Added docstrings to lightrag_server.py
Added docstrings to lightrag_server.py
This commit is contained in:
@@ -814,7 +814,23 @@ def create_app(args):
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@app.post("/documents/scan", dependencies=[Depends(optional_api_key)])
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async def scan_for_new_documents():
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"""Manually trigger scanning for new documents"""
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"""
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Manually trigger scanning for new documents in the directory managed by `doc_manager`.
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This endpoint facilitates manual initiation of a document scan to identify and index new files.
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It processes all newly detected files, attempts indexing each file, logs any errors that occur,
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and returns a summary of the operation.
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Returns:
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dict: A dictionary containing:
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- "status" (str): Indicates success or failure of the scanning process.
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- "indexed_count" (int): The number of successfully indexed documents.
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- "total_documents" (int): Total number of documents that have been indexed so far.
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Raises:
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HTTPException: If an error occurs during the document scanning process, a 500 status
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code is returned with details about the exception.
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"""
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try:
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new_files = doc_manager.scan_directory()
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indexed_count = 0
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@@ -836,7 +852,27 @@ def create_app(args):
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@app.post("/documents/upload", dependencies=[Depends(optional_api_key)])
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async def upload_to_input_dir(file: UploadFile = File(...)):
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"""Upload a file to the input directory"""
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"""
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Endpoint for uploading a file to the input directory and indexing it.
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This API endpoint accepts a file through an HTTP POST request, checks if the
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uploaded file is of a supported type, saves it in the specified input directory,
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indexes it for retrieval, and returns a success status with relevant details.
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Parameters:
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file (UploadFile): The file to be uploaded. It must have an allowed extension as per
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`doc_manager.supported_extensions`.
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Returns:
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dict: A dictionary containing the upload status ("success"),
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a message detailing the operation result, and
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the total number of indexed documents.
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Raises:
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HTTPException: If the file type is not supported, it raises a 400 Bad Request error.
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If any other exception occurs during the file handling or indexing,
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it raises a 500 Internal Server Error with details about the exception.
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"""
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try:
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if not doc_manager.is_supported_file(file.filename):
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raise HTTPException(
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@@ -863,6 +899,25 @@ def create_app(args):
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"/query", response_model=QueryResponse, dependencies=[Depends(optional_api_key)]
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)
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async def query_text(request: QueryRequest):
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"""
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Handle a POST request at the /query endpoint to process user queries using RAG capabilities.
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Parameters:
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request (QueryRequest): A Pydantic model containing the following fields:
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- query (str): The text of the user's query.
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- mode (ModeEnum): Optional. Specifies the mode of retrieval augmentation.
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- stream (bool): Optional. Determines if the response should be streamed.
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- only_need_context (bool): Optional. If true, returns only the context without further processing.
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Returns:
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QueryResponse: A Pydantic model containing the result of the query processing.
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If a string is returned (e.g., cache hit), it's directly returned.
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Otherwise, an async generator may be used to build the response.
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Raises:
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HTTPException: Raised when an error occurs during the request handling process,
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with status code 500 and detail containing the exception message.
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"""
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try:
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response = await rag.aquery(
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request.query,
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@@ -894,6 +949,16 @@ def create_app(args):
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@app.post("/query/stream", dependencies=[Depends(optional_api_key)])
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async def query_text_stream(request: QueryRequest):
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"""
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This endpoint performs a retrieval-augmented generation (RAG) query and streams the response.
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Args:
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request (QueryRequest): The request object containing the query parameters.
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optional_api_key (Optional[str], optional): An optional API key for authentication. Defaults to None.
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Returns:
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StreamingResponse: A streaming response containing the RAG query results.
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"""
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try:
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response = await rag.aquery( # Use aquery instead of query, and add await
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request.query,
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@@ -943,6 +1008,17 @@ def create_app(args):
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dependencies=[Depends(optional_api_key)],
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)
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async def insert_text(request: InsertTextRequest):
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"""
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Insert text into the Retrieval-Augmented Generation (RAG) system.
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This endpoint allows you to insert text data into the RAG system for later retrieval and use in generating responses.
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Args:
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request (InsertTextRequest): The request body containing the text to be inserted.
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Returns:
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InsertResponse: A response object containing the status of the operation, a message, and the number of documents inserted.
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"""
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try:
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await rag.ainsert(request.text)
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return InsertResponse(
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@@ -1176,6 +1252,15 @@ def create_app(args):
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dependencies=[Depends(optional_api_key)],
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)
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async def clear_documents():
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"""
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Clear all documents from the LightRAG system.
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This endpoint deletes all text chunks, entities vector database, and relationships vector database,
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effectively clearing all documents from the LightRAG system.
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Returns:
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InsertResponse: A response object containing the status, message, and the new document count (0 in this case).
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"""
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try:
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rag.text_chunks = []
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rag.entities_vdb = None
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@@ -1188,7 +1273,9 @@ def create_app(args):
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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# -------------------------------------------------
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# Ollama compatible API endpoints
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# -------------------------------------------------
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@app.get("/api/version")
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async def get_version():
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"""Get Ollama version information"""
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