Unified vector retrieval logic for mix and naive queries
This commit is contained in:
yangdx
@@ -1198,66 +1198,10 @@ async def mix_kg_vector_query(
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traceback.print_exc()
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return None
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async def get_vector_context():
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try:
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# Reduce top_k for vector search in hybrid mode since we have structured information from KG
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mix_topk = min(10, query_param.top_k)
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results = await chunks_vdb.query(
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query, top_k=mix_topk, ids=query_param.ids
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)
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if not results:
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return None
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valid_chunks = []
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for result in results:
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if "content" in result:
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# Directly use content from chunks_vdb.query result
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chunk_with_time = {
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"content": result["content"],
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"created_at": result.get("created_at", None),
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"file_path": result.get("file_path", None),
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}
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valid_chunks.append(chunk_with_time)
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if not valid_chunks:
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return None
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maybe_trun_chunks = truncate_list_by_token_size(
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valid_chunks,
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key=lambda x: x["content"],
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max_token_size=query_param.max_token_for_text_unit,
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tokenizer=tokenizer,
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)
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logger.debug(
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f"Truncate chunks from {len(valid_chunks)} to {len(maybe_trun_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
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)
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logger.info(
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f"Naive query: {len(maybe_trun_chunks)} chunks, top_k: {mix_topk}"
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)
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if not maybe_trun_chunks:
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return None
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# Include time information in content
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formatted_chunks = []
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for c in maybe_trun_chunks:
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chunk_text = "File path: " + c["file_path"] + "\r\n\r\n" + c["content"]
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if c["created_at"]:
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chunk_text = f"[Created at: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(c['created_at']))}]\r\n\r\n{chunk_text}"
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formatted_chunks.append(chunk_text)
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logger.debug(
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f"Truncate chunks from {len(valid_chunks)} to {len(formatted_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
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)
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return "\r\n\r\n--New Chunk--\r\n\r\n".join(formatted_chunks)
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except Exception as e:
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logger.error(f"Error in get_vector_context: {e}")
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return None
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# 3. Execute both retrievals in parallel
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kg_context, vector_context = await asyncio.gather(
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get_kg_context(), get_vector_context()
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get_kg_context(), _get_vector_context(query, chunks_vdb, query_param, tokenizer)
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)
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# 4. Merge contexts
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@@ -2038,44 +1982,12 @@ async def naive_query(
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if cached_response is not None:
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return cached_response
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results = await chunks_vdb.query(
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query, top_k=query_param.top_k, ids=query_param.ids
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)
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if not len(results):
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return PROMPTS["fail_response"]
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valid_chunks = [result for result in results if "content" in result]
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if not valid_chunks:
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logger.warning("No valid chunks found after filtering")
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return PROMPTS["fail_response"]
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tokenizer: Tokenizer = global_config["tokenizer"]
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maybe_trun_chunks = truncate_list_by_token_size(
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valid_chunks,
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key=lambda x: x["content"],
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max_token_size=query_param.max_token_for_text_unit,
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tokenizer=tokenizer,
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)
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if not maybe_trun_chunks:
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logger.warning("No chunks left after truncation")
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section = await _get_vector_context(query, chunks_vdb, query_param, tokenizer)
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if section is None:
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return PROMPTS["fail_response"]
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logger.debug(
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f"Truncate chunks from {len(valid_chunks)} to {len(maybe_trun_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
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)
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logger.info(
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f"Naive query: {len(maybe_trun_chunks)} chunks, top_k: {query_param.top_k}"
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)
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section = "\r\n\r\n--New Chunk--\r\n\r\n".join(
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[
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"File path: " + c["file_path"] + "\r\n\r\n" + c["content"]
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for c in maybe_trun_chunks
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]
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)
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if query_param.only_need_context:
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return section
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@@ -2287,6 +2199,84 @@ async def kg_query_with_keywords(
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return response
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async def _get_vector_context(
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query: str,
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chunks_vdb: BaseVectorStorage,
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query_param: QueryParam,
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tokenizer: Tokenizer,
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) -> str | None:
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"""
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Retrieve vector context from the vector database.
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This function performs vector search to find relevant text chunks for a query,
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formats them with file path and creation time information, and truncates
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the results to fit within token limits.
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Args:
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query: The query string to search for
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chunks_vdb: Vector database containing document chunks
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query_param: Query parameters including top_k and ids
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tokenizer: Tokenizer for counting tokens
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Returns:
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Formatted string containing relevant text chunks, or None if no results found
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"""
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try:
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# Reduce top_k for vector search in hybrid mode since we have structured information from KG
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mix_topk = min(10, query_param.top_k) if hasattr(query_param, 'mode') and query_param.mode == 'mix' else query_param.top_k
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results = await chunks_vdb.query(
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query, top_k=mix_topk, ids=query_param.ids
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)
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if not results:
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return None
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valid_chunks = []
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for result in results:
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if "content" in result:
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# Directly use content from chunks_vdb.query result
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chunk_with_time = {
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"content": result["content"],
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"created_at": result.get("created_at", None),
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"file_path": result.get("file_path", None),
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}
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valid_chunks.append(chunk_with_time)
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if not valid_chunks:
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return None
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maybe_trun_chunks = truncate_list_by_token_size(
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valid_chunks,
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key=lambda x: x["content"],
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max_token_size=query_param.max_token_for_text_unit,
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tokenizer=tokenizer,
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)
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logger.debug(
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f"Truncate chunks from {len(valid_chunks)} to {len(maybe_trun_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
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)
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logger.info(
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f"Vector query: {len(maybe_trun_chunks)} chunks, top_k: {mix_topk}"
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)
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if not maybe_trun_chunks:
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return None
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# Include time information in content
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formatted_chunks = []
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for c in maybe_trun_chunks:
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chunk_text = "File path: " + c["file_path"] + "\r\n\r\n" + c["content"]
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if c["created_at"]:
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chunk_text = f"[Created at: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(c['created_at']))}]\r\n\r\n{chunk_text}"
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formatted_chunks.append(chunk_text)
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logger.debug(
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f"Truncate chunks from {len(valid_chunks)} to {len(formatted_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
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)
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return "\r\n\r\n--New Chunk--\r\n\r\n".join(formatted_chunks)
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except Exception as e:
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logger.error(f"Error in _get_vector_context: {e}")
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return None
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async def query_with_keywords(
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query: str,
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prompt: str,
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