admin
09d10de6d5
- health check 改用 sys.executable 动态获取 Python 路径，适配容器内 /opt/venv - demo 数据 fallback 路径修正，移除硬编码的 F:/GraphRAGAgent Windows 路径 - 前端 index.html 标题从"构建产品原型"改为"GraphRAG Studio"
174 lines
6.5 KiB
Python
174 lines
6.5 KiB
Python
"""F 组：系统（4 个端点）"""
|
|
import os
|
|
import sys
|
|
import time
|
|
from pathlib import Path
|
|
|
|
from fastapi import APIRouter
|
|
|
|
from models.schemas import APIResponse
|
|
from storage import file_store as fs
|
|
|
|
router = APIRouter(tags=["System"])
|
|
|
|
_START_TIME = time.time()
|
|
|
|
|
|
@router.get("/health")
|
|
async def health_check():
|
|
env_path = Path(__file__).parent.parent / ".env"
|
|
from dotenv import load_dotenv
|
|
load_dotenv(env_path, override=False)
|
|
|
|
mineru_python = Path(os.getenv("MINERU_PYTHON", str(Path(__file__).parent.parent.parent / "mineru_mvp" / ".venv" / "bin" / "python")))
|
|
backend_python = Path(os.getenv("LANGEXTRACT_PYTHON", str(Path(sys.executable))))
|
|
deepseek_key = os.getenv("DEEPSEEK_API_KEY", "")
|
|
deepseek_url = os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com")
|
|
|
|
# Check if langextract is importable from backend's venv
|
|
try:
|
|
import subprocess
|
|
result = subprocess.run(
|
|
[str(backend_python), "-c", "import langextract; print('ok')"],
|
|
capture_output=True, text=True, timeout=10
|
|
)
|
|
langextract_ok = result.returncode == 0 and "ok" in result.stdout
|
|
except Exception:
|
|
langextract_ok = False
|
|
|
|
components = {
|
|
"mineru_venv": {
|
|
"status": "ok" if mineru_python.exists() else "error",
|
|
"path": str(mineru_python),
|
|
"exists": mineru_python.exists(),
|
|
},
|
|
"langextract_venv": {
|
|
"status": "ok" if langextract_ok else "error",
|
|
"path": str(backend_python),
|
|
"exists": backend_python.exists(),
|
|
},
|
|
"deepseek_api": {
|
|
"status": "ok" if deepseek_key else "error",
|
|
"base_url": deepseek_url,
|
|
"key_configured": bool(deepseek_key),
|
|
},
|
|
"storage": {
|
|
"status": "ok",
|
|
"kg_nodes_exists": fs.kg_nodes_path().exists(),
|
|
"kg_edges_exists": fs.kg_edges_path().exists(),
|
|
"uploads_dir_exists": fs.UPLOADS_DIR.exists(),
|
|
},
|
|
}
|
|
|
|
overall = "healthy" if all(c["status"] == "ok" for c in components.values()) else "degraded"
|
|
|
|
return APIResponse.ok({
|
|
"status": overall,
|
|
"version": "1.0.0",
|
|
"uptime_seconds": round(time.time() - _START_TIME, 1),
|
|
"components": components,
|
|
})
|
|
|
|
|
|
@router.get("/system/stats")
|
|
async def system_stats():
|
|
from services import indexing_service as idx_svc
|
|
|
|
docs = list(fs.load_docs_index().values())
|
|
nodes = fs.load_kg_nodes()
|
|
edges = fs.load_kg_edges()
|
|
history = fs.load_query_history()
|
|
|
|
type_dist: dict[str, int] = {}
|
|
for n in nodes:
|
|
t = n.get("type", "UNKNOWN")
|
|
type_dist[t] = type_dist.get(t, 0) + 1
|
|
|
|
return APIResponse.ok({
|
|
"total_documents": len(docs),
|
|
"indexed_documents": sum(1 for d in docs if d.get("status") == "indexed"),
|
|
"failed_documents": sum(1 for d in docs if d.get("status") == "failed"),
|
|
"total_nodes": len(nodes),
|
|
"total_edges": len(edges),
|
|
"type_distribution": type_dist,
|
|
"total_queries": len(history),
|
|
"active_jobs": idx_svc.count_active_jobs(),
|
|
"storage_used_mb": fs.storage_used_mb(),
|
|
})
|
|
|
|
|
|
@router.get("/system/formats")
|
|
async def list_formats():
|
|
return APIResponse.ok({
|
|
"formats": [
|
|
{"ext": "pdf", "description": "PDF 文档（文本型/扫描型/混合型）", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
{"ext": "docx", "description": "Microsoft Word（新版）", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
{"ext": "doc", "description": "Microsoft Word（旧版）", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
{"ext": "pptx", "description": "PowerPoint（新版）", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
{"ext": "ppt", "description": "PowerPoint（旧版）", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
{"ext": "png", "description": "PNG 图片（单页）", "max_size_mb": 200, "max_pages": 1, "requires_ocr": True},
|
|
{"ext": "jpg", "description": "JPEG 图片（单页）", "max_size_mb": 200, "max_pages": 1, "requires_ocr": True},
|
|
{"ext": "jpeg", "description": "JPEG 图片（单页）", "max_size_mb": 200, "max_pages": 1, "requires_ocr": True},
|
|
{"ext": "html", "description": "HTML 文件", "max_size_mb": 200, "max_pages": 600, "requires_ocr": False},
|
|
],
|
|
"ocr_languages": [
|
|
{"code": "ch", "name": "中文（默认）"},
|
|
{"code": "en", "name": "英文"},
|
|
{"code": "japan", "name": "日文"},
|
|
{"code": "korean", "name": "韩文"},
|
|
{"code": "french", "name": "法文"},
|
|
{"code": "german", "name": "德文"},
|
|
],
|
|
"notes": [
|
|
"language 参数默认值为 'ch'（非 'zh'），遵循 PaddleOCR v3 语言代码规范",
|
|
"上传时不需要携带 Content-Type，服务端自动识别",
|
|
"PNG/JPG/JPEG 单次最多处理 1 页",
|
|
],
|
|
})
|
|
|
|
|
|
@router.get("/system/demo")
|
|
async def get_demo_data():
|
|
# Try backend KG first, then fall back to graphrag_pipeline/output
|
|
nodes = fs.load_kg_nodes()
|
|
edges = fs.load_kg_edges()
|
|
|
|
if not nodes:
|
|
# Fallback: load from backend/output/ directory
|
|
legacy_output = Path(__file__).parent.parent / "output"
|
|
legacy_nodes_path = legacy_output / "kg_nodes.json"
|
|
legacy_edges_path = legacy_output / "kg_edges.json"
|
|
if legacy_nodes_path.exists():
|
|
import json
|
|
nodes = json.loads(legacy_nodes_path.read_text(encoding="utf-8"))
|
|
edges = json.loads(legacy_edges_path.read_text(encoding="utf-8")) if legacy_edges_path.exists() else []
|
|
else:
|
|
from fastapi.responses import JSONResponse
|
|
return JSONResponse(
|
|
status_code=400,
|
|
content=APIResponse.err(3002, "No demo data available. Index a document first.").model_dump(),
|
|
)
|
|
|
|
type_counts: dict[str, int] = {}
|
|
for n in nodes:
|
|
t = n.get("type", "UNKNOWN")
|
|
type_counts[t] = type_counts.get(t, 0) + 1
|
|
|
|
import networkx as nx
|
|
G = nx.Graph()
|
|
for n in nodes:
|
|
G.add_node(n["id"])
|
|
for e in edges:
|
|
G.add_edge(e["source"], e["target"])
|
|
|
|
return APIResponse.ok({
|
|
"nodes": nodes,
|
|
"edges": edges,
|
|
"stats": {
|
|
"nodes": len(nodes),
|
|
"edges": len(edges),
|
|
"type_counts": type_counts,
|
|
"density": round(nx.density(G), 4) if G.number_of_nodes() > 1 else 0.0,
|
|
},
|
|
})
|