76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
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"""
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LangChain Adapter
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Adapts Jarvis tools to LangChain tool format.
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"""
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from typing import List, Dict, Any, Optional, Callable
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import json
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class LangChainToolAdapter:
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"""Adapter for converting Jarvis tools to LangChain tools"""
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def __init__(self, registry: Any):
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self.registry = registry
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def to_langchain_tools(self) -> List[Dict[str, Any]]:
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"""Convert all enabled tools to LangChain format"""
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import asyncio
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async def _convert():
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tools = await self.registry.list_enabled()
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result = []
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for metadata in tools:
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lc_tool = await self._create_langchain_tool(metadata)
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if lc_tool:
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result.append(lc_tool)
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return result
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return asyncio.get_event_loop().run_until_complete(_convert())
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async def _create_langchain_tool(self, metadata: Any) -> Optional[Dict[str, Any]]:
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"""Create a single LangChain tool from metadata"""
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executor = await self.registry.get_executor(metadata.name)
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if not executor:
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return None
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config = await self.registry.get_config(metadata.name)
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return {
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"name": metadata.name,
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"description": metadata.description,
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"display_name": metadata.display_name,
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"tags": metadata.tags,
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"version": metadata.version,
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"executor": executor,
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"config": config,
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}
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def get_tool_schemas(self) -> List[Dict[str, Any]]:
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"""Get tool schemas for LLM function calling"""
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import asyncio
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async def _get():
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tools = await self.registry.list_enabled()
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schemas = []
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for tool in tools:
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schemas.append(
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{
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"name": tool.name,
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"description": tool.description,
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"parameters": {
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"type": "object",
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"properties": {},
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"required": [],
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},
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}
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)
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return schemas
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return asyncio.get_event_loop().run_until_complete(_get())
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