gmakstutis/LightRAG
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Update log messages

Browse source
This commit is contained in:
yangdx 2025-07-24 01:31:49 +08:00
parent 02f79508e0
commit 42710221f5
1 changed files with 11 additions and 22 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

33
lightrag/operate.py
View file

@ -2211,16 +2211,7 @@ async def _build_query_context(
merged_chunks = []
seen_chunk_ids = set()
max_len = max(len(vector_chunks), len(entity_chunks), len(relation_chunks))
logger.debug(
f"vector_chunks chunk_ids: {[chunk.get('chunk_id') or chunk.get('id') for chunk in vector_chunks]}"
)
logger.debug(
f"entity_chunks chunk_ids: {[chunk.get('chunk_id') or chunk.get('id') for chunk in entity_chunks]}"
)
logger.debug(
f"relation_chunks chunk_ids: {[chunk.get('chunk_id') or chunk.get('id') for chunk in relation_chunks]}"
)
origin_len = len(vector_chunks) + len(entity_chunks) + len(relation_chunks)
for i in range(max_len):
# Add from vector chunks first (Naive mode)
@ -2262,7 +2253,9 @@ async def _build_query_context(
}
)
logger.debug(f"Round-robin merged: {len(merged_chunks)} total chunks")
logger.debug(
f"Round-robin merged total chunks from {origin_len} to {len(merged_chunks)}"
)
# Apply token processing to merged chunks
text_units_context = []
@ -2534,8 +2527,11 @@ async def _find_most_related_text_unit_from_entities(
entities_with_chunks, max_related_chunks, min_related_chunks=1
)
logger.debug(
f"Found {len(selected_chunk_ids)} entity-related chunks using linear gradient weighted polling"
)
if not selected_chunk_ids:
logger.warning("No chunks selected by linear gradient weighted polling")
return []
# Step 5: Batch retrieve chunk data
@ -2553,9 +2549,6 @@ async def _find_most_related_text_unit_from_entities(
chunk_data_copy["chunk_id"] = chunk_id # Add chunk_id for deduplication
result_chunks.append(chunk_data_copy)
logger.debug(
f"Found {len(result_chunks)} entity-related chunks using linear gradient weighted polling"
)
return result_chunks
@ -2787,6 +2780,9 @@ async def _find_related_text_unit_from_relationships(
relations_with_chunks, max_related_chunks, min_related_chunks=1
)
logger.debug(
f"Found {len(selected_chunk_ids)} relationship-related chunks using linear gradient weighted polling"
)
logger.info(
f"KG related chunks: {len(entity_chunks)} from entitys, {len(selected_chunk_ids)} from relations"
)
@ -2834,9 +2830,6 @@ async def _find_related_text_unit_from_relationships(
chunk_data_copy["chunk_id"] = chunk_id # Add chunk_id for deduplication
result_chunks.append(chunk_data_copy)
logger.debug(
f"Found {len(result_chunks)} relationship-related chunks using linear gradient weighted polling"
)
return result_chunks
@ -3255,10 +3248,6 @@ async def apply_rerank_if_enabled(
return retrieved_docs
try:
logger.debug(
f"Applying rerank to {len(retrieved_docs)} documents, returning top {top_n}"
)
# Apply reranking - let rerank_model_func handle top_k internally
reranked_docs = await rerank_func(
query=query,