于最近对话帮我判断该聚焦什么') == 'schedule_analysis'
|
||||
|
||||
|
||||
def test_route_agent_from_user_query_routes_knowledge_requests_to_librarian():
|
||||
assert _route_agent_from_user_query('帮我搜索知识库里的项目资料') == AgentRole.LIBRARIAN
|
||||
|
||||
|
||||
def test_route_agent_from_user_query_routes_schedule_requests_to_schedule_planner():
|
||||
assert _route_agent_from_user_query('明天提醒我开会') == AgentRole.SCHEDULE_PLANNER
|
||||
|
||||
|
||||
def test_route_agent_from_user_query_routes_explicit_month_day_milestone_to_schedule_planner():
|
||||
assert _route_agent_from_user_query('3月29日，对话系统交付节点') == AgentRole.SCHEDULE_PLANNER
|
||||
|
||||
|
||||
def test_choose_sub_commander_routes_explicit_month_day_milestone_to_schedule_planning():
|
||||
assert _choose_sub_commander(AgentRole.SCHEDULE_PLANNER, '3月29日，对话系统交付节点') == 'schedule_planning'
|
||||
|
||||
|
||||
|
||||
|
||||
def test_parse_json_action_extracts_tool_calls_from_fenced_json():
|
||||
parsed = _parse_json_action(
|
||||
'```json\n{"mode":"tool_call","tool_calls":[{"name":"create_reminder","arguments":{"title":"开会","reminder_at":"明天 09:00"}}]}\n```',
|
||||
['create_reminder'],
|
||||
)
|
||||
|
||||
assert parsed == {
|
||||
'mode': 'tool_call',
|
||||
'tool_calls': [
|
||||
{
|
||||
'name': 'create_reminder',
|
||||
'args': {'title': '开会', 'reminder_at': '明天 09:00'},
|
||||
'reason': None,
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def test_parse_json_action_returns_none_for_invalid_or_unknown_payload():
|
||||
assert _parse_json_action('not json', ['create_reminder']) is None
|
||||
assert _parse_json_action('{"mode":"tool_call","tool_calls":[{"name":"unknown","arguments":{}}]}', ['create_reminder']) is None
|
||||
|
||||
|
||||
def test_parse_json_action_tolerates_prefix_and_suffix_text():
|
||||
parsed = _parse_json_action(
|
||||
'好的，下面是 JSON：\n```json\n{"mode":"tool_call","tool_calls":[{"name":"create_reminder","arguments":{"title":"开会","reminder_at":"明天 09:00"}}]}\n```\n谢谢',
|
||||
['create_reminder'],
|
||||
)
|
||||
assert parsed is not None
|
||||
assert parsed['mode'] == 'tool_call'
|
||||
assert parsed['tool_calls'][0]['name'] == 'create_reminder'
|
||||
|
||||
|
||||
def test_parse_json_action_accepts_parameters_alias_for_tool_calls():
|
||||
parsed = _parse_json_action(
|
||||
'{"mode":"tool_call","tool_calls":[{"name":"create_reminder","parameters":{"title":"收被子","reminder_at":"2026-03-29T09:00:00+08:00"}}]}',
|
||||
['create_reminder'],
|
||||
)
|
||||
|
||||
assert parsed == {
|
||||
'mode': 'tool_call',
|
||||
'tool_calls': [
|
||||
{
|
||||
'name': 'create_reminder',
|
||||
'args': {'title': '收被子', 'reminder_at': '2026-03-29T09:00:00+08:00'},
|
||||
'reason': None,
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
async def test_run_sub_commander_uses_json_fallback_for_non_native_provider(monkeypatch):
|
||||
fake_llm = FakeFallbackLLM(
|
||||
'{"mode":"tool_call","tool_calls":[{"name":"create_reminder","arguments":{"title":"开会","reminder_at":"明天 09:00"}}]}'
|
||||
)
|
||||
fake_tool = FakeTool('create_reminder', '成功创建 reminder: 开会 @ 明天 09:00')
|
||||
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: fake_llm)
|
||||
monkeypatch.setitem(
|
||||
__import__('app.agents.graph', fromlist=['SUB_COMMANDER_TOOLSETS']).SUB_COMMANDER_TOOLSETS,
|
||||
'schedule_planning',
|
||||
[fake_tool],
|
||||
)
|
||||
|
||||
state = _base_state('明天 9 点提醒我开会', {'provider': 'ollama', 'model': 'qwen2.5'})
|
||||
state['current_agent'] = AgentRole.SCHEDULE_PLANNER
|
||||
|
||||
result = await _run_sub_commander(
|
||||
state,
|
||||
AgentRole.SCHEDULE_PLANNER,
|
||||
'manager prompt',
|
||||
'明天 9 点提醒我开会',
|
||||
use_tools=True,
|
||||
)
|
||||
|
||||
assert result['tool_strategy_used'] == 'json_fallback'
|
||||
assert fake_tool.invocations == [{'title': '开会', 'reminder_at': '2026-03-29T09:00:00'}]
|
||||
assert result['tool_calls'][0]['name'] == 'create_reminder'
|
||||
assert result['created_entities'][0]['type'] == 'reminder'
|
||||
assert result['fallback_parse_error'] is None
|
||||
assert result['final_response'] == '已创建提醒：开会，时间为 2026-03-29 09:00（按当前时间理解为“明天早上9点”）。'
|
||||
|
||||
|
||||
async def test_run_sub_commander_includes_current_datetime_context_in_system_messages(monkeypatch):
|
||||
fake_llm = CapturingLLM('{"mode":"final","final_response":"好的。"}')
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: fake_llm)
|
||||
|
||||
state = _base_state('明天 9 点提醒我开会', {'provider': 'ollama', 'model': 'qwen2.5'})
|
||||
state['current_agent'] = AgentRole.SCHEDULE_PLANNER
|
||||
state['current_datetime_context'] = 'CURRENT_TIME: 2026-03-28T12:00:00+08:00'
|
||||
|
||||
await _run_sub_commander(
|
||||
state,
|
||||
AgentRole.SCHEDULE_PLANNER,
|
||||
'manager prompt',
|
||||
'明天 9 点提醒我开会',
|
||||
use_tools=True,
|
||||
)
|
||||
|
||||
assert fake_llm.messages is not None
|
||||
assert any(
|
||||
getattr(m, 'type', None) == 'system' and 'CURRENT_TIME:' in str(getattr(m, 'content', ''))
|
||||
for m in fake_llm.messages
|
||||
)
|
||||
|
||||
|
||||
async def test_run_sub_commander_uses_web_search_in_json_fallback(monkeypatch):
|
||||
fake_llm = FakeFallbackLLM(
|
||||
'{"mode":"tool_call","tool_calls":[{"name":"web_search","arguments":{"query":"Jarvis 最新模型更新","top_k":2}}]}',
|
||||
'我查了外部网页，下面是最新结果摘要。',
|
||||
)
|
||||
fake_tool = FakeTool('web_search', '成功搜索到 2 条网页结果')
|
||||
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: fake_llm)
|
||||
monkeypatch.setitem(
|
||||
__import__('app.agents.graph', fromlist=['SUB_COMMANDER_TOOLSETS']).SUB_COMMANDER_TOOLSETS,
|
||||
'librarian_retrieval',
|
||||
[fake_tool],
|
||||
)
|
||||
|
||||
state = _base_state('帮我上网查一下 Jarvis 最新模型更新', {'provider': 'ollama', 'model': 'qwen2.5'})
|
||||
state['current_agent'] = AgentRole.LIBRARIAN
|
||||
|
||||
result = await _run_sub_commander(
|
||||
state,
|
||||
AgentRole.LIBRARIAN,
|
||||
'manager prompt',
|
||||
'帮我上网查一下 Jarvis 最新模型更新',
|
||||
use_tools=True,
|
||||
summary_target='knowledge_context',
|
||||
)
|
||||
|
||||
assert result['tool_strategy_used'] == 'json_fallback'
|
||||
assert fake_tool.invocations == [{'query': 'Jarvis 最新模型更新', 'top_k': 2}]
|
||||
assert result['tool_calls'][0]['name'] == 'web_search'
|
||||
assert result['last_tool_result'] == '[web_search] 成功搜索到 2 条网页结果'
|
||||
assert result['final_response'] == '我查了外部网页，下面是最新结果摘要。'
|
||||
|
||||
|
||||
fake_llm = FakeNativeLLM()
|
||||
fake_tool = FakeTool('create_reminder', '成功创建 reminder: 开会 @ 明天 09:00')
|
||||
|
||||
monkeypatch.setattr('app.agents.graph._get_llm_for_state', lambda state: fake_llm)
|
||||
monkeypatch.setitem(
|
||||
__import__('app.agents.graph', fromlist=['SUB_COMMANDER_TOOLSETS']).SUB_COMMANDER_TOOLSETS,
|
||||
'schedule_planning',
|
||||
[fake_tool],
|
||||
)
|
||||
|
||||
state = _base_state('明天 9 点提醒我开会', {'provider': 'openai', 'model': 'gpt-4o'})
|
||||
state['current_agent'] = AgentRole.SCHEDULE_PLANNER
|
||||
|
||||
result = await _run_sub_commander(
|
||||
state,
|
||||
AgentRole.SCHEDULE_PLANNER,
|
||||
'manager prompt',
|
||||
'明天 9 点提醒我开会',
|
||||
use_tools=True,
|
||||
)
|
||||
|
||||
assert result['tool_strategy_used'] == 'native'
|
||||
assert fake_llm.tool_binding_count == 1
|
||||
assert fake_tool.invocations == [{'title': '开会', 'reminder_at': '2026-03-29T09:00:00'}]
|
||||
assert result['created_entities'][0]['type'] == 'reminder'
|
||||
assert result['final_response'] == '已创建提醒：开会，时间为 2026-03-29 09:00（按当前时间理解为“明天早上9点”）。'
|
||||
|
||||
49
backend/tests/backend/app/agents/test_search_tools.py
Normal file
49
backend/tests/backend/app/agents/test_search_tools.py
Normal file
@@ -0,0 +1,49 @@
|
||||
from types import SimpleNamespace
|
||||
|
||||
import pytest
|
||||
|
||||
from app.agents.tools.search import web_search
|
||||
|
||||
|
||||
class FakeResult(SimpleNamespace):
|
||||
pass
|
||||
|
||||
|
||||
def test_web_search_tool_formats_results(monkeypatch):
|
||||
class FakeService:
|
||||
async def search(self, query: str, limit: int | None = None):
|
||||
assert query == 'Jarvis 最新更新'
|
||||
assert limit == 2
|
||||
return [
|
||||
FakeResult(
|
||||
title='Jarvis release notes',
|
||||
url='https://example.com/jarvis-release',
|
||||
snippet='Latest Jarvis changes.',
|
||||
source='duckduckgo',
|
||||
published_at='2026-03-29',
|
||||
)
|
||||
]
|
||||
|
||||
monkeypatch.setattr('app.services.web_search_service.WebSearchService', FakeService)
|
||||
|
||||
result = web_search.func('Jarvis 最新更新', top_k=2)
|
||||
|
||||
assert '[1] Jarvis release notes' in result
|
||||
assert '链接: https://example.com/jarvis-release' in result
|
||||
assert '来源: duckduckgo' in result
|
||||
assert '时间: 2026-03-29' in result
|
||||
assert '摘要: Latest Jarvis changes.' in result
|
||||
|
||||
|
||||
def test_web_search_tool_returns_stable_message_when_unavailable(monkeypatch):
|
||||
from app.services.web_search_service import WebSearchConfigurationError
|
||||
|
||||
class FakeService:
|
||||
async def search(self, query: str, limit: int | None = None):
|
||||
raise WebSearchConfigurationError('网页搜索未启用或未配置')
|
||||
|
||||
monkeypatch.setattr('app.services.web_search_service.WebSearchService', FakeService)
|
||||
|
||||
result = web_search.func('Jarvis')
|
||||
|
||||
assert result == '网页搜索不可用: 网页搜索未启用或未配置'
|
||||
277
backend/tests/backend/app/agents/test_task_tools.py
Normal file
277
backend/tests/backend/app/agents/test_task_tools.py
Normal file
@@ -0,0 +1,277 @@
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from unittest.mock import Mock
|
||||
|
||||
import pytest
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
|
||||
|
||||
sys.modules.setdefault("psutil", Mock())
|
||||
|
||||
import app.models # noqa: F401
|
||||
from app.models.goal import Goal
|
||||
from app.models.reminder import Reminder
|
||||
from app.models.task import Task, TaskPriority, TaskStatus
|
||||
from app.models.todo import DailyTodo
|
||||
from app.models.user import User
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def tool_env(tmp_path):
|
||||
db_path = tmp_path / "test_task_tools.db"
|
||||
engine = create_async_engine(f"sqlite+aiosqlite:///{db_path}", future=True)
|
||||
session_factory = async_sessionmaker(engine, expire_on_commit=False)
|
||||
|
||||
async with engine.begin() as conn:
|
||||
# 只创建本测试需要的表，避免全量 metadata 引入未注册的外键表。
|
||||
await conn.run_sync(User.metadata.create_all, tables=[
|
||||
User.__table__,
|
||||
Task.__table__,
|
||||
DailyTodo.__table__,
|
||||
Reminder.__table__,
|
||||
Goal.__table__,
|
||||
])
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username="tool_user",
|
||||
email="tool@example.com",
|
||||
hashed_password=get_password_hash("secret123"),
|
||||
full_name="Tool Tester",
|
||||
)
|
||||
session.add(user)
|
||||
await session.commit()
|
||||
await session.refresh(user)
|
||||
|
||||
try:
|
||||
yield {"session_factory": session_factory, "user_id": user.id}
|
||||
finally:
|
||||
await engine.dispose()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_task_accepts_content_and_date_aliases_and_persists_task(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = task_tools.create_task.func(content="完成对话系统", date="2026-03-28")
|
||||
|
||||
assert "任务创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
saved = (await session.execute(select(Task))).scalar_one()
|
||||
|
||||
assert saved.title == "完成对话系统"
|
||||
assert saved.description == "完成对话系统"
|
||||
assert saved.priority == TaskPriority.MEDIUM
|
||||
assert saved.status == TaskStatus.TODO
|
||||
assert saved.due_date == datetime(2026, 3, 28, 0, 0)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_schedule_task_accepts_content_and_date_aliases_and_sets_morning_due_date(tool_env, monkeypatch):
|
||||
from app.agents.tools import schedule as schedule_tools
|
||||
|
||||
monkeypatch.setattr(schedule_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(schedule_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = schedule_tools.create_schedule_task.func(content="完成对话系统", date="2026-03-28")
|
||||
|
||||
assert "任务创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
saved = (await session.execute(select(Task))).scalar_one()
|
||||
|
||||
assert saved.title == "完成对话系统"
|
||||
assert saved.description == "完成对话系统"
|
||||
assert saved.priority == TaskPriority.MEDIUM
|
||||
assert saved.status == TaskStatus.TODO
|
||||
assert saved.due_date == datetime(2026, 3, 28, 9, 0)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
("priority_input", "expected"),
|
||||
[
|
||||
(1, TaskPriority.LOW),
|
||||
(2, TaskPriority.MEDIUM),
|
||||
(3, TaskPriority.HIGH),
|
||||
(4, TaskPriority.URGENT),
|
||||
("urgent", TaskPriority.URGENT),
|
||||
],
|
||||
)
|
||||
async def test_create_task_normalizes_legacy_and_string_priorities(tool_env, monkeypatch, priority_input, expected):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = task_tools.create_task.func(title=f"priority-{priority_input}", priority=priority_input)
|
||||
|
||||
assert "任务创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
rows = (await session.execute(select(Task).order_by(Task.created_at.asc()))).scalars().all()
|
||||
|
||||
assert rows[-1].priority == expected
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_task_accepts_iso_datetime_due_date(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = task_tools.create_task.func(title="timed task", due_date="2026-03-28T15:30:00Z")
|
||||
|
||||
assert "任务创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
saved = (await session.execute(select(Task))).scalar_one()
|
||||
|
||||
assert saved.due_date == datetime(2026, 3, 28, 15, 30, 0)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_task_returns_failure_for_missing_title_and_content(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = task_tools.create_task.func()
|
||||
|
||||
assert result == "创建任务失败: title 不能为空"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_task_returns_failure_for_invalid_priority(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = task_tools.create_task.func(title="bad priority", priority="top")
|
||||
|
||||
assert "创建任务失败:" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_task_status_rejects_invalid_status(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
create_result = task_tools.create_task.func(title="status test")
|
||||
assert "任务创建成功" in create_result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
saved = (await session.execute(select(Task))).scalar_one()
|
||||
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tasks_filters_by_normalized_status_and_formats_values(tool_env, monkeypatch):
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
monkeypatch.setattr(task_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(task_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
task_tools.create_task.func(title="todo task", priority="high")
|
||||
task_tools.create_task.func(title="done task", priority="low")
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
rows = (await session.execute(select(Task).order_by(Task.created_at.asc()))).scalars().all()
|
||||
rows[1].status = TaskStatus.DONE
|
||||
await session.commit()
|
||||
|
||||
result = task_tools.get_tasks.func(status="done")
|
||||
|
||||
assert "done task" in result
|
||||
assert "todo task" not in result
|
||||
assert "状态:done" in result
|
||||
assert "优先级:low" in result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_schedule_reminder_accepts_datetime_description_and_at_aliases(tool_env, monkeypatch):
|
||||
from app.agents.tools import schedule as schedule_tools
|
||||
|
||||
monkeypatch.setattr(schedule_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(schedule_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = schedule_tools.create_reminder.func(
|
||||
title="收被子",
|
||||
description="提醒收被子",
|
||||
datetime="2026-03-29T09:00:00",
|
||||
time_zone="Asia/Shanghai",
|
||||
)
|
||||
|
||||
assert "提醒创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
saved = (await session.execute(select(Reminder))).scalar_one()
|
||||
|
||||
assert saved.title == "收被子"
|
||||
assert saved.note == "提醒收被子"
|
||||
assert saved.reminder_at == datetime(2026, 3, 29, 9, 0)
|
||||
|
||||
result = schedule_tools.create_reminder.func(
|
||||
content="收被子",
|
||||
datetime="2026-03-29T09:00:00+08:00",
|
||||
)
|
||||
|
||||
assert "提醒创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
rows = (await session.execute(select(Reminder).order_by(Reminder.created_at.asc()))).scalars().all()
|
||||
|
||||
assert rows[-1].title == "收被子"
|
||||
assert rows[-1].note is None
|
||||
assert rows[-1].reminder_at == datetime(2026, 3, 29, 9, 0)
|
||||
|
||||
result = schedule_tools.create_reminder.func(
|
||||
content="收被子",
|
||||
time="2026-03-29T09:00:00",
|
||||
time_zone="Asia/Shanghai",
|
||||
)
|
||||
|
||||
assert "提醒创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
rows = (await session.execute(select(Reminder).order_by(Reminder.created_at.asc()))).scalars().all()
|
||||
|
||||
assert rows[-1].title == "收被子"
|
||||
assert rows[-1].note is None
|
||||
assert rows[-1].reminder_at == datetime(2026, 3, 29, 9, 0)
|
||||
|
||||
result = schedule_tools.create_reminder.func(
|
||||
title="收被子",
|
||||
remind_at="2026-03-29T18:00:00",
|
||||
)
|
||||
|
||||
assert "提醒创建成功" in result
|
||||
|
||||
async with tool_env["session_factory"]() as session:
|
||||
rows = (await session.execute(select(Reminder).order_by(Reminder.created_at.asc()))).scalars().all()
|
||||
|
||||
assert rows[-1].title == "收被子"
|
||||
assert rows[-1].note is None
|
||||
assert rows[-1].reminder_at == datetime(2026, 3, 29, 18, 0)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_schedule_reminder_returns_failure_when_time_aliases_missing(tool_env, monkeypatch):
|
||||
from app.agents.tools import schedule as schedule_tools
|
||||
|
||||
monkeypatch.setattr(schedule_tools, "async_session", tool_env["session_factory"])
|
||||
monkeypatch.setattr(schedule_tools, "get_current_user", lambda: tool_env["user_id"])
|
||||
|
||||
result = schedule_tools.create_reminder.func(title="收被子")
|
||||
|
||||
assert result == "创建提醒失败: reminder_at 不能为空"
|
||||
94
backend/tests/backend/app/agents/test_time_reasoning_tool.py
Normal file
94
backend/tests/backend/app/agents/test_time_reasoning_tool.py
Normal file
@@ -0,0 +1,94 @@
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from app.agents.tools.time_reasoning import (
|
||||
extract_reference_datetime,
|
||||
normalize_tool_time_arguments,
|
||||
resolve_time_expression_data,
|
||||
)
|
||||
|
||||
|
||||
def test_extract_reference_datetime_from_current_time_context():
|
||||
context = '【当前时间】\n- current_time_utc: 2026-03-28T12:00:00+00:00\n- current_date_utc: 2026-03-28\n说明：解析相对时间时请以 current_time_utc 为准。'
|
||||
|
||||
result = extract_reference_datetime(context)
|
||||
|
||||
assert result == datetime(2026, 3, 28, 12, 0, tzinfo=UTC)
|
||||
|
||||
|
||||
def test_resolve_time_expression_data_normalizes_relative_datetime():
|
||||
payload = resolve_time_expression_data(
|
||||
'明天早上9点',
|
||||
current_datetime_context='CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
prefer='datetime',
|
||||
)
|
||||
|
||||
assert payload['grain'] == 'datetime'
|
||||
assert payload['resolved_date'] == '2026-03-29'
|
||||
assert payload['resolved_datetime'] == '2026-03-29T09:00:00'
|
||||
assert payload['assumed_time'] is False
|
||||
|
||||
|
||||
def test_resolve_time_expression_data_normalizes_relative_date_window():
|
||||
payload = resolve_time_expression_data(
|
||||
'下周一下午',
|
||||
current_datetime_context='CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
prefer='datetime',
|
||||
)
|
||||
|
||||
assert payload['resolved_date'] == '2026-03-30'
|
||||
assert payload['resolved_datetime'] == '2026-03-30T15:00:00'
|
||||
assert payload['assumed_time'] is True
|
||||
assert 'assumed_time' in payload['reason']
|
||||
|
||||
|
||||
def test_normalize_tool_time_arguments_converts_reminder_time_aliases():
|
||||
normalized = normalize_tool_time_arguments(
|
||||
'create_reminder',
|
||||
{'title': '开会', 'reminder_at': '明天 09:00'},
|
||||
'CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
)
|
||||
|
||||
assert normalized['reminder_at'] == '2026-03-29T09:00:00'
|
||||
|
||||
|
||||
def test_normalize_tool_time_arguments_converts_date_only_tools():
|
||||
normalized = normalize_tool_time_arguments(
|
||||
'create_goal',
|
||||
{'title': '交付节点', 'goal_date': '明天'},
|
||||
'CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
)
|
||||
|
||||
assert normalized['goal_date'] == '2026-03-29'
|
||||
|
||||
|
||||
def test_resolve_time_expression_data_preserves_explicit_datetime_offset():
|
||||
payload = resolve_time_expression_data(
|
||||
'2026-03-29T09:00:00+08:00',
|
||||
current_datetime_context='CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
prefer='datetime',
|
||||
)
|
||||
|
||||
assert payload['resolved_datetime'] == '2026-03-29T09:00:00+08:00'
|
||||
|
||||
|
||||
def test_normalize_tool_time_arguments_keeps_create_task_date_without_explicit_time():
|
||||
normalized = normalize_tool_time_arguments(
|
||||
'create_task',
|
||||
{'title': '写周报', 'due_date': '明天'},
|
||||
'CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
)
|
||||
|
||||
assert normalized['due_date'] == '2026-03-29'
|
||||
|
||||
|
||||
def test_normalize_tool_time_arguments_raises_for_invalid_time_text():
|
||||
try:
|
||||
normalize_tool_time_arguments(
|
||||
'create_reminder',
|
||||
{'title': '开会', 'reminder_at': '明天25点'},
|
||||
'CURRENT_TIME: 2026-03-28T12:00:00+00:00',
|
||||
)
|
||||
except ValueError as exc:
|
||||
assert 'hour must be in 0..23' in str(exc)
|
||||
else:
|
||||
raise AssertionError('expected ValueError for invalid time text')
|
||||
23
backend/tests/backend/app/agents/test_tool_async_bridge.py
Normal file
23
backend/tests/backend/app/agents/test_tool_async_bridge.py
Normal file
@@ -0,0 +1,23 @@
|
||||
import pytest
|
||||
|
||||
from app.agents.tools import forum as forum_tools
|
||||
from app.agents.tools import schedule as schedule_tools
|
||||
from app.agents.tools import task as task_tools
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
("module", "label"),
|
||||
[
|
||||
(task_tools, "task"),
|
||||
(schedule_tools, "schedule"),
|
||||
(forum_tools, "forum"),
|
||||
],
|
||||
)
|
||||
async def test_run_async_bridge_works_inside_running_event_loop(module, label):
|
||||
async def sample():
|
||||
return f"ok:{label}"
|
||||
|
||||
result = module._run_async(sample())
|
||||
|
||||
assert result == f"ok:{label}"
|
||||
@@ -9,7 +9,7 @@ from starlette.datastructures import UploadFile
|
||||
import app.models # noqa: F401
|
||||
from app.database import Base
|
||||
from app.models.brain import BrainEvent, BrainMemory
|
||||
from app.models.conversation import Conversation
|
||||
from app.models.conversation import Conversation, Message
|
||||
from app.models.memory import MemorySummary, UserMemory
|
||||
from app.models.user import User
|
||||
from app.services import agent_service, memory_service
|
||||
@@ -32,6 +32,110 @@ class FakeStreamingGraph:
|
||||
}
|
||||
|
||||
|
||||
class FakeStreamingFinalResponseGraph:
|
||||
async def astream_events(self, state, version="v2"):
|
||||
yield {
|
||||
"event": "on_chain_end",
|
||||
"name": "master",
|
||||
"data": {"output": {"final_response": "这是最终回答。"}},
|
||||
}
|
||||
|
||||
|
||||
class FakeStreamingBadRequestError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class FakeStreamingBadRequestError2(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class FakeOpenAIBadRequestError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class FakeStreamingOpenAIBadRequestGraph:
|
||||
def __init__(self):
|
||||
self.astream_calls = 0
|
||||
self.ainvoke_calls = 0
|
||||
|
||||
async def astream_events(self, state, version="v2"):
|
||||
self.astream_calls += 1
|
||||
raise FakeOpenAIBadRequestError('invalid_request_error: tool arguments failed validation')
|
||||
yield
|
||||
|
||||
async def ainvoke(self, state):
|
||||
self.ainvoke_calls += 1
|
||||
return {"final_response": "不应触发同步回退。"}
|
||||
|
||||
|
||||
class FakeStreamingFallbackGraph:
|
||||
def __init__(self):
|
||||
self.astream_calls = 0
|
||||
self.ainvoke_calls = 0
|
||||
|
||||
async def astream_events(self, state, version="v2"):
|
||||
self.astream_calls += 1
|
||||
raise FakeStreamingBadRequestError('invalid params, invalid chat setting (2013)')
|
||||
yield
|
||||
|
||||
async def ainvoke(self, state):
|
||||
self.ainvoke_calls += 1
|
||||
return {"final_response": "这是回退后的同步回答。"}
|
||||
|
||||
|
||||
class FakeStreamingFallbackGraphGenericError:
|
||||
def __init__(self):
|
||||
self.astream_calls = 0
|
||||
self.ainvoke_calls = 0
|
||||
|
||||
async def astream_events(self, state, version="v2"):
|
||||
self.astream_calls += 1
|
||||
raise FakeStreamingBadRequestError2("Error code: 400 - {'type': 'error', 'error': {'type': 'bad_request_error', 'message': 'invalid params, invalid chat setting (2013)', 'http_code': '400'}}")
|
||||
yield
|
||||
|
||||
async def ainvoke(self, state):
|
||||
self.ainvoke_calls += 1
|
||||
return {"final_response": "这是通用异常回退后的同步回答。"}
|
||||
|
||||
|
||||
class FakeStreamingDelegationThenFinalResponseGraph:
|
||||
async def astream_events(self, state, version="v2"):
|
||||
yield {
|
||||
"event": "on_chat_model_stream",
|
||||
"name": "master",
|
||||
"data": {"chunk": SimpleNamespace(content="现在显示收到，3月28日的任务是完成对话系统。\n\n我将这部分转给schedule_planner，他会根据这个目标结合你当前的进度和资源，给出具体的安排建议。")},
|
||||
}
|
||||
yield {
|
||||
"event": "on_chain_end",
|
||||
"name": "schedule_planner",
|
||||
"data": {"output": {"final_response": "今天先把完成对话系统拆成三步：先回顾问题，再补测试，最后验证交互链路。"}},
|
||||
}
|
||||
|
||||
|
||||
class FakeStreamingDelegationThenModelEndGraph:
|
||||
async def astream_events(self, state, version="v2"):
|
||||
yield {
|
||||
"event": "on_chat_model_stream",
|
||||
"name": "master",
|
||||
"data": {"chunk": SimpleNamespace(content="我将这部分转给schedule_planner。")},
|
||||
}
|
||||
yield {
|
||||
"event": "on_chat_model_end",
|
||||
"name": "schedule_planner",
|
||||
"data": {"output": SimpleNamespace(content="最终建议：先完成对话系统，再回归验证。")},
|
||||
}
|
||||
|
||||
|
||||
class CapturingStateGraph:
|
||||
def __init__(self, final_response: str = '已记录你的请求。'):
|
||||
self.final_response = final_response
|
||||
self.captured_state = None
|
||||
|
||||
async def ainvoke(self, state):
|
||||
self.captured_state = state
|
||||
return {"final_response": self.final_response}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def brain_ingestion_env(tmp_path, monkeypatch):
|
||||
db_path = tmp_path / 'test_brain_ingestion.db'
|
||||
@@ -43,6 +147,7 @@ async def brain_ingestion_env(tmp_path, monkeypatch):
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username='brain-ingestion-tester',
|
||||
email='brain-ingestion@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Brain Ingestion Tester',
|
||||
@@ -178,6 +283,360 @@ async def test_streaming_chat_creates_brain_event_for_assistant_message(brain_in
|
||||
assert events[1].metadata_ == {'role': 'assistant'}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_emits_final_response_from_chain_end_when_no_model_chunks_exist(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: FakeStreamingFinalResponseGraph())
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'直接给我最终回答。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
|
||||
result = await session.execute(
|
||||
select(BrainEvent)
|
||||
.where(BrainEvent.user_id == user.id, BrainEvent.source_type == 'conversation')
|
||||
.order_by(BrainEvent.created_at.asc())
|
||||
)
|
||||
events = list(result.scalars().all())
|
||||
|
||||
assert ''.join(chunks) == '这是最终回答。'
|
||||
assert len(events) == 2
|
||||
assert events[1].source_id == conversation_id
|
||||
assert events[1].event_type == 'message_created'
|
||||
assert events[1].title == 'Assistant message'
|
||||
assert events[1].content_summary == '这是最终回答。'
|
||||
assert events[1].metadata_ == {'role': 'assistant'}
|
||||
|
||||
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_prefers_chain_end_final_response_over_delegation_chunk(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: FakeStreamingDelegationThenFinalResponseGraph())
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'帮我安排今天先做什么。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
|
||||
message_result = await session.execute(
|
||||
select(Message)
|
||||
.where(Message.conversation_id == conversation_id, Message.role == 'assistant')
|
||||
.order_by(Message.created_at.desc())
|
||||
)
|
||||
assistant_message = message_result.scalars().first()
|
||||
|
||||
assert '今天先把完成对话系统拆成三步：先回顾问题，再补测试，最后验证交互链路。' in chunks
|
||||
assert chunks[-1] == '今天先把完成对话系统拆成三步：先回顾问题，再补测试，最后验证交互链路。'
|
||||
assert assistant_message is not None
|
||||
assert assistant_message.content == '今天先把完成对话系统拆成三步：先回顾问题，再补测试，最后验证交互链路。'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_prefers_model_end_final_content_over_delegation_chunk(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: FakeStreamingDelegationThenModelEndGraph())
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'帮我安排今天先做什么。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
|
||||
message_result = await session.execute(
|
||||
select(Message)
|
||||
.where(Message.conversation_id == conversation_id, Message.role == 'assistant')
|
||||
.order_by(Message.created_at.desc())
|
||||
)
|
||||
assistant_message = message_result.scalars().first()
|
||||
|
||||
assert '最终建议：先完成对话系统，再回归验证。' in chunks
|
||||
assert chunks[-1] == '最终建议：先完成对话系统，再回归验证。'
|
||||
assert assistant_message is not None
|
||||
assert assistant_message.content == '最终建议：先完成对话系统，再回归验证。'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_does_not_fall_back_for_official_openai_bad_request_without_output(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
graph = FakeStreamingOpenAIBadRequestGraph()
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: graph)
|
||||
monkeypatch.setattr(agent_service, 'BadRequestError', FakeOpenAIBadRequestError)
|
||||
|
||||
original_get_user_llm_config = AgentService._get_user_llm_config
|
||||
|
||||
async def fake_get_user_llm_config(self, user_id, model_name=None):
|
||||
return {
|
||||
'name': 'Official OpenAI',
|
||||
'provider': 'openai',
|
||||
'model': 'gpt-4o',
|
||||
'base_url': 'https://api.openai.com/v1',
|
||||
'enabled': True,
|
||||
}
|
||||
|
||||
monkeypatch.setattr(AgentService, '_get_user_llm_config', fake_get_user_llm_config)
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'测试官方 OpenAI bad request 不应回退。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
errors = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
if event.get('type') == 'error':
|
||||
errors.append(event['error'])
|
||||
|
||||
message_result = await session.execute(
|
||||
select(Message)
|
||||
.where(Message.conversation_id == conversation_id, Message.role == 'assistant')
|
||||
.order_by(Message.created_at.desc())
|
||||
)
|
||||
assistant_message = message_result.scalars().first()
|
||||
|
||||
assert graph.astream_calls == 1
|
||||
assert graph.ainvoke_calls == 0
|
||||
assert errors == ['模型服务暂不可用，请稍后再试。']
|
||||
assert chunks == ['抱歉，发生错误: 模型服务暂不可用，请稍后再试。']
|
||||
assert assistant_message is not None
|
||||
assert assistant_message.content == '抱歉，发生错误: 模型服务暂不可用，请稍后再试。'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_falls_back_for_generic_400_streaming_error(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
fallback_graph = FakeStreamingFallbackGraphGenericError()
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: fallback_graph)
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'帮我制定一下明天的计划。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
|
||||
result = await session.execute(
|
||||
select(BrainEvent)
|
||||
.where(BrainEvent.user_id == user.id, BrainEvent.source_type == 'conversation')
|
||||
.order_by(BrainEvent.created_at.asc())
|
||||
)
|
||||
events = list(result.scalars().all())
|
||||
|
||||
assert fallback_graph.astream_calls == 1
|
||||
assert fallback_graph.ainvoke_calls == 1
|
||||
assert ''.join(chunks) == '这是通用异常回退后的同步回答。'
|
||||
assert len(events) == 2
|
||||
assert events[1].source_id == conversation_id
|
||||
assert events[1].content_summary == '这是通用异常回退后的同步回答。'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_does_not_fall_back_after_partial_stream_output(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
|
||||
class PartialThenFailGraph:
|
||||
def __init__(self):
|
||||
self.ainvoke_calls = 0
|
||||
|
||||
async def astream_events(self, state, version='v2'):
|
||||
yield {
|
||||
'event': 'on_chat_model_stream',
|
||||
'name': 'master',
|
||||
'data': {'chunk': SimpleNamespace(content='前半段')},
|
||||
}
|
||||
raise FakeStreamingBadRequestError('stream interrupted')
|
||||
|
||||
async def ainvoke(self, state):
|
||||
self.ainvoke_calls += 1
|
||||
return {'final_response': '不应触发'}
|
||||
|
||||
graph = PartialThenFailGraph()
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: graph)
|
||||
monkeypatch.setattr(agent_service, 'BadRequestError', FakeStreamingBadRequestError)
|
||||
service = AgentService(session)
|
||||
|
||||
conversation_id, _message_id, stream = await service.chat(
|
||||
user.id,
|
||||
'测试部分流式输出失败。',
|
||||
)
|
||||
|
||||
chunks = []
|
||||
errors = []
|
||||
async for event in stream:
|
||||
if event.get('type') == 'chunk':
|
||||
chunks.append(event['content'])
|
||||
if event.get('type') == 'error':
|
||||
errors.append(event['error'])
|
||||
|
||||
message_result = await session.execute(
|
||||
select(Message)
|
||||
.where(Message.conversation_id == conversation_id, Message.role == 'assistant')
|
||||
.order_by(Message.created_at.desc())
|
||||
)
|
||||
assistant_message = message_result.scalars().first()
|
||||
|
||||
brain_event_result = await session.execute(
|
||||
select(BrainEvent)
|
||||
.where(BrainEvent.user_id == user.id, BrainEvent.source_type == 'conversation')
|
||||
.order_by(BrainEvent.created_at.asc())
|
||||
)
|
||||
events = list(brain_event_result.scalars().all())
|
||||
|
||||
assert chunks == ['前半段']
|
||||
assert graph.ainvoke_calls == 0
|
||||
assert errors == ['stream interrupted']
|
||||
assert assistant_message is not None
|
||||
assert assistant_message.content == '前半段'
|
||||
assert events[1].content_summary == '前半段'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_simple_passes_current_datetime_context_into_langgraph_state(brain_ingestion_env, monkeypatch):
|
||||
session, user = brain_ingestion_env
|
||||
graph = CapturingStateGraph()
|
||||
monkeypatch.setattr(agent_service, 'get_agent_graph', lambda: graph)
|
||||
service = AgentService(session)
|
||||
|
||||
await service.chat_simple(
|
||||
user.id,
|
||||
'3月29日，对话系统交付节点',
|
||||
)
|
||||
|
||||
assert graph.captured_state is not None
|
||||
current_context = graph.captured_state.get('current_datetime_context')
|
||||
assert isinstance(current_context, str)
|
||||
assert current_context
|
||||
assert '当前时间' in current_context
|
||||
assert '2026' in current_context
|
||||
|
||||
current_reference = graph.captured_state.get('current_datetime_reference')
|
||||
assert isinstance(current_reference, dict)
|
||||
assert 'current_time_iso' in current_reference
|
||||
assert 'current_date_iso' in current_reference
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_user_llm_config_defaults_to_enabled_chat_model_not_vlm(brain_ingestion_env):
|
||||
session, user = brain_ingestion_env
|
||||
user.llm_config = {
|
||||
'chat': [
|
||||
{'name': 'Disabled Chat', 'provider': 'openai', 'model': 'disabled-chat', 'enabled': False},
|
||||
{'name': 'Enabled Chat', 'provider': 'openai', 'model': 'enabled-chat', 'enabled': True},
|
||||
],
|
||||
'vlm': [
|
||||
{'name': 'Enabled Vision', 'provider': 'openai', 'model': 'enabled-vision', 'enabled': True},
|
||||
],
|
||||
}
|
||||
await session.commit()
|
||||
|
||||
service = AgentService(session)
|
||||
|
||||
config = await service._get_user_llm_config(user.id)
|
||||
|
||||
assert config is not None
|
||||
assert config['name'] == 'Enabled Chat'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_user_llm_config_returns_none_when_only_vlm_is_enabled(brain_ingestion_env):
|
||||
session, user = brain_ingestion_env
|
||||
user.llm_config = {
|
||||
'chat': [
|
||||
{'name': 'Disabled Chat', 'provider': 'openai', 'model': 'disabled-chat', 'enabled': False},
|
||||
],
|
||||
'vlm': [
|
||||
{'name': 'Enabled Vision', 'provider': 'openai', 'model': 'enabled-vision', 'enabled': True},
|
||||
],
|
||||
}
|
||||
await session.commit()
|
||||
|
||||
service = AgentService(session)
|
||||
|
||||
config = await service._get_user_llm_config(user.id)
|
||||
|
||||
assert config is None
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_simple_rejects_vlm_model_without_persisting_conversation_state(brain_ingestion_env):
|
||||
session, user = brain_ingestion_env
|
||||
user.llm_config = {
|
||||
'chat': [
|
||||
{'name': 'Enabled Chat', 'provider': 'openai', 'model': 'enabled-chat', 'enabled': True},
|
||||
],
|
||||
'vlm': [
|
||||
{'name': 'Vision Only', 'provider': 'openai', 'model': 'vision-only', 'enabled': True},
|
||||
],
|
||||
}
|
||||
await session.commit()
|
||||
|
||||
service = AgentService(session)
|
||||
|
||||
with pytest.raises(ValueError, match='所选模型不可用于聊天，请切换到聊天模型'):
|
||||
await service.chat_simple(user.id, '测试聊天模型选择', model_name='Vision Only')
|
||||
|
||||
conversation_result = await session.execute(select(Conversation).where(Conversation.user_id == user.id))
|
||||
message_result = await session.execute(select(Message))
|
||||
brain_event_result = await session.execute(select(BrainEvent).where(BrainEvent.user_id == user.id))
|
||||
|
||||
assert conversation_result.scalars().all() == []
|
||||
assert message_result.scalars().all() == []
|
||||
assert brain_event_result.scalars().all() == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_streaming_chat_rejects_vlm_model_without_persisting_conversation_state(brain_ingestion_env):
|
||||
session, user = brain_ingestion_env
|
||||
user.llm_config = {
|
||||
'chat': [
|
||||
{'name': 'Enabled Chat', 'provider': 'openai', 'model': 'enabled-chat', 'enabled': True},
|
||||
],
|
||||
'vlm': [
|
||||
{'name': 'Vision Only', 'provider': 'openai', 'model': 'vision-only', 'enabled': True},
|
||||
],
|
||||
}
|
||||
await session.commit()
|
||||
|
||||
service = AgentService(session)
|
||||
|
||||
with pytest.raises(ValueError, match='所选模型不可用于聊天，请切换到聊天模型'):
|
||||
await service.chat(user.id, '测试流式聊天模型选择', model_name='Vision Only')
|
||||
|
||||
conversation_result = await session.execute(select(Conversation).where(Conversation.user_id == user.id))
|
||||
message_result = await session.execute(select(Message))
|
||||
brain_event_result = await session.execute(select(BrainEvent).where(BrainEvent.user_id == user.id))
|
||||
|
||||
assert conversation_result.scalars().all() == []
|
||||
assert message_result.scalars().all() == []
|
||||
assert brain_event_result.scalars().all() == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_build_memory_context_includes_brain_memory_section(brain_ingestion_env):
|
||||
session, user = brain_ingestion_env
|
||||
|
||||
@@ -0,0 +1,49 @@
|
||||
import pytest
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
|
||||
|
||||
import app.models # noqa: F401
|
||||
from app.database import Base
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.services.admin_bootstrap_service import ensure_builtin_skills
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_ensure_builtin_skills_creates_default_ability_skills(tmp_path):
|
||||
db_path = tmp_path / 'test_builtin_skills.db'
|
||||
engine = create_async_engine(f"sqlite+aiosqlite:///{db_path}", future=True)
|
||||
session_factory = async_sessionmaker(engine, expire_on_commit=False)
|
||||
|
||||
async with engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username='bootstrap_user',
|
||||
email='bootstrap@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Bootstrap User',
|
||||
is_active=True,
|
||||
is_superuser=True,
|
||||
)
|
||||
session.add(user)
|
||||
await session.commit()
|
||||
|
||||
async with session_factory() as session:
|
||||
await ensure_builtin_skills(session)
|
||||
await ensure_builtin_skills(session)
|
||||
result = await session.execute(select(Skill).order_by(Skill.agent_type, Skill.name))
|
||||
skills = result.scalars().all()
|
||||
|
||||
assert len(skills) >= 9
|
||||
assert any(skill.agent_type == 'schedule_planner' for skill in skills)
|
||||
assert any(skill.agent_type == 'executor' for skill in skills)
|
||||
assert any(skill.agent_type == 'librarian' for skill in skills)
|
||||
librarian_skill = next(skill for skill in skills if skill.name == '知识检索摘要')
|
||||
assert 'web_search' in (librarian_skill.tools or [])
|
||||
assert any(skill.agent_type == 'analyst' for skill in skills)
|
||||
assert len({skill.name for skill in skills}) == len(skills)
|
||||
|
||||
await engine.dispose()
|
||||
144
backend/tests/backend/app/services/test_web_search_service.py
Normal file
144
backend/tests/backend/app/services/test_web_search_service.py
Normal file
@@ -0,0 +1,144 @@
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
from app.services.web_search_service import (
|
||||
WebSearchConfigurationError,
|
||||
WebSearchRequestError,
|
||||
WebSearchResult,
|
||||
WebSearchService,
|
||||
)
|
||||
|
||||
|
||||
class FakeResponse:
|
||||
def __init__(self, payload: dict, status_code: int = 200):
|
||||
self._payload = payload
|
||||
self.status_code = status_code
|
||||
|
||||
def raise_for_status(self):
|
||||
if self.status_code >= 400:
|
||||
raise httpx.HTTPStatusError(
|
||||
'request failed',
|
||||
request=httpx.Request('GET', 'http://searx.example/search'),
|
||||
response=httpx.Response(self.status_code, request=httpx.Request('GET', 'http://searx.example/search')),
|
||||
)
|
||||
|
||||
def json(self):
|
||||
return self._payload
|
||||
|
||||
|
||||
class FakeAsyncClient:
|
||||
def __init__(self, *, response=None, error=None, recorder=None, **kwargs):
|
||||
self._response = response
|
||||
self._error = error
|
||||
self._recorder = recorder if recorder is not None else []
|
||||
|
||||
async def __aenter__(self):
|
||||
return self
|
||||
|
||||
async def __aexit__(self, exc_type, exc, tb):
|
||||
return False
|
||||
|
||||
async def get(self, url, *, params=None, headers=None):
|
||||
self._recorder.append({'url': url, 'params': params, 'headers': headers})
|
||||
if self._error is not None:
|
||||
raise self._error
|
||||
return self._response
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_web_search_service_returns_normalized_results_from_searxng(monkeypatch):
|
||||
requests = []
|
||||
payload = {
|
||||
'results': [
|
||||
{
|
||||
'title': 'Jarvis release notes',
|
||||
'url': 'https://example.com/jarvis-release',
|
||||
'content': 'Latest Jarvis changes and release notes.',
|
||||
'engine': 'duckduckgo',
|
||||
'publishedDate': '2026-03-29',
|
||||
}
|
||||
]
|
||||
}
|
||||
monkeypatch.setattr(
|
||||
'app.services.web_search_service.httpx.AsyncClient',
|
||||
lambda **kwargs: FakeAsyncClient(response=FakeResponse(payload), recorder=requests, **kwargs),
|
||||
)
|
||||
|
||||
service = WebSearchService(
|
||||
enabled=True,
|
||||
provider='searxng',
|
||||
base_url='http://searx.example',
|
||||
default_limit=5,
|
||||
timeout_seconds=10,
|
||||
)
|
||||
|
||||
results = await service.search('Jarvis 最新版本', limit=3)
|
||||
|
||||
assert results == [
|
||||
WebSearchResult(
|
||||
title='Jarvis release notes',
|
||||
url='https://example.com/jarvis-release',
|
||||
snippet='Latest Jarvis changes and release notes.',
|
||||
source='duckduckgo',
|
||||
published_at='2026-03-29',
|
||||
)
|
||||
]
|
||||
assert requests == [
|
||||
{
|
||||
'url': 'http://searx.example/search',
|
||||
'params': {
|
||||
'q': 'Jarvis 最新版本',
|
||||
'format': 'json',
|
||||
'language': 'zh-CN',
|
||||
'safesearch': 1,
|
||||
},
|
||||
'headers': {},
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_web_search_service_returns_empty_list_when_searxng_has_no_results(monkeypatch):
|
||||
monkeypatch.setattr(
|
||||
'app.services.web_search_service.httpx.AsyncClient',
|
||||
lambda **kwargs: FakeAsyncClient(response=FakeResponse({'results': []}), **kwargs),
|
||||
)
|
||||
|
||||
service = WebSearchService(
|
||||
enabled=True,
|
||||
provider='searxng',
|
||||
base_url='http://searx.example',
|
||||
)
|
||||
|
||||
results = await service.search('不存在的话题')
|
||||
|
||||
assert results == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_web_search_service_raises_clear_error_on_searxng_http_failure(monkeypatch):
|
||||
monkeypatch.setattr(
|
||||
'app.services.web_search_service.httpx.AsyncClient',
|
||||
lambda **kwargs: FakeAsyncClient(error=httpx.TimeoutException('timed out'), **kwargs),
|
||||
)
|
||||
|
||||
service = WebSearchService(
|
||||
enabled=True,
|
||||
provider='searxng',
|
||||
base_url='http://searx.example',
|
||||
)
|
||||
|
||||
with pytest.raises(WebSearchRequestError, match='SearxNG 请求失败'):
|
||||
await service.search('Jarvis')
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_web_search_service_raises_clear_error_when_not_configured():
|
||||
service = WebSearchService(
|
||||
enabled=False,
|
||||
provider='searxng',
|
||||
base_url='',
|
||||
)
|
||||
|
||||
with pytest.raises(WebSearchConfigurationError, match='网页搜索未启用或未配置'):
|
||||
await service.search('Jarvis')
|
||||
150
backend/tests/backend/app/test_agent_router.py
Normal file
150
backend/tests/backend/app/test_agent_router.py
Normal file
@@ -0,0 +1,150 @@
|
||||
import pytest
|
||||
from fastapi import FastAPI
|
||||
from httpx import ASGITransport, AsyncClient
|
||||
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
|
||||
|
||||
import app.models # noqa: F401
|
||||
from app.database import Base, get_db
|
||||
from app.models.agent import Agent
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.routers.agent import router as agent_router
|
||||
from app.routers.auth import get_current_user
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def agent_env(tmp_path):
|
||||
db_path = tmp_path / 'test_agent_router.db'
|
||||
engine = create_async_engine(f"sqlite+aiosqlite:///{db_path}", future=True)
|
||||
session_factory = async_sessionmaker(engine, expire_on_commit=False)
|
||||
|
||||
async with engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username='agent_user',
|
||||
email='agent@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Agent Tester',
|
||||
)
|
||||
session.add(user)
|
||||
await session.flush()
|
||||
skill_a = Skill(
|
||||
name='Planner skill A',
|
||||
description='planner',
|
||||
instructions='plan a',
|
||||
agent_type='schedule_planner',
|
||||
tools=['calendar'],
|
||||
required_context=[],
|
||||
visibility='private',
|
||||
is_active=True,
|
||||
owner_id=user.id,
|
||||
)
|
||||
skill_b = Skill(
|
||||
name='Planner skill B',
|
||||
description='planner',
|
||||
instructions='plan b',
|
||||
agent_type='schedule_planner',
|
||||
tools=['tasks'],
|
||||
required_context=[],
|
||||
visibility='private',
|
||||
is_active=True,
|
||||
owner_id=user.id,
|
||||
)
|
||||
session.add_all([
|
||||
Agent(
|
||||
name='SCHEDULE PLANNER',
|
||||
role='schedule_planner',
|
||||
description='日程规划师',
|
||||
system_prompt='prompt',
|
||||
is_active=True,
|
||||
),
|
||||
skill_a,
|
||||
skill_b,
|
||||
])
|
||||
await session.commit()
|
||||
await session.refresh(user)
|
||||
await session.refresh(skill_a)
|
||||
await session.refresh(skill_b)
|
||||
|
||||
async def override_get_db():
|
||||
async with session_factory() as session:
|
||||
yield session
|
||||
|
||||
async def override_get_current_user():
|
||||
return user
|
||||
|
||||
test_app = FastAPI()
|
||||
test_app.include_router(agent_router)
|
||||
test_app.dependency_overrides[get_db] = override_get_db
|
||||
test_app.dependency_overrides[get_current_user] = override_get_current_user
|
||||
|
||||
try:
|
||||
yield test_app, {'skill_a_id': skill_a.id, 'skill_b_id': skill_b.id}
|
||||
finally:
|
||||
await engine.dispose()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_agent_config_returns_default_empty_selected_skill_ids(agent_env):
|
||||
app, _ids = agent_env
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/agents/config/schedule_planner')
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload['selected_skill_ids'] == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_agent_config_persists_selected_skill_ids(agent_env):
|
||||
app, ids = agent_env
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
update_response = await client.put(
|
||||
'/api/agents/config/schedule_planner',
|
||||
json={'selected_skill_ids': [ids['skill_a_id'], ids['skill_b_id']]},
|
||||
)
|
||||
get_response = await client.get('/api/agents/config/schedule_planner')
|
||||
|
||||
assert update_response.status_code == 200
|
||||
assert update_response.json()['selected_skill_ids'] == [ids['skill_a_id'], ids['skill_b_id']]
|
||||
assert get_response.status_code == 200
|
||||
assert get_response.json()['selected_skill_ids'] == [ids['skill_a_id'], ids['skill_b_id']]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_agent_config_preserves_selected_skill_ids_when_omitted(agent_env):
|
||||
app, ids = agent_env
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
first_response = await client.put(
|
||||
'/api/agents/config/schedule_planner',
|
||||
json={'selected_skill_ids': [ids['skill_a_id']]},
|
||||
)
|
||||
update_response = await client.put(
|
||||
'/api/agents/config/schedule_planner',
|
||||
json={'description': 'updated description'},
|
||||
)
|
||||
|
||||
assert first_response.status_code == 200
|
||||
assert update_response.status_code == 200
|
||||
assert update_response.json()['description'] == 'updated description'
|
||||
assert update_response.json()['selected_skill_ids'] == [ids['skill_a_id']]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_agent_config_rejects_invalid_selected_skill_ids(agent_env):
|
||||
app, _ids = agent_env
|
||||
transport = ASGITransport(app=app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.put(
|
||||
'/api/agents/config/schedule_planner',
|
||||
json={'selected_skill_ids': ['missing-skill']},
|
||||
)
|
||||
|
||||
assert response.status_code == 400
|
||||
assert response.json()['detail'] == '存在无效的技能绑定'
|
||||
67
backend/tests/backend/app/test_config.py
Normal file
67
backend/tests/backend/app/test_config.py
Normal file
@@ -0,0 +1,67 @@
|
||||
from pathlib import Path
|
||||
|
||||
from app import config as config_module
|
||||
from app.services.llm_service import default_provider_capabilities, normalize_provider_name, resolve_provider_capabilities
|
||||
|
||||
|
||||
def test_env_file_points_to_repo_root_env_file():
|
||||
assert config_module.ENV_FILE == Path(__file__).resolve().parents[4] / '.env'
|
||||
|
||||
|
||||
def test_resolve_provider_capabilities_prefers_native_for_openai():
|
||||
capabilities = resolve_provider_capabilities({'provider': 'openai', 'model': 'gpt-4o', 'base_url': 'https://api.openai.com/v1'})
|
||||
|
||||
assert capabilities.provider == 'openai'
|
||||
assert capabilities.supports_native_tools is True
|
||||
assert capabilities.preferred_tool_strategy == 'native'
|
||||
|
||||
|
||||
def test_resolve_provider_capabilities_falls_back_for_openai_compatible_non_official_endpoint():
|
||||
capabilities = resolve_provider_capabilities(
|
||||
{'provider': 'openai', 'model': 'abab7.5-chat-preview', 'base_url': 'https://api.minimax.chat/v1'}
|
||||
)
|
||||
|
||||
assert capabilities.provider == 'minimax'
|
||||
assert capabilities.supports_native_tools is False
|
||||
assert capabilities.preferred_tool_strategy == 'json_fallback'
|
||||
|
||||
|
||||
def test_resolve_provider_capabilities_uses_global_openai_base_url_when_user_config_omits_it(monkeypatch):
|
||||
monkeypatch.setattr(config_module.settings, 'OPENAI_BASE_URL', 'https://api.minimax.chat/v1')
|
||||
|
||||
capabilities = resolve_provider_capabilities({'provider': 'openai', 'model': 'abab7.5-chat-preview'})
|
||||
|
||||
assert capabilities.provider == 'minimax'
|
||||
assert capabilities.supports_native_tools is False
|
||||
assert capabilities.preferred_tool_strategy == 'json_fallback'
|
||||
|
||||
|
||||
def test_normalize_provider_name_recognizes_minimax_from_custom_config():
|
||||
assert normalize_provider_name({'provider': 'custom', 'model': 'MiniMax-M2.7-highspeed'}) == 'minimax'
|
||||
|
||||
|
||||
def test_normalize_provider_name_recognizes_minimax_without_provider_when_base_url_matches():
|
||||
assert normalize_provider_name({'model': 'abab7.5-chat-preview', 'base_url': 'https://api.minimax.chat/v1'}) == 'minimax'
|
||||
|
||||
|
||||
def test_resolve_provider_capabilities_falls_back_for_ollama():
|
||||
capabilities = resolve_provider_capabilities({'provider': 'ollama', 'model': 'qwen2.5'})
|
||||
|
||||
assert capabilities.provider == 'ollama'
|
||||
assert capabilities.supports_native_tools is False
|
||||
assert capabilities.preferred_tool_strategy == 'json_fallback'
|
||||
|
||||
|
||||
def test_default_provider_capabilities_follows_global_settings(monkeypatch):
|
||||
monkeypatch.setattr(config_module.settings, 'LLM_PROVIDER', 'ollama')
|
||||
|
||||
capabilities = default_provider_capabilities()
|
||||
|
||||
assert capabilities.provider == 'ollama'
|
||||
assert capabilities.preferred_tool_strategy == 'json_fallback'
|
||||
|
||||
|
||||
def test_normalize_provider_name_without_provider_uses_global_default(monkeypatch):
|
||||
monkeypatch.setattr(config_module.settings, 'LLM_PROVIDER', 'ollama')
|
||||
|
||||
assert normalize_provider_name({'model': 'qwen2.5'}) == 'ollama'
|
||||
281
backend/tests/backend/app/test_schedule_center_router.py
Normal file
281
backend/tests/backend/app/test_schedule_center_router.py
Normal file
@@ -0,0 +1,281 @@
|
||||
import sys
|
||||
from datetime import UTC, date, datetime
|
||||
from unittest.mock import Mock
|
||||
|
||||
import pytest
|
||||
from fastapi import FastAPI
|
||||
from httpx import ASGITransport, AsyncClient
|
||||
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
|
||||
|
||||
sys.modules.setdefault('psutil', Mock())
|
||||
|
||||
import app.models # noqa: F401
|
||||
from app.database import Base, get_db
|
||||
from app.models.goal import Goal
|
||||
from app.models.reminder import Reminder
|
||||
from app.models.task import Task, TaskPriority, TaskStatus
|
||||
from app.models.todo import DailyTodo, TodoSource
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.routers.goal import router as goal_router
|
||||
from app.routers.reminder import router as reminder_router
|
||||
from app.routers.schedule_center import router as schedule_center_router
|
||||
from app.routers.task import router as task_router
|
||||
from app.routers.todo import router as todo_router
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def schedule_env(tmp_path):
|
||||
db_path = tmp_path / 'test_schedule_center.db'
|
||||
engine = create_async_engine(f"sqlite+aiosqlite:///{db_path}", future=True)
|
||||
session_factory = async_sessionmaker(engine, expire_on_commit=False)
|
||||
|
||||
async with engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username='schedule_user',
|
||||
email='schedule@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Schedule Tester',
|
||||
)
|
||||
other_user = User(
|
||||
username='other_schedule_user',
|
||||
email='other-schedule@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Other Schedule Tester',
|
||||
)
|
||||
session.add_all([user, other_user])
|
||||
await session.flush()
|
||||
|
||||
session.add_all([
|
||||
DailyTodo(
|
||||
user_id=user.id,
|
||||
title='Legacy todo',
|
||||
source=TodoSource.MANUAL,
|
||||
todo_date='2026-04-10',
|
||||
is_completed=False,
|
||||
),
|
||||
DailyTodo(
|
||||
user_id=user.id,
|
||||
title='Done todo',
|
||||
source=TodoSource.MANUAL,
|
||||
todo_date='2026-04-10',
|
||||
is_completed=True,
|
||||
completed_at=datetime(2026, 4, 10, 9, 30, tzinfo=UTC),
|
||||
),
|
||||
DailyTodo(
|
||||
user_id=other_user.id,
|
||||
title='Other user todo',
|
||||
source=TodoSource.MANUAL,
|
||||
todo_date='2026-04-10',
|
||||
is_completed=False,
|
||||
),
|
||||
Task(
|
||||
user_id=user.id,
|
||||
title='High priority task',
|
||||
priority=TaskPriority.HIGH,
|
||||
status=TaskStatus.TODO,
|
||||
due_date=datetime(2026, 4, 10, 14, 0, tzinfo=UTC),
|
||||
),
|
||||
Task(
|
||||
user_id=user.id,
|
||||
title='Urgent task next day',
|
||||
priority=TaskPriority.URGENT,
|
||||
status=TaskStatus.IN_PROGRESS,
|
||||
due_date=datetime(2026, 4, 11, 10, 0, tzinfo=UTC),
|
||||
),
|
||||
Task(
|
||||
user_id=other_user.id,
|
||||
title='Other user task',
|
||||
priority=TaskPriority.HIGH,
|
||||
status=TaskStatus.TODO,
|
||||
due_date=datetime(2026, 4, 10, 15, 0, tzinfo=UTC),
|
||||
),
|
||||
Reminder(
|
||||
user_id=user.id,
|
||||
title='Doctor reminder',
|
||||
note='Bring reports',
|
||||
reminder_at=datetime(2026, 4, 10, 8, 0, tzinfo=UTC),
|
||||
),
|
||||
Goal(
|
||||
user_id=user.id,
|
||||
title='Launch calendar beta',
|
||||
note='Ship MVP',
|
||||
goal_date='2026-04-10',
|
||||
),
|
||||
])
|
||||
await session.commit()
|
||||
await session.refresh(user)
|
||||
|
||||
async def override_get_db():
|
||||
async with session_factory() as session:
|
||||
yield session
|
||||
|
||||
async def override_get_current_user():
|
||||
return user
|
||||
|
||||
test_app = FastAPI()
|
||||
test_app.include_router(todo_router)
|
||||
test_app.include_router(task_router)
|
||||
test_app.include_router(reminder_router)
|
||||
test_app.include_router(goal_router)
|
||||
test_app.include_router(schedule_center_router)
|
||||
test_app.dependency_overrides[get_db] = override_get_db
|
||||
test_app.dependency_overrides[get_current_user] = override_get_current_user
|
||||
|
||||
try:
|
||||
yield test_app
|
||||
finally:
|
||||
await engine.dispose()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_todo_persists_explicit_todo_date(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.post('/api/todos', json={'title': 'Plan sprint', 'todo_date': '2026-04-12'})
|
||||
|
||||
assert response.status_code == 201
|
||||
payload = response.json()
|
||||
assert payload['title'] == 'Plan sprint'
|
||||
assert payload['todo_date'] == '2026-04-12'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_update_todo_allows_editing_non_today_todo(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
todos_response = await client.get('/api/todos', params={'date_str': '2026-04-10'})
|
||||
todo_id = todos_response.json()['items'][0]['id']
|
||||
response = await client.patch(f'/api/todos/{todo_id}', json={'title': 'Updated title', 'todo_date': '2026-04-11'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload['title'] == 'Updated title'
|
||||
assert payload['todo_date'] == '2026-04-11'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_delete_todo_allows_deleting_non_today_todo(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
todos_response = await client.get('/api/todos', params={'date_str': '2026-04-10'})
|
||||
todo_id = todos_response.json()['items'][0]['id']
|
||||
response = await client.delete(f'/api/todos/{todo_id}')
|
||||
after_response = await client.get('/api/todos', params={'date_str': '2026-04-10'})
|
||||
|
||||
assert response.status_code == 204
|
||||
assert all(item['id'] != todo_id for item in after_response.json()['items'])
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_tasks_filters_by_due_date(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/tasks', params={'due_date': '2026-04-10'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert [item['title'] for item in payload] == ['High priority task']
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_tasks_filters_by_due_date_range(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/tasks', params={'date_from': '2026-04-10', 'date_to': '2026-04-11'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert {item['title'] for item in payload} == {'High priority task', 'Urgent task next day'}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_schedule_center_date_returns_aggregated_resources(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/schedule-center/date', params={'date_str': '2026-04-10'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload['date'] == '2026-04-10'
|
||||
assert payload['summary'] == {
|
||||
'date': '2026-04-10',
|
||||
'todo_total': 2,
|
||||
'todo_completed': 1,
|
||||
'task_due_total': 1,
|
||||
'high_priority_total': 1,
|
||||
'reminder_total': 1,
|
||||
'goal_total': 1,
|
||||
}
|
||||
assert [item['title'] for item in payload['reminders']] == ['Doctor reminder']
|
||||
assert [item['title'] for item in payload['goals']] == ['Launch calendar beta']
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_schedule_center_month_returns_day_summaries(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/schedule-center/month', params={'year': 2026, 'month': 4})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
assert payload['month'] == '2026-04'
|
||||
day_10 = next(item for item in payload['days'] if item['date'] == '2026-04-10')
|
||||
day_11 = next(item for item in payload['days'] if item['date'] == '2026-04-11')
|
||||
assert day_10 == {
|
||||
'date': '2026-04-10',
|
||||
'todo_total': 2,
|
||||
'todo_completed': 1,
|
||||
'task_due_total': 1,
|
||||
'high_priority_total': 1,
|
||||
'reminder_total': 1,
|
||||
'goal_total': 1,
|
||||
}
|
||||
assert day_11['task_due_total'] == 1
|
||||
assert day_11['high_priority_total'] == 1
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_reminder_with_naive_datetime_and_time_zone_appears_in_schedule_center(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
create_response = await client.post(
|
||||
'/api/reminders',
|
||||
json={'title': '收被子', 'note': '提醒收被子', 'reminder_at': '2026-03-29T09:00:00'},
|
||||
)
|
||||
detail_response = await client.get('/api/schedule-center/date', params={'date_str': '2026-03-29'})
|
||||
|
||||
assert create_response.status_code == 201
|
||||
assert detail_response.status_code == 200
|
||||
payload = detail_response.json()
|
||||
assert [item['title'] for item in payload['reminders']] == ['收被子']
|
||||
assert payload['summary']['reminder_total'] == 1
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_reminder_and_goal_crud(schedule_env):
|
||||
transport = ASGITransport(app=schedule_env)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
reminder_response = await client.post('/api/reminders', json={'title': 'Standup', 'note': 'Daily sync', 'reminder_at': '2026-04-12T09:00:00Z'})
|
||||
goal_response = await client.post('/api/goals', json={'title': 'Finish polish', 'note': 'UI cleanup', 'goal_date': '2026-04-12', 'status': 'active'})
|
||||
reminder_id = reminder_response.json()['id']
|
||||
goal_id = goal_response.json()['id']
|
||||
patch_reminder = await client.patch(f'/api/reminders/{reminder_id}', json={'status': 'done'})
|
||||
patch_goal = await client.patch(f'/api/goals/{goal_id}', json={'status': 'done'})
|
||||
reminders_list = await client.get('/api/reminders', params={'date_str': '2026-04-12'})
|
||||
goals_list = await client.get('/api/goals', params={'date_str': '2026-04-12'})
|
||||
delete_reminder = await client.delete(f'/api/reminders/{reminder_id}')
|
||||
delete_goal = await client.delete(f'/api/goals/{goal_id}')
|
||||
|
||||
assert reminder_response.status_code == 201
|
||||
assert goal_response.status_code == 201
|
||||
assert patch_reminder.json()['status'] == 'done'
|
||||
assert patch_goal.json()['status'] == 'done'
|
||||
assert [item['title'] for item in reminders_list.json()['items']] == ['Standup']
|
||||
assert [item['title'] for item in goals_list.json()['items']] == ['Finish polish']
|
||||
assert delete_reminder.status_code == 204
|
||||
assert delete_goal.status_code == 204
|
||||
190
backend/tests/backend/app/test_skill_router.py
Normal file
190
backend/tests/backend/app/test_skill_router.py
Normal file
@@ -0,0 +1,190 @@
|
||||
import pytest
|
||||
from fastapi import FastAPI
|
||||
from httpx import ASGITransport, AsyncClient
|
||||
from sqlalchemy import select, text
|
||||
from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
|
||||
|
||||
import app.models # noqa: F401
|
||||
from app.database import Base, get_db
|
||||
from app.models.skill import Skill
|
||||
from app.models.user import User
|
||||
from app.routers.auth import get_current_user
|
||||
from app.routers.skill import router as skill_router
|
||||
from app.routers.auth import router as auth_router
|
||||
from app.services.auth_service import get_password_hash
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
async def skill_env(tmp_path, monkeypatch):
|
||||
db_path = tmp_path / 'test_skill_router.db'
|
||||
engine = create_async_engine(f"sqlite+aiosqlite:///{db_path}", future=True)
|
||||
session_factory = async_sessionmaker(engine, expire_on_commit=False)
|
||||
|
||||
# Ensure app.database.init_db() runs against the test database.
|
||||
import app.database as database_module
|
||||
|
||||
monkeypatch.setattr(database_module, "engine", engine)
|
||||
monkeypatch.setattr(database_module, "async_session", session_factory)
|
||||
|
||||
async with engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
|
||||
async with session_factory() as session:
|
||||
user = User(
|
||||
username='skill_user',
|
||||
email='skill@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Skill Tester',
|
||||
)
|
||||
other_user = User(
|
||||
username='other_skill_user',
|
||||
email='other-skill@example.com',
|
||||
hashed_password=get_password_hash('secret123'),
|
||||
full_name='Other Skill Tester',
|
||||
)
|
||||
session.add_all([user, other_user])
|
||||
await session.flush()
|
||||
session.add_all([
|
||||
Skill(
|
||||
name='Planner skill',
|
||||
description='planner',
|
||||
instructions='plan',
|
||||
agent_type='schedule_planner',
|
||||
tools=['calendar'],
|
||||
required_context=[],
|
||||
visibility='private',
|
||||
is_active=True,
|
||||
owner_id=user.id,
|
||||
),
|
||||
Skill(
|
||||
name='Executor skill',
|
||||
description='executor',
|
||||
instructions='execute',
|
||||
agent_type='executor',
|
||||
tools=['shell'],
|
||||
required_context=[],
|
||||
visibility='private',
|
||||
is_active=True,
|
||||
owner_id=user.id,
|
||||
),
|
||||
Skill(
|
||||
name='Other user planner skill',
|
||||
description='other',
|
||||
instructions='other',
|
||||
agent_type='schedule_planner',
|
||||
tools=['calendar'],
|
||||
required_context=[],
|
||||
visibility='private',
|
||||
is_active=True,
|
||||
owner_id=other_user.id,
|
||||
),
|
||||
])
|
||||
await session.commit()
|
||||
await session.refresh(user)
|
||||
|
||||
async def override_get_db():
|
||||
async with session_factory() as session:
|
||||
yield session
|
||||
|
||||
async def override_get_current_user():
|
||||
return user
|
||||
|
||||
test_app = FastAPI()
|
||||
test_app.include_router(auth_router)
|
||||
test_app.include_router(skill_router)
|
||||
test_app.dependency_overrides[get_db] = override_get_db
|
||||
test_app.dependency_overrides[get_current_user] = override_get_current_user
|
||||
|
||||
try:
|
||||
yield test_app, session_factory
|
||||
finally:
|
||||
await engine.dispose()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_skills_filters_by_agent_type(skill_env):
|
||||
test_app, _session_factory = skill_env
|
||||
transport = ASGITransport(app=test_app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/skills', params={'agent_type': 'schedule_planner'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
names = {item['name'] for item in payload}
|
||||
assert names == {'Planner skill'}
|
||||
assert 'Other user planner skill' not in names
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_init_db_migrates_planner_skills_to_schedule_planner(skill_env):
|
||||
app, session_factory = skill_env
|
||||
async with session_factory() as session:
|
||||
await session.execute(text("UPDATE skills SET agent_type = 'planner' WHERE name = 'Planner skill'"))
|
||||
await session.commit()
|
||||
|
||||
from app.database import init_db
|
||||
|
||||
await init_db()
|
||||
|
||||
async with session_factory() as session:
|
||||
migrated_response = await session.execute(text("SELECT agent_type FROM skills WHERE name = 'Planner skill'"))
|
||||
assert migrated_response.scalar_one() == 'schedule_planner'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_skills_visibility_filter_still_respects_access_scope(skill_env):
|
||||
test_app, _session_factory = skill_env
|
||||
transport = ASGITransport(app=test_app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/skills', params={'visibility': 'private'})
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
names = {item['name'] for item in payload}
|
||||
assert names == {'Planner skill', 'Executor skill'}
|
||||
assert 'Other user planner skill' not in names
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_skills_bootstraps_builtin_market_skills_for_current_user(skill_env):
|
||||
test_app, session_factory = skill_env
|
||||
async with session_factory() as session:
|
||||
await session.execute(text("DELETE FROM skills"))
|
||||
await session.commit()
|
||||
|
||||
transport = ASGITransport(app=test_app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
login_response = await client.post(
|
||||
'/api/auth/login',
|
||||
data={'username': 'skill_user', 'password': 'secret123'},
|
||||
headers={'content-type': 'application/x-www-form-urlencoded'},
|
||||
)
|
||||
|
||||
assert login_response.status_code == 200
|
||||
|
||||
async with session_factory() as session:
|
||||
result = await session.execute(select(Skill.name, Skill.is_builtin).order_by(Skill.name))
|
||||
skills = result.all()
|
||||
|
||||
names = {name for name, _is_builtin in skills}
|
||||
assert '今日重点拆解' in names
|
||||
assert '任务执行 SOP' in names
|
||||
assert any(is_builtin is True for _name, is_builtin in skills)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_skills_without_agent_type_returns_current_user_skills(skill_env):
|
||||
test_app, _session_factory = skill_env
|
||||
transport = ASGITransport(app=test_app)
|
||||
async with AsyncClient(transport=transport, base_url='http://testserver') as client:
|
||||
response = await client.get('/api/skills')
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.json()
|
||||
names = {item['name'] for item in payload}
|
||||
assert names == {'Planner skill', 'Executor skill'}
|
||||
assert 'Other user planner skill' not in names
|
||||
assert all(isinstance(item['created_at'], str) for item in payload)
|
||||
assert all(isinstance(item['updated_at'], str) for item in payload)
|
||||
assert all('is_builtin' in item for item in payload)
|
||||
assert all(item['is_builtin'] is False for item in payload)
|
||||
Binary file not shown.
BIN
data/chroma/1d804941-2e95-4374-a12a-494d382b6543/length.bin
Normal file
BIN
data/chroma/1d804941-2e95-4374-a12a-494d382b6543/length.bin
Normal file
Binary file not shown.
BIN
data/chroma/chroma.sqlite3
Normal file
BIN
data/chroma/chroma.sqlite3
Normal file
Binary file not shown.
BIN
data/jarvis.db
Normal file
BIN
data/jarvis.db
Normal file
Binary file not shown.
67
data/uploads/8e2ac9cc-53dd-4548-986f-8289d830cf99.txt
Normal file
67
data/uploads/8e2ac9cc-53dd-4548-986f-8289d830cf99.txt
Normal file
@@ -0,0 +1,67 @@
|
||||
中共中央办公厅 国务院办公厅印发《关于加强国有企业资产负债约束的指导意见》
|
||||
|
||||
新华社北京9月13日电 近日，中共中央办公厅、国务院办公厅印发了《关于加强国有企业资产负债约束的指导意见》，并发出通知，要求各地区各部门结合实际认真贯彻落实。
|
||||
|
||||
《关于加强国有企业资产负债约束的指导意见》全文如下：
|
||||
|
||||
为深入贯彻习近平新时代中国特色社会主义思想和党的十九大精神，落实中央经济工作会议、全国金融工作会议和中央财经委员会第一次会议部署，加强国有企业资产负债约束，降低国有企业杠杆率，推动国有资本做强做优做大，增强经济发展韧性，提高经济发展质量，现提出如下指导意见。
|
||||
|
||||
一、总体要求
|
||||
|
||||
（一）总体目标。加强国有企业资产负债约束是打好防范化解重大风险攻坚战的重要举措。要通过建立和完善国有企业资产负债约束机制，强化监督管理，促使高负债国有企业资产负债率尽快回归合理水平，推动国有企业平均资产负债率到2020年年末比2017年年末降低2个百分点左右，之后国有企业资产负债率基本保持在同行业同规模企业的平均水平。
|
||||
|
||||
（二）基本原则
|
||||
|
||||
——坚持全面覆盖与分类管理相结合。所有行业、所有类型国有企业均纳入资产负债约束管理体制。同时，根据不同行业资产负债特征，分行业设置国有企业资产负债约束指标标准。突出监管重点，对超出约束指标标准的国有企业，结合企业所处发展阶段，在综合评价企业各类财务指标和业务发展前景基础上，根据风险大小采取适当管控措施。严格控制产能过剩行业国有企业资产负债率，适度灵活掌握有利于推动经济转型升级发展的战略性新兴产业、创新创业等领域的国有企业资产负债率。
|
||||
|
||||
——坚持完善内部治理与强化外部约束相结合。加强国有企业资产负债约束要与深化国有企业改革、建立现代企业制度、优化企业治理结构等有机结合，建立健全长效机制。同时，通过强化考核、增强企业财务真实性和透明度、合理限制债务融资和投资等方式，加强国有企业资产负债外部约束。
|
||||
|
||||
——坚持提质增效与政策支持相结合。各有关方面要积极主动作为，根据总体目标要求进一步明确高负债国有企业降低资产负债率的目标、步骤、方式，并限期完成。国有企业要坚持提质增效、苦练内功，通过扩大经营积累增强企业资本实力，在严防国有资产流失前提下，不断降低资产负债率。同时，要为高负债国有企业降低资产负债率创造良好政策和制度环境，完善资本补充机制，扩大股权融资，支持盘活存量资产，稳妥有序开展债务重组和市场化债转股。
|
||||
|
||||
二、分类确定国有企业资产负债约束指标标准
|
||||
|
||||
国有企业资产负债约束以资产负债率为基础约束指标，对不同行业、不同类型国有企业实行分类管理并动态调整。原则上以本行业上年度规模以上全部企业平均资产负债率为基准线，基准线加5个百分点为本年度资产负债率预警线，基准线加10个百分点为本年度资产负债率重点监管线。国有企业集团合并报表资产负债率预警线和重点监管线，可由相关国有资产管理部门根据主业构成、发展水平以及分类监管要求确定。邮政、铁路等特殊行业或无法取得统计数据行业的企业资产负债率预警线和重点监管线，由相关国有资产管理部门根据国家政策导向、行业情况并参考国际经验确定。
|
||||
|
||||
由国务院国资委履行出资人职责的中央企业，资产负债率管控工作继续执行现行要求，实践中再予以调整完善。金融类国有企业资产负债约束按照现有管理制度和标准实施。
|
||||
|
||||
三、完善国有企业资产负债自我约束机制
|
||||
|
||||
（一）合理设定资产负债率水平和资产负债结构。国有企业要根据相应资产负债率预警线和重点监管线，综合考虑市场前景、资金成本、盈利能力、资产流动性等因素，加强资本结构规划与管理，合理设定企业资产负债率和资产负债结构，保持财务稳健、有竞争力。
|
||||
|
||||
（二）加强资产负债约束日常管理。国有企业经营管理层要忠实勤勉履职，审慎开展债务融资、投资、支出、对外担保等业务活动，防止有息负债和或有债务过度累积，确保资产负债率保持在合理水平。在年度董事会或股东（大）会议案中，要就资产负债状况及未来资产负债计划进行专项说明，并按照规范的公司治理程序，提交董事会或股东（大）会审议。在企业可能或已实质陷入财务困境时，要及时主动向相关债权人通报有关情况，依法依规与相关债权人协商，分类稳妥处置相关债务。
|
||||
|
||||
（三）强化国有企业集团公司对所属子企业资产负债约束。国有企业集团公司要根据子企业所处行业等情况，按照国有企业资产负债率控制指标要求，合理确定子企业的资产负债率水平，并将子企业的资产负债约束纳入集团公司考核体系，确保子企业严格贯彻执行。国有企业集团公司要进一步强化子企业资产、财务和业务独立性，减少母子企业、子企业与子企业之间的风险传染。
|
||||
|
||||
（四）增强内源性资本积累能力。国有企业要牢固树立新发展理念，以提高发展质量和效益为中心，着力提升经营管理水平，进一步明确并聚焦主业瘦身健体，通过创新驱动提高生产率，增强企业盈利能力，提高企业资产和资本回报率，为企业发展提供持续的内源性资本。
|
||||
|
||||
四、强化国有企业资产负债外部约束机制
|
||||
|
||||
（一）建立科学规范的企业资产负债监测与预警体系。相关国有资产管理部门要建立以资产负债率为核心，以企业成长性、效益、偿债能力等方面指标为辅助的企业资产负债监测与预警体系。对资产负债率超过预警线和重点监管线的国有企业，相关国有资产管理部门要综合分析企业所在行业特点、发展阶段、有息负债和经营性负债等债务类型结构、短期负债和中长期负债等债务期限结构，以及息税前利润、利息保障倍数、流动比率、速动比率、经营活动现金净流量等指标，科学评估其债务风险状况，并根据风险大小程度分别列出重点关注和重点监管企业名单，对其债务风险情况持续监测。
|
||||
|
||||
（二）建立高负债企业限期降低资产负债率机制。对列入重点监管企业名单的国有企业，相关国有资产管理部门要明确其降低资产负债率的目标和时限，并负责监督实施。不得实施推高资产负债率的境内外投资，重大投资要履行专门审批程序，严格高风险业务管理，并大幅压减各项费用支出。依据市场化法治化原则，与业务重组、提质增效相结合，积极通过优化债务结构、开展股权融资、实施市场化债转股、依法破产等途径有效降低企业债务水平。
|
||||
|
||||
（三）健全资产负债约束的考核引导。相关国有资产管理部门要加强过程监督检查，将降杠杆减负债成效作为企业考核和评价的重要内容。对列入重点关注和重点监管企业名单的企业，要将企业资产负债率纳入年度经营业绩考核范围，充分发挥考核引导作用，督促企业贯彻落实资产负债管控要求。
|
||||
|
||||
（四）加强金融机构对高负债企业的协同约束。对资产负债率超出预警线的国有企业，相关金融机构要加强贷款信息共享，摸清企业表外融资、对外担保和其他隐性负债情况，全面审慎评估其信用风险，并根据风险状况合理确定利率、抵质押物、担保等贷款条件。对列入重点关注企业名单或资产负债率超出重点监管线的国有企业，新增债务融资原则上应通过金融机构联合授信方式开展，由金融机构共同确定企业授信额度，避免金融机构无序竞争和过度授信，严控新增债务融资。对列入重点监管企业名单的国有企业，金融机构原则上不得对其新增债务融资。
|
||||
|
||||
（五）强化企业财务失信行为联合惩戒机制。加强企业财务真实性和透明度审核监督。国有企业负责人对企业财务真实性负全责，要确保企业不虚报资产隐匿债务，财务信息真实可靠。会计师事务所等专业中介机构要严格按照会计准则规范出具审计报告，客观准确反映企业资产负债状况。加强社会信用体系建设，完善企业财务失信行为联合惩戒机制，将违法违规企业、中介机构及相关责任人员纳入失信人名单，并依法依规严格追究责任，加大处罚力度。
|
||||
|
||||
五、加强国有企业资产负债约束的配套措施
|
||||
|
||||
（一）厘清政府债务与企业债务边界。坚决遏制地方政府以企业债务的形式增加隐性债务。严禁地方政府及其部门违法违规或变相通过国有企业举借债务，严禁国有企业违法违规向地方政府提供融资或配合地方政府变相举债；违法违规提供融资或配合地方政府变相举债的国有企业，应当依法承担相应责任。多渠道盘活各类资金和资产，积极稳妥化解以企业债务形式形成的地方政府存量隐性债务，保障国有企业合法权益。进一步完善国有企业参与国家或地方发展战略、承担公共服务等的合法权益保障机制。各级政府和社会组织要严格落实减轻企业负担的各项政策，一般情况下，不得强制要求国有企业承担应由政府或社会组织承担的公益性支出责任。国有企业自愿承担的，应严格履行相应决策程序。加快推进“三供一业”分离移交，减轻国有企业办社会负担，协助解决国有企业历史遗留问题。
|
||||
|
||||
（二）支持国有企业盘活存量资产优化债务结构。鼓励国有企业采取租赁承包、合作利用、资源再配置、资产置换或出售等方式实现闲置资产流动，提高资产使用效率，优化资源配置。鼓励国有企业整合内部资源，将与主业相关的资产整合清理后并入主业板块，提高存量资产利用水平，改善企业经营效益。鼓励国有企业加强资金集中管理，强化内部资金融通，提高企业资金使用效率。支持国有企业盘活土地使用权、探矿权、采矿权等无形资产，充分实现市场价值。积极支持国有企业按照真实出售、破产隔离原则，依法合规开展以企业应收账款、租赁债权等财产权利和基础设施、商业物业等不动产财产或财产权益为基础资产的资产证券化业务。推动国有企业开展债务清理，减少无效占用，加快资金周转。在风险可控前提下，鼓励国有企业利用债券市场提高直接融资比重，优化企业债务结构。
|
||||
|
||||
（三）完善国有企业多渠道资本补充机制。以增加经营效益为前提，进一步完善国有企业留存利润补充资本机制。与完善国有经济战略布局相结合，实现国有资本有进有退动态管理，将从产能过剩行业退出的国有资本用于急需发展行业和领域国有企业的资本补充。充分发挥国有资本经营预算资金的作用，在逐步解决企业历史遗留问题及相关改革成本后，更多作为资本投向关系国家安全、国民经济命脉的重要行业和关键领域。充分运用国有资本投资、运营公司，吸收社会资金转化为资本。积极推进混合所有制改革，鼓励国有企业通过出让股份、增资扩股、合资合作等方式引入民营资本。鼓励国有企业充分通过多层次资本市场进行股权融资，引导国有企业通过私募股权投资基金方式筹集股权性资金，扩大股权融资规模。支持国有企业通过股债结合、投贷联动等方式开展融资，有效控制债务风险。鼓励国有企业通过主动改造改制创造条件实施市场化债转股。
|
||||
|
||||
（四）积极推动国有企业兼并重组。支持通过兼并重组培育优质国有企业。鼓励国有企业跨地区开展兼并重组。加大对产业集中度不高、同质化竞争突出行业国有企业的联合重组力度。鼓励各类投资者通过股权投资基金、创业投资基金、产业投资基金等形式参与国有企业兼并重组。
|
||||
|
||||
（五）依法依规实施国有企业破产。充分发挥企业破产在解决债务矛盾、公平保障各方权利、优化资源配置等方面的重要作用。支持国有企业依法对扭亏无望、已失去生存发展前景的“僵尸子企业”进行破产清算。对符合破产条件但仍有发展前景的子企业，支持债权人和国有企业按照法院破产重整程序或自主协商对企业进行债务重组。对严重资不抵债失去清偿能力的地方政府融资平台公司，依法实施破产重整或清算，坚决防止“大而不能倒”，坚决防止风险累积形成系统性风险。同时，要做好与企业破产相关的维护社会稳定工作。
|
||||
|
||||
六、加强国有企业资产负债约束的组织实施
|
||||
|
||||
（一）明确各类责任主体。国有企业是落实资产负债约束的第一责任主体，要按照本指导意见要求，明确企业资产负债率控制目标，深化内部改革，强化自我约束，有效防范债务风险，严防国有资产流失，确保企业可持续经营。相关金融机构要根据国有企业资产负债和经营情况，审慎评估企业债务融资需求，平衡股债融资比例，加强贷后管理，开展债务重组，协助企业及时防范和化解债务风险。对落实本指导意见不力和经营行为不审慎导致资产负债率长期超出合理水平的国有企业及其主要负责人，相关部门要加大责任追究力度。对落实本指导意见弄虚作假的国有企业，相关部门要对其主要负责人及负有直接责任人员从严从重处罚。
|
||||
|
||||
（二）建立部门信息共享和社会公开监督约束机制。相关国有资产管理部门要将列入重点关注和重点监管企业名单的企业及其债务风险状况，报送积极稳妥降低企业杠杆率工作部际联席会议（以下简称联席会议）办公室，并由联席会议办公室通报相关部门，为相关部门开展工作提供必要基础信息。各级相关国有资产管理部门要将各类企业资产负债率预警线和重点监管线以及按照规定应公开的企业财务信息，通过“信用中国”等媒介向社会公开，接受社会监督。
|
||||
|
||||
（三）加强国有企业资产负债约束实施工作的组织协调。各级相关国有资产管理部门要按照本指导意见确定的降低国有企业资产负债率目标和约束标准，分解落实、细化要求、加强指导、严格考核，有关情况及时报告联席会议办公室。各级审计部门要依法独立开展审计监督，促进国有企业资产负债约束落实到位。相关金融管理部门要按照本指导意见进一步明确规则，加强对金融机构的业务指导和督促。各级政府向本级人大常委会报告国有资产管理情况时，应报告国有企业资产负债情况和资产负债率控制情况。联席会议要加强组织领导、统筹协调、检查督导和监督问责，确保国有企业降低资产负债率取得实效。重大问题要及时报告党中央、国务院。
|
||||
752
demo/index_backup.html
Normal file
752
demo/index_backup.html
Normal file
@@ -0,0 +1,752 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>J.A.R.V.I.S. Interface</title>
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
<link
|
||||
href="https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700;900&family=Share+Tech+Mono&display=swap"
|
||||
rel="stylesheet">
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
|
||||
<style>
|
||||
:root {
|
||||
--jarvis-blue: #00f3ff;
|
||||
--jarvis-blue-dim: rgba(0, 243, 255, 0.1);
|
||||
--jarvis-alert: #ff3333;
|
||||
--bg-color: #020408;
|
||||
}
|
||||
|
||||
body {
|
||||
background-color: var(--bg-color);
|
||||
color: var(--jarvis-blue);
|
||||
font-family: 'Orbitron', sans-serif;
|
||||
overflow: hidden;
|
||||
margin: 0;
|
||||
height: 100vh;
|
||||
width: 100vw;
|
||||
}
|
||||
|
||||
/* Scanline effect */
|
||||
body::after {
|
||||
content: "";
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100vw;
|
||||
height: 100vh;
|
||||
background: linear-gradient(to bottom,
|
||||
rgba(255, 255, 255, 0),
|
||||
rgba(255, 255, 255, 0) 50%,
|
||||
rgba(0, 0, 0, 0.1) 50%,
|
||||
rgba(0, 0, 0, 0.1));
|
||||
background-size: 100% 3px;
|
||||
pointer-events: none;
|
||||
z-index: 50;
|
||||
}
|
||||
|
||||
/* Vignette */
|
||||
.vignette {
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: radial-gradient(circle, transparent 50%, rgba(0, 0, 0, 0.95) 100%);
|
||||
pointer-events: none;
|
||||
z-index: 40;
|
||||
}
|
||||
|
||||
/* Text & Border Utilities */
|
||||
.text-glow {
|
||||
text-shadow: 0 0 5px var(--jarvis-blue), 0 0 10px var(--jarvis-blue);
|
||||
}
|
||||
|
||||
.text-dim {
|
||||
color: rgba(0, 243, 255, 0.6);
|
||||
}
|
||||
|
||||
/* Tech Panels */
|
||||
.tech-panel {
|
||||
background: rgba(0, 15, 30, 0.7);
|
||||
border-left: 1px solid rgba(0, 243, 255, 0.3);
|
||||
border-right: 1px solid rgba(0, 243, 255, 0.3);
|
||||
position: relative;
|
||||
backdrop-filter: blur(4px);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.tech-panel:hover {
|
||||
border-color: rgba(0, 243, 255, 0.8);
|
||||
background: rgba(0, 20, 40, 0.8);
|
||||
}
|
||||
|
||||
/* Corner accents */
|
||||
.tech-panel::before,
|
||||
.tech-panel::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border: 1px solid var(--jarvis-blue);
|
||||
transition: all 0.3s;
|
||||
}
|
||||
|
||||
.tech-panel::before {
|
||||
top: -1px;
|
||||
left: -1px;
|
||||
border-right: none;
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.tech-panel::after {
|
||||
bottom: -1px;
|
||||
right: -1px;
|
||||
border-left: none;
|
||||
border-top: none;
|
||||
}
|
||||
|
||||
/* Tech Border Box */
|
||||
.tech-border {
|
||||
clip-path: polygon(10px 0,
|
||||
100% 0,
|
||||
100% calc(100% - 10px),
|
||||
calc(100% - 10px) 100%,
|
||||
0 100%,
|
||||
0 10px);
|
||||
border-top: 1px solid var(--jarvis-blue-dim);
|
||||
}
|
||||
|
||||
/* Scrollbars */
|
||||
::-webkit-scrollbar {
|
||||
width: 4px;
|
||||
}
|
||||
|
||||
::-webkit-scrollbar-track {
|
||||
background: rgba(0, 0, 0, 0.3);
|
||||
}
|
||||
|
||||
::-webkit-scrollbar-thumb {
|
||||
background: var(--jarvis-blue);
|
||||
border-radius: 2px;
|
||||
}
|
||||
|
||||
/* Animations */
|
||||
@keyframes pulse-status {
|
||||
|
||||
0%,
|
||||
100% {
|
||||
opacity: 0.6;
|
||||
text-shadow: 0 0 2px var(--jarvis-blue);
|
||||
box-shadow: 0 0 5px var(--jarvis-blue-dim);
|
||||
}
|
||||
|
||||
50% {
|
||||
opacity: 1;
|
||||
text-shadow: 0 0 15px var(--jarvis-blue);
|
||||
box-shadow: 0 0 15px var(--jarvis-blue-dim);
|
||||
}
|
||||
}
|
||||
|
||||
.status-pulse {
|
||||
animation: pulse-status 3s infinite ease-in-out;
|
||||
}
|
||||
|
||||
@keyframes flash-row {
|
||||
0% {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
50% {
|
||||
background-color: rgba(0, 243, 255, 0.15);
|
||||
}
|
||||
|
||||
100% {
|
||||
background-color: transparent;
|
||||
}
|
||||
}
|
||||
|
||||
.flash-row:hover {
|
||||
animation: flash-row 0.8s infinite;
|
||||
cursor: pointer;
|
||||
background: rgba(0, 243, 255, 0.05);
|
||||
}
|
||||
|
||||
/* Smooth Bar Transition */
|
||||
.sys-bar {
|
||||
transition: width 0.5s ease-out, height 0.3s ease-out;
|
||||
}
|
||||
|
||||
/* Canvas Positioning */
|
||||
#canvas-container {
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -55%);
|
||||
z-index: 10;
|
||||
width: 800px;
|
||||
height: 800px;
|
||||
pointer-events: none;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<div class="vignette"></div>
|
||||
|
||||
<!-- MAIN UI WRAPPER -->
|
||||
<div class="relative z-30 h-full w-full flex flex-col p-4 md:p-6 pointer-events-none">
|
||||
|
||||
<!-- HEADER -->
|
||||
<header class="flex justify-between items-start pointer-events-auto mb-2 border-b border-cyan-500/20 pb-2">
|
||||
<div class="flex items-center gap-4">
|
||||
<div class="flex flex-col items-center justify-center">
|
||||
<div class="w-2 h-2 bg-cyan-400 rounded-full mb-1"></div>
|
||||
<div class="h-8 w-px bg-cyan-500/50"></div>
|
||||
</div>
|
||||
<div>
|
||||
<h1 class="text-4xl font-bold tracking-[0.15em] text-glow font-orbitron">J.A.R.V.I.S.</h1>
|
||||
<div class="flex items-center gap-2 mt-1">
|
||||
<div class="h-1 w-20 bg-cyan-500/30 overflow-hidden">
|
||||
<div class="h-full bg-cyan-400 w-1/2 animate-pulse"></div>
|
||||
</div>
|
||||
<div class="text-[9px] tracking-[0.3em] opacity-70">NEURAL INTERFACE V5.1</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="text-right">
|
||||
<div class="flex items-center justify-end gap-3 mb-1">
|
||||
<span class="text-[10px] tracking-widest opacity-60">LINK STATUS</span>
|
||||
<span id="connection-status"
|
||||
class="font-bold text-xs status-pulse bg-cyan-900/40 px-3 py-1 rounded-sm border border-cyan-500/30">DISCONNECTED</span>
|
||||
</div>
|
||||
<div class="flex justify-end items-baseline gap-2">
|
||||
<span class="text-[10px] opacity-50">SYS_TIME</span>
|
||||
<div id="time-display" class="font-mono text-xl tracking-wider text-cyan-200">00:00:00</div>
|
||||
</div>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<!-- MAIN GRID LAYOUT -->
|
||||
<div class="flex-grow grid grid-cols-1 md:grid-cols-4 gap-6 pointer-events-auto h-0 min-h-0 mt-2">
|
||||
|
||||
<!-- LEFT COLUMN: DEVICES & IOT -->
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<!-- Server Status -->
|
||||
<div class="tech-panel p-4 tech-border">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
SERVER CLUSTER LOAD</h3>
|
||||
<div class="space-y-4 font-mono text-[10px]">
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">MAIN_FRAME_01</span><span
|
||||
class="text-cyan-300" id="server-1-val">ONLINE</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-1-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[34%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">DATA_CORE_ZETA</span><span
|
||||
class="text-cyan-300" id="server-2-val">PROCESSING</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-2-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[89%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">STORAGE_ARRAY</span><span
|
||||
class="text-cyan-300" id="server-3-val">STABLE</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-3-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[12%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="grid grid-cols-2 gap-2 pt-2">
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">TEMP</div>
|
||||
<div id="sys-temp" class="text-sm font-bold text-cyan-300">42°C</div>
|
||||
</div>
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">POWER</div>
|
||||
<div id="sys-power" class="text-sm font-bold text-cyan-300">98%</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Connected Devices -->
|
||||
<div class="tech-panel p-4 flex-grow overflow-hidden flex flex-col">
|
||||
<div class="flex justify-between items-center border-b border-cyan-500/30 pb-2 mb-2">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300">CONNECTED DEVICES</h3>
|
||||
<span class="text-[9px] bg-cyan-500/20 px-1 rounded animate-pulse">SCANNING</span>
|
||||
</div>
|
||||
|
||||
<ul id="device-list"
|
||||
class="font-mono text-[11px] space-y-1 overflow-y-auto pr-1 flex-grow custom-scrollbar">
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>SMART_HOME_HUB</span>
|
||||
</div>
|
||||
<span class="opacity-50 text-[9px]">192.168.1.10</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>SECURITY_CAM_GRID</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">ACTIVE</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-yellow-500 rounded-full animate-pulse"></div>
|
||||
<span>DRONE_SENTRY_04</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">CHARGING</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>MAIN_GATE_LOCK</span>
|
||||
</div>
|
||||
<span class="opacity-50 text-[9px]">SECURE</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-red-500 rounded-full"></div>
|
||||
<span>EXT_PERIMETER_SENSORS</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">ALERT</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>LAB_3D_PRINTER</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">IDLE</span>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- CENTER COLUMN: NEURAL VISUALIZATION & OUTPUT -->
|
||||
<div class="md:col-span-2 relative flex flex-col justify-end items-center">
|
||||
|
||||
<!-- Floating Status -->
|
||||
<div class="absolute top-10 w-full text-center pointer-events-none">
|
||||
<div id="ai-status"
|
||||
class="text-xl md:text-2xl font-bold tracking-[0.3em] text-glow uppercase text-cyan-100">
|
||||
NEURAL ENGINE: STANDBY
|
||||
</div>
|
||||
<div class="text-[10px] text-cyan-400/70 tracking-[0.5em] mt-2">AWAITING INPUT PARAMETERS</div>
|
||||
</div>
|
||||
|
||||
<!-- Main Terminal (Bottom Center) -->
|
||||
<div
|
||||
class="terminal-window w-full h-56 bg-black/90 border-t border-cyan-500/50 rounded-tl-lg rounded-tr-lg overflow-hidden flex flex-col backdrop-blur-md shadow-[0_-5px_20px_rgba(0,243,255,0.1)]">
|
||||
<div
|
||||
class="bg-cyan-900/20 px-3 py-1.5 text-[10px] flex justify-between border-b border-cyan-500/30 items-center">
|
||||
<span class="tracking-widest text-cyan-400">CONSOLE_OUT // ROOT_ACCESS</span>
|
||||
<div class="flex gap-2 font-mono text-cyan-600">
|
||||
<span id="pid-val">PID:4092</span>
|
||||
<span id="mem-val">MEM:24%</span>
|
||||
</div>
|
||||
</div>
|
||||
<div id="terminal-content"
|
||||
class="p-4 font-mono text-xs text-cyan-300/80 overflow-y-auto flex-grow space-y-1.5">
|
||||
<!-- Logs inject here -->
|
||||
<div class="opacity-50 border-l-2 border-cyan-800 pl-2">>> Initializing neural weights... OK
|
||||
</div>
|
||||
<div class="opacity-50 border-l-2 border-cyan-800 pl-2">>> Mounting device file system... OK
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- RIGHT COLUMN: FILES & ALGORITHMS -->
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<!-- Algorithm Status -->
|
||||
<div class="tech-panel p-4 flex-grow flex flex-col">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-2 text-cyan-300">
|
||||
ACTIVE THREADS</h3>
|
||||
<div class="font-mono text-[11px] overflow-y-auto pr-1 flex-grow space-y-3">
|
||||
|
||||
<div class="mb-2">
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/VISION</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">object_recognition.py</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">RUNNING</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">facial_scan_v2.exe</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">IDLE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/LANGUAGE</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">nlp_core_en.lib</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">LOADED</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">voice_synth_mod.dll</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">ACTIVE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/NETWORK</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">packet_sniffer.sh</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">BG</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">firewall_daemon</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">ACTIVE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Network Topology (Active Visualizer) -->
|
||||
<div class="tech-panel h-32 p-4 relative overflow-hidden flex flex-col justify-between">
|
||||
<div class="text-[10px] opacity-60 tracking-widest mb-1">NETWORK_TRAFFIC</div>
|
||||
<!-- Mock Graph Bars -->
|
||||
<div class="flex items-end justify-between h-full gap-1 pt-2" id="network-graph">
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[50%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[80%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[40%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[60%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[90%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[45%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[70%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[60%]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- THREE.JS CONTAINER -->
|
||||
<div id="canvas-container"></div>
|
||||
|
||||
<script>
|
||||
(function () {
|
||||
// --- CLOCK UTILITY ---
|
||||
function updateTime() {
|
||||
const now = new Date();
|
||||
const timeDisplay = document.getElementById('time-display');
|
||||
if (timeDisplay) {
|
||||
timeDisplay.innerText = now.toLocaleTimeString('en-US', { hour12: false });
|
||||
}
|
||||
}
|
||||
setInterval(updateTime, 1000);
|
||||
updateTime();
|
||||
|
||||
// --- THREE.JS ADVANCED NEURAL VISUALIZATION ---
|
||||
const container = document.getElementById('canvas-container');
|
||||
|
||||
if (container) {
|
||||
const scene = new THREE.Scene();
|
||||
// Subtler fog for deep space feel
|
||||
scene.fog = new THREE.FogExp2(0x020408, 0.003);
|
||||
|
||||
const camera = new THREE.PerspectiveCamera(75, 1, 0.1, 1000);
|
||||
camera.position.z = 20;
|
||||
|
||||
const renderer = new THREE.WebGLRenderer({ alpha: true, antialias: true });
|
||||
renderer.setSize(800, 800);
|
||||
renderer.setPixelRatio(window.devicePixelRatio);
|
||||
container.appendChild(renderer.domElement);
|
||||
|
||||
// --- GROUPING ---
|
||||
const brainGroup = new THREE.Group();
|
||||
scene.add(brainGroup);
|
||||
|
||||
// 1. INNER CORE (Dense Wireframe Sphere)
|
||||
const coreGeo = new THREE.IcosahedronGeometry(4, 2);
|
||||
const coreMat = new THREE.MeshBasicMaterial({
|
||||
color: 0x00f3ff,
|
||||
wireframe: true,
|
||||
transparent: true,
|
||||
opacity: 0.15
|
||||
});
|
||||
const coreMesh = new THREE.Mesh(coreGeo, coreMat);
|
||||
brainGroup.add(coreMesh);
|
||||
|
||||
// 2. NEURAL CLOUD (Nodes & Lines)
|
||||
const particleCount = 400; // Increased count
|
||||
const cloudRadius = 9;
|
||||
const particlesData = [];
|
||||
let particlePositions = new Float32Array(particleCount * 3);
|
||||
|
||||
const pMaterial = new THREE.PointsMaterial({
|
||||
color: 0x00f3ff,
|
||||
size: 0.15,
|
||||
blending: THREE.AdditiveBlending,
|
||||
transparent: true,
|
||||
opacity: 0.8
|
||||
});
|
||||
|
||||
// Generate random points in a spherical shell
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
const r = cloudRadius + (Math.random() - 0.5) * 4; // Vary radius for depth
|
||||
const theta = Math.random() * Math.PI * 2;
|
||||
const phi = Math.acos((Math.random() * 2) - 1);
|
||||
|
||||
const x = r * Math.sin(phi) * Math.cos(theta);
|
||||
const y = r * Math.sin(phi) * Math.sin(theta);
|
||||
const z = r * Math.cos(phi);
|
||||
|
||||
particlePositions[i * 3] = x;
|
||||
particlePositions[i * 3 + 1] = y;
|
||||
particlePositions[i * 3 + 2] = z;
|
||||
|
||||
particlesData.push({
|
||||
velocity: new THREE.Vector3(
|
||||
(-1 + Math.random() * 2) * 0.02,
|
||||
(-1 + Math.random() * 2) * 0.02,
|
||||
(-1 + Math.random() * 2) * 0.02
|
||||
),
|
||||
originalPos: new THREE.Vector3(x, y, z)
|
||||
});
|
||||
}
|
||||
|
||||
const particlesGeo = new THREE.BufferGeometry();
|
||||
particlesGeo.setAttribute('position', new THREE.BufferAttribute(particlePositions, 3));
|
||||
const particleSystem = new THREE.Points(particlesGeo, pMaterial);
|
||||
brainGroup.add(particleSystem);
|
||||
|
||||
// Lines setup
|
||||
const maxConnections = particleCount;
|
||||
const linesGeo = new THREE.BufferGeometry();
|
||||
const linePositions = new Float32Array(maxConnections * maxConnections * 3);
|
||||
const lineColors = new Float32Array(maxConnections * maxConnections * 3);
|
||||
|
||||
linesGeo.setAttribute('position', new THREE.BufferAttribute(linePositions, 3));
|
||||
linesGeo.setAttribute('color', new THREE.BufferAttribute(lineColors, 3));
|
||||
|
||||
const lMaterial = new THREE.LineBasicMaterial({
|
||||
vertexColors: true,
|
||||
blending: THREE.AdditiveBlending,
|
||||
transparent: true,
|
||||
opacity: 0.2
|
||||
});
|
||||
|
||||
const linesMesh = new THREE.LineSegments(linesGeo, lMaterial);
|
||||
brainGroup.add(linesMesh);
|
||||
|
||||
// 3. ORBITAL RINGS (Fast moving outer data)
|
||||
const ringGroup = new THREE.Group();
|
||||
brainGroup.add(ringGroup);
|
||||
|
||||
function createOrbitalRing(radius, count, speedX, speedY) {
|
||||
const ringGeo = new THREE.BufferGeometry();
|
||||
const ringPos = new Float32Array(count * 3);
|
||||
for (let i = 0; i < count; i++) {
|
||||
const theta = (i / count) * Math.PI * 2;
|
||||
ringPos[i * 3] = Math.cos(theta) * radius;
|
||||
ringPos[i * 3 + 1] = Math.sin(theta) * radius;
|
||||
ringPos[i * 3 + 2] = (Math.random() - 0.5) * 0.5;
|
||||
}
|
||||
ringGeo.setAttribute('position', new THREE.BufferAttribute(ringPos, 3));
|
||||
const ringMat = new THREE.PointsMaterial({ color: 0x00f3ff, size: 0.1, transparent: true, opacity: 0.6 });
|
||||
const ring = new THREE.Points(ringGeo, ringMat);
|
||||
ring.userData = { speedX, speedY };
|
||||
return ring;
|
||||
}
|
||||
|
||||
const ring1 = createOrbitalRing(11, 100, 0.005, 0.01);
|
||||
const ring2 = createOrbitalRing(13, 80, -0.01, 0.002);
|
||||
ringGroup.add(ring1);
|
||||
ringGroup.add(ring2);
|
||||
|
||||
|
||||
// --- ANIMATION LOOP ---
|
||||
function animate() {
|
||||
requestAnimationFrame(animate);
|
||||
|
||||
// 1. Rotate entire group
|
||||
brainGroup.rotation.y += 0.002;
|
||||
|
||||
// 2. Animate Core
|
||||
coreMesh.rotation.x -= 0.005;
|
||||
coreMesh.rotation.z += 0.002;
|
||||
|
||||
// 3. Animate Particles & Lines
|
||||
let vertexpos = 0;
|
||||
let colorpos = 0;
|
||||
let numConnected = 0;
|
||||
|
||||
// Update particles
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
// Jitter particles
|
||||
const p = particlesData[i];
|
||||
// Constrain to radius roughly
|
||||
particlePositions[i * 3] += p.velocity.x;
|
||||
particlePositions[i * 3 + 1] += p.velocity.y;
|
||||
particlePositions[i * 3 + 2] += p.velocity.z;
|
||||
|
||||
// Very simple bounce back logic
|
||||
if (Math.abs(particlePositions[i * 3] - p.originalPos.x) > 1) p.velocity.x = -p.velocity.x;
|
||||
if (Math.abs(particlePositions[i * 3 + 1] - p.originalPos.y) > 1) p.velocity.y = -p.velocity.y;
|
||||
if (Math.abs(particlePositions[i * 3 + 2] - p.originalPos.z) > 1) p.velocity.z = -p.velocity.z;
|
||||
}
|
||||
particlesGeo.attributes.position.needsUpdate = true;
|
||||
|
||||
// Connect lines (Optimize: only check subset or smaller distance)
|
||||
const connectionDist = 2.5;
|
||||
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
for (let j = i + 1; j < particleCount; j++) {
|
||||
const dx = particlePositions[i * 3] - particlePositions[j * 3];
|
||||
const dy = particlePositions[i * 3 + 1] - particlePositions[j * 3 + 1];
|
||||
const dz = particlePositions[i * 3 + 2] - particlePositions[j * 3 + 2];
|
||||
const dist = Math.sqrt(dx * dx + dy * dy + dz * dz);
|
||||
|
||||
if (dist < connectionDist) {
|
||||
const alpha = 1.0 - dist / connectionDist;
|
||||
|
||||
linePositions[vertexpos++] = particlePositions[i * 3];
|
||||
linePositions[vertexpos++] = particlePositions[i * 3 + 1];
|
||||
linePositions[vertexpos++] = particlePositions[i * 3 + 2];
|
||||
|
||||
linePositions[vertexpos++] = particlePositions[j * 3];
|
||||
linePositions[vertexpos++] = particlePositions[j * 3 + 1];
|
||||
linePositions[vertexpos++] = particlePositions[j * 3 + 2];
|
||||
|
||||
lineColors[colorpos++] = 0; lineColors[colorpos++] = alpha; lineColors[colorpos++] = 1;
|
||||
lineColors[colorpos++] = 0; lineColors[colorpos++] = alpha; lineColors[colorpos++] = 1;
|
||||
|
||||
numConnected++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
linesMesh.geometry.setDrawRange(0, numConnected * 2);
|
||||
linesMesh.geometry.attributes.position.needsUpdate = true;
|
||||
linesMesh.geometry.attributes.color.needsUpdate = true;
|
||||
|
||||
// 4. Animate Rings
|
||||
ring1.rotation.x += ring1.userData.speedX;
|
||||
ring1.rotation.y += ring1.userData.speedY;
|
||||
ring2.rotation.x += ring2.userData.speedX;
|
||||
ring2.rotation.y += ring2.userData.speedY;
|
||||
|
||||
renderer.render(scene, camera);
|
||||
}
|
||||
animate();
|
||||
}
|
||||
|
||||
|
||||
// --- MOCK DATA SIMULATION (The "Life" of the Dashboard) ---
|
||||
|
||||
// 1. Terminal Logger
|
||||
const terminal = document.getElementById('terminal-content');
|
||||
function addLog(message) {
|
||||
if (!terminal) return;
|
||||
const div = document.createElement('div');
|
||||
div.className = 'text-cyan-300 opacity-80 border-l-2 border-transparent hover:border-cyan-500 pl-2 py-0.5 animate-pulse-fast';
|
||||
div.innerHTML = `<span class="text-[10px] text-cyan-600 mr-2 font-bold">[${new Date().toLocaleTimeString('en-US', { hour12: false })}]</span> <span class="text-xs font-mono">${message}</span>`;
|
||||
terminal.appendChild(div);
|
||||
if (terminal.children.length > 20) terminal.removeChild(terminal.firstChild); // Keep DOM light
|
||||
terminal.scrollTop = terminal.scrollHeight;
|
||||
}
|
||||
|
||||
// 2. Update System Bars & Text
|
||||
function updateSystemStats() {
|
||||
// Server Load Bars
|
||||
document.getElementById('server-1-bar').style.width = Math.floor(Math.random() * 40 + 30) + '%'; // 30-70%
|
||||
document.getElementById('server-2-bar').style.width = Math.floor(Math.random() * 20 + 70) + '%'; // 70-90%
|
||||
document.getElementById('server-3-bar').style.width = Math.floor(Math.random() * 10 + 5) + '%'; // 5-15%
|
||||
|
||||
// Temp & Power
|
||||
document.getElementById('sys-temp').innerText = Math.floor(Math.random() * 5 + 40) + '°C';
|
||||
document.getElementById('sys-power').innerText = Math.floor(Math.random() * 3 + 96) + '%';
|
||||
|
||||
// Memory PID
|
||||
document.getElementById('mem-val').innerText = 'MEM:' + Math.floor(Math.random() * 10 + 20) + '%';
|
||||
}
|
||||
|
||||
// 3. Animate Network Graph
|
||||
function updateNetworkGraph() {
|
||||
const bars = document.querySelectorAll('#network-graph .sys-bar');
|
||||
bars.forEach(bar => {
|
||||
bar.style.height = Math.floor(Math.random() * 80 + 10) + '%';
|
||||
});
|
||||
}
|
||||
|
||||
// 4. Device Status Rotation
|
||||
function updateDeviceStatus() {
|
||||
const statuses = document.querySelectorAll('.device-status');
|
||||
const randomIdx = Math.floor(Math.random() * statuses.length);
|
||||
const el = statuses[randomIdx];
|
||||
|
||||
const states = ['ACTIVE', 'PINGING', 'SENDING', 'IDLE'];
|
||||
const newState = states[Math.floor(Math.random() * states.length)];
|
||||
|
||||
el.innerText = newState;
|
||||
if (newState === 'ACTIVE' || newState === 'SENDING') el.className = 'device-status text-cyan-300 text-[9px]';
|
||||
else el.className = 'device-status opacity-50 text-[9px]';
|
||||
}
|
||||
|
||||
// --- START SIMULATION ---
|
||||
setTimeout(() => {
|
||||
const statusEl = document.getElementById('connection-status');
|
||||
const aiStatusEl = document.getElementById('ai-status');
|
||||
|
||||
if (statusEl) {
|
||||
statusEl.innerText = "SECURE LINK ESTABLISHED";
|
||||
statusEl.classList.remove('text-red-500');
|
||||
statusEl.classList.add('text-cyan-300', 'bg-cyan-500/20', 'border-cyan-400');
|
||||
}
|
||||
|
||||
if (aiStatusEl) {
|
||||
aiStatusEl.innerHTML = "NEURAL ENGINE: <span class='text-cyan-300 drop-shadow-[0_0_10px_rgba(0,243,255,0.8)]'>ONLINE</span>";
|
||||
}
|
||||
|
||||
addLog(">> Handshake protocol complete.");
|
||||
addLog(">> Neural weights loaded into memory.");
|
||||
|
||||
// Start Interval Loops
|
||||
setInterval(() => {
|
||||
const logs = [
|
||||
"Optimizing neural pathways...", "Garbage collection active...",
|
||||
"Packet sniffing: 192.168.1.X...", "Updating heuristic models...",
|
||||
"Thermal throttling check... OK", "Syncing cloud replica...",
|
||||
"Analyzing biometric feed...", "Background process [PID:8821] started"
|
||||
];
|
||||
addLog(">> " + logs[Math.floor(Math.random() * logs.length)]);
|
||||
}, 2000);
|
||||
|
||||
setInterval(updateSystemStats, 1500);
|
||||
setInterval(updateNetworkGraph, 300); // Fast update for graph
|
||||
setInterval(updateDeviceStatus, 3000);
|
||||
|
||||
}, 1000);
|
||||
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
|
||||
</html>
|
||||
561
docs/superpowers/specs/2026-03-25-schedule-planner-design.md
Normal file
561
docs/superpowers/specs/2026-03-25-schedule-planner-design.md
Normal file
@@ -0,0 +1,561 @@
|
||||
# Schedule Planner Agent Redesign
|
||||
|
||||
## Goal
|
||||
|
||||
Replace the current planner role with a schedule-focused planning system that analyzes conversation history, the task board, and forum signals to produce actionable scheduling recommendations for the user.
|
||||
|
||||
## Scope
|
||||
|
||||
This redesign covers both the main planner role and its subagents across backend orchestration, prompts, routing, scheduled execution, todo generation, frontend presentation, and related tests.
|
||||
|
||||
## User-Approved Direction
|
||||
|
||||
- Replace the current path-planning semantics with schedule-planning semantics.
|
||||
- Redesign both the main planner role and its subagents.
|
||||
- Inputs for planning:
|
||||
- conversation history
|
||||
- task board
|
||||
- forum information
|
||||
- Output style:
|
||||
- conclusion first
|
||||
- executable schedule next
|
||||
- Trigger modes:
|
||||
- when the user explicitly asks for scheduling advice
|
||||
- at a fixed daily time
|
||||
- Daily scheduled analysis should write actionable suggestions into todo items.
|
||||
|
||||
## Architecture
|
||||
|
||||
### Main Role
|
||||
|
||||
The current `planner` role will be replaced at the system level by a new role id:
|
||||
|
||||
- `schedule_planner`
|
||||
|
||||
Its responsibility is no longer “find the shortest execution path for a goal.” Instead, it becomes the scheduling brain that:
|
||||
|
||||
1. understands current commitments and pressure signals
|
||||
2. evaluates urgency, importance, dependency, and timing
|
||||
3. recommends near-term scheduling actions
|
||||
4. converts useful scheduled guidance into concrete todo items when triggered by the daily scheduler
|
||||
|
||||
### Subagents
|
||||
|
||||
The existing planner subagent structure will be redesigned into two schedule-specific subagents:
|
||||
|
||||
- `schedule_analysis`
|
||||
- analyzes conversation history, task board state, and forum signals
|
||||
- identifies priorities, pressure points, conflicts, dependencies, risks, and things that can be delayed
|
||||
|
||||
- `schedule_planning`
|
||||
- converts analysis into an execution-oriented schedule recommendation
|
||||
- outputs conclusion first, then a practical schedule proposal
|
||||
- when running from the daily scheduled workflow, produces todo-ready action items
|
||||
|
||||
### Trigger Paths
|
||||
|
||||
#### Interactive Trigger
|
||||
|
||||
When the user asks questions such as:
|
||||
|
||||
- what should I do today
|
||||
- how should I arrange this week
|
||||
- based on my recent work, what should I focus on next
|
||||
- help me schedule upcoming work
|
||||
|
||||
The master agent should route to `schedule_planner`.
|
||||
|
||||
The expected response shape:
|
||||
|
||||
1. current conclusion
|
||||
2. today / near-term schedule recommendation
|
||||
3. next actions
|
||||
|
||||
#### Daily Scheduled Trigger
|
||||
|
||||
A daily scheduled job invokes the schedule planner flow automatically.
|
||||
|
||||
The daily run should:
|
||||
|
||||
1. collect relevant context from conversation history, tasks, and forum data
|
||||
2. run `schedule_analysis`
|
||||
3. run `schedule_planning`
|
||||
4. convert only actionable, non-duplicate recommendations into todo items
|
||||
|
||||
The daily run should not dump raw analysis into todos. Only concise, action-worthy, user-meaningful recommendations become todos.
|
||||
|
||||
## Data Flow
|
||||
|
||||
### Inputs
|
||||
|
||||
The schedule planning system should read from three sources:
|
||||
|
||||
1. **Conversation history**
|
||||
- recent user intent
|
||||
- commitments implied in prior discussion
|
||||
- stated priorities, urgency, and unresolved threads
|
||||
|
||||
2. **Task board**
|
||||
- open items
|
||||
- current statuses
|
||||
- stalled work
|
||||
- high-priority or overdue work
|
||||
|
||||
3. **Forum information**
|
||||
- new items requiring attention
|
||||
- external pressure or discussion signals
|
||||
- updates that may change priority
|
||||
|
||||
### Internal Processing
|
||||
|
||||
The main flow should be:
|
||||
|
||||
- Master decides scheduling intent
|
||||
- `schedule_planner` receives context
|
||||
- `schedule_analysis` identifies priority structure
|
||||
- `schedule_planning` produces human-usable output
|
||||
- scheduled mode additionally writes selected suggestions into todos
|
||||
|
||||
### Outputs
|
||||
|
||||
#### Interactive Output
|
||||
|
||||
The default answer structure should be:
|
||||
|
||||
- conclusion first
|
||||
- suggested schedule second
|
||||
- next actions last
|
||||
|
||||
#### Scheduled Output
|
||||
|
||||
The scheduled run should create todo entries with:
|
||||
|
||||
- concise action phrasing
|
||||
- enough context to be actionable
|
||||
- source attribution where useful (conversation/task/forum)
|
||||
- duplicate avoidance
|
||||
|
||||
## Migration Strategy
|
||||
|
||||
This redesign uses a two-phase migration to avoid breaking stored state and UI rendering.
|
||||
|
||||
### Phase 1: Compatibility Window
|
||||
|
||||
- accept legacy `planner` values from stored traces, mock payloads, and historical records
|
||||
- normalize legacy `planner` to `schedule_planner` at read boundaries where practical
|
||||
- accept legacy `planner_scope` and `planner_steps` as read-only legacy values and normalize them to `schedule_analysis` and `schedule_planning`
|
||||
- write only the new ids going forward:
|
||||
- `schedule_planner`
|
||||
- `schedule_analysis`
|
||||
- `schedule_planning`
|
||||
|
||||
### Phase 2: Legacy Removal
|
||||
|
||||
After the migration is complete and all active UI payloads, mock data, and tests are updated:
|
||||
|
||||
- remove legacy id acceptance from orchestration and frontend display logic
|
||||
- remove legacy mock fixtures
|
||||
- keep migration code out of prompts and core scheduling behavior
|
||||
|
||||
### Migration Scope
|
||||
|
||||
The migration must cover:
|
||||
|
||||
- backend enums and routing
|
||||
- frontend agent ids and telemetry labels
|
||||
- stored trace rendering paths
|
||||
- mock data used by agent dashboards and chat orchestration views
|
||||
- tests that still refer to `planner`, `planner_scope`, or `planner_steps`
|
||||
|
||||
## Input Contracts
|
||||
|
||||
The schedule planning system reads from three sources with explicit limits.
|
||||
|
||||
### Conversation History Contract
|
||||
|
||||
- use recent conversation history from the current user context
|
||||
- default retrieval window: last 7 days of relevant conversation turns, capped at the latest 50 turns
|
||||
- prefer turns that include commitments, priorities, deadlines, blockers, or future-oriented intent
|
||||
- if conversation history is unavailable, continue with degraded confidence
|
||||
|
||||
### Task Board Contract
|
||||
|
||||
- include open, in-progress, blocked, overdue, and high-priority tasks
|
||||
- exclude completed and archived items by default
|
||||
- include enough task metadata to reason about urgency and dependency:
|
||||
- title
|
||||
- status
|
||||
- priority
|
||||
- due date if present
|
||||
- last updated time if present
|
||||
- if task data is unavailable, continue with degraded confidence
|
||||
|
||||
### Forum Information Contract
|
||||
|
||||
- include recent forum items that may affect user priorities
|
||||
- default retrieval window: last 7 days of relevant forum signals
|
||||
- forum signals may include:
|
||||
- new posts requiring attention
|
||||
- replies or escalations
|
||||
- updates that change urgency or expected follow-up
|
||||
- if forum data is unavailable, continue with degraded confidence
|
||||
|
||||
## Output Contracts
|
||||
|
||||
### `schedule_analysis` Output Schema
|
||||
|
||||
The analysis stage should produce a structured summary with these fields:
|
||||
|
||||
- `top_priorities`: list of current highest-priority focus areas
|
||||
- `risks`: list of risk or pressure signals
|
||||
- `conflicts`: list of timing or dependency conflicts
|
||||
- `deferrable_items`: list of lower-priority items that can be delayed
|
||||
- `evidence`: source references grouped by `conversation`, `task_board`, or `forum`
|
||||
- `confidence`: one of `high`, `medium`, `low`
|
||||
|
||||
### `schedule_planning` Output Schema
|
||||
|
||||
The planning stage should produce a structured recommendation with these fields:
|
||||
|
||||
- `conclusion`: short decision-oriented summary
|
||||
- `today_plan`: list of suggested actions for the current day or immediate next window
|
||||
- `near_term_plan`: list of actions for the next few days or current week
|
||||
- `next_actions`: short ordered action list
|
||||
- `todo_candidates`: only present in scheduled mode; candidate todo items derived from the recommendation
|
||||
- `confidence`: one of `high`, `medium`, `low`
|
||||
|
||||
### `todo_candidates` Schema
|
||||
|
||||
Each `todo_candidate` must use this structure:
|
||||
|
||||
- `title`: required short action text
|
||||
- `description`: required short rationale grounded in source context
|
||||
- `sources`: required list of provenance objects
|
||||
- `priority`: optional normalized priority such as `high`, `medium`, `low`
|
||||
- `target_window`: optional string such as `today` or `this_week`
|
||||
|
||||
Each provenance object in `sources` must contain:
|
||||
|
||||
- `type`: one of `conversation`, `task_board`, `forum`
|
||||
- `id`: source object id when available, otherwise a stable synthetic reference
|
||||
- `label`: short human-readable source label
|
||||
|
||||
### Evidence Structure
|
||||
|
||||
Each item in `schedule_analysis.evidence` must contain:
|
||||
|
||||
- `type`: one of `conversation`, `task_board`, `forum`
|
||||
- `id`: source object id when available, otherwise a stable synthetic reference
|
||||
- `label`: short human-readable identifier
|
||||
- `reason`: brief explanation of why the signal matters to scheduling
|
||||
|
||||
### Interactive Response Contract
|
||||
|
||||
The user-facing answer should always follow this shape:
|
||||
|
||||
1. conclusion
|
||||
2. suggested schedule
|
||||
3. next actions
|
||||
|
||||
If confidence is low, the response must say that explicitly and avoid overconfident scheduling language.
|
||||
|
||||
## Daily Scheduler Contract
|
||||
|
||||
The daily scheduled trigger must follow explicit execution semantics.
|
||||
|
||||
### Execution Model
|
||||
|
||||
- run once per user per local date
|
||||
- default execution time: 07:00 in the user's configured timezone
|
||||
- if the user has no configured timezone, skip the run and log the skip reason
|
||||
- do not automatically backfill missed runs
|
||||
- enforce idempotency by `(user_id, local_date, job_type)` so the same daily analysis is not executed more than once successfully
|
||||
|
||||
### Scheduled Mode Behavior
|
||||
|
||||
A successful scheduled run should:
|
||||
|
||||
1. gather available context from the three input sources
|
||||
2. execute `schedule_analysis`
|
||||
3. execute `schedule_planning`
|
||||
4. create todo items from selected `todo_candidates`
|
||||
5. store run telemetry and outcome metadata
|
||||
|
||||
If one or more sources are missing, continue when there is still enough evidence to produce a useful recommendation and mark confidence as reduced.
|
||||
|
||||
Signal evaluation rules:
|
||||
|
||||
- a **strong source** is a source with enough current evidence to support prioritization on its own, such as multiple open high-priority tasks or a recent forum escalation
|
||||
- a **meaningful signal** is a discrete scheduling-relevant item extracted from any source, such as an overdue task, a stated commitment in conversation history, or a forum escalation
|
||||
- the planner may still run with one strong source
|
||||
- scheduled mode may create todos only when at least two meaningful signals exist across all inputs
|
||||
|
||||
If fewer than two meaningful signals are available across all sources, the scheduler should not create todos and should log a low-context outcome.
|
||||
|
||||
Delayed execution rule:
|
||||
|
||||
- if the 07:00 run is delayed by temporary outage or worker unavailability, the system may still execute one delayed run later on the same user-local date
|
||||
- if the entire local date passes without a successful run, do not backfill on the next day
|
||||
|
||||
## Todo Creation Rules
|
||||
|
||||
Todo creation is the main scheduled side effect and must be tightly constrained.
|
||||
|
||||
### Creation Rules
|
||||
|
||||
- create at most 3 todo items per daily run
|
||||
- only create todos for actions that are concrete, near-term, and user-actionable
|
||||
- do not create todos for vague advice, reflections, or duplicated reminders
|
||||
- store source provenance when available:
|
||||
- `conversation`
|
||||
- `task_board`
|
||||
- `forum`
|
||||
|
||||
### Duplicate Detection
|
||||
|
||||
A candidate todo is considered a duplicate if there is already an open todo that matches all of the following:
|
||||
|
||||
- same normalized action text
|
||||
- same source category or same source object when available
|
||||
- created within the last 7 days
|
||||
|
||||
Normalization rules for action text:
|
||||
|
||||
- trim surrounding whitespace
|
||||
- collapse repeated internal whitespace to a single space
|
||||
- lowercase Latin characters
|
||||
- remove trailing full stop / period punctuation only
|
||||
|
||||
Source comparison rules:
|
||||
|
||||
- if a provenance object includes a stable source `id`, compare by `(type, id)`
|
||||
- if no stable source id exists, compare by `(type, normalized label)`
|
||||
- if multiple sources support one recommendation, compare against the highest-priority provenance in this order: `task_board`, `forum`, `conversation`
|
||||
|
||||
When a duplicate is detected:
|
||||
|
||||
- do not create a new todo
|
||||
- record the skip reason in scheduler telemetry
|
||||
|
||||
### Todo Fields
|
||||
|
||||
Scheduled-created todos should include at minimum these persisted fields:
|
||||
|
||||
- `title`: required
|
||||
- `description`: required
|
||||
- `source_type`: required primary provenance type
|
||||
- `source_id`: optional stable source id
|
||||
- `source_label`: required fallback human-readable provenance label
|
||||
- `created_by`: required and set to `schedule_planner`
|
||||
- `created_at`: required timestamp
|
||||
- `priority`: optional normalized priority
|
||||
- `target_window`: optional normalized scheduling window
|
||||
|
||||
## Routing Boundaries
|
||||
|
||||
The system must distinguish scheduling from adjacent planning behaviors.
|
||||
|
||||
### Route to `schedule_planner` when the user asks for:
|
||||
|
||||
- today or this week planning
|
||||
- what to focus on next
|
||||
- priority ordering across ongoing work
|
||||
- time-aware sequencing of current commitments
|
||||
|
||||
### Do not route to `schedule_planner` when the user asks for:
|
||||
|
||||
- deep implementation planning for a feature
|
||||
- code execution or task fulfillment
|
||||
- research-only retrieval
|
||||
- pure analysis without scheduling intent
|
||||
|
||||
In ambiguous cases such as "what should I do next?", prefer `schedule_planner` when the available context includes multiple active tasks, recent commitments, or forum pressure signals.
|
||||
|
||||
## Backend Changes
|
||||
|
||||
### Role and Graph Layer
|
||||
|
||||
Update the orchestration layer so the planner role is redefined as `schedule_planner` rather than `planner`.
|
||||
|
||||
Files likely involved:
|
||||
|
||||
- `backend/app/agents/state.py`
|
||||
- `backend/app/agents/graph.py`
|
||||
- `backend/app/agents/prompts.py`
|
||||
- `backend/app/routers/agent.py`
|
||||
- `backend/app/services/agent_service.py`
|
||||
|
||||
Required changes:
|
||||
|
||||
- rename role ids where appropriate
|
||||
- update graph node registration
|
||||
- update master routing rules
|
||||
- replace planner subagent mappings
|
||||
- update telemetry and sub-commander trace labels
|
||||
|
||||
### Prompt Layer
|
||||
|
||||
Replace the current planner prompt family with schedule-specific instructions.
|
||||
|
||||
Needed prompt families:
|
||||
|
||||
- `SCHEDULE_PLANNER_SYSTEM_PROMPT`
|
||||
- `SCHEDULE_ANALYSIS_PROMPT`
|
||||
- `SCHEDULE_PLANNING_PROMPT`
|
||||
|
||||
Prompt requirements:
|
||||
|
||||
- reason over conversation history, tasks, and forum state
|
||||
- prioritize urgency, importance, and dependency
|
||||
- avoid abstract productivity advice
|
||||
- produce concrete, immediate scheduling output
|
||||
- in scheduled mode, generate todo-worthy suggestions only
|
||||
|
||||
### Scheduled Execution Layer
|
||||
|
||||
Add or update the daily scheduled workflow so it can call the schedule planner flow automatically.
|
||||
|
||||
Likely touchpoints:
|
||||
|
||||
- scheduler service
|
||||
- existing daily planning jobs
|
||||
- todo creation services
|
||||
|
||||
Required behavior:
|
||||
|
||||
- fixed daily execution time
|
||||
- fetch relevant context
|
||||
- call schedule planner pipeline
|
||||
- write selected recommendations into todos
|
||||
- skip duplicate todo creation
|
||||
|
||||
## Frontend Changes
|
||||
|
||||
Frontend needs to reflect the new role system consistently.
|
||||
|
||||
Files likely involved:
|
||||
|
||||
- `frontend/src/data/agents.ts`
|
||||
- `frontend/src/pages/agents/index.vue`
|
||||
- `frontend/src/components/chat/OrchestrationPanel.vue`
|
||||
- `frontend/src/pages/chat/composables/useChatView.ts`
|
||||
- related frontend tests
|
||||
|
||||
Required updates:
|
||||
|
||||
- replace planner display labels with schedule planner labels
|
||||
- rename planner subagents to schedule analysis / schedule planning
|
||||
- update orchestration telemetry labels
|
||||
- update example mock state and tests
|
||||
- use these exact frontend ids:
|
||||
- `schedule_planner`
|
||||
- `schedule_analysis`
|
||||
- `schedule_planning`
|
||||
- use these exact default Chinese labels:
|
||||
- `日程规划师`
|
||||
- `日程分析员`
|
||||
- `日程编排员`
|
||||
- update active route visualization and commander skill labels to the new ids
|
||||
|
||||
## Naming
|
||||
|
||||
### Main Agent
|
||||
|
||||
- old: `planner`
|
||||
- new: `schedule_planner`
|
||||
- display role: `日程规划师`
|
||||
|
||||
### Subagents
|
||||
|
||||
- old: `planner_scope`
|
||||
- new: `schedule_analysis`
|
||||
- display role: `日程分析员`
|
||||
|
||||
- old: `planner_steps`
|
||||
- new: `schedule_planning`
|
||||
- display role: `日程编排员`
|
||||
|
||||
## Constraints
|
||||
|
||||
- do not keep dual role names for long-term compatibility unless a specific dependency forces it
|
||||
- do not create todos for every suggestion
|
||||
- do not turn the planner into a generic life coach
|
||||
- keep scheduling grounded in current project signals
|
||||
- preserve the existing agent architecture where possible, while fully changing planner semantics
|
||||
|
||||
## Observability
|
||||
|
||||
The redesign must emit enough telemetry to debug routing and scheduled execution.
|
||||
|
||||
Required telemetry fields:
|
||||
|
||||
- selected main route
|
||||
- selected subagent
|
||||
- available input sources
|
||||
- missing input sources
|
||||
- run mode: `interactive` or `scheduled`
|
||||
- confidence level
|
||||
- todos created count
|
||||
- todos skipped as duplicates count
|
||||
- scheduler run success / skipped / failed
|
||||
|
||||
## Acceptance Criteria
|
||||
|
||||
### Backend Acceptance Criteria
|
||||
|
||||
- a scheduling-intent user query routes to `schedule_planner`
|
||||
- `schedule_analysis` and `schedule_planning` are both reachable through the orchestration layer
|
||||
- legacy planner ids are normalized during the compatibility window
|
||||
- daily scheduled runs do not execute more than once per user per local date
|
||||
- low-context daily runs do not create todos
|
||||
- duplicate todo candidates are skipped instead of recreated
|
||||
|
||||
### Frontend Acceptance Criteria
|
||||
|
||||
- the agents page displays `日程规划师` instead of the previous planner label
|
||||
- the planner subagent chips display `日程分析员` and `日程编排员`
|
||||
- orchestration mock data and route highlights use the new ids
|
||||
- tests no longer depend on `planner_scope` or `planner_steps` after migration is complete
|
||||
|
||||
### Failure and Fallback Criteria
|
||||
|
||||
- if forum data is missing, the planner still runs with degraded confidence
|
||||
- if task board data is missing, the planner still runs with degraded confidence when other strong context exists
|
||||
- if fewer than two meaningful signals are available, scheduled mode creates no todos
|
||||
- if the user has no timezone configured, the daily scheduled run is skipped and logged
|
||||
|
||||
## Testing Strategy
|
||||
|
||||
### Backend
|
||||
|
||||
Add or update tests for:
|
||||
|
||||
- master routing to `schedule_planner`
|
||||
- schedule subagent selection behavior
|
||||
- prompt invariants for schedule-focused output
|
||||
- scheduled daily run creates todos from actionable suggestions
|
||||
- duplicate todo protection
|
||||
|
||||
### Frontend
|
||||
|
||||
Add or update tests for:
|
||||
|
||||
- renamed main role and subagent labels
|
||||
- orchestration panel route display
|
||||
- active subagent telemetry
|
||||
- mock agent graph data using `schedule_planner`, `schedule_analysis`, and `schedule_planning`
|
||||
|
||||
## Risks
|
||||
|
||||
1. **Broad rename surface**
|
||||
- `planner` is referenced across backend and frontend, so a full rename must be systematic
|
||||
|
||||
2. **Scheduled todo spam**
|
||||
- daily runs may create low-value or duplicate todos unless filtered carefully
|
||||
|
||||
3. **Prompt drift**
|
||||
- if prompts stay too abstract, the new agent will sound renamed but not actually scheduling-oriented
|
||||
|
||||
## Recommendation
|
||||
|
||||
Implement this as a real role-system redesign, not as a display-only rename. The role id, subagent ids, prompt family, routing logic, and frontend telemetry should all align on the new scheduling semantics so the system remains internally coherent.
|
||||
445
frontend/package-lock.json
generated
445
frontend/package-lock.json
generated
@@ -9,17 +9,20 @@
|
||||
"version": "0.0.0",
|
||||
"dependencies": {
|
||||
"@vueuse/core": "^14.2.1",
|
||||
"3d-force-graph": "^1.79.0",
|
||||
"axios": "^1.13.6",
|
||||
"echarts": "^6.0.0",
|
||||
"element-plus": "^2.13.6",
|
||||
"lucide-vue-next": "^0.577.0",
|
||||
"motion": "^12.38.0",
|
||||
"pinia": "^3.0.4",
|
||||
"three": "^0.180.0",
|
||||
"vue": "^3.5.30",
|
||||
"vue-router": "^4.6.4"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^25.5.0",
|
||||
"@types/three": "^0.180.0",
|
||||
"@vitejs/plugin-vue": "^6.0.5",
|
||||
"@vue/test-utils": "^2.4.6",
|
||||
"@vue/tsconfig": "^0.9.0",
|
||||
@@ -104,6 +107,15 @@
|
||||
"node": ">=6.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@babel/runtime": {
|
||||
"version": "7.29.2",
|
||||
"resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.29.2.tgz",
|
||||
"integrity": "sha512-JiDShH45zKHWyGe4ZNVRrCjBz8Nh9TMmZG1kh4QTK8hCBTWBi8Da+i7s1fJw7/lYpM4ccepSNfqzZ/QvABBi5g==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=6.9.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@babel/types": {
|
||||
"version": "7.29.0",
|
||||
"resolved": "https://registry.npmmirror.com/@babel/types/-/types-7.29.0.tgz",
|
||||
@@ -218,6 +230,7 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=20.19.0"
|
||||
},
|
||||
@@ -266,6 +279,7 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=20.19.0"
|
||||
}
|
||||
@@ -279,6 +293,13 @@
|
||||
"node": ">=14"
|
||||
}
|
||||
},
|
||||
"node_modules/@dimforge/rapier3d-compat": {
|
||||
"version": "0.12.0",
|
||||
"resolved": "https://registry.npmjs.org/@dimforge/rapier3d-compat/-/rapier3d-compat-0.12.0.tgz",
|
||||
"integrity": "sha512-uekIGetywIgopfD97oDL5PfeezkFpNhwlzlaEYNOA0N6ghdsOvh/HYjSMek5Q2O1PYvRSDFcqFVJl4r4ZBwOow==",
|
||||
"dev": true,
|
||||
"license": "Apache-2.0"
|
||||
},
|
||||
"node_modules/@element-plus/icons-vue": {
|
||||
"version": "2.3.2",
|
||||
"resolved": "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-2.3.2.tgz",
|
||||
@@ -714,6 +735,12 @@
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@tweenjs/tween.js": {
|
||||
"version": "25.0.0",
|
||||
"resolved": "https://registry.npmjs.org/@tweenjs/tween.js/-/tween.js-25.0.0.tgz",
|
||||
"integrity": "sha512-XKLA6syeBUaPzx4j3qwMqzzq+V4uo72BnlbOjmuljLrRqdsd3qnzvZZoxvMHZ23ndsRS4aufU6JOZYpCbU6T1A==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@tybys/wasm-util": {
|
||||
"version": "0.10.1",
|
||||
"resolved": "https://registry.npmmirror.com/@tybys/wasm-util/-/wasm-util-0.10.1.tgz",
|
||||
@@ -761,6 +788,7 @@
|
||||
"resolved": "https://registry.npmmirror.com/@types/lodash-es/-/lodash-es-4.17.12.tgz",
|
||||
"integrity": "sha512-0NgftHUcV4v34VhXm8QBSftKVXtbkBG3ViCjs6+eJ5a6y6Mi/jiFGPc1sC7QK+9BFhWrURE3EOggmWaSxL9OzQ==",
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"@types/lodash": "*"
|
||||
}
|
||||
@@ -771,16 +799,54 @@
|
||||
"integrity": "sha512-jp2P3tQMSxWugkCUKLRPVUpGaL5MVFwF8RDuSRztfwgN1wmqJeMSbKlnEtQqU8UrhTmzEmZdu2I6v2dpp7XIxw==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"undici-types": "~7.18.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@types/stats.js": {
|
||||
"version": "0.17.4",
|
||||
"resolved": "https://registry.npmjs.org/@types/stats.js/-/stats.js-0.17.4.tgz",
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"integrity": "sha512-jIBvWWShCvlBqBNIZt0KAshWpvSjhkwkEu4ZUcASoAvhmrgAUI2t1dXrjSL4xXVLB4FznPrIsX3nKXFl/Dt4vA==",
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@types/three": {
|
||||
"version": "0.180.0",
|
||||
"resolved": "https://registry.npmjs.org/@types/three/-/three-0.180.0.tgz",
|
||||
"integrity": "sha512-ykFtgCqNnY0IPvDro7h+9ZeLY+qjgUWv+qEvUt84grhenO60Hqd4hScHE7VTB9nOQ/3QM8lkbNE+4vKjEpUxKg==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@dimforge/rapier3d-compat": "~0.12.0",
|
||||
"@tweenjs/tween.js": "~23.1.3",
|
||||
"@types/stats.js": "*",
|
||||
"@types/webxr": "*",
|
||||
"@webgpu/types": "*",
|
||||
"fflate": "~0.8.2",
|
||||
"meshoptimizer": "~0.22.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@types/three/node_modules/@tweenjs/tween.js": {
|
||||
"version": "23.1.3",
|
||||
"resolved": "https://registry.npmjs.org/@tweenjs/tween.js/-/tween.js-23.1.3.tgz",
|
||||
"integrity": "sha512-vJmvvwFxYuGnF2axRtPYocag6Clbb5YS7kLL+SO/TeVFzHqDIWrNKYtcsPMibjDx9O+bu+psAy9NKfWklassUA==",
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@types/web-bluetooth": {
|
||||
"version": "0.0.21",
|
||||
"resolved": "https://registry.npmmirror.com/@types/web-bluetooth/-/web-bluetooth-0.0.21.tgz",
|
||||
"integrity": "sha512-oIQLCGWtcFZy2JW77j9k8nHzAOpqMHLQejDA48XXMWH6tjCQHz5RCFz1bzsmROyL6PUm+LLnUiI4BCn221inxA==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@types/webxr": {
|
||||
"version": "0.5.24",
|
||||
"resolved": "https://registry.npmjs.org/@types/webxr/-/webxr-0.5.24.tgz",
|
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"integrity": "sha512-h8fgEd/DpoS9CBrjEQXR+dIDraopAEfu4wYVNY2tEPwk60stPWhvZMf4Foo5FakuQ7HFZoa8WceaWFervK2Ovg==",
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@vitejs/plugin-vue": {
|
||||
"version": "6.0.5",
|
||||
"resolved": "https://registry.npmmirror.com/@vitejs/plugin-vue/-/plugin-vue-6.0.5.tgz",
|
||||
@@ -1194,6 +1260,29 @@
|
||||
"vue": "^3.5.0"
|
||||
}
|
||||
},
|
||||
"node_modules/@webgpu/types": {
|
||||
"version": "0.1.69",
|
||||
"resolved": "https://registry.npmjs.org/@webgpu/types/-/types-0.1.69.tgz",
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||||
"integrity": "sha512-RPmm6kgRbI8e98zSD3RVACvnuktIja5+yLgDAkTmxLr90BEwdTXRQWNLF3ETTTyH/8mKhznZuN5AveXYFEsMGQ==",
|
||||
"dev": true,
|
||||
"license": "BSD-3-Clause"
|
||||
},
|
||||
"node_modules/3d-force-graph": {
|
||||
"version": "1.79.1",
|
||||
"resolved": "https://registry.npmjs.org/3d-force-graph/-/3d-force-graph-1.79.1.tgz",
|
||||
"integrity": "sha512-iscIVt4jWjJ11KEEswgOIOWk8Ew4EFKHRyERJXJ0ouycqzHCtWwb9E5imnxS5rYF1f1IESkFNAfB+h3EkU0Irw==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"accessor-fn": "1",
|
||||
"kapsule": "^1.16",
|
||||
"three": ">=0.118 <1",
|
||||
"three-forcegraph": "1",
|
||||
"three-render-objects": "^1.35"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
}
|
||||
},
|
||||
"node_modules/abbrev": {
|
||||
"version": "2.0.0",
|
||||
"resolved": "https://registry.npmmirror.com/abbrev/-/abbrev-2.0.0.tgz",
|
||||
@@ -1204,6 +1293,15 @@
|
||||
"node": "^14.17.0 || ^16.13.0 || >=18.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/accessor-fn": {
|
||||
"version": "1.5.3",
|
||||
"resolved": "https://registry.npmjs.org/accessor-fn/-/accessor-fn-1.5.3.tgz",
|
||||
"integrity": "sha512-rkAofCwe/FvYFUlMB0v0gWmhqtfAtV1IUkdPbfhTUyYniu5LrC0A0UJkTH0Jv3S8SvwkmfuAlY+mQIJATdocMA==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
}
|
||||
},
|
||||
"node_modules/alien-signals": {
|
||||
"version": "1.0.13",
|
||||
"resolved": "https://registry.npmmirror.com/alien-signals/-/alien-signals-1.0.13.tgz",
|
||||
@@ -1439,6 +1537,177 @@
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||||
"integrity": "sha512-z1HGKcYy2xA8AGQfwrn0PAy+PB7X/GSj3UVJW9qKyn43xWa+gl5nXmU4qqLMRzWVLFC8KusUX8T/0kCiOYpAIQ==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/d3-array": {
|
||||
"version": "3.2.4",
|
||||
"resolved": "https://registry.npmjs.org/d3-array/-/d3-array-3.2.4.tgz",
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"integrity": "sha512-tdQAmyA18i4J7wprpYq8ClcxZy3SC31QMeByyCFyRt7BVHdREQZ5lpzoe5mFEYZUWe+oq8HBvk9JjpibyEV4Jg==",
|
||||
"license": "ISC",
|
||||
"dependencies": {
|
||||
"internmap": "1 - 2"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
}
|
||||
},
|
||||
"node_modules/d3-binarytree": {
|
||||
"version": "1.0.2",
|
||||
"resolved": "https://registry.npmjs.org/d3-binarytree/-/d3-binarytree-1.0.2.tgz",
|
||||
"integrity": "sha512-cElUNH+sHu95L04m92pG73t2MEJXKu+GeKUN1TJkFsu93E5W8E9Sc3kHEGJKgenGvj19m6upSn2EunvMgMD2Yw==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/d3-color": {
|
||||
"version": "3.1.0",
|
||||
"resolved": "https://registry.npmjs.org/d3-color/-/d3-color-3.1.0.tgz",
|
||||
"integrity": "sha512-zg/chbXyeBtMQ1LbD/WSoW2DpC3I0mpmPdW+ynRTj/x2DAWYrIY7qeZIHidozwV24m4iavr15lNwIwLxRmOxhA==",
|
||||
"license": "ISC",
|
||||
"engines": {
|
||||
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||||
"version": "1.2.4",
|
||||
"resolved": "https://registry.npmmirror.com/proto-list/-/proto-list-1.2.4.tgz",
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@@ -3040,6 +3422,56 @@
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||||
"dev": true,
|
||||
"license": "MIT"
|
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},
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||||
"node_modules/three": {
|
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"version": "0.180.0",
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"resolved": "https://registry.npmjs.org/three/-/three-0.180.0.tgz",
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"integrity": "sha512-o+qycAMZrh+TsE01GqWUxUIKR1AL0S8pq7zDkYOQw8GqfX8b8VoCKYUoHbhiX5j+7hr8XsuHDVU6+gkQJQKg9w==",
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"license": "MIT",
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"peer": true
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},
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||||
"node_modules/three-forcegraph": {
|
||||
"version": "1.43.1",
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"resolved": "https://registry.npmjs.org/three-forcegraph/-/three-forcegraph-1.43.1.tgz",
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"integrity": "sha512-lQnYPLvR31gb91mF5xHhU0jPHJgBPw9QB23R6poCk8Tgvz8sQtq7wTxwClcPdfKCBbHXsb7FSqK06Osiu1kQ5A==",
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"license": "MIT",
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"dependencies": {
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"accessor-fn": "1",
|
||||
"d3-array": "1 - 3",
|
||||
"d3-force-3d": "2 - 3",
|
||||
"d3-scale": "1 - 4",
|
||||
"d3-scale-chromatic": "1 - 3",
|
||||
"data-bind-mapper": "1",
|
||||
"kapsule": "^1.16",
|
||||
"ngraph.forcelayout": "3",
|
||||
"ngraph.graph": "20",
|
||||
"tinycolor2": "1"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
},
|
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"peerDependencies": {
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"three": ">=0.118.3"
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}
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},
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"node_modules/three-render-objects": {
|
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"version": "1.40.5",
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"resolved": "https://registry.npmjs.org/three-render-objects/-/three-render-objects-1.40.5.tgz",
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"integrity": "sha512-iA+rYdal0tkond37YeXIvEMAxUFGxw1wU6+ce/GsuiOUKL+8zaxFXY7PTVft0F+Km50mbmtKQ24b2FdwSG3p3A==",
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"license": "MIT",
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"dependencies": {
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"@tweenjs/tween.js": "18 - 25",
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"accessor-fn": "1",
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"float-tooltip": "^1.7",
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"kapsule": "^1.16",
|
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"polished": "4"
|
||||
},
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"engines": {
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"node": ">=12"
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"three": ">=0.168"
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"node_modules/tinybench": {
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"version": "2.9.0",
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"resolved": "https://registry.npmmirror.com/tinybench/-/tinybench-2.9.0.tgz",
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@@ -3047,6 +3479,12 @@
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"dev": true,
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||||
"license": "MIT"
|
||||
},
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"node_modules/tinycolor2": {
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"version": "1.6.0",
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"resolved": "https://registry.npmjs.org/tinycolor2/-/tinycolor2-1.6.0.tgz",
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"license": "MIT"
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"node_modules/tinyexec": {
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||||
"version": "1.0.4",
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"resolved": "https://registry.npmmirror.com/tinyexec/-/tinyexec-1.0.4.tgz",
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@@ -3142,6 +3580,7 @@
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"integrity": "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw==",
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"devOptional": true,
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"peer": true,
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"bin": {
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"tsc": "bin/tsc",
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"tsserver": "bin/tsserver"
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@@ -3173,6 +3612,7 @@
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"integrity": "sha512-wt+Z2qIhfFt85uiyRt5LPU4oVEJBXj8hZNWKeqFG4gRG/0RaRGJ7njQCwzFVjO+v4+Ipmf5CY7VdmZRAYYBPHw==",
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"dev": true,
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"license": "MIT",
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"peer": true,
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"dependencies": {
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"lightningcss": "^1.32.0",
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"picomatch": "^4.0.3",
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@@ -3339,6 +3779,7 @@
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||||
"resolved": "https://registry.npmmirror.com/vue/-/vue-3.5.30.tgz",
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"integrity": "sha512-hTHLc6VNZyzzEH/l7PFGjpcTvUgiaPK5mdLkbjrTeWSRcEfxFrv56g/XckIYlE9ckuobsdwqd5mk2g1sBkMewg==",
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"license": "MIT",
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"peer": true,
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"dependencies": {
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"@vue/compiler-dom": "3.5.30",
|
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"@vue/compiler-sfc": "3.5.30",
|
||||
|
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@@ -10,6 +10,7 @@
|
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"test": "vitest run"
|
||||
},
|
||||
"dependencies": {
|
||||
"3d-force-graph": "^1.79.0",
|
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"@vueuse/core": "^14.2.1",
|
||||
"axios": "^1.13.6",
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||||
"echarts": "^6.0.0",
|
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@@ -17,11 +18,13 @@
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||||
"lucide-vue-next": "^0.577.0",
|
||||
"motion": "^12.38.0",
|
||||
"pinia": "^3.0.4",
|
||||
"three": "^0.180.0",
|
||||
"vue": "^3.5.30",
|
||||
"vue-router": "^4.6.4"
|
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},
|
||||
"devDependencies": {
|
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"@types/node": "^25.5.0",
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"@types/three": "^0.180.0",
|
||||
"@vitejs/plugin-vue": "^6.0.5",
|
||||
"@vue/test-utils": "^2.4.6",
|
||||
"@vue/tsconfig": "^0.9.0",
|
||||
|
||||
866
frontend/prototypes/holographic-brain-chat.html
Normal file
866
frontend/prototypes/holographic-brain-chat.html
Normal file
@@ -0,0 +1,866 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh">
|
||||
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>J.A.R.V.I.S. - Neural Command Center</title>
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
<link href="https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700;900&family=Share+Tech+Mono&display=swap" rel="stylesheet">
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
|
||||
<style>
|
||||
:root {
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--jarvis-blue: #00f3ff;
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--jarvis-blue-dim: rgba(0, 243, 255, 0.1);
|
||||
--bg-color: #020408;
|
||||
}
|
||||
|
||||
* { margin: 0; padding: 0; box-sizing: border-box; }
|
||||
|
||||
body {
|
||||
background-color: var(--bg-color);
|
||||
color: var(--jarvis-blue);
|
||||
font-family: 'Orbitron', 'Share Tech Mono', monospace;
|
||||
overflow: hidden;
|
||||
margin: 0;
|
||||
height: 100vh;
|
||||
width: 100vw;
|
||||
}
|
||||
|
||||
.scanlines {
|
||||
position: fixed;
|
||||
inset: 0;
|
||||
pointer-events: none;
|
||||
z-index: 100;
|
||||
background: linear-gradient(to bottom,
|
||||
rgba(255, 255, 255, 0),
|
||||
rgba(255, 255, 255, 0) 50%,
|
||||
rgba(0, 0, 0, 0.08) 50%,
|
||||
rgba(0, 0, 0, 0.08));
|
||||
background-size: 100% 3px;
|
||||
}
|
||||
|
||||
.vignette {
|
||||
position: fixed;
|
||||
inset: 0;
|
||||
background: radial-gradient(circle, transparent 40%, rgba(0, 0, 0, 0.8) 100%);
|
||||
pointer-events: none;
|
||||
z-index: 90;
|
||||
}
|
||||
|
||||
.text-glow {
|
||||
text-shadow: 0 0 8px var(--jarvis-blue), 0 0 15px rgba(0, 243, 255, 0.5);
|
||||
}
|
||||
|
||||
.tech-panel {
|
||||
background: rgba(0, 12, 28, 0.75);
|
||||
border: 1px solid rgba(0, 243, 255, 0.2);
|
||||
position: relative;
|
||||
backdrop-filter: blur(8px);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.tech-panel::before {
|
||||
content: '';
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 10px;
|
||||
height: 10px;
|
||||
border-top: 1px solid var(--jarvis-blue);
|
||||
border-left: 1px solid var(--jarvis-blue);
|
||||
}
|
||||
|
||||
.tech-panel::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
bottom: 0;
|
||||
right: 0;
|
||||
width: 10px;
|
||||
height: 10px;
|
||||
border-bottom: 1px solid var(--jarvis-blue);
|
||||
border-right: 1px solid var(--jarvis-blue);
|
||||
}
|
||||
|
||||
@keyframes pulse-status {
|
||||
0%, 100% { opacity: 0.7; text-shadow: 0 0 5px var(--jarvis-blue); }
|
||||
50% { opacity: 1; text-shadow: 0 0 15px var(--jarvis-blue), 0 0 30px rgba(0, 243, 255, 0.3); }
|
||||
}
|
||||
|
||||
.status-pulse {
|
||||
animation: pulse-status 2s infinite ease-in-out;
|
||||
}
|
||||
|
||||
@keyframes spin {
|
||||
to { transform: rotate(360deg); }
|
||||
}
|
||||
|
||||
@keyframes typing-bounce {
|
||||
0%, 60%, 100% { transform: translateY(0); opacity: 0.4; }
|
||||
30% { transform: translateY(-4px); opacity: 1; }
|
||||
}
|
||||
|
||||
.typing-dot {
|
||||
display: inline-block;
|
||||
width: 6px;
|
||||
height: 6px;
|
||||
border-radius: 50%;
|
||||
background: var(--jarvis-blue);
|
||||
margin: 0 3px;
|
||||
animation: typing-bounce 1.2s ease-in-out infinite;
|
||||
}
|
||||
|
||||
.typing-dot:nth-child(2) { animation-delay: 0.2s; }
|
||||
.typing-dot:nth-child(3) { animation-delay: 0.4s; }
|
||||
|
||||
@keyframes msg-in {
|
||||
from { opacity: 0; transform: translateY(10px); }
|
||||
to { opacity: 1; transform: translateY(0); }
|
||||
}
|
||||
|
||||
.msg-animate {
|
||||
animation: msg-in 0.3s ease both;
|
||||
}
|
||||
|
||||
#brain-canvas {
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
z-index: 1;
|
||||
opacity: 0.7;
|
||||
}
|
||||
|
||||
.chat-panel {
|
||||
position: relative;
|
||||
z-index: 10;
|
||||
background: rgba(0, 8, 20, 0.85);
|
||||
}
|
||||
|
||||
.msg-bubble {
|
||||
background: rgba(0, 30, 50, 0.6);
|
||||
border: 1px solid rgba(0, 243, 255, 0.15);
|
||||
padding: 10px 14px;
|
||||
border-radius: 4px 12px 12px 12px;
|
||||
max-width: 85%;
|
||||
line-height: 1.6;
|
||||
font-size: 13px;
|
||||
}
|
||||
|
||||
.msg-bubble.user {
|
||||
background: rgba(0, 243, 255, 0.08);
|
||||
border-color: rgba(0, 243, 255, 0.25);
|
||||
border-radius: 12px 4px 12px 12px;
|
||||
}
|
||||
|
||||
.input-holo {
|
||||
background: rgba(0, 15, 30, 0.7);
|
||||
border: 1px solid rgba(0, 243, 255, 0.3);
|
||||
padding: 12px 16px;
|
||||
border-radius: 8px;
|
||||
width: 100%;
|
||||
color: #e0f7ff;
|
||||
font-family: 'Share Tech Mono', monospace;
|
||||
font-size: 13px;
|
||||
outline: none;
|
||||
transition: all 0.3s;
|
||||
}
|
||||
|
||||
.input-holo:focus {
|
||||
border-color: rgba(0, 243, 255, 0.6);
|
||||
box-shadow: 0 0 20px rgba(0, 243, 255, 0.15);
|
||||
}
|
||||
|
||||
.input-holo::placeholder {
|
||||
color: rgba(0, 243, 255, 0.4);
|
||||
}
|
||||
|
||||
.send-btn {
|
||||
background: rgba(0, 243, 255, 0.1);
|
||||
border: 1px solid rgba(0, 243, 255, 0.3);
|
||||
color: var(--jarvis-blue);
|
||||
padding: 10px 20px;
|
||||
border-radius: 8px;
|
||||
cursor: pointer;
|
||||
font-family: 'Orbitron', monospace;
|
||||
font-size: 11px;
|
||||
letter-spacing: 0.1em;
|
||||
transition: all 0.3s;
|
||||
}
|
||||
|
||||
.send-btn:hover {
|
||||
background: rgba(0, 243, 255, 0.2);
|
||||
box-shadow: 0 0 20px rgba(0, 243, 255, 0.3);
|
||||
}
|
||||
|
||||
.send-btn:disabled {
|
||||
opacity: 0.4;
|
||||
cursor: not-allowed;
|
||||
}
|
||||
|
||||
.legend-dot {
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border-radius: 50%;
|
||||
box-shadow: 0 0 8px currentColor;
|
||||
}
|
||||
|
||||
.node-item {
|
||||
padding: 6px 10px;
|
||||
border-bottom: 1px solid rgba(0, 243, 255, 0.08);
|
||||
cursor: pointer;
|
||||
transition: all 0.2s;
|
||||
font-size: 10px;
|
||||
}
|
||||
|
||||
.node-item:hover {
|
||||
background: rgba(0, 243, 255, 0.05);
|
||||
}
|
||||
|
||||
.node-item.selected {
|
||||
background: rgba(0, 243, 255, 0.1);
|
||||
border-left: 2px solid var(--jarvis-blue);
|
||||
}
|
||||
|
||||
::-webkit-scrollbar { width: 4px; }
|
||||
::-webkit-scrollbar-track { background: rgba(0, 0, 0, 0.3); }
|
||||
::-webkit-scrollbar-thumb { background: rgba(0, 243, 255, 0.4); border-radius: 2px; }
|
||||
|
||||
.metric-bar {
|
||||
height: 3px;
|
||||
background: rgba(0, 243, 255, 0.2);
|
||||
border-radius: 2px;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.metric-fill {
|
||||
height: 100%;
|
||||
background: var(--jarvis-blue);
|
||||
box-shadow: 0 0 8px var(--jarvis-blue);
|
||||
transition: width 0.5s ease-out;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<div class="scanlines"></div>
|
||||
<div class="vignette"></div>
|
||||
|
||||
<div class="relative z-30 h-full w-full flex flex-col">
|
||||
|
||||
<!-- HEADER -->
|
||||
<header class="flex justify-between items-center px-6 py-3 border-b border-cyan-500/20 bg-black/40 backdrop-blur-md">
|
||||
<div class="flex items-center gap-4">
|
||||
<div class="flex flex-col items-center">
|
||||
<div class="w-2 h-2 bg-cyan-400 rounded-full shadow-[0_0_10px_#00f3ff]"></div>
|
||||
<div class="w-px h-6 bg-cyan-500/50 my-1"></div>
|
||||
</div>
|
||||
<div>
|
||||
<h1 class="text-2xl font-bold tracking-[0.2em] text-glow">J.A.R.V.I.S.</h1>
|
||||
<div class="flex items-center gap-2 mt-1">
|
||||
<div class="h-1 w-16 bg-cyan-500/30 overflow-hidden rounded">
|
||||
<div class="h-full bg-cyan-400 w-1/3 animate-pulse"></div>
|
||||
</div>
|
||||
<span class="text-[9px] tracking-[0.3em] opacity-60">NEURAL COMMAND v2.0</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="flex items-center gap-6">
|
||||
<div class="flex items-center gap-2">
|
||||
<span class="text-[10px] tracking-widest opacity-60">BRAIN MATRIX</span>
|
||||
<span id="brain-status" class="text-xs font-bold px-3 py-1 rounded status-pulse bg-cyan-900/40 border border-cyan-500/30">ONLINE</span>
|
||||
</div>
|
||||
<div class="text-right">
|
||||
<div class="text-[10px] opacity-50">SYS_TIME</div>
|
||||
<div id="time-display" class="font-mono text-lg text-cyan-200 tracking-wider">00:00:00</div>
|
||||
</div>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<!-- MAIN CONTENT -->
|
||||
<div class="flex-grow flex relative">
|
||||
|
||||
<!-- BRAIN CANVAS BACKGROUND -->
|
||||
<div id="brain-canvas" class="absolute inset-0 pointer-events-none"></div>
|
||||
|
||||
<!-- LEFT PANEL: Brain Metrics -->
|
||||
<aside class="w-64 p-4 flex flex-col gap-4 relative z-20 bg-gradient-to-b from-black/60 to-transparent">
|
||||
|
||||
<div class="tech-panel p-4">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300 mb-3 border-b border-cyan-500/20 pb-2">NODE REGISTRY</h3>
|
||||
<div id="node-list" class="max-h-40 overflow-y-auto space-y-1">
|
||||
<!-- nodes injected -->
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel p-4">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300 mb-3 border-b border-cyan-500/20 pb-2">BRAIN METRICS</h3>
|
||||
<div class="space-y-3 text-[10px]">
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-60">NODES</span><span id="m-nodes" class="text-cyan-300">14</span></div>
|
||||
<div class="metric-bar"><div id="bar-nodes" class="metric-fill" style="width: 70%"></div></div>
|
||||
</div>
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-60">LINKS</span><span id="m-links" class="text-cyan-300">20</span></div>
|
||||
<div class="metric-bar"><div id="bar-links" class="metric-fill" style="width: 66%"></div></div>
|
||||
</div>
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-60">CLUSTERS</span><span id="m-clusters" class="text-cyan-300">3</span></div>
|
||||
<div class="metric-bar"><div id="bar-clusters" class="metric-fill" style="width: 60%"></div></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel p-4 flex-grow">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300 mb-3 border-b border-cyan-500/20 pb-2">SIGNAL LEGEND</h3>
|
||||
<div class="space-y-2 text-[11px]">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #00f3ff; color: #00f3ff;"></div>
|
||||
<span class="text-cyan-300">KNOWLEDGE</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #ff6b9d; color: #ff6b9d;"></div>
|
||||
<span class="text-cyan-300">CHAT</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #a855f7; color: #a855f7;"></div>
|
||||
<span class="text-cyan-300">FORUM</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #fbbf24; color: #fbbf24;"></div>
|
||||
<span class="text-cyan-300">SCHEDULE</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</aside>
|
||||
|
||||
<!-- CENTER: Brain Activity (clickable area) -->
|
||||
<div class="flex-grow relative z-10 flex flex-col justify-end pointer-events-none">
|
||||
<div class="absolute inset-0 flex items-center justify-center pointer-events-auto" id="brain-click-zone">
|
||||
<!-- Brain visualization is rendered here by Three.js -->
|
||||
</div>
|
||||
|
||||
<!-- Terminal Log at bottom -->
|
||||
<div class="tech-panel m-4 p-3 pointer-events-auto max-h-40 overflow-y-auto">
|
||||
<div class="text-[10px] text-cyan-500/70 tracking-widest mb-2">// SYSTEM LOG</div>
|
||||
<div id="terminal-log" class="space-y-1 text-[10px] font-mono">
|
||||
<div class="text-cyan-400/60">>> Neural matrix initialized.</div>
|
||||
<div class="text-cyan-400/60">>> 14 nodes, 20 connections active.</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- RIGHT PANEL: Chat -->
|
||||
<aside class="w-96 p-4 flex flex-col gap-4 relative z-20 bg-gradient-to-l from-black/60 to-transparent">
|
||||
|
||||
<div class="tech-panel p-4 flex-grow flex flex-col overflow-hidden">
|
||||
<div class="flex justify-between items-center mb-3 border-b border-cyan-500/20 pb-2">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300">NEURAL CHAT</h3>
|
||||
<span class="text-[9px] bg-cyan-500/20 px-2 py-1 rounded status-pulse">LIVE</span>
|
||||
</div>
|
||||
|
||||
<div id="chat-messages" class="flex-grow overflow-y-auto space-y-3 mb-4 pr-1">
|
||||
<!-- Welcome -->
|
||||
<div class="text-center py-8">
|
||||
<div class="text-3xl font-bold tracking-[0.3em] text-glow mb-2">JARVIS</div>
|
||||
<div class="text-[10px] tracking-[0.2em] opacity-50">STRATEGIC THINKING PARTNER</div>
|
||||
<div class="text-xs opacity-40 mt-4">有什么我可以帮您分析的？</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Chat Input -->
|
||||
<div class="flex gap-2">
|
||||
<input type="text" id="chat-input" class="input-holo flex-grow" placeholder="输入指令..." onkeydown="if(event.key==='Enter')sendMsg()">
|
||||
<button id="send-btn" class="send-btn" onclick="sendMsg()">SEND</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Selected Node Detail -->
|
||||
<div id="node-detail" class="tech-panel p-4 hidden">
|
||||
<div class="flex justify-between items-center mb-2 border-b border-cyan-500/20 pb-2">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300">SELECTED NODE</h3>
|
||||
<button onclick="clearSelection()" class="text-cyan-500/60 hover:text-cyan-300 text-lg">×</button>
|
||||
</div>
|
||||
<div id="detail-content" class="text-[11px] space-y-2">
|
||||
<!-- detail injected -->
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</aside>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
(function() {
|
||||
const NODES = [
|
||||
{ id: 'core-1', name: 'Orchestrator Prime', type: 'knowledge', importance: 0.98, description: '中枢编排核心' },
|
||||
{ id: 'core-2', name: 'Memory Vault', type: 'knowledge', importance: 0.91, description: '知识存储层' },
|
||||
{ id: 'chat-1', name: 'Session Cluster', type: 'chat', importance: 0.89, description: '实时会话汇聚' },
|
||||
{ id: 'chat-2', name: 'Operator Feed', type: 'chat', importance: 0.76, description: '操控台输入流' },
|
||||
{ id: 'forum-1', name: 'Research Swarm', type: 'forum', importance: 0.81, description: '外部案例趋势池' },
|
||||
{ id: 'forum-2', name: 'Threat Monitor', type: 'forum', importance: 0.72, description: '异常风险观察哨' },
|
||||
{ id: 'sched-1', name: 'Sprint Grid', type: 'schedule', importance: 0.87, description: '执行排期矩阵' },
|
||||
{ id: 'sched-2', name: 'Review Window', type: 'schedule', importance: 0.74, description: '评审验收窗口' },
|
||||
{ id: 'bridge-1', name: 'Signal Bridge', type: 'knowledge', importance: 0.84, description: '跨域桥接节点' },
|
||||
{ id: 'arch-1', name: 'Knowledge Archive', type: 'knowledge', importance: 0.66, description: '知识存档' },
|
||||
{ id: 'thread-1', name: 'Conversation Thread', type: 'chat', importance: 0.62, description: '对话线程' },
|
||||
{ id: 'signal-1', name: 'Forum Signal', type: 'forum', importance: 0.58, description: '外部论坛信号' },
|
||||
{ id: 'lane-1', name: 'Schedule Lane', type: 'schedule', importance: 0.57, description: '排程支线' },
|
||||
{ id: 'dormant-1', name: 'Dormant Trace', type: 'forum', importance: 0.45, description: '低优先级线索' },
|
||||
];
|
||||
|
||||
const EDGES = [
|
||||
{ id: 'e1', source: 'core-1', target: 'core-2', relation: '读取知识' },
|
||||
{ id: 'e2', source: 'core-1', target: 'chat-1', relation: '接收会话' },
|
||||
{ id: 'e3', source: 'core-1', target: 'sched-1', relation: '下发编排' },
|
||||
{ id: 'e4', source: 'core-1', target: 'bridge-1', relation: '稳定桥接' },
|
||||
{ id: 'e5', source: 'core-2', target: 'bridge-1', relation: '提供事实' },
|
||||
{ id: 'e6', source: 'chat-1', target: 'chat-2', relation: '扩展输入' },
|
||||
{ id: 'e7', source: 'chat-1', target: 'bridge-1', relation: '触发同步' },
|
||||
{ id: 'e8', source: 'forum-1', target: 'bridge-1', relation: '补充趋势' },
|
||||
{ id: 'e9', source: 'forum-2', target: 'bridge-1', relation: '反馈风险' },
|
||||
{ id: 'e10', source: 'bridge-1', target: 'sched-1', relation: '投递任务' },
|
||||
{ id: 'e11', source: 'sched-1', target: 'sched-2', relation: '进入评审' },
|
||||
{ id: 'e12', source: 'forum-1', target: 'sched-2', relation: '支撑验证' },
|
||||
{ id: 'e13', source: 'core-2', target: 'arch-1', relation: '归档事实' },
|
||||
{ id: 'e14', source: 'bridge-1', target: 'arch-1', relation: '桥接引用' },
|
||||
{ id: 'e15', source: 'chat-1', target: 'thread-1', relation: '拆分会话' },
|
||||
{ id: 'e16', source: 'chat-2', target: 'thread-1', relation: '补充回执' },
|
||||
{ id: 'e17', source: 'forum-1', target: 'signal-1', relation: '吸收案例' },
|
||||
{ id: 'e18', source: 'sched-1', target: 'lane-1', relation: '拆分排期' },
|
||||
{ id: 'e19', source: 'sched-2', target: 'lane-1', relation: '投递评审' },
|
||||
{ id: 'e20', source: 'forum-2', target: 'dormant-1', relation: '弱风险' },
|
||||
];
|
||||
|
||||
const TYPE_COLORS = { knowledge: 0x00f3ff, chat: 0xff6b9d, forum: 0xa855f7, schedule: 0xfbbf24 };
|
||||
const TYPE_LABELS = { knowledge: '知识库', chat: '对话', forum: '论坛', schedule: '日程' };
|
||||
|
||||
let scene, camera, renderer;
|
||||
let nodeObjects = new Map();
|
||||
let particleSystem, coreMesh, innerMesh;
|
||||
let hoveredNodeId = null;
|
||||
let selectedNodeId = null;
|
||||
let mouseX = 0, mouseY = 0;
|
||||
let targetRotX = 0, targetRotY = 0;
|
||||
let windowHalfX = window.innerWidth / 2;
|
||||
let windowHalfY = window.innerHeight / 2;
|
||||
const nodeMeshes = [];
|
||||
|
||||
function updateTime() {
|
||||
const now = new Date();
|
||||
const el = document.getElementById('time-display');
|
||||
if (el) el.textContent = now.toLocaleTimeString('en-US', { hour12: false });
|
||||
}
|
||||
setInterval(updateTime, 1000);
|
||||
updateTime();
|
||||
|
||||
function init() {
|
||||
const container = document.getElementById('brain-canvas');
|
||||
const w = window.innerWidth;
|
||||
const h = window.innerHeight;
|
||||
|
||||
scene = new THREE.Scene();
|
||||
scene.fog = new THREE.FogExp2(0x020408, 0.003);
|
||||
|
||||
camera = new THREE.PerspectiveCamera(55, w / h, 0.1, 2000);
|
||||
camera.position.z = 70;
|
||||
|
||||
renderer = new THREE.WebGLRenderer({ alpha: true, antialias: true });
|
||||
renderer.setSize(w, h);
|
||||
renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2));
|
||||
renderer.toneMapping = THREE.ACESFilmicToneMapping;
|
||||
renderer.toneMappingExposure = 1.3;
|
||||
container.style.width = w + 'px';
|
||||
container.style.height = h + 'px';
|
||||
container.appendChild(renderer.domElement);
|
||||
|
||||
const ambient = new THREE.AmbientLight(0x404060, 0.5);
|
||||
scene.add(ambient);
|
||||
|
||||
const point = new THREE.PointLight(0x00f3ff, 2, 250);
|
||||
point.position.set(0, 30, 50);
|
||||
scene.add(point);
|
||||
|
||||
createBackground();
|
||||
createBrainCore();
|
||||
createNodes();
|
||||
createEdges();
|
||||
createOrbitalRings();
|
||||
|
||||
document.addEventListener('mousemove', onMouseMove);
|
||||
document.addEventListener('wheel', onWheel);
|
||||
window.addEventListener('resize', onResize);
|
||||
|
||||
updateNodeList();
|
||||
animate();
|
||||
}
|
||||
|
||||
function createBackground() {
|
||||
const count = 1200;
|
||||
const positions = new Float32Array(count * 3);
|
||||
const colors = new Float32Array(count * 3);
|
||||
|
||||
for (let i = 0; i < count; i++) {
|
||||
positions[i * 3] = (Math.random() - 0.5) * 500;
|
||||
positions[i * 3 + 1] = (Math.random() - 0.5) * 500;
|
||||
positions[i * 3 + 2] = (Math.random() - 0.5) * 500;
|
||||
|
||||
const c = new THREE.Color();
|
||||
c.setHSL(0.55 + Math.random() * 0.1, 0.8, 0.5 + Math.random() * 0.3);
|
||||
colors[i * 3] = c.r;
|
||||
colors[i * 3 + 1] = c.g;
|
||||
colors[i * 3 + 2] = c.b;
|
||||
}
|
||||
|
||||
const geo = new THREE.BufferGeometry();
|
||||
geo.setAttribute('position', new THREE.BufferAttribute(positions, 3));
|
||||
geo.setAttribute('color', new THREE.BufferAttribute(colors, 3));
|
||||
|
||||
const mat = new THREE.PointsMaterial({
|
||||
size: 0.4, vertexColors: true, transparent: true, opacity: 0.5,
|
||||
blending: THREE.AdditiveBlending,
|
||||
});
|
||||
|
||||
particleSystem = new THREE.Points(geo, mat);
|
||||
scene.add(particleSystem);
|
||||
}
|
||||
|
||||
function createBrainCore() {
|
||||
coreMesh = new THREE.Mesh(
|
||||
new THREE.IcosahedronGeometry(3, 2),
|
||||
new THREE.MeshBasicMaterial({ color: 0x00f3ff, wireframe: true, transparent: true, opacity: 0.1 })
|
||||
);
|
||||
scene.add(coreMesh);
|
||||
|
||||
innerMesh = new THREE.Mesh(
|
||||
new THREE.IcosahedronGeometry(1.8, 1),
|
||||
new THREE.MeshBasicMaterial({ color: 0x00f3ff, transparent: true, opacity: 0.15 })
|
||||
);
|
||||
scene.add(innerMesh);
|
||||
}
|
||||
|
||||
function createHexShape(r) {
|
||||
const shape = new THREE.Shape();
|
||||
for (let i = 0; i < 6; i++) {
|
||||
const a = (i / 6) * Math.PI * 2 - Math.PI / 6;
|
||||
const x = Math.cos(a) * r, y = Math.sin(a) * r;
|
||||
if (i === 0) shape.moveTo(x, y); else shape.lineTo(x, y);
|
||||
}
|
||||
shape.closePath();
|
||||
return shape;
|
||||
}
|
||||
|
||||
function createNodes() {
|
||||
const angleStep = (Math.PI * 2) / NODES.length;
|
||||
const radius = 28;
|
||||
|
||||
NODES.forEach((node, i) => {
|
||||
const angle = i * angleStep;
|
||||
const layer = Math.floor(i / 7);
|
||||
const r = radius + layer * 16;
|
||||
const x = Math.cos(angle) * r;
|
||||
const z = Math.sin(angle) * r;
|
||||
const y = (Math.random() - 0.5) * 6 + layer * 3;
|
||||
|
||||
const color = TYPE_COLORS[node.type];
|
||||
const imp = node.importance;
|
||||
const height = 2.5 + imp * 10;
|
||||
const r2 = 1.2 + imp * 1.2;
|
||||
|
||||
const group = new THREE.Group();
|
||||
group.userData = { nodeId: node.id };
|
||||
group.position.set(x, y, z);
|
||||
|
||||
const geo = new THREE.ExtrudeGeometry(createHexShape(r2), {
|
||||
depth: height, bevelEnabled: true, bevelThickness: 0.15, bevelSize: 0.1, bevelSegments: 1,
|
||||
});
|
||||
geo.center();
|
||||
|
||||
const mat = new THREE.MeshBasicMaterial({ color, transparent: true, opacity: 0.1, side: THREE.DoubleSide });
|
||||
const mesh = new THREE.Mesh(geo, mat);
|
||||
mesh.rotation.x = -Math.PI / 2;
|
||||
group.add(mesh);
|
||||
|
||||
const edgesGeo = new THREE.EdgesGeometry(geo);
|
||||
const edgesMat = new THREE.LineBasicMaterial({ color, transparent: true, opacity: 0.7 });
|
||||
const edges = new THREE.LineSegments(edgesGeo, edgesMat);
|
||||
edges.rotation.x = -Math.PI / 2;
|
||||
group.add(edges);
|
||||
|
||||
const glowGeo = new THREE.SphereGeometry(r2 * 0.5, 10, 10);
|
||||
const glowMat = new THREE.MeshBasicMaterial({
|
||||
color, transparent: true, opacity: 0.25 + imp * 0.4, blending: THREE.AdditiveBlending,
|
||||
});
|
||||
const glow = new THREE.Mesh(glowGeo, glowMat);
|
||||
group.add(glow);
|
||||
nodeMeshes.push(glow);
|
||||
|
||||
const topGeo = new THREE.CircleGeometry(r2 * 0.35, 6);
|
||||
const topMat = new THREE.MeshBasicMaterial({ color, transparent: true, opacity: 0.6, side: THREE.DoubleSide });
|
||||
const top = new THREE.Mesh(topGeo, topMat);
|
||||
top.rotation.x = -Math.PI / 2;
|
||||
top.position.y = height / 2;
|
||||
group.add(top);
|
||||
|
||||
group.rotation.y = Math.random() * Math.PI;
|
||||
scene.add(group);
|
||||
nodeObjects.set(node.id, group);
|
||||
});
|
||||
}
|
||||
|
||||
function createEdges() {
|
||||
EDGES.forEach(edge => {
|
||||
const src = nodeObjects.get(edge.source);
|
||||
const tgt = nodeObjects.get(edge.target);
|
||||
if (!src || !tgt) return;
|
||||
|
||||
const srcNode = NODES.find(n => n.id === edge.source);
|
||||
const color = TYPE_COLORS[srcNode?.type || 'knowledge'];
|
||||
|
||||
const points = [src.position.clone(), tgt.position.clone()];
|
||||
const geo = new THREE.BufferGeometry().setFromPoints(points);
|
||||
const mat = new THREE.LineDashedMaterial({
|
||||
color, transparent: true, opacity: 0.35,
|
||||
dashSize: 1.2, gapSize: 0.8, blending: THREE.AdditiveBlending,
|
||||
});
|
||||
const line = new THREE.Line(geo, mat);
|
||||
line.computeLineDistances();
|
||||
scene.add(line);
|
||||
});
|
||||
}
|
||||
|
||||
function createOrbitalRings() {
|
||||
const ring1Geo = new THREE.BufferGeometry();
|
||||
const ring1Pos = new Float32Array(60 * 3);
|
||||
for (let i = 0; i < 60; i++) {
|
||||
const t = (i / 60) * Math.PI * 2;
|
||||
ring1Pos[i * 3] = Math.cos(t) * 40;
|
||||
ring1Pos[i * 3 + 1] = (Math.random() - 0.5) * 0.4;
|
||||
ring1Pos[i * 3 + 2] = Math.sin(t) * 40;
|
||||
}
|
||||
ring1Geo.setAttribute('position', new THREE.BufferAttribute(ring1Pos, 3));
|
||||
const ring1 = new THREE.Points(ring1Geo, new THREE.PointsMaterial({ color: 0x00f3ff, size: 0.25, transparent: true, opacity: 0.35 }));
|
||||
ring1.userData = { sx: 0.0008, sy: 0.0015 };
|
||||
scene.add(ring1);
|
||||
|
||||
const ring2Geo = new THREE.BufferGeometry();
|
||||
const ring2Pos = new Float32Array(50 * 3);
|
||||
for (let i = 0; i < 50; i++) {
|
||||
const t = (i / 50) * Math.PI * 2;
|
||||
ring2Pos[i * 3] = (Math.random() - 0.5) * 0.4;
|
||||
ring2Pos[i * 3 + 1] = Math.cos(t) * 45;
|
||||
ring2Pos[i * 3 + 2] = Math.sin(t) * 45;
|
||||
}
|
||||
ring2Geo.setAttribute('position', new THREE.BufferAttribute(ring2Pos, 3));
|
||||
const ring2 = new THREE.Points(ring2Geo, new THREE.PointsMaterial({ color: 0xa855f7, size: 0.2, transparent: true, opacity: 0.25 }));
|
||||
ring2.userData = { sx: 0.0015, sy: 0.0008 };
|
||||
scene.add(ring2);
|
||||
}
|
||||
|
||||
function onMouseMove(e) {
|
||||
mouseX = e.clientX - windowHalfX;
|
||||
mouseY = e.clientY - windowHalfY;
|
||||
targetRotY = mouseX * 0.0004;
|
||||
targetRotX = -mouseY * 0.0004;
|
||||
}
|
||||
|
||||
function onWheel(e) {
|
||||
camera.position.z += e.deltaY * 0.04;
|
||||
camera.position.z = Math.max(35, Math.min(180, camera.position.z));
|
||||
}
|
||||
|
||||
function onResize() {
|
||||
const w = window.innerWidth;
|
||||
const h = window.innerHeight;
|
||||
camera.aspect = w / h;
|
||||
camera.updateProjectionMatrix();
|
||||
renderer.setSize(w, h);
|
||||
const container = document.getElementById('brain-canvas');
|
||||
container.style.width = w + 'px';
|
||||
container.style.height = h + 'px';
|
||||
}
|
||||
|
||||
function animate() {
|
||||
requestAnimationFrame(animate);
|
||||
const t = Date.now() * 0.001;
|
||||
|
||||
if (coreMesh) {
|
||||
coreMesh.rotation.y += 0.001;
|
||||
coreMesh.rotation.x -= 0.002;
|
||||
}
|
||||
if (innerMesh) {
|
||||
innerMesh.rotation.y -= 0.002;
|
||||
innerMesh.rotation.z += 0.001;
|
||||
}
|
||||
|
||||
scene.rotation.y += (targetRotY - scene.rotation.y) * 0.03;
|
||||
scene.rotation.x += (targetRotX - scene.rotation.x) * 0.03;
|
||||
|
||||
if (particleSystem) {
|
||||
particleSystem.rotation.y += 0.00008;
|
||||
particleSystem.rotation.x += 0.00004;
|
||||
}
|
||||
|
||||
nodeMeshes.forEach((m, i) => {
|
||||
const p = Math.sin(t * 1.8 + i * 0.4) * 0.12;
|
||||
m.scale.setScalar(1 + p);
|
||||
});
|
||||
|
||||
scene.children.forEach(c => {
|
||||
if (c instanceof THREE.Points && c.userData.sx) {
|
||||
c.rotation.x += c.userData.sx;
|
||||
c.rotation.y += c.userData.sy;
|
||||
}
|
||||
});
|
||||
|
||||
renderer.render(scene, camera);
|
||||
}
|
||||
|
||||
function updateNodeList() {
|
||||
const list = document.getElementById('node-list');
|
||||
list.innerHTML = '';
|
||||
NODES.forEach(node => {
|
||||
const color = '#' + TYPE_COLORS[node.type].toString(16).padStart(6, '0');
|
||||
const div = document.createElement('div');
|
||||
div.className = 'node-item flex items-center gap-2';
|
||||
div.innerHTML = `
|
||||
<div class="w-2 h-2 rounded-full flex-shrink-0" style="background: ${color}; box-shadow: 0 0 6px ${color};"></div>
|
||||
<span class="text-cyan-300 truncate flex-grow">${node.name}</span>
|
||||
<span class="opacity-50">${Math.round(node.importance * 100)}%</span>
|
||||
`;
|
||||
div.onclick = () => selectNode(node.id);
|
||||
list.appendChild(div);
|
||||
});
|
||||
}
|
||||
|
||||
function selectNode(nodeId) {
|
||||
selectedNodeId = nodeId;
|
||||
const node = NODES.find(n => n.id === nodeId);
|
||||
if (!node) return;
|
||||
|
||||
document.querySelectorAll('.node-item').forEach(el => el.classList.remove('selected'));
|
||||
const items = document.querySelectorAll('.node-item');
|
||||
const idx = NODES.findIndex(n => n.id === nodeId);
|
||||
if (items[idx]) items[idx].classList.add('selected');
|
||||
|
||||
const color = '#' + TYPE_COLORS[node.type].toString(16).padStart(6, '0');
|
||||
const detail = document.getElementById('detail-content');
|
||||
const labels = { knowledge: '知识库', chat: '对话', forum: '论坛', schedule: '日程' };
|
||||
detail.innerHTML = `
|
||||
<div class="text-center mb-2">
|
||||
<div class="text-[9px] opacity-50 uppercase tracking-widest" style="color: ${color}">${labels[node.type]}</div>
|
||||
<div class="text-sm font-bold text-cyan-100 tracking-wider">${node.name}</div>
|
||||
</div>
|
||||
<div class="flex justify-between"><span class="opacity-60">重要性</span><span class="text-cyan-300">${Math.round(node.importance * 100)}%</span></div>
|
||||
<div class="opacity-60">描述</div>
|
||||
<div class="text-cyan-300/80 pl-2 border-l border-cyan-500/30">${node.description}</div>
|
||||
<div class="mt-2">
|
||||
<div class="opacity-60 mb-1">关联链路</div>
|
||||
${EDGES.filter(e => e.source === nodeId || e.target === nodeId).map(e => {
|
||||
const otherId = e.source === nodeId ? e.target : e.source;
|
||||
const other = NODES.find(n => n.id === otherId);
|
||||
return `<div class="text-[9px] text-cyan-500/70">${e.relation} → ${other?.name || ''}</div>`;
|
||||
}).join('')}
|
||||
</div>
|
||||
`;
|
||||
document.getElementById('node-detail').classList.remove('hidden');
|
||||
addLog('>> Node selected: ' + node.name);
|
||||
}
|
||||
|
||||
window.clearSelection = function() {
|
||||
selectedNodeId = null;
|
||||
document.querySelectorAll('.node-item').forEach(el => el.classList.remove('selected'));
|
||||
document.getElementById('node-detail').classList.add('hidden');
|
||||
};
|
||||
|
||||
function addLog(msg) {
|
||||
const log = document.getElementById('terminal-log');
|
||||
if (!log) return;
|
||||
const div = document.createElement('div');
|
||||
div.className = 'text-cyan-400/60';
|
||||
div.textContent = '>> ' + msg;
|
||||
log.appendChild(div);
|
||||
log.scrollTop = log.scrollHeight;
|
||||
while (log.children.length > 20) log.removeChild(log.firstChild);
|
||||
}
|
||||
|
||||
window.sendMsg = function() {
|
||||
const input = document.getElementById('chat-input');
|
||||
const val = input.value.trim();
|
||||
if (!val) return;
|
||||
|
||||
const messages = document.getElementById('chat-messages');
|
||||
|
||||
// User msg
|
||||
const userDiv = document.createElement('div');
|
||||
userDiv.className = 'flex justify-end msg-animate';
|
||||
userDiv.innerHTML = `<div class="msg-bubble user">${escapeHtml(val)}</div>`;
|
||||
messages.appendChild(userDiv);
|
||||
|
||||
input.value = '';
|
||||
|
||||
// Simulate Jarvis response
|
||||
setTimeout(() => {
|
||||
const respDiv = document.createElement('div');
|
||||
respDiv.className = 'flex justify-start msg-animate';
|
||||
respDiv.innerHTML = `<div class="msg-bubble">正在分析您的请求...</div>`;
|
||||
messages.appendChild(respDiv);
|
||||
messages.scrollTop = messages.scrollHeight;
|
||||
|
||||
setTimeout(() => {
|
||||
respDiv.querySelector('.msg-bubble').innerHTML = `我已经分析了这个问题。基于当前知识图谱的相关节点：<br><br>
|
||||
<span class="text-cyan-400">• Signal Bridge</span> 跨域桥接节点正在协调<br>
|
||||
<span class="text-cyan-400">• Sprint Grid</span> 执行排期矩阵已就绪<br><br>
|
||||
需要我展开某个节点的详细信息吗？`;
|
||||
addLog('Response generated for: ' + val.substring(0, 30) + '...');
|
||||
}, 1200);
|
||||
}, 500);
|
||||
|
||||
messages.scrollTop = messages.scrollHeight;
|
||||
addLog('User input: ' + val.substring(0, 40));
|
||||
};
|
||||
|
||||
function escapeHtml(str) {
|
||||
return str.replace(/&/g, '&').replace(/</g, '<').replace(/>/g, '>');
|
||||
}
|
||||
|
||||
// Raycasting for node hover
|
||||
document.addEventListener('mousemove', (e) => {
|
||||
const canvas = renderer.domElement;
|
||||
const rect = canvas.getBoundingClientRect();
|
||||
if (e.clientX < rect.left || e.clientX > rect.right || e.clientY < rect.top || e.clientY > rect.bottom) return;
|
||||
|
||||
const x = ((e.clientX - rect.left) / rect.width) * 2 - 1;
|
||||
const y = -((e.clientY - rect.top) / rect.height) * 2 + 1;
|
||||
|
||||
const raycaster = new THREE.Raycaster();
|
||||
raycaster.setFromCamera({ x, y }, camera);
|
||||
const hits = raycaster.intersectObjects(scene.children, true);
|
||||
|
||||
let found = null;
|
||||
for (const hit of hits) {
|
||||
let obj = hit.object;
|
||||
while (obj) {
|
||||
if (obj.userData?.nodeId) { found = obj.userData.nodeId; break; }
|
||||
obj = obj.parent;
|
||||
}
|
||||
if (found) break;
|
||||
}
|
||||
hoveredNodeId = found;
|
||||
canvas.style.cursor = found ? 'pointer' : 'grab';
|
||||
});
|
||||
|
||||
document.addEventListener('click', (e) => {
|
||||
const canvas = renderer.domElement;
|
||||
const rect = canvas.getBoundingClientRect();
|
||||
if (e.clientX >= rect.left && e.clientX <= rect.right && e.clientY >= rect.top && e.clientY <= rect.bottom) {
|
||||
if (hoveredNodeId) selectNode(hoveredNodeId);
|
||||
}
|
||||
});
|
||||
|
||||
init();
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
831
frontend/prototypes/holographic-brain-demo.html
Normal file
831
frontend/prototypes/holographic-brain-demo.html
Normal file
@@ -0,0 +1,831 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="zh">
|
||||
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>J.A.R.V.I.S. - 知识脑图</title>
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
<link href="https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700;900&family=Share+Tech+Mono&display=swap" rel="stylesheet">
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
|
||||
<style>
|
||||
:root {
|
||||
--jarvis-blue: #00f3ff;
|
||||
--jarvis-blue-dim: rgba(0, 243, 255, 0.1);
|
||||
--jarvis-alert: #ff3333;
|
||||
--bg-color: #020408;
|
||||
}
|
||||
|
||||
* { margin: 0; padding: 0; box-sizing: border-box; }
|
||||
|
||||
body {
|
||||
background-color: var(--bg-color);
|
||||
color: var(--jarvis-blue);
|
||||
font-family: 'Orbitron', sans-serif;
|
||||
overflow: hidden;
|
||||
margin: 0;
|
||||
height: 100vh;
|
||||
width: 100vw;
|
||||
}
|
||||
|
||||
body::after {
|
||||
content: "";
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100vw;
|
||||
height: 100vh;
|
||||
background: linear-gradient(to bottom,
|
||||
rgba(255, 255, 255, 0),
|
||||
rgba(255, 255, 255, 0) 50%,
|
||||
rgba(0, 0, 0, 0.1) 50%,
|
||||
rgba(0, 0, 0, 0.1));
|
||||
background-size: 100% 3px;
|
||||
pointer-events: none;
|
||||
z-index: 50;
|
||||
}
|
||||
|
||||
.vignette {
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: radial-gradient(circle, transparent 50%, rgba(0, 0, 0, 0.95) 100%);
|
||||
pointer-events: none;
|
||||
z-index: 40;
|
||||
}
|
||||
|
||||
.text-glow {
|
||||
text-shadow: 0 0 5px var(--jarvis-blue), 0 0 10px var(--jarvis-blue);
|
||||
}
|
||||
|
||||
.tech-panel {
|
||||
background: rgba(0, 15, 30, 0.7);
|
||||
border-left: 1px solid rgba(0, 243, 255, 0.3);
|
||||
border-right: 1px solid rgba(0, 243, 255, 0.3);
|
||||
position: relative;
|
||||
backdrop-filter: blur(4px);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.tech-panel:hover {
|
||||
border-color: rgba(0, 243, 255, 0.8);
|
||||
background: rgba(0, 20, 40, 0.8);
|
||||
}
|
||||
|
||||
.tech-panel::before,
|
||||
.tech-panel::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border: 1px solid var(--jarvis-blue);
|
||||
transition: all 0.3s;
|
||||
}
|
||||
|
||||
.tech-panel::before {
|
||||
top: -1px;
|
||||
left: -1px;
|
||||
border-right: none;
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.tech-panel::after {
|
||||
bottom: -1px;
|
||||
right: -1px;
|
||||
border-left: none;
|
||||
border-top: none;
|
||||
}
|
||||
|
||||
.tech-border {
|
||||
clip-path: polygon(10px 0,
|
||||
100% 0,
|
||||
100% calc(100% - 10px),
|
||||
calc(100% - 10px) 100%,
|
||||
0 100%,
|
||||
0 10px);
|
||||
border-top: 1px solid var(--jarvis-blue-dim);
|
||||
}
|
||||
|
||||
@keyframes pulse-status {
|
||||
0%, 100% { opacity: 0.6; text-shadow: 0 0 2px var(--jarvis-blue); box-shadow: 0 0 5px var(--jarvis-blue-dim); }
|
||||
50% { opacity: 1; text-shadow: 0 0 15px var(--jarvis-blue); box-shadow: 0 0 15px var(--jarvis-blue-dim); }
|
||||
}
|
||||
|
||||
.status-pulse {
|
||||
animation: pulse-status 3s infinite ease-in-out;
|
||||
}
|
||||
|
||||
@keyframes flash-row {
|
||||
0% { background-color: transparent; }
|
||||
50% { background-color: rgba(0, 243, 255, 0.15); }
|
||||
100% { background-color: transparent; }
|
||||
}
|
||||
|
||||
.flash-row:hover {
|
||||
animation: flash-row 0.8s infinite;
|
||||
cursor: pointer;
|
||||
background: rgba(0, 243, 255, 0.05);
|
||||
}
|
||||
|
||||
#brain-canvas-container {
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
z-index: 10;
|
||||
}
|
||||
|
||||
#brain-canvas-container canvas {
|
||||
pointer-events: auto;
|
||||
cursor: grab;
|
||||
}
|
||||
|
||||
#brain-canvas-container canvas:active {
|
||||
cursor: grabbing;
|
||||
}
|
||||
|
||||
.legend-dot {
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border-radius: 50%;
|
||||
box-shadow: 0 0 6px currentColor;
|
||||
}
|
||||
|
||||
.detail-panel {
|
||||
transform: translateX(100%);
|
||||
transition: transform 0.3s ease;
|
||||
}
|
||||
|
||||
.detail-panel.active {
|
||||
transform: translateX(0);
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<div class="vignette"></div>
|
||||
|
||||
<div class="relative z-30 h-full w-full flex flex-col p-4 md:p-6 pointer-events-none">
|
||||
|
||||
<header class="flex justify-between items-start pointer-events-auto mb-2 border-b border-cyan-500/20 pb-2">
|
||||
<div class="flex items-center gap-4">
|
||||
<div class="flex flex-col items-center justify-center">
|
||||
<div class="w-2 h-2 bg-cyan-400 rounded-full mb-1"></div>
|
||||
<div class="h-8 w-px bg-cyan-500/50"></div>
|
||||
</div>
|
||||
<div>
|
||||
<h1 class="text-4xl font-bold tracking-[0.15em] text-glow font-orbitron">J.A.R.V.I.S.</h1>
|
||||
<div class="flex items-center gap-2 mt-1">
|
||||
<div class="h-1 w-20 bg-cyan-500/30 overflow-hidden">
|
||||
<div class="h-full bg-cyan-400 w-1/2 animate-pulse"></div>
|
||||
</div>
|
||||
<div class="text-[9px] tracking-[0.3em] opacity-70">KNOWLEDGE BRAIN V2.0</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="text-right">
|
||||
<div class="flex items-center justify-end gap-3 mb-1">
|
||||
<span class="text-[10px] tracking-widest opacity-60">BRAIN STATUS</span>
|
||||
<span id="brain-status" class="font-bold text-xs status-pulse bg-cyan-900/40 px-3 py-1 rounded-sm border border-cyan-500/30">INITIALIZING</span>
|
||||
</div>
|
||||
<div class="flex justify-end items-baseline gap-2">
|
||||
<span class="text-[10px] opacity-50">SYS_TIME</span>
|
||||
<div id="time-display" class="font-mono text-xl tracking-wider text-cyan-200">00:00:00</div>
|
||||
</div>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<div class="flex-grow grid grid-cols-1 md:grid-cols-4 gap-6 pointer-events-auto h-0 min-h-0 mt-2">
|
||||
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<div class="tech-panel p-4 tech-border">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
NODE REGISTRY</h3>
|
||||
<div class="space-y-2 font-mono text-[10px] max-h-48 overflow-y-auto pr-1">
|
||||
<div id="node-list"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel p-4 tech-border">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
BRAIN METRICS</h3>
|
||||
<div class="space-y-4 font-mono text-[10px]">
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">NODE_COUNT</span><span class="text-cyan-300" id="metric-nodes">0</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="nodes-bar" class="sys-bar bg-cyan-400 h-full w-[0%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">LINK_DENSITY</span><span class="text-cyan-300" id="metric-links">0</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="links-bar" class="sys-bar bg-cyan-400 h-full w-[0%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">CLUSTER_COUNT</span><span class="text-cyan-300" id="metric-clusters">0</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="clusters-bar" class="sys-bar bg-cyan-400 h-full w-[0%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="grid grid-cols-2 gap-2 pt-2">
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">CORE_NODES</div>
|
||||
<div id="core-nodes" class="text-sm font-bold text-cyan-300">0</div>
|
||||
</div>
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">BRIDGE_NODES</div>
|
||||
<div id="bridge-nodes" class="text-sm font-bold text-cyan-300">0</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel p-4 flex-grow overflow-hidden flex flex-col">
|
||||
<div class="flex justify-between items-center border-b border-cyan-500/30 pb-2 mb-2">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300">SIGNAL LEGEND</h3>
|
||||
</div>
|
||||
<div class="space-y-3 font-mono text-[11px]">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #00f3ff; color: #00f3ff;"></div>
|
||||
<span class="text-cyan-300">KNOWLEDGE</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #ff6b9d; color: #ff6b9d;"></div>
|
||||
<span class="text-cyan-300">CHAT</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #a855f7; color: #a855f7;"></div>
|
||||
<span class="text-cyan-300">FORUM</span>
|
||||
</div>
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="legend-dot" style="background: #fbbf24; color: #fbbf24;"></div>
|
||||
<span class="text-cyan-300">SCHEDULE</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="md:col-span-2 relative flex flex-col justify-end items-center">
|
||||
|
||||
<div class="absolute top-10 w-full text-center pointer-events-none">
|
||||
<div id="brain-title" class="text-xl md:text-2xl font-bold tracking-[0.3em] text-glow uppercase text-cyan-100">
|
||||
NEURAL BRAIN MATRIX
|
||||
</div>
|
||||
<div class="text-[10px] text-cyan-400/70 tracking-[0.5em] mt-2">INTERACTIVE 3D GRAPH</div>
|
||||
<div class="text-[10px] text-cyan-400/50 tracking-[0.2em] mt-1">DRAG TO ROTATE / SCROLL TO ZOOM</div>
|
||||
</div>
|
||||
|
||||
<div id="brain-canvas-container" class="w-full h-full"></div>
|
||||
|
||||
<div class="terminal-window w-full h-48 bg-black/90 border-t border-cyan-500/50 rounded-tl-lg rounded-tr-lg overflow-hidden flex flex-col backdrop-blur-md shadow-[0_-5px_20px_rgba(0,243,255,0.1)]">
|
||||
<div class="bg-cyan-900/20 px-3 py-1.5 text-[10px] flex justify-between border-b border-cyan-500/30 items-center">
|
||||
<span class="tracking-widest text-cyan-400">BRAIN_CONSOLE // SYSTEM LOG</span>
|
||||
<div class="flex gap-2 font-mono text-cyan-600">
|
||||
<span id="active-nodes-val">ACTIVE: 0</span>
|
||||
<span id="selected-val">SELECTED: NONE</span>
|
||||
</div>
|
||||
</div>
|
||||
<div id="brain-terminal" class="p-4 font-mono text-xs text-cyan-300/80 overflow-y-auto flex-grow space-y-1.5">
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<div id="detail-panel" class="tech-panel p-4 tech-border detail-panel">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
SELECTED NODE</h3>
|
||||
<div id="node-detail" class="font-mono text-[11px] space-y-3">
|
||||
<div class="text-center text-cyan-500/50 py-8">NO NODE SELECTED</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel p-4 flex-grow flex flex-col overflow-hidden">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
OUTGOING CONNECTIONS</h3>
|
||||
<div id="connections-list" class="font-mono text-[10px] overflow-y-auto flex-grow space-y-2">
|
||||
<div class="text-center text-cyan-500/50 py-4">SELECT A NODE</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="tech-panel h-32 p-4 relative overflow-hidden flex flex-col justify-between">
|
||||
<div class="text-[10px] opacity-60 tracking-widest mb-1">BRAIN ACTIVITY</div>
|
||||
<div class="flex items-end justify-between h-full gap-1 pt-2" id="activity-graph">
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[50%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[80%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[40%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[60%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[90%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[45%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[70%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[60%]"></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
(function() {
|
||||
const NODES = [
|
||||
{ id: 'core-1', name: 'Orchestrator Prime', type: 'knowledge', importance: 0.98, description: '中枢编排核心' },
|
||||
{ id: 'core-2', name: 'Memory Vault', type: 'knowledge', importance: 0.91, description: '知识存储层' },
|
||||
{ id: 'chat-1', name: 'Session Cluster', type: 'chat', importance: 0.89, description: '实时会话汇聚' },
|
||||
{ id: 'chat-2', name: 'Operator Feed', type: 'chat', importance: 0.76, description: '操控台输入流' },
|
||||
{ id: 'forum-1', name: 'Research Swarm', type: 'forum', importance: 0.81, description: '外部案例趋势池' },
|
||||
{ id: 'forum-2', name: 'Threat Monitor', type: 'forum', importance: 0.72, description: '异常风险观察哨' },
|
||||
{ id: 'sched-1', name: 'Sprint Grid', type: 'schedule', importance: 0.87, description: '执行排期矩阵' },
|
||||
{ id: 'sched-2', name: 'Review Window', type: 'schedule', importance: 0.74, description: '评审验收窗口' },
|
||||
{ id: 'bridge-1', name: 'Signal Bridge', type: 'knowledge', importance: 0.84, description: '跨域桥接节点' },
|
||||
{ id: 'arch-1', name: 'Knowledge Archive', type: 'knowledge', importance: 0.66, description: '知识存档' },
|
||||
{ id: 'thread-1', name: 'Conversation Thread', type: 'chat', importance: 0.62, description: '对话线程' },
|
||||
{ id: 'signal-1', name: 'Forum Signal', type: 'forum', importance: 0.58, description: '外部论坛信号' },
|
||||
{ id: 'lane-1', name: 'Schedule Lane', type: 'schedule', importance: 0.57, description: '排程支线' },
|
||||
{ id: 'dormant-1', name: 'Dormant Trace', type: 'forum', importance: 0.45, description: '低优先级线索' },
|
||||
];
|
||||
|
||||
const EDGES = [
|
||||
{ id: 'e1', source: 'core-1', target: 'core-2', relation: '读取知识' },
|
||||
{ id: 'e2', source: 'core-1', target: 'chat-1', relation: '接收会话' },
|
||||
{ id: 'e3', source: 'core-1', target: 'sched-1', relation: '下发编排' },
|
||||
{ id: 'e4', source: 'core-1', target: 'bridge-1', relation: '稳定桥接' },
|
||||
{ id: 'e5', source: 'core-2', target: 'bridge-1', relation: '提供事实' },
|
||||
{ id: 'e6', source: 'chat-1', target: 'chat-2', relation: '扩展输入' },
|
||||
{ id: 'e7', source: 'chat-1', target: 'bridge-1', relation: '触发同步' },
|
||||
{ id: 'e8', source: 'forum-1', target: 'bridge-1', relation: '补充趋势' },
|
||||
{ id: 'e9', source: 'forum-2', target: 'bridge-1', relation: '反馈风险' },
|
||||
{ id: 'e10', source: 'bridge-1', target: 'sched-1', relation: '投递任务' },
|
||||
{ id: 'e11', source: 'sched-1', target: 'sched-2', relation: '进入评审' },
|
||||
{ id: 'e12', source: 'forum-1', target: 'sched-2', relation: '支撑验证' },
|
||||
{ id: 'e13', source: 'core-2', target: 'arch-1', relation: '归档事实' },
|
||||
{ id: 'e14', source: 'bridge-1', target: 'arch-1', relation: '桥接引用' },
|
||||
{ id: 'e15', source: 'chat-1', target: 'thread-1', relation: '拆分会话' },
|
||||
{ id: 'e16', source: 'chat-2', target: 'thread-1', relation: '补充回执' },
|
||||
{ id: 'e17', source: 'forum-1', target: 'signal-1', relation: '吸收案例' },
|
||||
{ id: 'e18', source: 'sched-1', target: 'lane-1', relation: '拆分排期' },
|
||||
{ id: 'e19', source: 'sched-2', target: 'lane-1', relation: '投递评审' },
|
||||
{ id: 'e20', source: 'forum-2', target: 'dormant-1', relation: '弱风险' },
|
||||
];
|
||||
|
||||
const TYPE_COLORS = {
|
||||
knowledge: 0x00f3ff,
|
||||
chat: 0xff6b9d,
|
||||
forum: 0xa855f7,
|
||||
schedule: 0xfbbf24,
|
||||
};
|
||||
|
||||
const TYPE_LABELS = {
|
||||
knowledge: '知识库',
|
||||
chat: '对话',
|
||||
forum: '论坛',
|
||||
schedule: '日程',
|
||||
};
|
||||
|
||||
let scene, camera, renderer;
|
||||
let nodeObjects = new Map();
|
||||
let edgeObjects = [];
|
||||
let particleSystem;
|
||||
let hoveredNodeId = null;
|
||||
let selectedNodeId = null;
|
||||
let mouseX = 0, mouseY = 0;
|
||||
let targetX = 0, targetY = 0;
|
||||
let windowHalfX = window.innerWidth / 2;
|
||||
let windowHalfY = window.innerHeight / 2;
|
||||
const nodeMeshes = [];
|
||||
|
||||
function updateTime() {
|
||||
const now = new Date();
|
||||
const el = document.getElementById('time-display');
|
||||
if (el) el.innerText = now.toLocaleTimeString('en-US', { hour12: false });
|
||||
}
|
||||
setInterval(updateTime, 1000);
|
||||
updateTime();
|
||||
|
||||
function init() {
|
||||
const container = document.getElementById('brain-canvas-container');
|
||||
const w = container.parentElement.clientWidth || 600;
|
||||
const h = container.parentElement.clientHeight || 600;
|
||||
|
||||
scene = new THREE.Scene();
|
||||
scene.fog = new THREE.FogExp2(0x020408, 0.0025);
|
||||
|
||||
camera = new THREE.PerspectiveCamera(60, w / h, 0.1, 2000);
|
||||
camera.position.z = 80;
|
||||
|
||||
renderer = new THREE.WebGLRenderer({ alpha: true, antialias: true });
|
||||
renderer.setSize(w, h);
|
||||
renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2));
|
||||
renderer.toneMapping = THREE.ACESFilmicToneMapping;
|
||||
renderer.toneMappingExposure = 1.2;
|
||||
container.appendChild(renderer.domElement);
|
||||
|
||||
const ambientLight = new THREE.AmbientLight(0x404060, 0.4);
|
||||
scene.add(ambientLight);
|
||||
|
||||
const pointLight = new THREE.PointLight(0x00f3ff, 1.5, 300);
|
||||
pointLight.position.set(0, 50, 50);
|
||||
scene.add(pointLight);
|
||||
|
||||
createBackground();
|
||||
createBrainCore();
|
||||
createNodes();
|
||||
createEdges();
|
||||
createOrbitalRings();
|
||||
|
||||
document.addEventListener('mousemove', onDocumentMouseMove);
|
||||
document.addEventListener('mousedown', onDocumentMouseDown);
|
||||
document.addEventListener('mouseup', onDocumentMouseUp);
|
||||
document.addEventListener('wheel', onDocumentWheel);
|
||||
window.addEventListener('resize', onWindowResize);
|
||||
|
||||
updateMetrics();
|
||||
updateNodeList();
|
||||
|
||||
setTimeout(() => {
|
||||
const statusEl = document.getElementById('brain-status');
|
||||
if (statusEl) {
|
||||
statusEl.innerText = "ONLINE";
|
||||
statusEl.classList.remove('text-red-500');
|
||||
statusEl.classList.add('text-cyan-300', 'bg-cyan-500/20', 'border-cyan-400');
|
||||
}
|
||||
addLog(">> Brain matrix initialized.");
|
||||
addLog(">> Neural pathways loaded.");
|
||||
addLog(">> 14 nodes, 20 connections active.");
|
||||
}, 1500);
|
||||
|
||||
animate();
|
||||
}
|
||||
|
||||
function createBackground() {
|
||||
const count = 1500;
|
||||
const positions = new Float32Array(count * 3);
|
||||
const colors = new Float32Array(count * 3);
|
||||
|
||||
for (let i = 0; i < count; i++) {
|
||||
positions[i * 3] = (Math.random() - 0.5) * 600;
|
||||
positions[i * 3 + 1] = (Math.random() - 0.5) * 600;
|
||||
positions[i * 3 + 2] = (Math.random() - 0.5) * 600;
|
||||
|
||||
const c = new THREE.Color();
|
||||
c.setHSL(0.55 + Math.random() * 0.1, 0.7, 0.5 + Math.random() * 0.4);
|
||||
colors[i * 3] = c.r;
|
||||
colors[i * 3 + 1] = c.g;
|
||||
colors[i * 3 + 2] = c.b;
|
||||
}
|
||||
|
||||
const geo = new THREE.BufferGeometry();
|
||||
geo.setAttribute('position', new THREE.BufferAttribute(positions, 3));
|
||||
geo.setAttribute('color', new THREE.BufferAttribute(colors, 3));
|
||||
|
||||
const mat = new THREE.PointsMaterial({
|
||||
size: 0.5, vertexColors: true, transparent: true, opacity: 0.6,
|
||||
blending: THREE.AdditiveBlending,
|
||||
});
|
||||
|
||||
particleSystem = new THREE.Points(geo, mat);
|
||||
scene.add(particleSystem);
|
||||
}
|
||||
|
||||
function createBrainCore() {
|
||||
const coreGeo = new THREE.IcosahedronGeometry(3, 2);
|
||||
const coreMat = new THREE.MeshBasicMaterial({
|
||||
color: 0x00f3ff,
|
||||
wireframe: true,
|
||||
transparent: true,
|
||||
opacity: 0.12
|
||||
});
|
||||
const coreMesh = new THREE.Mesh(coreGeo, coreMat);
|
||||
scene.add(coreMesh);
|
||||
|
||||
const innerGeo = new THREE.IcosahedronGeometry(2, 1);
|
||||
const innerMat = new THREE.MeshBasicMaterial({
|
||||
color: 0x00f3ff,
|
||||
transparent: true,
|
||||
opacity: 0.2
|
||||
});
|
||||
const innerMesh = new THREE.Mesh(innerGeo, innerMat);
|
||||
scene.add(innerMesh);
|
||||
}
|
||||
|
||||
function createHexShape(r) {
|
||||
const shape = new THREE.Shape();
|
||||
for (let i = 0; i < 6; i++) {
|
||||
const a = (i / 6) * Math.PI * 2 - Math.PI / 6;
|
||||
const x = Math.cos(a) * r, y = Math.sin(a) * r;
|
||||
if (i === 0) shape.moveTo(x, y); else shape.lineTo(x, y);
|
||||
}
|
||||
shape.closePath();
|
||||
return shape;
|
||||
}
|
||||
|
||||
function createNodes() {
|
||||
const angleStep = (Math.PI * 2) / NODES.length;
|
||||
const radius = 30;
|
||||
|
||||
NODES.forEach((node, i) => {
|
||||
const angle = i * angleStep;
|
||||
const layer = Math.floor(i / 7);
|
||||
const r = radius + layer * 18;
|
||||
const x = Math.cos(angle) * r;
|
||||
const z = Math.sin(angle) * r;
|
||||
const y = (Math.random() - 0.5) * 8 + layer * 4;
|
||||
|
||||
const color = TYPE_COLORS[node.type];
|
||||
const imp = node.importance;
|
||||
const height = 3 + imp * 12;
|
||||
const radius = 1.5 + imp * 1.5;
|
||||
|
||||
const group = new THREE.Group();
|
||||
group.userData = { nodeId: node.id };
|
||||
group.position.set(x, y, z);
|
||||
|
||||
const geo = new THREE.ExtrudeGeometry(createHexShape(radius), {
|
||||
depth: height, bevelEnabled: true, bevelThickness: 0.2, bevelSize: 0.15, bevelSegments: 2,
|
||||
});
|
||||
geo.center();
|
||||
|
||||
const mat = new THREE.MeshBasicMaterial({ color, transparent: true, opacity: 0.12, side: THREE.DoubleSide });
|
||||
const mesh = new THREE.Mesh(geo, mat);
|
||||
mesh.rotation.x = -Math.PI / 2;
|
||||
group.add(mesh);
|
||||
|
||||
const edgesGeo = new THREE.EdgesGeometry(geo);
|
||||
const edgesMat = new THREE.LineBasicMaterial({ color, transparent: true, opacity: 0.8 });
|
||||
const edges = new THREE.LineSegments(edgesGeo, edgesMat);
|
||||
edges.rotation.x = -Math.PI / 2;
|
||||
group.add(edges);
|
||||
|
||||
const glowGeo = new THREE.SphereGeometry(radius * 0.6, 12, 12);
|
||||
const glowMat = new THREE.MeshBasicMaterial({
|
||||
color, transparent: true, opacity: 0.3 + imp * 0.4, blending: THREE.AdditiveBlending,
|
||||
});
|
||||
const glow = new THREE.Mesh(glowGeo, glowMat);
|
||||
group.add(glow);
|
||||
|
||||
const topGeo = new THREE.CircleGeometry(radius * 0.4, 6);
|
||||
const topMat = new THREE.MeshBasicMaterial({ color, transparent: true, opacity: 0.7, side: THREE.DoubleSide });
|
||||
const top = new THREE.Mesh(topGeo, topMat);
|
||||
top.rotation.x = -Math.PI / 2;
|
||||
top.position.y = height / 2;
|
||||
group.add(top);
|
||||
|
||||
group.rotation.y = Math.random() * Math.PI;
|
||||
scene.add(group);
|
||||
nodeObjects.set(node.id, group);
|
||||
nodeMeshes.push(glow);
|
||||
});
|
||||
}
|
||||
|
||||
function createEdges() {
|
||||
EDGES.forEach(edge => {
|
||||
const src = nodeObjects.get(edge.source);
|
||||
const tgt = nodeObjects.get(edge.target);
|
||||
if (!src || !tgt) return;
|
||||
|
||||
const srcNode = NODES.find(n => n.id === edge.source);
|
||||
const color = TYPE_COLORS[srcNode?.type || 'knowledge'];
|
||||
|
||||
const points = [src.position.clone(), tgt.position.clone()];
|
||||
const geo = new THREE.BufferGeometry().setFromPoints(points);
|
||||
const mat = new THREE.LineDashedMaterial({
|
||||
color, transparent: true, opacity: 0.4,
|
||||
dashSize: 1.5, gapSize: 1, blending: THREE.AdditiveBlending,
|
||||
});
|
||||
const line = new THREE.Line(geo, mat);
|
||||
line.computeLineDistances();
|
||||
scene.add(line);
|
||||
edgeObjects.push(line);
|
||||
});
|
||||
}
|
||||
|
||||
function createOrbitalRings() {
|
||||
const ring1Geo = new THREE.BufferGeometry();
|
||||
const ring1Pos = new Float32Array(80 * 3);
|
||||
for (let i = 0; i < 80; i++) {
|
||||
const theta = (i / 80) * Math.PI * 2;
|
||||
ring1Pos[i * 3] = Math.cos(theta) * 45;
|
||||
ring1Pos[i * 3 + 1] = (Math.random() - 0.5) * 0.5;
|
||||
ring1Pos[i * 3 + 2] = Math.sin(theta) * 45;
|
||||
}
|
||||
ring1Geo.setAttribute('position', new THREE.BufferAttribute(ring1Pos, 3));
|
||||
const ring1Mat = new THREE.PointsMaterial({ color: 0x00f3ff, size: 0.3, transparent: true, opacity: 0.4 });
|
||||
const ring1 = new THREE.Points(ring1Geo, ring1Mat);
|
||||
ring1.userData = { speedX: 0.001, speedY: 0.002 };
|
||||
scene.add(ring1);
|
||||
|
||||
const ring2Geo = new THREE.BufferGeometry();
|
||||
const ring2Pos = new Float32Array(60 * 3);
|
||||
for (let i = 0; i < 60; i++) {
|
||||
const theta = (i / 60) * Math.PI * 2;
|
||||
ring2Pos[i * 3] = (Math.random() - 0.5) * 0.5;
|
||||
ring2Pos[i * 3 + 1] = Math.cos(theta) * 50;
|
||||
ring2Pos[i * 3 + 2] = Math.sin(theta) * 50;
|
||||
}
|
||||
ring2Geo.setAttribute('position', new THREE.BufferAttribute(ring2Pos, 3));
|
||||
const ring2Mat = new THREE.PointsMaterial({ color: 0xa855f7, size: 0.25, transparent: true, opacity: 0.3 });
|
||||
const ring2 = new THREE.Points(ring2Geo, ring2Mat);
|
||||
ring2.userData = { speedX: 0.002, speedY: 0.001 };
|
||||
scene.add(ring2);
|
||||
}
|
||||
|
||||
function onDocumentMouseMove(e) {
|
||||
mouseX = e.clientX - windowHalfX;
|
||||
mouseY = e.clientY - windowHalfY;
|
||||
}
|
||||
|
||||
function onDocumentMouseDown(e) {}
|
||||
function onDocumentMouseUp(e) {
|
||||
if (hoveredNodeId) selectNode(hoveredNodeId);
|
||||
}
|
||||
|
||||
function onDocumentWheel(e) {
|
||||
camera.position.z += e.deltaY * 0.05;
|
||||
camera.position.z = Math.max(30, Math.min(200, camera.position.z));
|
||||
}
|
||||
|
||||
function onWindowResize() {
|
||||
const container = document.getElementById('brain-canvas-container');
|
||||
const w = container.parentElement.clientWidth || 600;
|
||||
const h = container.parentElement.clientHeight || 600;
|
||||
camera.aspect = w / h;
|
||||
camera.updateProjectionMatrix();
|
||||
renderer.setSize(w, h);
|
||||
}
|
||||
|
||||
function animate() {
|
||||
requestAnimationFrame(animate);
|
||||
|
||||
const t = Date.now() * 0.001;
|
||||
|
||||
targetX = mouseX * 0.0005;
|
||||
targetY = mouseY * 0.0005;
|
||||
|
||||
camera.rotation.y += (targetX - camera.rotation.y) * 0.05;
|
||||
camera.rotation.x += (-targetY - camera.rotation.x) * 0.05;
|
||||
|
||||
particleSystem.rotation.y += 0.0001;
|
||||
particleSystem.rotation.x += 0.00005;
|
||||
|
||||
nodeMeshes.forEach((mesh, i) => {
|
||||
const pulse = Math.sin(t * 2 + i * 0.5) * 0.15;
|
||||
mesh.scale.setScalar(1 + pulse);
|
||||
});
|
||||
|
||||
edgeObjects.forEach(line => {
|
||||
const mat = line.material;
|
||||
mat.dashSize = 1.5 + Math.sin(t) * 0.3;
|
||||
});
|
||||
|
||||
scene.children.forEach(child => {
|
||||
if (child instanceof THREE.Points && child.userData.speedX) {
|
||||
child.rotation.x += child.userData.speedX;
|
||||
child.rotation.y += child.userData.speedY;
|
||||
}
|
||||
});
|
||||
|
||||
renderer.render(scene, camera);
|
||||
}
|
||||
|
||||
function updateMetrics() {
|
||||
document.getElementById('metric-nodes').textContent = NODES.length;
|
||||
document.getElementById('metric-links').textContent = EDGES.length;
|
||||
document.getElementById('nodes-bar').style.width = (NODES.length / 20 * 100) + '%';
|
||||
document.getElementById('links-bar').style.width = (EDGES.length / 30 * 100) + '%';
|
||||
|
||||
const clusters = 3;
|
||||
document.getElementById('metric-clusters').textContent = clusters;
|
||||
document.getElementById('clusters-bar').style.width = (clusters / 5 * 100) + '%';
|
||||
|
||||
const coreCount = NODES.filter(n => n.importance >= 0.86).length;
|
||||
const bridgeCount = NODES.filter(n => n.importance >= 0.7 && n.importance < 0.86).length;
|
||||
document.getElementById('core-nodes').textContent = coreCount;
|
||||
document.getElementById('bridge-nodes').textContent = bridgeCount;
|
||||
document.getElementById('active-nodes-val').textContent = 'ACTIVE: ' + NODES.length;
|
||||
}
|
||||
|
||||
function updateNodeList() {
|
||||
const list = document.getElementById('node-list');
|
||||
list.innerHTML = '';
|
||||
NODES.forEach(node => {
|
||||
const color = '#' + TYPE_COLORS[node.type].toString(16).padStart(6, '0');
|
||||
const div = document.createElement('div');
|
||||
div.className = 'flash-row p-2 flex justify-between items-center border-b border-cyan-500/10';
|
||||
div.innerHTML = `
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 rounded-full" style="background: ${color}; box-shadow: 0 0 4px ${color};"></div>
|
||||
<span class="text-cyan-300 truncate max-w-[100px]">${node.name}</span>
|
||||
</div>
|
||||
<span class="opacity-50 text-[9px]">${Math.round(node.importance * 100)}%</span>
|
||||
`;
|
||||
div.onclick = () => selectNode(node.id);
|
||||
list.appendChild(div);
|
||||
});
|
||||
}
|
||||
|
||||
function selectNode(nodeId) {
|
||||
selectedNodeId = nodeId;
|
||||
const node = NODES.find(n => n.id === nodeId);
|
||||
if (!node) return;
|
||||
|
||||
document.getElementById('selected-val').textContent = 'SELECTED: ' + node.name;
|
||||
|
||||
const color = '#' + TYPE_COLORS[node.type].toString(16).padStart(6, '0');
|
||||
const detail = document.getElementById('node-detail');
|
||||
detail.innerHTML = `
|
||||
<div class="mb-3 text-center">
|
||||
<div class="text-[9px] opacity-50 uppercase tracking-widest">${TYPE_LABELS[node.type]}</div>
|
||||
<div class="text-lg font-bold text-cyan-100 tracking-wider">${node.name}</div>
|
||||
</div>
|
||||
<div class="space-y-2">
|
||||
<div class="flex justify-between"><span class="opacity-60">IMPORTANCE</span><span class="text-cyan-300">${Math.round(node.importance * 100)}%</span></div>
|
||||
<div class="flex justify-between"><span class="opacity-60">DESCRIPTION</span></div>
|
||||
<div class="text-cyan-300/80 text-[10px] pl-2 border-l border-cyan-500/30">${node.description}</div>
|
||||
</div>
|
||||
`;
|
||||
|
||||
const conns = EDGES.filter(e => e.source === nodeId || e.target === nodeId);
|
||||
const list = document.getElementById('connections-list');
|
||||
list.innerHTML = '';
|
||||
if (conns.length === 0) {
|
||||
list.innerHTML = '<div class="text-center text-cyan-500/50 py-4">NO CONNECTIONS</div>';
|
||||
} else {
|
||||
conns.forEach(conn => {
|
||||
const otherId = conn.source === nodeId ? conn.target : conn.source;
|
||||
const other = NODES.find(n => n.id === otherId);
|
||||
const otherColor = '#' + TYPE_COLORS[other?.type || 'knowledge'].toString(16).padStart(6, '0');
|
||||
const div = document.createElement('div');
|
||||
div.className = 'border-b border-cyan-500/10 pb-1 mb-1';
|
||||
div.innerHTML = `
|
||||
<div class="flex items-center gap-1 text-[9px]">
|
||||
<span class="text-cyan-500">${conn.relation}</span>
|
||||
<span class="opacity-30">→</span>
|
||||
<span class="w-2 h-2 rounded-full inline-block" style="background: ${otherColor}; box-shadow: 0 0 4px ${otherColor};"></span>
|
||||
<span class="text-cyan-300">${other?.name || ''}</span>
|
||||
</div>
|
||||
`;
|
||||
list.appendChild(div);
|
||||
});
|
||||
}
|
||||
|
||||
document.getElementById('detail-panel').classList.add('active');
|
||||
addLog('>> Node selected: ' + node.name);
|
||||
}
|
||||
|
||||
function addLog(msg) {
|
||||
const terminal = document.getElementById('brain-terminal');
|
||||
if (!terminal) return;
|
||||
const div = document.createElement('div');
|
||||
div.className = 'border-l-2 border-cyan-800 pl-2 py-0.5';
|
||||
div.innerHTML = `<span class="text-[10px] text-cyan-600 mr-2 font-bold">[${new Date().toLocaleTimeString('en-US', { hour12: false })}]</span><span class="text-xs font-mono text-cyan-300/80">${msg}</span>`;
|
||||
terminal.appendChild(div);
|
||||
if (terminal.children.length > 15) terminal.removeChild(terminal.firstChild);
|
||||
terminal.scrollTop = terminal.scrollHeight;
|
||||
}
|
||||
|
||||
function updateActivityGraph() {
|
||||
const bars = document.querySelectorAll('#activity-graph .sys-bar');
|
||||
bars.forEach(bar => {
|
||||
bar.style.height = Math.floor(Math.random() * 80 + 10) + '%';
|
||||
});
|
||||
}
|
||||
|
||||
setInterval(updateActivityGraph, 500);
|
||||
|
||||
document.addEventListener('mousemove', (e) => {
|
||||
const container = document.getElementById('brain-canvas-container');
|
||||
if (!container) return;
|
||||
const rect = container.getBoundingClientRect();
|
||||
if (e.clientX >= rect.left && e.clientX <= rect.right && e.clientY >= rect.top && e.clientY <= rect.bottom) {
|
||||
const x = ((e.clientX - rect.left) / rect.width) * 2 - 1;
|
||||
const y = -((e.clientY - rect.top) / rect.height) * 2 + 1;
|
||||
|
||||
const raycaster = new THREE.Raycaster();
|
||||
raycaster.setFromCamera({ x, y }, camera);
|
||||
const intersects = raycaster.intersectObjects(scene.children, true);
|
||||
|
||||
let found = null;
|
||||
for (const hit of intersects) {
|
||||
let obj = hit.object;
|
||||
while (obj) {
|
||||
if (obj.userData?.nodeId) { found = obj.userData.nodeId; break; }
|
||||
obj = obj.parent;
|
||||
}
|
||||
if (found) break;
|
||||
}
|
||||
hoveredNodeId = found;
|
||||
container.style.cursor = found ? 'pointer' : 'grab';
|
||||
}
|
||||
});
|
||||
|
||||
init();
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
752
frontend/prototypes/index_backup.html
Normal file
752
frontend/prototypes/index_backup.html
Normal file
@@ -0,0 +1,752 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>J.A.R.V.I.S. Interface</title>
|
||||
<script src="https://cdn.tailwindcss.com"></script>
|
||||
<link
|
||||
href="https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;700;900&family=Share+Tech+Mono&display=swap"
|
||||
rel="stylesheet">
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
|
||||
<style>
|
||||
:root {
|
||||
--jarvis-blue: #00f3ff;
|
||||
--jarvis-blue-dim: rgba(0, 243, 255, 0.1);
|
||||
--jarvis-alert: #ff3333;
|
||||
--bg-color: #020408;
|
||||
}
|
||||
|
||||
body {
|
||||
background-color: var(--bg-color);
|
||||
color: var(--jarvis-blue);
|
||||
font-family: 'Orbitron', sans-serif;
|
||||
overflow: hidden;
|
||||
margin: 0;
|
||||
height: 100vh;
|
||||
width: 100vw;
|
||||
}
|
||||
|
||||
/* Scanline effect */
|
||||
body::after {
|
||||
content: "";
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100vw;
|
||||
height: 100vh;
|
||||
background: linear-gradient(to bottom,
|
||||
rgba(255, 255, 255, 0),
|
||||
rgba(255, 255, 255, 0) 50%,
|
||||
rgba(0, 0, 0, 0.1) 50%,
|
||||
rgba(0, 0, 0, 0.1));
|
||||
background-size: 100% 3px;
|
||||
pointer-events: none;
|
||||
z-index: 50;
|
||||
}
|
||||
|
||||
/* Vignette */
|
||||
.vignette {
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: radial-gradient(circle, transparent 50%, rgba(0, 0, 0, 0.95) 100%);
|
||||
pointer-events: none;
|
||||
z-index: 40;
|
||||
}
|
||||
|
||||
/* Text & Border Utilities */
|
||||
.text-glow {
|
||||
text-shadow: 0 0 5px var(--jarvis-blue), 0 0 10px var(--jarvis-blue);
|
||||
}
|
||||
|
||||
.text-dim {
|
||||
color: rgba(0, 243, 255, 0.6);
|
||||
}
|
||||
|
||||
/* Tech Panels */
|
||||
.tech-panel {
|
||||
background: rgba(0, 15, 30, 0.7);
|
||||
border-left: 1px solid rgba(0, 243, 255, 0.3);
|
||||
border-right: 1px solid rgba(0, 243, 255, 0.3);
|
||||
position: relative;
|
||||
backdrop-filter: blur(4px);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.tech-panel:hover {
|
||||
border-color: rgba(0, 243, 255, 0.8);
|
||||
background: rgba(0, 20, 40, 0.8);
|
||||
}
|
||||
|
||||
/* Corner accents */
|
||||
.tech-panel::before,
|
||||
.tech-panel::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
border: 1px solid var(--jarvis-blue);
|
||||
transition: all 0.3s;
|
||||
}
|
||||
|
||||
.tech-panel::before {
|
||||
top: -1px;
|
||||
left: -1px;
|
||||
border-right: none;
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.tech-panel::after {
|
||||
bottom: -1px;
|
||||
right: -1px;
|
||||
border-left: none;
|
||||
border-top: none;
|
||||
}
|
||||
|
||||
/* Tech Border Box */
|
||||
.tech-border {
|
||||
clip-path: polygon(10px 0,
|
||||
100% 0,
|
||||
100% calc(100% - 10px),
|
||||
calc(100% - 10px) 100%,
|
||||
0 100%,
|
||||
0 10px);
|
||||
border-top: 1px solid var(--jarvis-blue-dim);
|
||||
}
|
||||
|
||||
/* Scrollbars */
|
||||
::-webkit-scrollbar {
|
||||
width: 4px;
|
||||
}
|
||||
|
||||
::-webkit-scrollbar-track {
|
||||
background: rgba(0, 0, 0, 0.3);
|
||||
}
|
||||
|
||||
::-webkit-scrollbar-thumb {
|
||||
background: var(--jarvis-blue);
|
||||
border-radius: 2px;
|
||||
}
|
||||
|
||||
/* Animations */
|
||||
@keyframes pulse-status {
|
||||
|
||||
0%,
|
||||
100% {
|
||||
opacity: 0.6;
|
||||
text-shadow: 0 0 2px var(--jarvis-blue);
|
||||
box-shadow: 0 0 5px var(--jarvis-blue-dim);
|
||||
}
|
||||
|
||||
50% {
|
||||
opacity: 1;
|
||||
text-shadow: 0 0 15px var(--jarvis-blue);
|
||||
box-shadow: 0 0 15px var(--jarvis-blue-dim);
|
||||
}
|
||||
}
|
||||
|
||||
.status-pulse {
|
||||
animation: pulse-status 3s infinite ease-in-out;
|
||||
}
|
||||
|
||||
@keyframes flash-row {
|
||||
0% {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
50% {
|
||||
background-color: rgba(0, 243, 255, 0.15);
|
||||
}
|
||||
|
||||
100% {
|
||||
background-color: transparent;
|
||||
}
|
||||
}
|
||||
|
||||
.flash-row:hover {
|
||||
animation: flash-row 0.8s infinite;
|
||||
cursor: pointer;
|
||||
background: rgba(0, 243, 255, 0.05);
|
||||
}
|
||||
|
||||
/* Smooth Bar Transition */
|
||||
.sys-bar {
|
||||
transition: width 0.5s ease-out, height 0.3s ease-out;
|
||||
}
|
||||
|
||||
/* Canvas Positioning */
|
||||
#canvas-container {
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -55%);
|
||||
z-index: 10;
|
||||
width: 800px;
|
||||
height: 800px;
|
||||
pointer-events: none;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<div class="vignette"></div>
|
||||
|
||||
<!-- MAIN UI WRAPPER -->
|
||||
<div class="relative z-30 h-full w-full flex flex-col p-4 md:p-6 pointer-events-none">
|
||||
|
||||
<!-- HEADER -->
|
||||
<header class="flex justify-between items-start pointer-events-auto mb-2 border-b border-cyan-500/20 pb-2">
|
||||
<div class="flex items-center gap-4">
|
||||
<div class="flex flex-col items-center justify-center">
|
||||
<div class="w-2 h-2 bg-cyan-400 rounded-full mb-1"></div>
|
||||
<div class="h-8 w-px bg-cyan-500/50"></div>
|
||||
</div>
|
||||
<div>
|
||||
<h1 class="text-4xl font-bold tracking-[0.15em] text-glow font-orbitron">J.A.R.V.I.S.</h1>
|
||||
<div class="flex items-center gap-2 mt-1">
|
||||
<div class="h-1 w-20 bg-cyan-500/30 overflow-hidden">
|
||||
<div class="h-full bg-cyan-400 w-1/2 animate-pulse"></div>
|
||||
</div>
|
||||
<div class="text-[9px] tracking-[0.3em] opacity-70">NEURAL INTERFACE V5.1</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="text-right">
|
||||
<div class="flex items-center justify-end gap-3 mb-1">
|
||||
<span class="text-[10px] tracking-widest opacity-60">LINK STATUS</span>
|
||||
<span id="connection-status"
|
||||
class="font-bold text-xs status-pulse bg-cyan-900/40 px-3 py-1 rounded-sm border border-cyan-500/30">DISCONNECTED</span>
|
||||
</div>
|
||||
<div class="flex justify-end items-baseline gap-2">
|
||||
<span class="text-[10px] opacity-50">SYS_TIME</span>
|
||||
<div id="time-display" class="font-mono text-xl tracking-wider text-cyan-200">00:00:00</div>
|
||||
</div>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<!-- MAIN GRID LAYOUT -->
|
||||
<div class="flex-grow grid grid-cols-1 md:grid-cols-4 gap-6 pointer-events-auto h-0 min-h-0 mt-2">
|
||||
|
||||
<!-- LEFT COLUMN: DEVICES & IOT -->
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<!-- Server Status -->
|
||||
<div class="tech-panel p-4 tech-border">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-3 text-cyan-300">
|
||||
SERVER CLUSTER LOAD</h3>
|
||||
<div class="space-y-4 font-mono text-[10px]">
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">MAIN_FRAME_01</span><span
|
||||
class="text-cyan-300" id="server-1-val">ONLINE</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-1-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[34%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">DATA_CORE_ZETA</span><span
|
||||
class="text-cyan-300" id="server-2-val">PROCESSING</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-2-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[89%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="flex justify-between mb-1"><span class="opacity-70">STORAGE_ARRAY</span><span
|
||||
class="text-cyan-300" id="server-3-val">STABLE</span></div>
|
||||
<div class="w-full bg-cyan-900/50 h-1">
|
||||
<div id="server-3-bar"
|
||||
class="sys-bar bg-cyan-400 h-full w-[12%] shadow-[0_0_8px_#00f3ff]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="grid grid-cols-2 gap-2 pt-2">
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">TEMP</div>
|
||||
<div id="sys-temp" class="text-sm font-bold text-cyan-300">42°C</div>
|
||||
</div>
|
||||
<div class="bg-cyan-900/20 p-2 border border-cyan-500/20 text-center">
|
||||
<div class="opacity-50 text-[9px]">POWER</div>
|
||||
<div id="sys-power" class="text-sm font-bold text-cyan-300">98%</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Connected Devices -->
|
||||
<div class="tech-panel p-4 flex-grow overflow-hidden flex flex-col">
|
||||
<div class="flex justify-between items-center border-b border-cyan-500/30 pb-2 mb-2">
|
||||
<h3 class="text-xs font-bold tracking-widest text-cyan-300">CONNECTED DEVICES</h3>
|
||||
<span class="text-[9px] bg-cyan-500/20 px-1 rounded animate-pulse">SCANNING</span>
|
||||
</div>
|
||||
|
||||
<ul id="device-list"
|
||||
class="font-mono text-[11px] space-y-1 overflow-y-auto pr-1 flex-grow custom-scrollbar">
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>SMART_HOME_HUB</span>
|
||||
</div>
|
||||
<span class="opacity-50 text-[9px]">192.168.1.10</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>SECURITY_CAM_GRID</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">ACTIVE</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-yellow-500 rounded-full animate-pulse"></div>
|
||||
<span>DRONE_SENTRY_04</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">CHARGING</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>MAIN_GATE_LOCK</span>
|
||||
</div>
|
||||
<span class="opacity-50 text-[9px]">SECURE</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-red-500 rounded-full"></div>
|
||||
<span>EXT_PERIMETER_SENSORS</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">ALERT</span>
|
||||
</li>
|
||||
<li
|
||||
class="flash-row p-2 flex justify-between items-center group border-b border-cyan-500/10 hover:border-cyan-500/50 transition-colors">
|
||||
<div class="flex items-center gap-2">
|
||||
<div class="w-1.5 h-1.5 bg-green-500 rounded-full"></div>
|
||||
<span>LAB_3D_PRINTER</span>
|
||||
</div>
|
||||
<span class="device-status opacity-50 text-[9px]">IDLE</span>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- CENTER COLUMN: NEURAL VISUALIZATION & OUTPUT -->
|
||||
<div class="md:col-span-2 relative flex flex-col justify-end items-center">
|
||||
|
||||
<!-- Floating Status -->
|
||||
<div class="absolute top-10 w-full text-center pointer-events-none">
|
||||
<div id="ai-status"
|
||||
class="text-xl md:text-2xl font-bold tracking-[0.3em] text-glow uppercase text-cyan-100">
|
||||
NEURAL ENGINE: STANDBY
|
||||
</div>
|
||||
<div class="text-[10px] text-cyan-400/70 tracking-[0.5em] mt-2">AWAITING INPUT PARAMETERS</div>
|
||||
</div>
|
||||
|
||||
<!-- Main Terminal (Bottom Center) -->
|
||||
<div
|
||||
class="terminal-window w-full h-56 bg-black/90 border-t border-cyan-500/50 rounded-tl-lg rounded-tr-lg overflow-hidden flex flex-col backdrop-blur-md shadow-[0_-5px_20px_rgba(0,243,255,0.1)]">
|
||||
<div
|
||||
class="bg-cyan-900/20 px-3 py-1.5 text-[10px] flex justify-between border-b border-cyan-500/30 items-center">
|
||||
<span class="tracking-widest text-cyan-400">CONSOLE_OUT // ROOT_ACCESS</span>
|
||||
<div class="flex gap-2 font-mono text-cyan-600">
|
||||
<span id="pid-val">PID:4092</span>
|
||||
<span id="mem-val">MEM:24%</span>
|
||||
</div>
|
||||
</div>
|
||||
<div id="terminal-content"
|
||||
class="p-4 font-mono text-xs text-cyan-300/80 overflow-y-auto flex-grow space-y-1.5">
|
||||
<!-- Logs inject here -->
|
||||
<div class="opacity-50 border-l-2 border-cyan-800 pl-2">>> Initializing neural weights... OK
|
||||
</div>
|
||||
<div class="opacity-50 border-l-2 border-cyan-800 pl-2">>> Mounting device file system... OK
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- RIGHT COLUMN: FILES & ALGORITHMS -->
|
||||
<div class="flex flex-col gap-4 h-full overflow-hidden">
|
||||
|
||||
<!-- Algorithm Status -->
|
||||
<div class="tech-panel p-4 flex-grow flex flex-col">
|
||||
<h3 class="text-xs font-bold tracking-widest border-b border-cyan-500/30 pb-2 mb-2 text-cyan-300">
|
||||
ACTIVE THREADS</h3>
|
||||
<div class="font-mono text-[11px] overflow-y-auto pr-1 flex-grow space-y-3">
|
||||
|
||||
<div class="mb-2">
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/VISION</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">object_recognition.py</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">RUNNING</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">facial_scan_v2.exe</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">IDLE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/LANGUAGE</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">nlp_core_en.lib</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">LOADED</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">voice_synth_mod.dll</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">ACTIVE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<div class="text-cyan-100 opacity-60 mb-1 text-[10px]">/PROCESS/NETWORK</div>
|
||||
<div class="pl-2 border-l border-cyan-500/30 space-y-1.5">
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">packet_sniffer.sh</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">BG</span></div>
|
||||
<div class="flash-row flex items-center justify-between"><span
|
||||
class="text-cyan-400">firewall_daemon</span> <span
|
||||
class="text-[9px] bg-cyan-900 px-1 rounded">ACTIVE</span></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Network Topology (Active Visualizer) -->
|
||||
<div class="tech-panel h-32 p-4 relative overflow-hidden flex flex-col justify-between">
|
||||
<div class="text-[10px] opacity-60 tracking-widest mb-1">NETWORK_TRAFFIC</div>
|
||||
<!-- Mock Graph Bars -->
|
||||
<div class="flex items-end justify-between h-full gap-1 pt-2" id="network-graph">
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[50%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[80%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[40%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[60%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[90%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-600 h-[45%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-500 h-[70%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-400 h-[30%]"></div>
|
||||
<div class="sys-bar w-1 bg-cyan-300 h-[60%]"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- THREE.JS CONTAINER -->
|
||||
<div id="canvas-container"></div>
|
||||
|
||||
<script>
|
||||
(function () {
|
||||
// --- CLOCK UTILITY ---
|
||||
function updateTime() {
|
||||
const now = new Date();
|
||||
const timeDisplay = document.getElementById('time-display');
|
||||
if (timeDisplay) {
|
||||
timeDisplay.innerText = now.toLocaleTimeString('en-US', { hour12: false });
|
||||
}
|
||||
}
|
||||
setInterval(updateTime, 1000);
|
||||
updateTime();
|
||||
|
||||
// --- THREE.JS ADVANCED NEURAL VISUALIZATION ---
|
||||
const container = document.getElementById('canvas-container');
|
||||
|
||||
if (container) {
|
||||
const scene = new THREE.Scene();
|
||||
// Subtler fog for deep space feel
|
||||
scene.fog = new THREE.FogExp2(0x020408, 0.003);
|
||||
|
||||
const camera = new THREE.PerspectiveCamera(75, 1, 0.1, 1000);
|
||||
camera.position.z = 20;
|
||||
|
||||
const renderer = new THREE.WebGLRenderer({ alpha: true, antialias: true });
|
||||
renderer.setSize(800, 800);
|
||||
renderer.setPixelRatio(window.devicePixelRatio);
|
||||
container.appendChild(renderer.domElement);
|
||||
|
||||
// --- GROUPING ---
|
||||
const brainGroup = new THREE.Group();
|
||||
scene.add(brainGroup);
|
||||
|
||||
// 1. INNER CORE (Dense Wireframe Sphere)
|
||||
const coreGeo = new THREE.IcosahedronGeometry(4, 2);
|
||||
const coreMat = new THREE.MeshBasicMaterial({
|
||||
color: 0x00f3ff,
|
||||
wireframe: true,
|
||||
transparent: true,
|
||||
opacity: 0.15
|
||||
});
|
||||
const coreMesh = new THREE.Mesh(coreGeo, coreMat);
|
||||
brainGroup.add(coreMesh);
|
||||
|
||||
// 2. NEURAL CLOUD (Nodes & Lines)
|
||||
const particleCount = 400; // Increased count
|
||||
const cloudRadius = 9;
|
||||
const particlesData = [];
|
||||
let particlePositions = new Float32Array(particleCount * 3);
|
||||
|
||||
const pMaterial = new THREE.PointsMaterial({
|
||||
color: 0x00f3ff,
|
||||
size: 0.15,
|
||||
blending: THREE.AdditiveBlending,
|
||||
transparent: true,
|
||||
opacity: 0.8
|
||||
});
|
||||
|
||||
// Generate random points in a spherical shell
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
const r = cloudRadius + (Math.random() - 0.5) * 4; // Vary radius for depth
|
||||
const theta = Math.random() * Math.PI * 2;
|
||||
const phi = Math.acos((Math.random() * 2) - 1);
|
||||
|
||||
const x = r * Math.sin(phi) * Math.cos(theta);
|
||||
const y = r * Math.sin(phi) * Math.sin(theta);
|
||||
const z = r * Math.cos(phi);
|
||||
|
||||
particlePositions[i * 3] = x;
|
||||
particlePositions[i * 3 + 1] = y;
|
||||
particlePositions[i * 3 + 2] = z;
|
||||
|
||||
particlesData.push({
|
||||
velocity: new THREE.Vector3(
|
||||
(-1 + Math.random() * 2) * 0.02,
|
||||
(-1 + Math.random() * 2) * 0.02,
|
||||
(-1 + Math.random() * 2) * 0.02
|
||||
),
|
||||
originalPos: new THREE.Vector3(x, y, z)
|
||||
});
|
||||
}
|
||||
|
||||
const particlesGeo = new THREE.BufferGeometry();
|
||||
particlesGeo.setAttribute('position', new THREE.BufferAttribute(particlePositions, 3));
|
||||
const particleSystem = new THREE.Points(particlesGeo, pMaterial);
|
||||
brainGroup.add(particleSystem);
|
||||
|
||||
// Lines setup
|
||||
const maxConnections = particleCount;
|
||||
const linesGeo = new THREE.BufferGeometry();
|
||||
const linePositions = new Float32Array(maxConnections * maxConnections * 3);
|
||||
const lineColors = new Float32Array(maxConnections * maxConnections * 3);
|
||||
|
||||
linesGeo.setAttribute('position', new THREE.BufferAttribute(linePositions, 3));
|
||||
linesGeo.setAttribute('color', new THREE.BufferAttribute(lineColors, 3));
|
||||
|
||||
const lMaterial = new THREE.LineBasicMaterial({
|
||||
vertexColors: true,
|
||||
blending: THREE.AdditiveBlending,
|
||||
transparent: true,
|
||||
opacity: 0.2
|
||||
});
|
||||
|
||||
const linesMesh = new THREE.LineSegments(linesGeo, lMaterial);
|
||||
brainGroup.add(linesMesh);
|
||||
|
||||
// 3. ORBITAL RINGS (Fast moving outer data)
|
||||
const ringGroup = new THREE.Group();
|
||||
brainGroup.add(ringGroup);
|
||||
|
||||
function createOrbitalRing(radius, count, speedX, speedY) {
|
||||
const ringGeo = new THREE.BufferGeometry();
|
||||
const ringPos = new Float32Array(count * 3);
|
||||
for (let i = 0; i < count; i++) {
|
||||
const theta = (i / count) * Math.PI * 2;
|
||||
ringPos[i * 3] = Math.cos(theta) * radius;
|
||||
ringPos[i * 3 + 1] = Math.sin(theta) * radius;
|
||||
ringPos[i * 3 + 2] = (Math.random() - 0.5) * 0.5;
|
||||
}
|
||||
ringGeo.setAttribute('position', new THREE.BufferAttribute(ringPos, 3));
|
||||
const ringMat = new THREE.PointsMaterial({ color: 0x00f3ff, size: 0.1, transparent: true, opacity: 0.6 });
|
||||
const ring = new THREE.Points(ringGeo, ringMat);
|
||||
ring.userData = { speedX, speedY };
|
||||
return ring;
|
||||
}
|
||||
|
||||
const ring1 = createOrbitalRing(11, 100, 0.005, 0.01);
|
||||
const ring2 = createOrbitalRing(13, 80, -0.01, 0.002);
|
||||
ringGroup.add(ring1);
|
||||
ringGroup.add(ring2);
|
||||
|
||||
|
||||
// --- ANIMATION LOOP ---
|
||||
function animate() {
|
||||
requestAnimationFrame(animate);
|
||||
|
||||
// 1. Rotate entire group
|
||||
brainGroup.rotation.y += 0.002;
|
||||
|
||||
// 2. Animate Core
|
||||
coreMesh.rotation.x -= 0.005;
|
||||
coreMesh.rotation.z += 0.002;
|
||||
|
||||
// 3. Animate Particles & Lines
|
||||
let vertexpos = 0;
|
||||
let colorpos = 0;
|
||||
let numConnected = 0;
|
||||
|
||||
// Update particles
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
// Jitter particles
|
||||
const p = particlesData[i];
|
||||
// Constrain to radius roughly
|
||||
particlePositions[i * 3] += p.velocity.x;
|
||||
particlePositions[i * 3 + 1] += p.velocity.y;
|
||||
particlePositions[i * 3 + 2] += p.velocity.z;
|
||||
|
||||
// Very simple bounce back logic
|
||||
if (Math.abs(particlePositions[i * 3] - p.originalPos.x) > 1) p.velocity.x = -p.velocity.x;
|
||||
if (Math.abs(particlePositions[i * 3 + 1] - p.originalPos.y) > 1) p.velocity.y = -p.velocity.y;
|
||||
if (Math.abs(particlePositions[i * 3 + 2] - p.originalPos.z) > 1) p.velocity.z = -p.velocity.z;
|
||||
}
|
||||
particlesGeo.attributes.position.needsUpdate = true;
|
||||
|
||||
// Connect lines (Optimize: only check subset or smaller distance)
|
||||
const connectionDist = 2.5;
|
||||
|
||||
for (let i = 0; i < particleCount; i++) {
|
||||
for (let j = i + 1; j < particleCount; j++) {
|
||||
const dx = particlePositions[i * 3] - particlePositions[j * 3];
|
||||
const dy = particlePositions[i * 3 + 1] - particlePositions[j * 3 + 1];
|
||||
const dz = particlePositions[i * 3 + 2] - particlePositions[j * 3 + 2];
|
||||
const dist = Math.sqrt(dx * dx + dy * dy + dz * dz);
|
||||
|
||||
if (dist < connectionDist) {
|
||||
const alpha = 1.0 - dist / connectionDist;
|
||||
|
||||
linePositions[vertexpos++] = particlePositions[i * 3];
|
||||
linePositions[vertexpos++] = particlePositions[i * 3 + 1];
|
||||
linePositions[vertexpos++] = particlePositions[i * 3 + 2];
|
||||
|
||||
linePositions[vertexpos++] = particlePositions[j * 3];
|
||||
linePositions[vertexpos++] = particlePositions[j * 3 + 1];
|
||||
linePositions[vertexpos++] = particlePositions[j * 3 + 2];
|
||||
|
||||
lineColors[colorpos++] = 0; lineColors[colorpos++] = alpha; lineColors[colorpos++] = 1;
|
||||
lineColors[colorpos++] = 0; lineColors[colorpos++] = alpha; lineColors[colorpos++] = 1;
|
||||
|
||||
numConnected++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
linesMesh.geometry.setDrawRange(0, numConnected * 2);
|
||||
linesMesh.geometry.attributes.position.needsUpdate = true;
|
||||
linesMesh.geometry.attributes.color.needsUpdate = true;
|
||||
|
||||
// 4. Animate Rings
|
||||
ring1.rotation.x += ring1.userData.speedX;
|
||||
ring1.rotation.y += ring1.userData.speedY;
|
||||
ring2.rotation.x += ring2.userData.speedX;
|
||||
ring2.rotation.y += ring2.userData.speedY;
|
||||
|
||||
renderer.render(scene, camera);
|
||||
}
|
||||
animate();
|
||||
}
|
||||
|
||||
|
||||
// --- MOCK DATA SIMULATION (The "Life" of the Dashboard) ---
|
||||
|
||||
// 1. Terminal Logger
|
||||
const terminal = document.getElementById('terminal-content');
|
||||
function addLog(message) {
|
||||
if (!terminal) return;
|
||||
const div = document.createElement('div');
|
||||
div.className = 'text-cyan-300 opacity-80 border-l-2 border-transparent hover:border-cyan-500 pl-2 py-0.5 animate-pulse-fast';
|
||||
div.innerHTML = `<span class="text-[10px] text-cyan-600 mr-2 font-bold">[${new Date().toLocaleTimeString('en-US', { hour12: false })}]</span> <span class="text-xs font-mono">${message}</span>`;
|
||||
terminal.appendChild(div);
|
||||
if (terminal.children.length > 20) terminal.removeChild(terminal.firstChild); // Keep DOM light
|
||||
terminal.scrollTop = terminal.scrollHeight;
|
||||
}
|
||||
|
||||
// 2. Update System Bars & Text
|
||||
function updateSystemStats() {
|
||||
// Server Load Bars
|
||||
document.getElementById('server-1-bar').style.width = Math.floor(Math.random() * 40 + 30) + '%'; // 30-70%
|
||||
document.getElementById('server-2-bar').style.width = Math.floor(Math.random() * 20 + 70) + '%'; // 70-90%
|
||||
document.getElementById('server-3-bar').style.width = Math.floor(Math.random() * 10 + 5) + '%'; // 5-15%
|
||||
|
||||
// Temp & Power
|
||||
document.getElementById('sys-temp').innerText = Math.floor(Math.random() * 5 + 40) + '°C';
|
||||
document.getElementById('sys-power').innerText = Math.floor(Math.random() * 3 + 96) + '%';
|
||||
|
||||
// Memory PID
|
||||
document.getElementById('mem-val').innerText = 'MEM:' + Math.floor(Math.random() * 10 + 20) + '%';
|
||||
}
|
||||
|
||||
// 3. Animate Network Graph
|
||||
function updateNetworkGraph() {
|
||||
const bars = document.querySelectorAll('#network-graph .sys-bar');
|
||||
bars.forEach(bar => {
|
||||
bar.style.height = Math.floor(Math.random() * 80 + 10) + '%';
|
||||
});
|
||||
}
|
||||
|
||||
// 4. Device Status Rotation
|
||||
function updateDeviceStatus() {
|
||||
const statuses = document.querySelectorAll('.device-status');
|
||||
const randomIdx = Math.floor(Math.random() * statuses.length);
|
||||
const el = statuses[randomIdx];
|
||||
|
||||
const states = ['ACTIVE', 'PINGING', 'SENDING', 'IDLE'];
|
||||
const newState = states[Math.floor(Math.random() * states.length)];
|
||||
|
||||
el.innerText = newState;
|
||||
if (newState === 'ACTIVE' || newState === 'SENDING') el.className = 'device-status text-cyan-300 text-[9px]';
|
||||
else el.className = 'device-status opacity-50 text-[9px]';
|
||||
}
|
||||
|
||||
// --- START SIMULATION ---
|
||||
setTimeout(() => {
|
||||
const statusEl = document.getElementById('connection-status');
|
||||
const aiStatusEl = document.getElementById('ai-status');
|
||||
|
||||
if (statusEl) {
|
||||
statusEl.innerText = "SECURE LINK ESTABLISHED";
|
||||
statusEl.classList.remove('text-red-500');
|
||||
statusEl.classList.add('text-cyan-300', 'bg-cyan-500/20', 'border-cyan-400');
|
||||
}
|
||||
|
||||
if (aiStatusEl) {
|
||||
aiStatusEl.innerHTML = "NEURAL ENGINE: <span class='text-cyan-300 drop-shadow-[0_0_10px_rgba(0,243,255,0.8)]'>ONLINE</span>";
|
||||
}
|
||||
|
||||
addLog(">> Handshake protocol complete.");
|
||||
addLog(">> Neural weights loaded into memory.");
|
||||
|
||||
// Start Interval Loops
|
||||
setInterval(() => {
|
||||
const logs = [
|
||||
"Optimizing neural pathways...", "Garbage collection active...",
|
||||
"Packet sniffing: 192.168.1.X...", "Updating heuristic models...",
|
||||
"Thermal throttling check... OK", "Syncing cloud replica...",
|
||||
"Analyzing biometric feed...", "Background process [PID:8821] started"
|
||||
];
|
||||
addLog(">> " + logs[Math.floor(Math.random() * logs.length)]);
|
||||
}, 2000);
|
||||
|
||||
setInterval(updateSystemStats, 1500);
|
||||
setInterval(updateNetworkGraph, 300); // Fast update for graph
|
||||
setInterval(updateDeviceStatus, 3000);
|
||||
|
||||
}, 1000);
|
||||
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
|
||||
</html>
|
||||
@@ -22,6 +22,7 @@ export interface AgentConfig {
|
||||
description: string
|
||||
system_prompt: string
|
||||
enabled: boolean
|
||||
selected_skill_ids?: string[]
|
||||
}
|
||||
|
||||
export const agentApi = {
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user