Remove list_of_list_to_dict function
This commit is contained in:
yangdx
@@ -25,7 +25,6 @@ from .utils import (
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CacheData,
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get_conversation_turns,
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use_llm_func_with_cache,
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list_of_list_to_dict,
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)
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from .base import (
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BaseGraphStorage,
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@@ -1175,22 +1174,17 @@ async def _get_vector_context(
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entities_context = []
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relations_context = []
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# Create text_units_context in the same format as _get_edge_data and _get_node_data
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text_units_section_list = [["id", "content", "file_path"]]
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# Create text_units_context directly as a list of dictionaries
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text_units_context = []
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for i, chunk in enumerate(maybe_trun_chunks):
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# Add to text_units_section_list
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text_units_section_list.append(
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[
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i + 1, # id
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chunk["content"], # content
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chunk["file_path"], # file_path
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]
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text_units_context.append(
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{
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"id": i + 1,
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"content": chunk["content"],
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"file_path": chunk["file_path"],
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}
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)
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# Convert to dictionary format using list_of_list_to_dict
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text_units_context = list_of_list_to_dict(text_units_section_list)
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return entities_context, relations_context, text_units_context
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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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@@ -1398,17 +1392,7 @@ async def _get_node_data(
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)
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# build prompt
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entites_section_list = [
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[
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"id",
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"entity",
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"type",
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"description",
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"rank",
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"created_at",
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"file_path",
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]
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]
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entities_context = []
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for i, n in enumerate(node_datas):
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created_at = n.get("created_at", "UNKNOWN")
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if isinstance(created_at, (int, float)):
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@@ -1417,32 +1401,19 @@ async def _get_node_data(
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# Get file path from node data
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file_path = n.get("file_path", "unknown_source")
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entites_section_list.append(
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[
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i + 1,
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n["entity_name"],
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n.get("entity_type", "UNKNOWN"),
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n.get("description", "UNKNOWN"),
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n["rank"],
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created_at,
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file_path,
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]
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entities_context.append(
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{
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"id": i + 1,
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"entity": n["entity_name"],
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"type": n.get("entity_type", "UNKNOWN"),
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"description": n.get("description", "UNKNOWN"),
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"rank": n["rank"],
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"created_at": created_at,
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"file_path": file_path,
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}
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)
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entities_context = list_of_list_to_dict(entites_section_list)
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relations_section_list = [
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[
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"id",
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"entity1",
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"entity2",
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"description",
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"keywords",
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"weight",
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"rank",
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"created_at",
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"file_path",
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]
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]
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relations_context = []
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for i, e in enumerate(use_relations):
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created_at = e.get("created_at", "UNKNOWN")
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# Convert timestamp to readable format
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@@ -1452,27 +1423,29 @@ async def _get_node_data(
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# Get file path from edge data
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file_path = e.get("file_path", "unknown_source")
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relations_section_list.append(
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[
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i + 1,
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e["src_tgt"][0],
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e["src_tgt"][1],
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e["description"],
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e["keywords"],
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e["weight"],
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e["rank"],
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created_at,
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file_path,
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]
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relations_context.append(
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{
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"id": i + 1,
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"entity1": e["src_tgt"][0],
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"entity2": e["src_tgt"][1],
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"description": e["description"],
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"keywords": e["keywords"],
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"weight": e["weight"],
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"rank": e["rank"],
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"created_at": created_at,
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"file_path": file_path,
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}
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)
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relations_context = list_of_list_to_dict(relations_section_list)
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text_units_section_list = [["id", "content", "file_path"]]
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text_units_context = []
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for i, t in enumerate(use_text_units):
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text_units_section_list.append(
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[i + 1, t["content"], t.get("file_path", "unknown_source")]
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text_units_context.append(
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{
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"id": i + 1,
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"content": t["content"],
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"file_path": t.get("file_path", "unknown_source"),
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}
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)
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text_units_context = list_of_list_to_dict(text_units_section_list)
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return entities_context, relations_context, text_units_context
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@@ -1715,19 +1688,7 @@ async def _get_edge_data(
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f"Global query uses {len(use_entities)} entites, {len(edge_datas)} relations, {len(use_text_units)} chunks"
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)
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relations_section_list = [
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[
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"id",
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"entity1",
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"entity2",
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"description",
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"keywords",
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"weight",
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"rank",
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"created_at",
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"file_path",
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]
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]
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relations_context = []
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for i, e in enumerate(edge_datas):
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created_at = e.get("created_at", "UNKNOWN")
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# Convert timestamp to readable format
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@@ -1737,24 +1698,21 @@ async def _get_edge_data(
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# Get file path from edge data
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file_path = e.get("file_path", "unknown_source")
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relations_section_list.append(
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[
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i + 1,
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e["src_id"],
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e["tgt_id"],
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e["description"],
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e["keywords"],
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e["weight"],
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e["rank"],
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created_at,
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file_path,
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]
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relations_context.append(
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{
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"id": i + 1,
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"entity1": e["src_id"],
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"entity2": e["tgt_id"],
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"description": e["description"],
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"keywords": e["keywords"],
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"weight": e["weight"],
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"rank": e["rank"],
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"created_at": created_at,
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"file_path": file_path,
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}
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)
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relations_context = list_of_list_to_dict(relations_section_list)
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entites_section_list = [
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["id", "entity", "type", "description", "rank", "created_at", "file_path"]
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]
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entities_context = []
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for i, n in enumerate(use_entities):
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created_at = n.get("created_at", "UNKNOWN")
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# Convert timestamp to readable format
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@@ -1764,25 +1722,27 @@ async def _get_edge_data(
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# Get file path from node data
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file_path = n.get("file_path", "unknown_source")
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entites_section_list.append(
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[
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i + 1,
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n["entity_name"],
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n.get("entity_type", "UNKNOWN"),
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n.get("description", "UNKNOWN"),
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n["rank"],
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created_at,
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file_path,
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]
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entities_context.append(
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{
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"id": i + 1,
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"entity": n["entity_name"],
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"type": n.get("entity_type", "UNKNOWN"),
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"description": n.get("description", "UNKNOWN"),
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"rank": n["rank"],
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"created_at": created_at,
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"file_path": file_path,
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}
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)
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entities_context = list_of_list_to_dict(entites_section_list)
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text_units_section_list = [["id", "content", "file_path"]]
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text_units_context = []
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for i, t in enumerate(use_text_units):
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text_units_section_list.append(
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[i + 1, t["content"], t.get("file_path", "unknown")]
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text_units_context.append(
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{
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"id": i + 1,
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"content": t["content"],
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"file_path": t.get("file_path", "unknown"),
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}
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)
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text_units_context = list_of_list_to_dict(text_units_section_list)
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return entities_context, relations_context, text_units_context
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@@ -719,44 +719,6 @@ def truncate_list_by_token_size(
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return list_data
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def list_of_list_to_dict(data: list[list[str]]) -> list[dict[str, str]]:
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"""Convert a 2D string list (table-like data) into a list of dictionaries.
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The first row is treated as header containing field names. Subsequent rows become
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dictionary entries where keys come from header and values from row data.
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Args:
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data: 2D string array where first row contains headers and rest are data rows.
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Minimum 2 columns required in data rows (rows with <2 elements are skipped).
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Returns:
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List of dictionaries where each dict represents a data row with:
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- Keys: Header values from first row
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- Values: Corresponding row values (empty string if missing)
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Example:
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Input: [["Name","Age"], ["Alice","23"], ["Bob"]]
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Output: [{"Name":"Alice","Age":"23"}, {"Name":"Bob","Age":""}]
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"""
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if not data or len(data) <= 1:
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return []
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header = data[0]
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result = []
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for row in data[1:]:
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if len(row) >= 2:
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item = {}
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for i, field_name in enumerate(header):
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if i < len(row):
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item[field_name] = str(row[i])
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else:
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item[field_name] = ""
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result.append(item)
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return result
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def save_data_to_file(data, file_name):
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with open(file_name, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=4)
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