Merge branch 'main' of github.com:lcjqyml/LightRAG
This commit is contained in:
@@ -432,19 +432,31 @@ class PGVectorStorage(BaseVectorStorage):
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def _upsert_entities(self, item: dict[str, Any]) -> tuple[str, dict[str, Any]]:
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upsert_sql = SQL_TEMPLATES["upsert_entity"]
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source_id = item["source_id"]
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if isinstance(source_id, str) and "<SEP>" in source_id:
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chunk_ids = source_id.split("<SEP>")
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else:
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chunk_ids = [source_id]
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data: dict[str, Any] = {
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"workspace": self.db.workspace,
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"id": item["__id__"],
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"entity_name": item["entity_name"],
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"content": item["content"],
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"content_vector": json.dumps(item["__vector__"].tolist()),
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"chunk_id": item["source_id"],
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"chunk_ids": chunk_ids,
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# TODO: add document_id
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}
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return upsert_sql, data
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def _upsert_relationships(self, item: dict[str, Any]) -> tuple[str, dict[str, Any]]:
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upsert_sql = SQL_TEMPLATES["upsert_relationship"]
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source_id = item["source_id"]
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if isinstance(source_id, str) and "<SEP>" in source_id:
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chunk_ids = source_id.split("<SEP>")
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else:
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chunk_ids = [source_id]
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data: dict[str, Any] = {
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"workspace": self.db.workspace,
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"id": item["__id__"],
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@@ -452,7 +464,7 @@ class PGVectorStorage(BaseVectorStorage):
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"target_id": item["tgt_id"],
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"content": item["content"],
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"content_vector": json.dumps(item["__vector__"].tolist()),
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"chunk_id": item["source_id"],
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"chunk_ids": chunk_ids,
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# TODO: add document_id
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}
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return upsert_sql, data
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@@ -950,10 +962,11 @@ class PGGraphStorage(BaseGraphStorage):
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vertices.get(edge["end_id"], {}),
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)
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else:
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if v is None or (v.count("{") < 1 and v.count("[") < 1):
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d[k] = v
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else:
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d[k] = json.loads(v) if isinstance(v, str) else v
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d[k] = (
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json.loads(v)
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if isinstance(v, str) and ("{" in v or "[" in v)
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else v
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)
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return d
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@@ -1410,29 +1423,22 @@ class PGGraphStorage(BaseGraphStorage):
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"""
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MAX_GRAPH_NODES = 1000
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# Build the query based on whether we want the full graph or a specific subgraph.
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if node_label == "*":
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query = """SELECT * FROM cypher('%s', $$
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MATCH (n:Entity)
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OPTIONAL MATCH (n)-[r]->(m:Entity)
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RETURN n, r, m
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LIMIT %d
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$$) AS (n agtype, r agtype, m agtype)""" % (
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self.graph_name,
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MAX_GRAPH_NODES,
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)
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query = f"""SELECT * FROM cypher('{self.graph_name}', $$
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MATCH (n:Entity)
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OPTIONAL MATCH (n)-[r]->(m:Entity)
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RETURN n, r, m
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LIMIT {MAX_GRAPH_NODES}
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$$) AS (n agtype, r agtype, m agtype)"""
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else:
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encoded_node_label = self._encode_graph_label(node_label.strip('"'))
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query = """SELECT * FROM cypher('%s', $$
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MATCH (n:Entity {node_id: "%s"})
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OPTIONAL MATCH p = (n)-[*..%d]-(m)
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RETURN nodes(p) AS nodes, relationships(p) AS relationships
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LIMIT %d
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$$) AS (nodes agtype, relationships agtype)""" % (
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self.graph_name,
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encoded_node_label,
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max_depth,
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MAX_GRAPH_NODES,
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)
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encoded_label = self._encode_graph_label(node_label.strip('"'))
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query = f"""SELECT * FROM cypher('{self.graph_name}', $$
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MATCH (n:Entity {{node_id: "{encoded_label}"}})
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OPTIONAL MATCH p = (n)-[*..{max_depth}]-(m)
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RETURN nodes(p) AS nodes, relationships(p) AS relationships
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LIMIT {MAX_GRAPH_NODES}
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$$) AS (nodes agtype, relationships agtype)"""
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results = await self._query(query)
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@@ -1440,56 +1446,57 @@ class PGGraphStorage(BaseGraphStorage):
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edges = []
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unique_edge_ids = set()
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for result in results:
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if node_label == "*":
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if result["n"]:
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node = result["n"]
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node_id = self._decode_graph_label(node["node_id"])
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if node_id not in nodes:
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nodes[node_id] = node
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def add_node(node_data: dict):
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node_id = self._decode_graph_label(node_data["node_id"])
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if node_id not in nodes:
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nodes[node_id] = node_data
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if result["m"]:
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node = result["m"]
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node_id = self._decode_graph_label(node["node_id"])
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if node_id not in nodes:
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nodes[node_id] = node
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if result["r"]:
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edge = result["r"]
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src_id = self._decode_graph_label(edge["start_id"])
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tgt_id = self._decode_graph_label(edge["end_id"])
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edges.append((src_id, tgt_id))
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else:
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if result["nodes"]:
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for node in result["nodes"]:
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node_id = self._decode_graph_label(node["node_id"])
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if node_id not in nodes:
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nodes[node_id] = node
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def add_edge(edge_data: list):
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src_id = self._decode_graph_label(edge_data[0]["node_id"])
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tgt_id = self._decode_graph_label(edge_data[2]["node_id"])
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edge_key = f"{src_id},{tgt_id}"
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if edge_key not in unique_edge_ids:
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unique_edge_ids.add(edge_key)
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edges.append(
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(
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edge_key,
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src_id,
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tgt_id,
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{"source": edge_data[0], "target": edge_data[2]},
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)
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)
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if result["relationships"]:
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for edge in result["relationships"]: # src --DIRECTED--> target
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src_id = self._decode_graph_label(edge[0]["node_id"])
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tgt_id = self._decode_graph_label(edge[2]["node_id"])
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id = src_id + "," + tgt_id
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if id in unique_edge_ids:
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continue
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else:
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unique_edge_ids.add(id)
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edges.append(
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(id, src_id, tgt_id, {"source": edge[0], "target": edge[2]})
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)
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# Process the query results.
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if node_label == "*":
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for result in results:
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if result.get("n"):
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add_node(result["n"])
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if result.get("m"):
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add_node(result["m"])
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if result.get("r"):
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add_edge(result["r"])
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else:
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for result in results:
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for node in result.get("nodes", []):
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add_node(node)
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for edge in result.get("relationships", []):
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add_edge(edge)
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# Construct and return the KnowledgeGraph.
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kg = KnowledgeGraph(
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nodes=[
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KnowledgeGraphNode(
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id=node_id, labels=[node_id], properties=nodes[node_id]
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)
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for node_id in nodes
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KnowledgeGraphNode(id=node_id, labels=[node_id], properties=node_data)
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for node_id, node_data in nodes.items()
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],
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edges=[
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KnowledgeGraphEdge(
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id=id, type="DIRECTED", source=src, target=tgt, properties=props
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id=edge_id,
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type="DIRECTED",
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source=src,
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target=tgt,
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properties=props,
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)
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for id, src, tgt, props in edges
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for edge_id, src, tgt, props in edges
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],
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)
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@@ -1654,22 +1661,25 @@ SQL_TEMPLATES = {
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update_time = CURRENT_TIMESTAMP
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""",
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"upsert_entity": """INSERT INTO LIGHTRAG_VDB_ENTITY (workspace, id, entity_name, content,
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content_vector, chunk_id)
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VALUES ($1, $2, $3, $4, $5, $6)
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content_vector, chunk_ids)
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VALUES ($1, $2, $3, $4, $5, $6::varchar[])
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ON CONFLICT (workspace,id) DO UPDATE
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SET entity_name=EXCLUDED.entity_name,
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content=EXCLUDED.content,
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content_vector=EXCLUDED.content_vector,
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chunk_ids=EXCLUDED.chunk_ids,
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update_time=CURRENT_TIMESTAMP
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""",
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"upsert_relationship": """INSERT INTO LIGHTRAG_VDB_RELATION (workspace, id, source_id,
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target_id, content, content_vector, chunk_id)
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VALUES ($1, $2, $3, $4, $5, $6, $7)
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target_id, content, content_vector, chunk_ids)
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VALUES ($1, $2, $3, $4, $5, $6, $7::varchar[])
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ON CONFLICT (workspace,id) DO UPDATE
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SET source_id=EXCLUDED.source_id,
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target_id=EXCLUDED.target_id,
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content=EXCLUDED.content,
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content_vector=EXCLUDED.content_vector, update_time = CURRENT_TIMESTAMP
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content_vector=EXCLUDED.content_vector,
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chunk_ids=EXCLUDED.chunk_ids,
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update_time = CURRENT_TIMESTAMP
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""",
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# SQL for VectorStorage
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# "entities": """SELECT entity_name FROM
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@@ -1720,8 +1730,8 @@ SQL_TEMPLATES = {
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FROM (
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SELECT r.id, r.source_id, r.target_id, 1 - (r.content_vector <=> '[{embedding_string}]'::vector) as distance
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FROM LIGHTRAG_VDB_RELATION r
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JOIN relevant_chunks c ON c.chunk_id = ANY(r.chunk_ids)
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WHERE r.workspace=$1
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AND r.chunk_id IN (SELECT chunk_id FROM relevant_chunks)
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) filtered
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WHERE distance>$2
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ORDER BY distance DESC
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@@ -1735,10 +1745,10 @@ SQL_TEMPLATES = {
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)
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SELECT entity_name FROM
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(
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SELECT id, entity_name, 1 - (content_vector <=> '[{embedding_string}]'::vector) as distance
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FROM LIGHTRAG_VDB_ENTITY
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where workspace=$1
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AND chunk_id IN (SELECT chunk_id FROM relevant_chunks)
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SELECT e.id, e.entity_name, 1 - (e.content_vector <=> '[{embedding_string}]'::vector) as distance
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FROM LIGHTRAG_VDB_ENTITY e
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JOIN relevant_chunks c ON c.chunk_id = ANY(e.chunk_ids)
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WHERE e.workspace=$1
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)
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WHERE distance>$2
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ORDER BY distance DESC
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@@ -1756,7 +1766,7 @@ SQL_TEMPLATES = {
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FROM LIGHTRAG_DOC_CHUNKS
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where workspace=$1
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AND id IN (SELECT chunk_id FROM relevant_chunks)
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)
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) as chunk_distances
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WHERE distance>$2
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ORDER BY distance DESC
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LIMIT $3
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@@ -404,7 +404,7 @@ async def extract_entities(
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language=language,
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)
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continue_prompt = PROMPTS["entity_continue_extraction"]
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continue_prompt = PROMPTS["entity_continue_extraction"].format(**context_base)
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if_loop_prompt = PROMPTS["entity_if_loop_extraction"]
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processed_chunks = 0
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