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Fix linting

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This commit is contained in:
yangdx
2025-05-07 03:57:14 +08:00
parent 910a7a8936
commit 2485bfe53c
1 changed files with 11 additions and 11 deletions
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22
lightrag/operate.py
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@@ -1198,7 +1198,6 @@ async def mix_kg_vector_query(
traceback.print_exc() traceback.print_exc()
return None return None
# 3. Execute both retrievals in parallel # 3. Execute both retrievals in parallel
kg_context, vector_context = await asyncio.gather( kg_context, vector_context = await asyncio.gather(
get_kg_context(), _get_vector_context(query, chunks_vdb, query_param, tokenizer) get_kg_context(), _get_vector_context(query, chunks_vdb, query_param, tokenizer)
@@ -1984,7 +1983,7 @@ async def naive_query(
tokenizer: Tokenizer = global_config["tokenizer"] tokenizer: Tokenizer = global_config["tokenizer"]
section = await _get_vector_context(query, chunks_vdb, query_param, tokenizer) section = await _get_vector_context(query, chunks_vdb, query_param, tokenizer)
if section is None: if section is None:
return PROMPTS["fail_response"] return PROMPTS["fail_response"]
@@ -2207,26 +2206,28 @@ async def _get_vector_context(
) -> str | None: ) -> str | None:
""" """
Retrieve vector context from the vector database. Retrieve vector context from the vector database.
This function performs vector search to find relevant text chunks for a query, This function performs vector search to find relevant text chunks for a query,
formats them with file path and creation time information, and truncates formats them with file path and creation time information, and truncates
the results to fit within token limits. the results to fit within token limits.
Args: Args:
query: The query string to search for query: The query string to search for
chunks_vdb: Vector database containing document chunks chunks_vdb: Vector database containing document chunks
query_param: Query parameters including top_k and ids query_param: Query parameters including top_k and ids
tokenizer: Tokenizer for counting tokens tokenizer: Tokenizer for counting tokens
Returns: Returns:
Formatted string containing relevant text chunks, or None if no results found Formatted string containing relevant text chunks, or None if no results found
""" """
try: try:
# Reduce top_k for vector search in hybrid mode since we have structured information from KG # Reduce top_k for vector search in hybrid mode since we have structured information from KG
mix_topk = min(10, query_param.top_k) if hasattr(query_param, 'mode') and query_param.mode == 'mix' else query_param.top_k mix_topk = (
results = await chunks_vdb.query( min(10, query_param.top_k)
query, top_k=mix_topk, ids=query_param.ids if hasattr(query_param, "mode") and query_param.mode == "mix"
else query_param.top_k
) )
results = await chunks_vdb.query(query, top_k=mix_topk, ids=query_param.ids)
if not results: if not results:
return None return None
@@ -2254,9 +2255,7 @@ async def _get_vector_context(
logger.debug( logger.debug(
f"Truncate chunks from {len(valid_chunks)} to {len(maybe_trun_chunks)} (max tokens:{query_param.max_token_for_text_unit})" f"Truncate chunks from {len(valid_chunks)} to {len(maybe_trun_chunks)} (max tokens:{query_param.max_token_for_text_unit})"
) )
logger.info( logger.info(f"Vector query: {len(maybe_trun_chunks)} chunks, top_k: {mix_topk}")
f"Vector query: {len(maybe_trun_chunks)} chunks, top_k: {mix_topk}"
)
if not maybe_trun_chunks: if not maybe_trun_chunks:
return None return None
@@ -2277,6 +2276,7 @@ async def _get_vector_context(
logger.error(f"Error in _get_vector_context: {e}") logger.error(f"Error in _get_vector_context: {e}")
return None return None
async def query_with_keywords( async def query_with_keywords(
query: str, query: str,
prompt: str, prompt: str,