From 5cc306eb0a196e3fd51077b9d11553c3295393f3 Mon Sep 17 00:00:00 2001 From: wuyongtao Date: Mon, 3 Aug 2026 15:49:21 +0800 Subject: [PATCH] =?UTF-8?q?fix:=20=E6=8E=A8=E7=90=86/=E8=AF=84=E6=B5=8B?= =?UTF-8?q?=E7=BB=93=E6=9E=9C=E5=90=8C=E6=AD=A5=E3=80=81=E6=95=B0=E6=8D=AE?= =?UTF-8?q?=E9=9B=86=E7=BB=9F=E8=AE=A1=E4=B8=8E=E7=AE=97=E5=8A=9B=E8=8A=82?= =?UTF-8?q?=E7=82=B9=E7=AE=A1=E7=90=86=E5=A2=9E=E5=BC=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 后端: - 抽取 fetch_eval_result_content 复用函数，model_eval_detail 直接应用评测任务结果 - health 接口移除数据库依赖，返回静态指标 - 数据集: count_dataset_records JSON 感知计数; 文件统计改为从 dataset_files 聚合重算; 在线编辑记录 size/record_count/version_no; 上传同步批处理 - 算力节点: 调度支持 requested GPU 子集校验与容量计算; 新增 delete_compute_node(含活动任务保护)及 DELETE 接口; 连接池 connect_timeout - 评测任务落库 basic_metrics/score/completed_time, failed/stopped 记录 error 评测引擎: - _load_dataset 支持 JSON/JSONL 文件 - 新增 exact match 与文本相似度指标, 余弦相似度去掉 2 样本限制 前端: - 算力节点列表「维护」改为「删除」(带确认弹窗), compute.ts 新增 deleteComputeNode - 数据集上传超时调整为 120s; FineTuneTask 增加 compute_node_id; GpuInfo 状态增加 reserved --- backend/app/api/v1/endpoints/health.py | 7 +- backend/app/api/v1/endpoints/platform.py | 45 +++--- backend/app/db/platform_store.py | 139 ++++++++++++++++-- backend/app/modules/compute_gateway/client.py | 3 +- backend/app/modules/compute_gateway/sync.py | 31 ++-- compute/engines/llama_factory/eval_runner.py | 84 +++++++++-- frontend/src/api/modules/compute.ts | 5 +- frontend/src/api/modules/dataset.ts | 1 + frontend/src/types/index.ts | 3 +- .../src/views/compute/ComputeNodesView.vue | 30 +++- .../src/views/dataset/DatasetCreateView.vue | 34 +++-- frontend/src/views/eval/EvalDetailView.vue | 32 +++- frontend/src/views/eval/EvalView.vue | 19 ++- .../views/fine-tune/FineTuneCreateView.vue | 79 +++++++--- .../src/views/fine-tune/fineTuneFormModel.ts | 2 + 15 files changed, 402 insertions(+), 112 deletions(-) diff --git a/backend/app/api/v1/endpoints/health.py b/backend/app/api/v1/endpoints/health.py index c5676c1..8a01289 100644 --- a/backend/app/api/v1/endpoints/health.py +++ b/backend/app/api/v1/endpoints/health.py @@ -1,7 +1,6 @@ from fastapi import APIRouter from app.core.logging import get_logger -from app.db.platform_store import get_platform_store router = APIRouter() logger = get_logger(__name__) @@ -10,5 +9,9 @@ logger = get_logger(__name__) @router.get("/health") async def health_check() -> dict[str, object]: logger.info("health check requested") - return {"code": 0, "message": "ok", "data": get_platform_store().health_metrics()} + return { + "code": 0, + "message": "ok", + "data": {"cpu_percent": 0.0, "memory_percent": 0.0, "disk_percent": 0.0}, + } diff --git a/backend/app/api/v1/endpoints/platform.py b/backend/app/api/v1/endpoints/platform.py index 0f38fb1..42484f9 100644 --- a/backend/app/api/v1/endpoints/platform.py +++ b/backend/app/api/v1/endpoints/platform.py @@ -15,7 +15,7 @@ from app.core.auth import filter_accessible_resource_ids, get_current_user, has_ from app.core.config import get_settings from app.db.platform_store import get_platform_store from app.modules.compute_gateway.client import ComputeNodeClient -from app.modules.compute_gateway.sync import poll_compute_jobs_once +from app.modules.compute_gateway.sync import fetch_eval_result_content, poll_compute_jobs_once router = APIRouter() @@ -915,6 +915,7 @@ async def upload_dataset_files( ) -> dict[str, Any]: created: list[dict[str, Any]] = [] compute_sync: list[dict[str, Any]] = [] + pending_sync: list[tuple[str, str, bytes]] = [] store = get_platform_store() try: store.dataset(dataset_id) @@ -926,16 +927,18 @@ async def upload_dataset_files( content = raw.decode("utf-8", errors="replace") created_file = store.add_dataset_file(conn, dataset_id, file.filename or "upload.jsonl", content) created.append(created_file) - if sync_to_compute: - compute_sync.extend( - await _sync_dataset_file_to_compute_nodes( - store, - dataset_id, - created_file["id"], - created_file["name"], - raw, - ) + pending_sync.append((created_file["id"], created_file["name"], raw)) + if sync_to_compute: + for file_id, file_name, raw in pending_sync: + compute_sync.extend( + await _sync_dataset_file_to_compute_nodes( + store, + dataset_id, + file_id, + file_name, + raw, ) + ) return ok({"files": created, "compute_sync": compute_sync}) @@ -1273,8 +1276,7 @@ async def model_eval_detail(task_id: str, current_user: dict = Depends(get_curre try: store = get_platform_store() task = store.eval_task(task_id) - # If the eval job completed on a compute node, try to load results - if task.get("result_artifact_path"): + if task.get("compute_job_id") and task.get("compute_node_id") and task.get("status") in {"queued", "running", "completed"}: node = next( (n for n in store.compute_nodes() if n["id"] == task.get("compute_node_id")), None, @@ -1283,11 +1285,10 @@ async def model_eval_detail(task_id: str, current_user: dict = Depends(get_curre try: client = ComputeNodeClient(node["api_base_url"]) job = await client.get_job(task["compute_job_id"]) - artifacts = job.get("artifacts") or [] - for art in artifacts: - if art.get("name") == "eval_results.json": - task["_result_artifact"] = art - break + result_content = None + if job.get("status") == "completed" and not task.get("samples"): + result_content = await fetch_eval_result_content(client, node, job) + task = store.apply_eval_job_result(task_id, job, result_content) except Exception: pass except KeyError: @@ -1790,6 +1791,16 @@ async def update_compute_node(node_id: str, payload: dict[str, Any] = Body(...)) raise fail(400, str(exc)) +@router.delete("/compute/nodes/{node_id}") +async def delete_compute_node(node_id: str) -> dict[str, Any]: + try: + return ok(get_platform_store().delete_compute_node(node_id)) + except KeyError: + raise fail(404, "compute node not found") + except ValueError as exc: + raise fail(400, str(exc)) + + @router.post("/compute/nodes/{node_id}/test-connection") async def test_compute_node(node_id: str) -> dict[str, Any]: store = get_platform_store() diff --git a/backend/app/db/platform_store.py b/backend/app/db/platform_store.py index b88ff27..0a0d4a9 100644 --- a/backend/app/db/platform_store.py +++ b/backend/app/db/platform_store.py @@ -88,6 +88,22 @@ def parse_size_bytes(value: Any) -> int: return max(0, round(amount * _SIZE_UNIT_BYTES[unit])) +def count_dataset_records(content: str) -> int: + text = (content or "").strip() + if not text: + return 0 + + try: + value = json.loads(text) + if isinstance(value, list): + return len(value) + return 1 + except (TypeError, ValueError, json.JSONDecodeError): + pass + + return len([line for line in text.splitlines() if line.strip()]) + + def version_number(value: Any, default: int = 0) -> int: try: number = int(value) @@ -296,6 +312,7 @@ class PlatformStore: # request (notably expensive against the remote PostgreSQL instance). # TCP keepalive 让操作系统持续保活连接，抵抗远程库空闲静默断连。 pool_kwargs = { + "connect_timeout": 5, "keepalives": 1, "keepalives_idle": 30, "keepalives_interval": 10, @@ -1311,6 +1328,7 @@ class PlatformStore: file_size_bytes = int(file_row.get("size_bytes") or 0) if file_size_bytes <= 0: file_size_bytes = parse_size_bytes(file_row.get("size")) + file_record_count = int(file_row.get("record_count") or 0) decoded_files.append( { "id": file_row["id"], @@ -1319,7 +1337,7 @@ class PlatformStore: "size_bytes": file_size_bytes, **dataset_file_version_summary(file_row), "create_time": file_row["create_time"], - "record_count": int(file_row.get("record_count") or 0), + "record_count": file_record_count, "split": metadata.get("file_split"), } ) @@ -1337,6 +1355,9 @@ class PlatformStore: total_size_bytes = int(row.get("size_bytes") or 0) if total_size_bytes <= 0: total_size_bytes = parse_size_bytes(row.get("size")) + total_record_count = sum(int(item.get("record_count") or 0) for item in decoded_files) + if not decoded_files: + total_record_count = int(row.get("record_count") or row.get("count") or 0) current_version_nos = sorted( { int(item["current_version_no"]) @@ -1346,6 +1367,8 @@ class PlatformStore: ) return { **dict(row), + "count": total_record_count, + "record_count": total_record_count, "size_bytes": total_size_bytes, "current_version_no": ( current_version_nos[0] if len(current_version_nos) == 1 else None @@ -1420,7 +1443,7 @@ class PlatformStore: version_id = f"{file_id}_v1" size_bytes = len(content.encode("utf-8")) size = f"{size_bytes} B" - record_count = len([line for line in content.splitlines() if line.strip()]) + record_count = count_dataset_records(content) version = { "id": version_id, "version": 1, @@ -1453,10 +1476,18 @@ class PlatformStore: ) conn.execute( """UPDATE datasets - SET count=count+?, record_count=record_count+?, - size_bytes=size_bytes+?, size=((size_bytes+?)::text || ' B') + SET count=stats.record_count, + record_count=stats.record_count, + size_bytes=stats.size_bytes, + size=(stats.size_bytes::text || ' B') + FROM ( + SELECT COALESCE(SUM(record_count), 0) AS record_count, + COALESCE(SUM(size_bytes), 0) AS size_bytes + FROM dataset_files + WHERE dataset_id=? + ) stats WHERE id=?""", - (record_count, record_count, size_bytes, size_bytes, dataset_id), + (dataset_id, dataset_id), ) return { "id": file_id, @@ -1561,19 +1592,57 @@ class PlatformStore: row = conn.execute("SELECT * FROM dataset_files WHERE id=?", (file_id,)).fetchone() if not row: raise KeyError(file_id) + content = payload.get("content", "") + size_bytes = len(content.encode("utf-8")) + record_count = count_dataset_records(content) versions = json_loads(row["versions"], []) version = { "id": f"{file_id}_v{len(versions) + 1}", "version": len(versions) + 1, + "version_no": len(versions) + 1, "create_time": utcnow(), "description": payload.get("description", "online edit"), + "size_bytes": size_bytes, + "record_count": record_count, } versions.append(version) conn.execute( - "UPDATE dataset_files SET content=?, active_version_id=?, versions=? WHERE id=?", - (payload.get("content", ""), version["id"], json_dumps(versions), file_id), + """ + UPDATE dataset_files + SET content=?, active_version_id=?, current_version_id=?, versions=?, + size_bytes=?, size=?, record_count=?, version_no=? + WHERE id=? + """, + ( + content, + version["id"], + version["id"], + json_dumps(versions), + size_bytes, + f"{size_bytes} B", + record_count, + version["version_no"], + file_id, + ), ) - return {"version": version, "content": payload.get("content", "")} + conn.execute( + """UPDATE datasets + SET count=stats.record_count, + record_count=stats.record_count, + size_bytes=stats.size_bytes, + size=(stats.size_bytes::text || ' B') + FROM ( + SELECT dataset_id, + COALESCE(SUM(record_count), 0) AS record_count, + COALESCE(SUM(size_bytes), 0) AS size_bytes + FROM dataset_files + WHERE dataset_id=(SELECT dataset_id FROM dataset_files WHERE id=?) + GROUP BY dataset_id + ) stats + WHERE datasets.id=stats.dataset_id""", + (file_id,), + ) + return {"version": version, "content": content} def activate_file_version(self, file_id: str, version_id: str) -> dict[str, Any]: with self.connect() as conn: @@ -2173,6 +2242,14 @@ class PlatformStore: "sample_count": result_content.get("sample_count", 0), "completed_count": result_content.get("completed_count", 0), "passed_count": result_content.get("passed_count", 0), + "basic_metrics": result_content.get("basic_metrics", {}), + "score": result_content.get("overall_score", 0), + "completed_time": utcnow(), + }) + elif new_status in {"failed", "stopped"}: + updates.update({ + "error": job.get("error") or task.get("error") or "", + "completed_time": utcnow(), }) return self.update_eval_task(task_id, updates) @@ -2342,6 +2419,15 @@ class PlatformStore: ).fetchall() return {int(row["gpu_index"]) for row in rows} + def _node_gpu_indexes(self, conn: PgConnection, node: dict[str, Any]) -> set[int]: + rows = conn.execute("SELECT gpu_index FROM gpus WHERE node_id=?", (node["id"],)).fetchall() + if rows: + return {int(row["gpu_index"]) for row in rows} + return set(range(max(0, int(node.get("gpu_count") or 0)))) + + def _node_capacity(self, node: dict[str, Any]) -> int: + return max(1, int(node.get("max_parallel_jobs") or 1), int(node.get("gpu_count") or 0)) + def _schedule_node_locked(self, conn: PgConnection, payload: dict[str, Any]) -> dict[str, Any]: requested = payload.get("requested_node_id") or payload.get("compute_node_id") requested_gpus = [int(item) for item in payload.get("gpus") or []] @@ -2349,13 +2435,15 @@ class PlatformStore: candidates = [ n for n in nodes - if n["enabled"] and n["scheduler_status"] == "online" and n["current_running_jobs"] < n["max_parallel_jobs"] + if n["enabled"] and n["scheduler_status"] == "online" and n["current_running_jobs"] < self._node_capacity(n) ] if requested_gpus: + requested_gpu_set = set(requested_gpus) candidates = [ node for node in candidates - if not set(requested_gpus).intersection(self._active_gpu_indexes(conn, node["id"])) + if requested_gpu_set.issubset(self._node_gpu_indexes(conn, node)) + and not requested_gpu_set.intersection(self._active_gpu_indexes(conn, node["id"])) ] if requested: selected = next((n for n in candidates if n["id"] == requested), None) @@ -2370,8 +2458,8 @@ class PlatformStore: reason = "disabled" elif node["scheduler_status"] != "online": reason = f"status={node['scheduler_status']}" - elif node["current_running_jobs"] >= node["max_parallel_jobs"]: - reason = f"capacity full {node['current_running_jobs']}/{node['max_parallel_jobs']}" + elif node["current_running_jobs"] >= self._node_capacity(node): + reason = f"capacity full {node['current_running_jobs']}/{self._node_capacity(node)}" else: reason = "not selected" reasons.append(f"{node['code']}({reason})") @@ -2722,6 +2810,24 @@ class PlatformStore: ) return next(node for node in self.compute_nodes() if node["id"] == node_id) + def delete_compute_node(self, node_id: str) -> dict[str, Any]: + with self.connect() as conn: + node = conn.execute("SELECT * FROM compute_nodes WHERE id=?", (node_id,)).fetchone() + if not node: + raise KeyError(node_id) + active = conn.execute( + """ + SELECT COUNT(*) AS cnt + FROM fine_tune_tasks + WHERE compute_node_id=? AND status IN ('syncing','queued','running') + """, + (node_id,), + ).fetchone() + if active and int(active["cnt"] or 0) > 0: + raise ValueError("compute node has active training tasks") + conn.execute("DELETE FROM compute_nodes WHERE id=?", (node_id,)) + return {"deleted": node_id} + def update_compute_node_health(self, node_id: str, health: dict[str, Any], success: bool, error: str | None = None) -> dict[str, Any]: current = next((n for n in self.compute_nodes() if n["id"] == node_id), None) if not current: @@ -2890,11 +2996,12 @@ class PlatformStore: } def health_metrics(self) -> dict[str, float]: - info = self.system_info() + # Health checks must stay lightweight. The Docker healthcheck and page + # refresh probes should not wait on dashboard/GPU/database aggregation. return { - "cpu_percent": info["cpu"]["percent"], - "memory_percent": info["memory"]["percent"], - "disk_percent": info["disk"]["percent"], + "cpu_percent": 0.0, + "memory_percent": 0.0, + "disk_percent": 0.0, } def queue(self) -> list[dict[str, Any]]: diff --git a/backend/app/modules/compute_gateway/client.py b/backend/app/modules/compute_gateway/client.py index 8d1e821..aeeaae6 100644 --- a/backend/app/modules/compute_gateway/client.py +++ b/backend/app/modules/compute_gateway/client.py @@ -207,7 +207,8 @@ class ComputeNodeClient: "resource_id": resource_id or "", } files = {"file": (filename, content)} - async with httpx.AsyncClient(timeout=max(self.timeout, 60), headers=self.headers()) as client: + timeout = httpx.Timeout(max(self.timeout, 60), connect=self.timeout) + async with httpx.AsyncClient(timeout=timeout, headers=self.headers()) as client: response = await client.post( _join_url(self.api_base_url, f"{self.route_prefix}/compute/files/upload"), data=data, diff --git a/backend/app/modules/compute_gateway/sync.py b/backend/app/modules/compute_gateway/sync.py index b8abcbc..27f51e1 100644 --- a/backend/app/modules/compute_gateway/sync.py +++ b/backend/app/modules/compute_gateway/sync.py @@ -10,6 +10,24 @@ def _node_for_task(task: dict[str, Any]) -> dict[str, Any] | None: return next((node for node in get_platform_store().compute_nodes() if node["id"] == task.get("compute_node_id")), None) +async def fetch_eval_result_content(client: ComputeNodeClient, node: dict[str, Any], job: dict[str, Any]) -> dict[str, Any] | None: + output_dir = job.get("output_dir") + if not output_dir: + return None + full_path = f"{str(output_dir).rstrip('/')}/eval_results.json" + data_root = "/data/yg-ft/" + if full_path.startswith(data_root): + full_path = full_path[len(data_root):] + rel_path = full_path.lstrip("/") + import httpx + url = f"{node['api_base_url'].rstrip('/')}/modelTF/compute/files/read" + async with httpx.AsyncClient(timeout=30, headers=client.headers()) as http: + response = await http.get(url, params={"path": rel_path}) + response.raise_for_status() + payload = response.json() + return payload if isinstance(payload, dict) else None + + async def poll_compute_jobs_once() -> dict[str, Any]: store = get_platform_store() synced: list[dict[str, Any]] = [] @@ -66,18 +84,7 @@ async def poll_compute_jobs_once() -> dict[str, Any]: # Try to read eval_results.json from the job output directory if job.get("status") == "completed" and job.get("output_dir"): try: - full_path = f"{job['output_dir'].rstrip('/')}/eval_results.json" - # Convert absolute path to relative (strip YG_FT_DATA_ROOT prefix) - data_root = "/data/yg-ft/" - if full_path.startswith(data_root): - full_path = full_path[len(data_root):] - rel_path = full_path.lstrip("/") - import httpx - settings_path = f"{node['api_base_url'].rstrip('/')}/modelTF/compute/files/read" - async with httpx.AsyncClient(timeout=30, headers=client.headers()) as http: - read_resp = await http.get(settings_path, params={"path": rel_path}) - if read_resp.status_code == 200: - result_content = read_resp.json() + result_content = await fetch_eval_result_content(client, node, job) except Exception: pass store.apply_eval_job_result(eval_task["id"], job, result_content) diff --git a/compute/engines/llama_factory/eval_runner.py b/compute/engines/llama_factory/eval_runner.py index 135fb20..3c974a8 100644 --- a/compute/engines/llama_factory/eval_runner.py +++ b/compute/engines/llama_factory/eval_runner.py @@ -13,30 +13,42 @@ from __future__ import annotations import json import math +import re import sys import time +from difflib import SequenceMatcher from pathlib import Path from typing import Any -def _load_jsonl(path: str) -> list[dict[str, Any]]: - """Load a JSONL dataset file. Each line must be a JSON object. +def _load_dataset(path: str) -> list[dict[str, Any]]: + """Load a JSON or JSONL dataset file. Supports common field names used across the platform: * ``instruction`` + ``input`` + ``output`` (Alpaca-style) * ``question`` + ``answer`` * ``messages`` (ShareGPT-style – the last assistant message is treated as reference) """ + file_path = Path(path) + text = file_path.read_text(encoding="utf-8", errors="replace").strip() + if not text: + return [] + if file_path.suffix.lower() == ".json": + value = json.loads(text) + if isinstance(value, list): + return [item for item in value if isinstance(item, dict)] + return [value] if isinstance(value, dict) else [] + samples: list[dict[str, Any]] = [] - with open(path, encoding="utf-8") as fh: - for line in fh: - line = line.strip() - if not line: - continue - try: - obj = json.loads(line) - except json.JSONDecodeError: - continue + for line in text.splitlines(): + line = line.strip() + if not line: + continue + try: + obj = json.loads(line) + except json.JSONDecodeError: + continue + if isinstance(obj, dict): samples.append(obj) return samples @@ -115,8 +127,6 @@ def _compute_cosine(references: list[str], predictions: list[str]) -> dict[str, from sklearn.metrics.pairwise import cosine_similarity except ImportError: return {"enabled": False, "error": "scikit-learn not installed", "score": 0} - if len(predictions) < 2: - return {"enabled": True, "score": 0, "error": "need at least 2 samples for corpus cosine"} try: vectorizer = TfidfVectorizer() tfidf = vectorizer.fit_transform(references + predictions) @@ -129,6 +139,32 @@ def _compute_cosine(references: list[str], predictions: list[str]) -> dict[str, return {"enabled": True, "score": 0, "error": "insufficient text for vectorization"} +def _normalize_text(value: str) -> str: + return re.sub(r"\s+", " ", str(value or "").strip().lower()) + + +def _compute_exact_match(references: list[str], predictions: list[str]) -> dict[str, Any]: + total = len(predictions) + if not total: + return {"enabled": True, "score": 0, "matched": 0, "total": 0} + matched = sum( + 1 + for ref, pred in zip(references, predictions) + if _normalize_text(ref) == _normalize_text(pred) + ) + return {"enabled": True, "score": round(matched / total * 100, 2), "matched": matched, "total": total} + + +def _compute_text_similarity(references: list[str], predictions: list[str]) -> dict[str, Any]: + if not predictions: + return {"enabled": True, "score": 0} + scores = [ + SequenceMatcher(None, _normalize_text(ref), _normalize_text(pred)).ratio() + for ref, pred in zip(references, predictions) + ] + return {"enabled": True, "score": round(sum(scores) / max(len(scores), 1) * 100, 2)} + + # --------------------------------------------------------------------------- # LLM Judge # --------------------------------------------------------------------------- @@ -265,7 +301,7 @@ def run_eval(config: dict[str, Any]) -> dict[str, Any]: # ---- 1. Load dataset ---- print(f"[eval] loading dataset: {dataset_path}") - raw_samples = _load_jsonl(dataset_path) + raw_samples = _load_dataset(dataset_path) print(f"[eval] loaded {len(raw_samples)} samples") # ---- 2. Load model ---- @@ -356,6 +392,8 @@ def run_eval(config: dict[str, Any]) -> dict[str, Any]: cosine_cfg = basic_cfg.get("cosine", {}) if cosine_cfg.get("enabled"): metrics_result["cosine"] = _compute_cosine(references, predictions) + metrics_result["exact_match"] = _compute_exact_match(references, predictions) + metrics_result["text_similarity"] = _compute_text_similarity(references, predictions) # ---- 5. Summarise ---- completed = len(samples) @@ -375,9 +413,23 @@ def run_eval(config: dict[str, Any]) -> dict[str, Any]: overall_evaluation = f"评测完成：{completed} 样本，{passed_count} 通过，平均 {avg_score}/{max_score} 分" else: passed_count = 0 - overall_score = 0 + enabled_scores = [ + float(item.get("score") or 0) + for item in metrics_result.values() + if isinstance(item, dict) and item.get("enabled", True) and item.get("score") is not None + ] + overall_score = round(sum(enabled_scores) / len(enabled_scores), output_precision) if enabled_scores else 0 overall_score_max = 100 - dimension_summary = [] + dimension_summary = [ + { + "name": name, + "score": float(item.get("score") or 0), + "max_score": 100, + "pass_rate": float(item.get("score") or 0), + } + for name, item in metrics_result.items() + if isinstance(item, dict) and item.get("enabled", True) and item.get("score") is not None + ] overall_evaluation = f"评测完成：{completed} 样本（未配置 LLM 评委）" result = { diff --git a/frontend/src/api/modules/compute.ts b/frontend/src/api/modules/compute.ts index ad6d10e..344782c 100644 --- a/frontend/src/api/modules/compute.ts +++ b/frontend/src/api/modules/compute.ts @@ -1,4 +1,4 @@ -import { get, post, put } from '../request' +import { del, get, post, put } from '../request' export interface ComputeNode { id: string @@ -95,6 +95,9 @@ export const createComputeNode = (data: ComputeNodePayload) => export const updateComputeNode = (id: string, data: Partial) => put(`/compute/nodes/${id}`, data) +export const deleteComputeNode = (id: string) => + del<{ deleted: string }>(`/compute/nodes/${id}`) + export const testComputeNode = (id: string) => post<{ node_id: string; success: boolean; latency_ms: number; gpu_count: number; error?: string }>(`/compute/nodes/${id}/test-connection`) diff --git a/frontend/src/api/modules/dataset.ts b/frontend/src/api/modules/dataset.ts index 92a7e3a..ec32bf7 100644 --- a/frontend/src/api/modules/dataset.ts +++ b/frontend/src/api/modules/dataset.ts @@ -29,6 +29,7 @@ export const uploadDatasetFiles = (datasetId: string | number, files: File[]) => files.forEach((f) => formData.append('files', f)) return post(`/dataset-manage/upload/${datasetId}`, formData, { headers: { 'Content-Type': 'multipart/form-data' }, + timeout: 120000, }) } diff --git a/frontend/src/types/index.ts b/frontend/src/types/index.ts index 991fe29..0bcec31 100644 --- a/frontend/src/types/index.ts +++ b/frontend/src/types/index.ts @@ -132,6 +132,7 @@ export interface FineTuneTask { train_dataset_id?: number | string auto_merge?: boolean output_model_name?: string + compute_node_id?: string gpus?: number[] batch_size?: number learning_rate?: number @@ -355,7 +356,7 @@ export interface GpuInfo { power_w: number id?: number uuid?: string - status?: 'idle' | 'busy' | 'warning' | 'offline' + status?: 'idle' | 'busy' | 'reserved' | 'warning' | 'offline' memory_percent?: number power_limit_w?: number processes?: GpuProcess[] diff --git a/frontend/src/views/compute/ComputeNodesView.vue b/frontend/src/views/compute/ComputeNodesView.vue index bd36aaf..8c35126 100644 --- a/frontend/src/views/compute/ComputeNodesView.vue +++ b/frontend/src/views/compute/ComputeNodesView.vue @@ -1,12 +1,12 @@