Refactor code formatting in lightrag_api_openai_compatible_demo.py
This commit is contained in:
@@ -16,7 +16,7 @@ DEFAULT_RAG_DIR = "index_default"
|
||||
app = FastAPI(title="LightRAG API", description="API for RAG operations")
|
||||
|
||||
# Configure working directory
|
||||
WORKING_DIR = os.environ.get('RAG_DIR', f'{DEFAULT_RAG_DIR}')
|
||||
WORKING_DIR = os.environ.get("RAG_DIR", f"{DEFAULT_RAG_DIR}")
|
||||
print(f"WORKING_DIR: {WORKING_DIR}")
|
||||
if not os.path.exists(WORKING_DIR):
|
||||
os.mkdir(WORKING_DIR)
|
||||
@@ -32,11 +32,12 @@ async def llm_model_func(
|
||||
prompt,
|
||||
system_prompt=system_prompt,
|
||||
history_messages=history_messages,
|
||||
api_key='YOUR_API_KEY',
|
||||
api_key="YOUR_API_KEY",
|
||||
base_url="YourURL/v1",
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
|
||||
# Embedding function
|
||||
|
||||
|
||||
@@ -44,10 +45,11 @@ async def embedding_func(texts: list[str]) -> np.ndarray:
|
||||
return await openai_embedding(
|
||||
texts,
|
||||
model="text-embedding-3-large",
|
||||
api_key='YOUR_API_KEY',
|
||||
api_key="YOUR_API_KEY",
|
||||
base_url="YourURL/v1",
|
||||
)
|
||||
|
||||
|
||||
# Initialize RAG instance
|
||||
rag = LightRAG(
|
||||
working_dir=WORKING_DIR,
|
||||
@@ -78,6 +80,7 @@ class Response(BaseModel):
|
||||
data: Optional[str] = None
|
||||
message: Optional[str] = None
|
||||
|
||||
|
||||
# API routes
|
||||
|
||||
|
||||
@@ -86,14 +89,9 @@ async def query_endpoint(request: QueryRequest):
|
||||
try:
|
||||
loop = asyncio.get_event_loop()
|
||||
result = await loop.run_in_executor(
|
||||
None,
|
||||
lambda: rag.query(
|
||||
request.query, param=QueryParam(mode=request.mode))
|
||||
)
|
||||
return Response(
|
||||
status="success",
|
||||
data=result
|
||||
None, lambda: rag.query(request.query, param=QueryParam(mode=request.mode))
|
||||
)
|
||||
return Response(status="success", data=result)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@@ -103,10 +101,7 @@ async def insert_endpoint(request: InsertRequest):
|
||||
try:
|
||||
loop = asyncio.get_event_loop()
|
||||
await loop.run_in_executor(None, lambda: rag.insert(request.text))
|
||||
return Response(
|
||||
status="success",
|
||||
message="Text inserted successfully"
|
||||
)
|
||||
return Response(status="success", message="Text inserted successfully")
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@@ -117,17 +112,16 @@ async def insert_file(request: InsertFileRequest):
|
||||
# Check if file exists
|
||||
if not os.path.exists(request.file_path):
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail=f"File not found: {request.file_path}"
|
||||
status_code=404, detail=f"File not found: {request.file_path}"
|
||||
)
|
||||
|
||||
# Read file content
|
||||
try:
|
||||
with open(request.file_path, 'r', encoding='utf-8') as f:
|
||||
with open(request.file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
except UnicodeDecodeError:
|
||||
# If UTF-8 decoding fails, try other encodings
|
||||
with open(request.file_path, 'r', encoding='gbk') as f:
|
||||
with open(request.file_path, "r", encoding="gbk") as f:
|
||||
content = f.read()
|
||||
|
||||
# Insert file content
|
||||
@@ -136,7 +130,7 @@ async def insert_file(request: InsertFileRequest):
|
||||
|
||||
return Response(
|
||||
status="success",
|
||||
message=f"File content from {request.file_path} inserted successfully"
|
||||
message=f"File content from {request.file_path} inserted successfully",
|
||||
)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
@@ -146,8 +140,10 @@ async def insert_file(request: InsertFileRequest):
|
||||
async def health_check():
|
||||
return {"status": "healthy"}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
|
||||
uvicorn.run(app, host="0.0.0.0", port=8020)
|
||||
|
||||
# Usage example
|
||||
|
Reference in New Issue
Block a user