diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py index 191a5acd..dff637f6 100644 --- a/lightrag/lightrag.py +++ b/lightrag/lightrag.py @@ -1699,10 +1699,16 @@ class LightRAG: semaphore: asyncio.Semaphore, ) -> None: """Process single document""" + # Initialize variables at the start to prevent UnboundLocalError in error handling + file_path = "unknown_source" + current_file_number = 0 file_extraction_stage_ok = False + processing_start_time = int(time.time()) + first_stage_tasks = [] + entity_relation_task = None + async with semaphore: nonlocal processed_count - current_file_number = 0 # Initialize to prevent UnboundLocalError in error handling first_stage_tasks = [] entity_relation_task = None @@ -1833,16 +1839,29 @@ class LightRAG: file_extraction_stage_ok = True except Exception as e: - # Log error and update pipeline status - logger.error(traceback.format_exc()) - error_msg = f"Failed to extract document {current_file_number}/{total_files}: {file_path}" - logger.error(error_msg) - async with pipeline_status_lock: - pipeline_status["latest_message"] = error_msg - pipeline_status["history_messages"].append( - traceback.format_exc() - ) - pipeline_status["history_messages"].append(error_msg) + # Check if this is a user cancellation + if isinstance(e, PipelineCancelledException): + # User cancellation - log brief message only, no traceback + error_msg = f"User cancelled {current_file_number}/{total_files}: {file_path}" + logger.warning(error_msg) + async with pipeline_status_lock: + pipeline_status["latest_message"] = error_msg + pipeline_status["history_messages"].append( + error_msg + ) + else: + # Other exceptions - log with traceback + logger.error(traceback.format_exc()) + error_msg = f"Failed to extract document {current_file_number}/{total_files}: {file_path}" + logger.error(error_msg) + async with pipeline_status_lock: + pipeline_status["latest_message"] = error_msg + pipeline_status["history_messages"].append( + traceback.format_exc() + ) + pipeline_status["history_messages"].append( + error_msg + ) # Cancel tasks that are not yet completed all_tasks = first_stage_tasks + ( @@ -1951,18 +1970,29 @@ class LightRAG: ) except Exception as e: - # Log error and update pipeline status - logger.error(traceback.format_exc()) - error_msg = f"Merging stage failed in document {current_file_number}/{total_files}: {file_path}" - logger.error(error_msg) - async with pipeline_status_lock: - pipeline_status["latest_message"] = error_msg - pipeline_status["history_messages"].append( - traceback.format_exc() - ) - pipeline_status["history_messages"].append( - error_msg - ) + # Check if this is a user cancellation + if isinstance(e, PipelineCancelledException): + # User cancellation - log brief message only, no traceback + error_msg = f"User cancelled during merge {current_file_number}/{total_files}: {file_path}" + logger.warning(error_msg) + async with pipeline_status_lock: + pipeline_status["latest_message"] = error_msg + pipeline_status["history_messages"].append( + error_msg + ) + else: + # Other exceptions - log with traceback + logger.error(traceback.format_exc()) + error_msg = f"Merging stage failed in document {current_file_number}/{total_files}: {file_path}" + logger.error(error_msg) + async with pipeline_status_lock: + pipeline_status["latest_message"] = error_msg + pipeline_status["history_messages"].append( + traceback.format_exc() + ) + pipeline_status["history_messages"].append( + error_msg + ) # Persistent llm cache if self.llm_response_cache: diff --git a/lightrag/operate.py b/lightrag/operate.py index eac58349..496c000c 100644 --- a/lightrag/operate.py +++ b/lightrag/operate.py @@ -1,5 +1,6 @@ from __future__ import annotations from functools import partial +from pathlib import Path import asyncio import json @@ -58,6 +59,8 @@ from lightrag.constants import ( SOURCE_IDS_LIMIT_METHOD_KEEP, SOURCE_IDS_LIMIT_METHOD_FIFO, DEFAULT_FILE_PATH_MORE_PLACEHOLDER, + DEFAULT_MAX_FILE_PATHS, + DEFAULT_ENTITY_NAME_MAX_LENGTH, ) from lightrag.kg.shared_storage import get_storage_keyed_lock import time @@ -66,7 +69,28 @@ from dotenv import load_dotenv # use the .env that is inside the current folder # allows to use different .env file for each lightrag instance # the OS environment variables take precedence over the .env file -load_dotenv(dotenv_path=".env", override=False) +load_dotenv(dotenv_path=Path(__file__).resolve().parent / ".env", override=False) + + +def _truncate_entity_identifier( + identifier: str, limit: int, chunk_key: str, identifier_role: str +) -> str: + """Truncate entity identifiers that exceed the configured length limit.""" + + if len(identifier) <= limit: + return identifier + + display_value = identifier[:limit] + preview = identifier[:20] # Show first 20 characters as preview + logger.warning( + "%s: %s len %d > %d chars (Name: '%s...')", + chunk_key, + identifier_role, + len(identifier), + limit, + preview, + ) + return display_value def chunking_by_token_size( @@ -952,7 +976,14 @@ async def _process_extraction_result( record_attributes, chunk_key, timestamp, file_path ) if entity_data is not None: - maybe_nodes[entity_data["entity_name"]].append(entity_data) + truncated_name = _truncate_entity_identifier( + entity_data["entity_name"], + DEFAULT_ENTITY_NAME_MAX_LENGTH, + chunk_key, + "Entity name", + ) + entity_data["entity_name"] = truncated_name + maybe_nodes[truncated_name].append(entity_data) continue # Try to parse as relationship @@ -960,9 +991,21 @@ async def _process_extraction_result( record_attributes, chunk_key, timestamp, file_path ) if relationship_data is not None: - maybe_edges[ - (relationship_data["src_id"], relationship_data["tgt_id"]) - ].append(relationship_data) + truncated_source = _truncate_entity_identifier( + relationship_data["src_id"], + DEFAULT_ENTITY_NAME_MAX_LENGTH, + chunk_key, + "Relation entity", + ) + truncated_target = _truncate_entity_identifier( + relationship_data["tgt_id"], + DEFAULT_ENTITY_NAME_MAX_LENGTH, + chunk_key, + "Relation entity", + ) + relationship_data["src_id"] = truncated_source + relationship_data["tgt_id"] = truncated_target + maybe_edges[(truncated_source, truncated_target)].append(relationship_data) return dict(maybe_nodes), dict(maybe_edges) @@ -1026,7 +1069,7 @@ async def _rebuild_single_entity( async def _update_entity_storage( final_description: str, entity_type: str, - file_paths: set[str], + file_paths: list[str], source_chunk_ids: list[str], truncation_info: str = "", ): @@ -1189,14 +1232,12 @@ async def _rebuild_single_entity( file_paths_list = file_paths_list[:max_file_paths] file_paths_list.append( - f"...{file_path_placeholder}({limit_method}:{max_file_paths}/{original_count})..." + f"...{file_path_placeholder}...({limit_method} {max_file_paths}/{original_count})" ) logger.info( f"Limited `{entity_name}`: file_path {original_count} -> {max_file_paths} ({limit_method})" ) - file_paths = set(file_paths_list) - # Remove duplicates while preserving order description_list = list(dict.fromkeys(descriptions)) entity_types = list(dict.fromkeys(entity_types)) @@ -1223,7 +1264,7 @@ async def _rebuild_single_entity( if len(limited_chunk_ids) < len(normalized_chunk_ids): truncation_info = ( - f"{limit_method}:{len(limited_chunk_ids)}/{len(normalized_chunk_ids)}" + f"{limit_method} {len(limited_chunk_ids)}/{len(normalized_chunk_ids)}" ) else: truncation_info = "" @@ -1231,7 +1272,7 @@ async def _rebuild_single_entity( await _update_entity_storage( final_description, entity_type, - file_paths, + file_paths_list, limited_chunk_ids, truncation_info, ) @@ -1348,14 +1389,12 @@ async def _rebuild_single_relationship( file_paths_list = file_paths_list[:max_file_paths] file_paths_list.append( - f"...{file_path_placeholder}({limit_method}:{max_file_paths}/{original_count})..." + f"...{file_path_placeholder}...({limit_method} {max_file_paths}/{original_count})" ) logger.info( f"Limited `{src}`~`{tgt}`: file_path {original_count} -> {max_file_paths} ({limit_method})" ) - file_paths = set(file_paths_list) - # Remove duplicates while preserving order description_list = list(dict.fromkeys(descriptions)) keywords = list(dict.fromkeys(keywords)) @@ -1384,7 +1423,7 @@ async def _rebuild_single_relationship( if len(limited_chunk_ids) < len(normalized_chunk_ids): truncation_info = ( - f"{limit_method}:{len(limited_chunk_ids)}/{len(normalized_chunk_ids)}" + f"{limit_method} {len(limited_chunk_ids)}/{len(normalized_chunk_ids)}" ) else: truncation_info = "" @@ -1398,8 +1437,8 @@ async def _rebuild_single_relationship( "keywords": combined_keywords, "weight": weight, "source_id": GRAPH_FIELD_SEP.join(limited_chunk_ids), - "file_path": GRAPH_FIELD_SEP.join([fp for fp in file_paths if fp]) - if file_paths + "file_path": GRAPH_FIELD_SEP.join([fp for fp in file_paths_list if fp]) + if file_paths_list else current_relationship.get("file_path", "unknown_source"), "truncate": truncation_info, } @@ -1484,6 +1523,7 @@ async def _merge_nodes_then_upsert( already_description = [] already_file_paths = [] + # 1. Get existing node data from knowledge graph already_node = await knowledge_graph_inst.get_node(entity_name) if already_node: already_entity_types.append(already_node["entity_type"]) @@ -1491,14 +1531,6 @@ async def _merge_nodes_then_upsert( already_file_paths.extend(already_node["file_path"].split(GRAPH_FIELD_SEP)) already_description.extend(already_node["description"].split(GRAPH_FIELD_SEP)) - entity_type = sorted( - Counter( - [dp["entity_type"] for dp in nodes_data] + already_entity_types - ).items(), - key=lambda x: x[1], - reverse=True, - )[0][0] # Get the entity type with the highest count - new_source_ids = [dp["source_id"] for dp in nodes_data if dp.get("source_id")] existing_full_source_ids = [] @@ -1514,6 +1546,7 @@ async def _merge_nodes_then_upsert( chunk_id for chunk_id in already_source_ids if chunk_id ] + # 2. Merging new source ids with existing ones full_source_ids = merge_source_ids(existing_full_source_ids, new_source_ids) if entity_chunks_storage is not None and full_source_ids: @@ -1526,6 +1559,7 @@ async def _merge_nodes_then_upsert( } ) + # 3. Finalize source_id by applying source ids limit limit_method = global_config.get("source_ids_limit_method") max_source_limit = global_config.get("max_source_ids_per_entity") source_ids = apply_source_ids_limit( @@ -1535,7 +1569,7 @@ async def _merge_nodes_then_upsert( identifier=f"`{entity_name}`", ) - # Only apply filtering in KEEP(ignore new) mode + # 4. Only keep nodes not filter by apply_source_ids_limit if limit_method is KEEP if limit_method == SOURCE_IDS_LIMIT_METHOD_KEEP: allowed_source_ids = set(source_ids) filtered_nodes = [] @@ -1550,18 +1584,40 @@ async def _merge_nodes_then_upsert( continue filtered_nodes.append(dp) nodes_data = filtered_nodes - else: - # In FIFO mode, keep all node descriptions - truncation happens at source_ids level only + else: # In FIFO mode, keep all nodes - truncation happens at source_ids level only nodes_data = list(nodes_data) - skip_summary_due_to_limit = ( + # 5. Check if we need to skip summary due to source_ids limit + if ( limit_method == SOURCE_IDS_LIMIT_METHOD_KEEP and len(existing_full_source_ids) >= max_source_limit and not nodes_data - and already_description - ) + ): + if already_node: + logger.info( + f"Skipped `{entity_name}`: KEEP old chunks {already_source_ids}/{len(full_source_ids)}" + ) + existing_node_data = dict(already_node) + return existing_node_data + else: + logger.error(f"Internal Error: already_node missing for `{entity_name}`") + raise ValueError( + f"Internal Error: already_node missing for `{entity_name}`" + ) - # Deduplicate by description, keeping first occurrence + # 6.1 Finalize source_id + source_id = GRAPH_FIELD_SEP.join(source_ids) + + # 6.2 Finalize entity type by highest count + entity_type = sorted( + Counter( + [dp["entity_type"] for dp in nodes_data] + already_entity_types + ).items(), + key=lambda x: x[1], + reverse=True, + )[0][0] + + # 7. Deduplicate nodes by description, keeping first occurrence in the same document unique_nodes = {} for dp in nodes_data: desc = dp.get("description") @@ -1570,154 +1626,128 @@ async def _merge_nodes_then_upsert( if desc not in unique_nodes: unique_nodes[desc] = dp - # Sort description by timestamp, then by description length (largest to smallest) when timestamps are the same + # Sort description by timestamp, then by description length when timestamps are the same sorted_nodes = sorted( unique_nodes.values(), key=lambda x: (x.get("timestamp", 0), -len(x.get("description", ""))), ) sorted_descriptions = [dp["description"] for dp in sorted_nodes] - truncation_info = "" - dd_message = "" - has_placeholder = False # Initialize to track placeholder in file paths - # Combine already_description with sorted new sorted descriptions description_list = already_description + sorted_descriptions - num_fragment = len(description_list) - already_fragment = len(already_description) - deduplicated_num = already_fragment + len(nodes_data) - num_fragment - if deduplicated_num > 0: - dd_message = f"dd:{deduplicated_num}" - - if skip_summary_due_to_limit: - logger.info(f"Skipped `{entity_name}`: KEEP old chunks") - description = ( - already_node.get("description", "(no description)") - if already_node - else "(no description)" - ) - existing_node_data = dict(already_node or {}) - if not existing_node_data: - existing_node_data = { - "entity_id": entity_name, - "entity_type": entity_type, - "description": description, - "source_id": GRAPH_FIELD_SEP.join(existing_full_source_ids), - "file_path": GRAPH_FIELD_SEP.join(already_file_paths), - "created_at": int(time.time()), - "truncate": "", - } - existing_node_data["entity_name"] = entity_name - return existing_node_data - elif num_fragment > 0: - # Get summary and LLM usage status - description, llm_was_used = await _handle_entity_relation_summary( - "Entity", - entity_name, - description_list, - GRAPH_FIELD_SEP, - global_config, - llm_response_cache, - ) - - # Log based on actual LLM usage - if llm_was_used: - status_message = f"LLMmrg: `{entity_name}` | {already_fragment}+{num_fragment - already_fragment}" - else: - status_message = f"Merged: `{entity_name}` | {already_fragment}+{num_fragment - already_fragment}" - - # Add truncation info from apply_source_ids_limit if truncation occurred - if len(source_ids) < len(full_source_ids): - # Add + sign if has_placeholder is True, indicating actual file count is higher - full_source_count_str = ( - f"{len(full_source_ids)}+" - if has_placeholder - else str(len(full_source_ids)) - ) - truncation_info = ( - f"{limit_method}:{len(source_ids)}/{full_source_count_str}" - ) - - if dd_message or truncation_info: - status_message += ( - f" ({', '.join(filter(None, [truncation_info, dd_message]))})" - ) - - if already_fragment > 0 or llm_was_used: - logger.info(status_message) - if pipeline_status is not None and pipeline_status_lock is not None: - async with pipeline_status_lock: - pipeline_status["latest_message"] = status_message - pipeline_status["history_messages"].append(status_message) - else: - logger.debug(status_message) - - else: + if not description_list: logger.error(f"Entity {entity_name} has no description") - description = "(no description)" + raise ValueError(f"Entity {entity_name} has no description") - source_id = GRAPH_FIELD_SEP.join(source_ids) + # Check for cancellation before LLM summary + if pipeline_status is not None and pipeline_status_lock is not None: + async with pipeline_status_lock: + if pipeline_status.get("cancellation_requested", False): + raise PipelineCancelledException("User cancelled during entity summary") - # Build file_path with count limit - if skip_summary_due_to_limit: - # Skip limit, keep original file_path - file_path = GRAPH_FIELD_SEP.join(fp for fp in already_file_paths if fp) - else: - # Collect and apply limit - file_paths_list = [] - seen_paths = set() - has_placeholder = False # Track if already_file_paths contains placeholder + # 8. Get summary description an LLM usage status + description, llm_was_used = await _handle_entity_relation_summary( + "Entity", + entity_name, + description_list, + GRAPH_FIELD_SEP, + global_config, + llm_response_cache, + ) - # Get placeholder to filter it out + # 9. Build file_path within MAX_FILE_PATHS + file_paths_list = [] + seen_paths = set() + has_placeholder = False # Indicating file_path has been truncated before + + max_file_paths = global_config.get("max_file_paths", DEFAULT_MAX_FILE_PATHS) + file_path_placeholder = global_config.get( + "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER + ) + + # Collect from already_file_paths, excluding placeholder + for fp in already_file_paths: + if fp and fp.startswith(f"...{file_path_placeholder}"): # Skip placeholders + has_placeholder = True + continue + if fp and fp not in seen_paths: + file_paths_list.append(fp) + seen_paths.add(fp) + + # Collect from new data + for dp in nodes_data: + file_path_item = dp.get("file_path") + if file_path_item and file_path_item not in seen_paths: + file_paths_list.append(file_path_item) + seen_paths.add(file_path_item) + + # Apply count limit + if len(file_paths_list) > max_file_paths: + limit_method = global_config.get( + "source_ids_limit_method", SOURCE_IDS_LIMIT_METHOD_KEEP + ) file_path_placeholder = global_config.get( "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER ) + # Add + sign to indicate actual file count is higher + original_count_str = ( + f"{len(file_paths_list)}+" if has_placeholder else str(len(file_paths_list)) + ) - # Collect from already_file_paths, excluding placeholder - for fp in already_file_paths: - # Check if this is a placeholder record - if fp and fp.startswith(f"...{file_path_placeholder}"): # Skip placeholders - has_placeholder = True - continue - if fp and fp not in seen_paths: - file_paths_list.append(fp) - seen_paths.add(fp) + if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: + # FIFO: keep tail (newest), discard head + file_paths_list = file_paths_list[-max_file_paths:] + file_paths_list.append(f"...{file_path_placeholder}...(FIFO)") + else: + # KEEP: keep head (earliest), discard tail + file_paths_list = file_paths_list[:max_file_paths] + file_paths_list.append(f"...{file_path_placeholder}...(KEEP Old)") - # Collect from new data - for dp in nodes_data: - file_path_item = dp.get("file_path") - if file_path_item and file_path_item not in seen_paths: - file_paths_list.append(file_path_item) - seen_paths.add(file_path_item) + logger.info( + f"Limited `{entity_name}`: file_path {original_count_str} -> {max_file_paths} ({limit_method})" + ) + # Finalize file_path + file_path = GRAPH_FIELD_SEP.join(file_paths_list) - # Apply count limit - max_file_paths = global_config.get("max_file_paths") + # 10.Log based on actual LLM usage + num_fragment = len(description_list) + already_fragment = len(already_description) + if llm_was_used: + status_message = f"LLMmrg: `{entity_name}` | {already_fragment}+{num_fragment - already_fragment}" + else: + status_message = f"Merged: `{entity_name}` | {already_fragment}+{num_fragment - already_fragment}" - if len(file_paths_list) > max_file_paths: - limit_method = global_config.get( - "source_ids_limit_method", SOURCE_IDS_LIMIT_METHOD_KEEP - ) - file_path_placeholder = global_config.get( - "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER - ) - original_count = len(file_paths_list) + truncation_info = truncation_info_log = "" + if len(source_ids) < len(full_source_ids): + # Add truncation info from apply_source_ids_limit if truncation occurred + truncation_info_log = f"{limit_method} {len(source_ids)}/{len(full_source_ids)}" + if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: + truncation_info = truncation_info_log + else: + truncation_info = "KEEP Old" - if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: - # FIFO: keep tail (newest), discard head - file_paths_list = file_paths_list[-max_file_paths:] - else: - # KEEP: keep head (earliest), discard tail - file_paths_list = file_paths_list[:max_file_paths] + deduplicated_num = already_fragment + len(nodes_data) - num_fragment + dd_message = "" + if deduplicated_num > 0: + # Duplicated description detected across multiple trucks for the same entity + dd_message = f"dd {deduplicated_num}" - file_paths_list.append( - f"...{file_path_placeholder}({limit_method}:{max_file_paths}/{original_count})..." - ) - logger.info( - f"Limited `{entity_name}`: file_path {original_count} -> {max_file_paths} ({limit_method})" - ) + if dd_message or truncation_info_log: + status_message += ( + f" ({', '.join(filter(None, [truncation_info_log, dd_message]))})" + ) - file_path = GRAPH_FIELD_SEP.join(file_paths_list) + # Add message to pipeline satus when merge happens + if already_fragment > 0 or llm_was_used: + logger.info(status_message) + if pipeline_status is not None and pipeline_status_lock is not None: + async with pipeline_status_lock: + pipeline_status["latest_message"] = status_message + pipeline_status["history_messages"].append(status_message) + else: + logger.debug(status_message) + # 11. Update both graph and vector db node_data = dict( entity_id=entity_name, entity_type=entity_type, @@ -1778,6 +1808,7 @@ async def _merge_edges_then_upsert( already_keywords = [] already_file_paths = [] + # 1. Get existing edge data from graph storage if await knowledge_graph_inst.has_edge(src_id, tgt_id): already_edge = await knowledge_graph_inst.get_edge(src_id, tgt_id) # Handle the case where get_edge returns None or missing fields @@ -1827,6 +1858,7 @@ async def _merge_edges_then_upsert( chunk_id for chunk_id in already_source_ids if chunk_id ] + # 2. Merge new source ids with existing ones full_source_ids = merge_source_ids(existing_full_source_ids, new_source_ids) if relation_chunks_storage is not None and full_source_ids: @@ -1839,6 +1871,7 @@ async def _merge_edges_then_upsert( } ) + # 3. Finalize source_id by applying source ids limit limit_method = global_config.get("source_ids_limit_method") max_source_limit = global_config.get("max_source_ids_per_relation") source_ids = apply_source_ids_limit( @@ -1851,7 +1884,7 @@ async def _merge_edges_then_upsert( global_config.get("source_ids_limit_method") or SOURCE_IDS_LIMIT_METHOD_KEEP ) - # Only apply filtering in KEEP(ignore new) mode + # 4. Only keep edges with source_id in the final source_ids list if in KEEP mode if limit_method == SOURCE_IDS_LIMIT_METHOD_KEEP: allowed_source_ids = set(source_ids) filtered_edges = [] @@ -1866,21 +1899,51 @@ async def _merge_edges_then_upsert( continue filtered_edges.append(dp) edges_data = filtered_edges - else: - # In FIFO mode, keep all edge descriptions - truncation happens at source_ids level only + else: # In FIFO mode, keep all edges - truncation happens at source_ids level only edges_data = list(edges_data) - skip_summary_due_to_limit = ( + # 5. Check if we need to skip summary due to source_ids limit + if ( limit_method == SOURCE_IDS_LIMIT_METHOD_KEEP and len(existing_full_source_ids) >= max_source_limit and not edges_data - and already_description - ) + ): + if already_edge: + logger.info( + f"Skipped `{src_id}`~`{tgt_id}`: KEEP old chunks {already_source_ids}/{len(full_source_ids)}" + ) + existing_edge_data = dict(already_edge) + return existing_edge_data + else: + logger.error( + f"Internal Error: already_node missing for `{src_id}`~`{tgt_id}`" + ) + raise ValueError( + f"Internal Error: already_node missing for `{src_id}`~`{tgt_id}`" + ) - # Process edges_data with None checks + # 6.1 Finalize source_id + source_id = GRAPH_FIELD_SEP.join(source_ids) + + # 6.2 Finalize weight by summing new edges and existing weights weight = sum([dp["weight"] for dp in edges_data] + already_weights) - # Deduplicate by description, keeping first occurrence + # 6.2 Finalize keywords by merging existing and new keywords + all_keywords = set() + # Process already_keywords (which are comma-separated) + for keyword_str in already_keywords: + if keyword_str: # Skip empty strings + all_keywords.update(k.strip() for k in keyword_str.split(",") if k.strip()) + # Process new keywords from edges_data + for edge in edges_data: + if edge.get("keywords"): + all_keywords.update( + k.strip() for k in edge["keywords"].split(",") if k.strip() + ) + # Join all unique keywords with commas + keywords = ",".join(sorted(all_keywords)) + + # 7. Deduplicate by description, keeping first occurrence in the same document unique_edges = {} for dp in edges_data: description_value = dp.get("description") @@ -1896,165 +1959,127 @@ async def _merge_edges_then_upsert( ) sorted_descriptions = [dp["description"] for dp in sorted_edges] - truncation_info = "" - dd_message = "" - has_placeholder = False # Initialize to track placeholder in file paths - # Combine already_description with sorted new descriptions description_list = already_description + sorted_descriptions + if not description_list: + logger.error(f"Relation {src_id}~{tgt_id} has no description") + raise ValueError(f"Relation {src_id}~{tgt_id} has no description") - num_fragment = len(description_list) - already_fragment = len(already_description) - deduplicated_num = already_fragment + len(edges_data) - num_fragment - if deduplicated_num > 0: - dd_message = f"dd:{deduplicated_num}" + # Check for cancellation before LLM summary + if pipeline_status is not None and pipeline_status_lock is not None: + async with pipeline_status_lock: + if pipeline_status.get("cancellation_requested", False): + raise PipelineCancelledException( + "User cancelled during relation summary" + ) - if skip_summary_due_to_limit: - logger.info(f"Skipped `{src_id}`~`{tgt_id}`: KEEP old chunks") - description = ( - already_edge.get("description", "(no description)") - if already_edge - else "(no description)" + # 8. Get summary description an LLM usage status + description, llm_was_used = await _handle_entity_relation_summary( + "Relation", + f"({src_id}, {tgt_id})", + description_list, + GRAPH_FIELD_SEP, + global_config, + llm_response_cache, + ) + + # 9. Build file_path within MAX_FILE_PATHS limit + file_paths_list = [] + seen_paths = set() + has_placeholder = False # Track if already_file_paths contains placeholder + + max_file_paths = global_config.get("max_file_paths", DEFAULT_MAX_FILE_PATHS) + file_path_placeholder = global_config.get( + "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER + ) + + # Collect from already_file_paths, excluding placeholder + for fp in already_file_paths: + # Check if this is a placeholder record + if fp and fp.startswith(f"...{file_path_placeholder}"): # Skip placeholders + has_placeholder = True + continue + if fp and fp not in seen_paths: + file_paths_list.append(fp) + seen_paths.add(fp) + + # Collect from new data + for dp in edges_data: + file_path_item = dp.get("file_path") + if file_path_item and file_path_item not in seen_paths: + file_paths_list.append(file_path_item) + seen_paths.add(file_path_item) + + # Apply count limit + max_file_paths = global_config.get("max_file_paths") + + if len(file_paths_list) > max_file_paths: + limit_method = global_config.get( + "source_ids_limit_method", SOURCE_IDS_LIMIT_METHOD_KEEP ) - existing_edge_data = dict(already_edge or {}) - if not existing_edge_data: - existing_edge_data = { - "description": description, - "keywords": GRAPH_FIELD_SEP.join(already_keywords), - "source_id": GRAPH_FIELD_SEP.join(existing_full_source_ids), - "file_path": GRAPH_FIELD_SEP.join(already_file_paths), - "weight": sum(already_weights) if already_weights else 0.0, - "truncate": "", - "created_at": int(time.time()), - } - existing_edge_data.setdefault("created_at", int(time.time())) - existing_edge_data["src_id"] = src_id - existing_edge_data["tgt_id"] = tgt_id - return existing_edge_data - elif num_fragment > 0: - # Get summary and LLM usage status - description, llm_was_used = await _handle_entity_relation_summary( - "Relation", - f"({src_id}, {tgt_id})", - description_list, - GRAPH_FIELD_SEP, - global_config, - llm_response_cache, - ) - - # Log based on actual LLM usage - if llm_was_used: - status_message = f"LLMmrg: `{src_id}`~`{tgt_id}` | {already_fragment}+{num_fragment - already_fragment}" - else: - status_message = f"Merged: `{src_id}`~`{tgt_id}` | {already_fragment}+{num_fragment - already_fragment}" - - # Add truncation info from apply_source_ids_limit if truncation occurred - if len(source_ids) < len(full_source_ids): - # Add + sign if has_placeholder is True, indicating actual file count is higher - full_source_count_str = ( - f"{len(full_source_ids)}+" - if has_placeholder - else str(len(full_source_ids)) - ) - truncation_info = ( - f"{limit_method}:{len(source_ids)}/{full_source_count_str}" - ) - - if dd_message or truncation_info: - status_message += ( - f" ({', '.join(filter(None, [truncation_info, dd_message]))})" - ) - - if already_fragment > 0 or llm_was_used: - logger.info(status_message) - if pipeline_status is not None and pipeline_status_lock is not None: - async with pipeline_status_lock: - pipeline_status["latest_message"] = status_message - pipeline_status["history_messages"].append(status_message) - else: - logger.debug(status_message) - - else: - logger.error(f"Edge {src_id} - {tgt_id} has no description") - description = "(no description)" - - # Split all existing and new keywords into individual terms, then combine and deduplicate - all_keywords = set() - # Process already_keywords (which are comma-separated) - for keyword_str in already_keywords: - if keyword_str: # Skip empty strings - all_keywords.update(k.strip() for k in keyword_str.split(",") if k.strip()) - # Process new keywords from edges_data - for edge in edges_data: - if edge.get("keywords"): - all_keywords.update( - k.strip() for k in edge["keywords"].split(",") if k.strip() - ) - # Join all unique keywords with commas - keywords = ",".join(sorted(all_keywords)) - - source_id = GRAPH_FIELD_SEP.join(source_ids) - - # Build file_path with count limit - if skip_summary_due_to_limit: - # Skip limit, keep original file_path - file_path = GRAPH_FIELD_SEP.join(fp for fp in already_file_paths if fp) - else: - # Collect and apply limit - file_paths_list = [] - seen_paths = set() - has_placeholder = False # Track if already_file_paths contains placeholder - - # Get placeholder to filter it out file_path_placeholder = global_config.get( "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER ) - # Collect from already_file_paths, excluding placeholder - for fp in already_file_paths: - # Check if this is a placeholder record - if fp and fp.startswith(f"...{file_path_placeholder}"): # Skip placeholders - has_placeholder = True - continue - if fp and fp not in seen_paths: - file_paths_list.append(fp) - seen_paths.add(fp) + # Add + sign to indicate actual file count is higher + original_count_str = ( + f"{len(file_paths_list)}+" if has_placeholder else str(len(file_paths_list)) + ) - # Collect from new data - for dp in edges_data: - file_path_item = dp.get("file_path") - if file_path_item and file_path_item not in seen_paths: - file_paths_list.append(file_path_item) - seen_paths.add(file_path_item) + if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: + # FIFO: keep tail (newest), discard head + file_paths_list = file_paths_list[-max_file_paths:] + file_paths_list.append(f"...{file_path_placeholder}...(FIFO)") + else: + # KEEP: keep head (earliest), discard tail + file_paths_list = file_paths_list[:max_file_paths] + file_paths_list.append(f"...{file_path_placeholder}...(KEEP Old)") - # Apply count limit - max_file_paths = global_config.get("max_file_paths") + logger.info( + f"Limited `{src_id}`~`{tgt_id}`: file_path {original_count_str} -> {max_file_paths} ({limit_method})" + ) + # Finalize file_path + file_path = GRAPH_FIELD_SEP.join(file_paths_list) - if len(file_paths_list) > max_file_paths: - limit_method = global_config.get( - "source_ids_limit_method", SOURCE_IDS_LIMIT_METHOD_KEEP - ) - file_path_placeholder = global_config.get( - "file_path_more_placeholder", DEFAULT_FILE_PATH_MORE_PLACEHOLDER - ) - original_count = len(file_paths_list) + # 10. Log based on actual LLM usage + num_fragment = len(description_list) + already_fragment = len(already_description) + if llm_was_used: + status_message = f"LLMmrg: `{src_id}`~`{tgt_id}` | {already_fragment}+{num_fragment - already_fragment}" + else: + status_message = f"Merged: `{src_id}`~`{tgt_id}` | {already_fragment}+{num_fragment - already_fragment}" - if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: - # FIFO: keep tail (newest), discard head - file_paths_list = file_paths_list[-max_file_paths:] - else: - # KEEP: keep head (earliest), discard tail - file_paths_list = file_paths_list[:max_file_paths] + truncation_info = truncation_info_log = "" + if len(source_ids) < len(full_source_ids): + # Add truncation info from apply_source_ids_limit if truncation occurred + truncation_info_log = f"{limit_method} {len(source_ids)}/{len(full_source_ids)}" + if limit_method == SOURCE_IDS_LIMIT_METHOD_FIFO: + truncation_info = truncation_info_log + else: + truncation_info = "KEEP Old" - file_paths_list.append( - f"...{file_path_placeholder}({limit_method}:{max_file_paths}/{original_count})..." - ) - logger.info( - f"Limited `{src_id}`~`{tgt_id}`: file_path {original_count} -> {max_file_paths} ({limit_method})" - ) + deduplicated_num = already_fragment + len(edges_data) - num_fragment + dd_message = "" + if deduplicated_num > 0: + # Duplicated description detected across multiple trucks for the same entity + dd_message = f"dd {deduplicated_num}" - file_path = GRAPH_FIELD_SEP.join(file_paths_list) + if dd_message or truncation_info_log: + status_message += ( + f" ({', '.join(filter(None, [truncation_info_log, dd_message]))})" + ) + # Add message to pipeline satus when merge happens + if already_fragment > 0 or llm_was_used: + logger.info(status_message) + if pipeline_status is not None and pipeline_status_lock is not None: + async with pipeline_status_lock: + pipeline_status["latest_message"] = status_message + pipeline_status["history_messages"].append(status_message) + else: + logger.debug(status_message) + + # 11. Update both graph and vector db for need_insert_id in [src_id, tgt_id]: if not (await knowledge_graph_inst.has_node(need_insert_id)): node_created_at = int(time.time())