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feat(memory): support perception-aware memory writing in workflow and Neo4j nodes

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This commit is contained in:
Eternity
2026-03-23 16:33:25 +08:00
parent 31085ed678
commit 2ff81ba101
22 changed files with 820 additions and 519 deletions
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111
api/app/repositories/neo4j/add_nodes.py
View File

@@ -1,7 +1,8 @@
from typing import List, Optional
from app.repositories.neo4j.cypher_queries import DIALOGUE_NODE_SAVE, STATEMENT_NODE_SAVE, CHUNK_NODE_SAVE,MEMORY_SUMMARY_NODE_SAVE
from app.core.memory.models.graph_models import DialogueNode, StatementNode, ChunkNode, MemorySummaryNode
from app.repositories.neo4j.cypher_queries import DIALOGUE_NODE_SAVE, STATEMENT_NODE_SAVE, CHUNK_NODE_SAVE, \
MEMORY_SUMMARY_NODE_SAVE, PERCEPTUAL_NODE_SAVE, PERCEPTUAL_DIALOGUE_EDGE_SAVE
# 使用新的仓储层
from app.repositories.neo4j.neo4j_connector import Neo4jConnector
@@ -12,6 +13,7 @@ async def delete_all_nodes(end_user_id: str, connector: Neo4jConnector):
print(f"All end_user_id: {end_user_id} node and edge deleted successfully")
return result
async def add_dialogue_nodes(dialogues: List[DialogueNode], connector: Neo4jConnector) -> Optional[List[str]]:
"""Add dialogue nodes to Neo4j database.
@@ -127,6 +129,7 @@ async def add_statement_nodes(statements: List[StatementNode], connector: Neo4jC
print(f"Error creating statement nodes: {e}")
return None
async def add_chunk_nodes(chunks: List[ChunkNode], connector: Neo4jConnector) -> Optional[List[str]]:
"""Add chunk nodes to Neo4j in batch.
@@ -179,8 +182,8 @@ async def add_chunk_nodes(chunks: List[ChunkNode], connector: Neo4jConnector) ->
return None
async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector: Neo4jConnector) -> Optional[List[str]]:
async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector: Neo4jConnector) -> Optional[
List[str]]:
"""Add memory summary nodes to Neo4j in batch.
Args:
@@ -211,7 +214,7 @@ async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector
"summary_embedding": s.summary_embedding if s.summary_embedding else None,
"config_id": s.config_id, # 添加 config_id
})
result = await connector.execute_query(
MEMORY_SUMMARY_NODE_SAVE,
summaries=flattened
@@ -224,3 +227,103 @@ async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector
return None
async def add_perceptual_nodes(
perceptuals: list,
connector: Neo4jConnector,
embedder_client=None,
) -> Optional[List[str]]:
"""Add perceptual memory nodes to Neo4j in batch.
Args:
perceptuals: List of MemoryPerceptualModel objects from PostgreSQL
connector: Neo4j connector instance
embedder_client: Optional embedder client for generating summary embeddings
Returns:
List of created node UUIDs or None if failed
"""
if not perceptuals:
print("No perceptual nodes to add")
return []
try:
flattened = []
for p in perceptuals:
meta = p.meta_data or {}
content_meta = meta.get("content", {})
# 生成 summary embedding（如果有 embedder_client）
summary_embedding = None
if embedder_client and p.summary:
try:
summary_embedding = (await embedder_client.response([p.summary]))[0]
except Exception as emb_err:
print(f"Failed to embed perceptual summary: {emb_err}")
flattened.append({
"id": str(p.id),
"end_user_id": str(p.end_user_id),
"perceptual_type": p.perceptual_type,
"file_path": p.file_path or "",
"file_name": p.file_name or "",
"file_ext": p.file_ext or "",
"summary": p.summary or "",
"keywords": content_meta.get("keywords", []),
"topic": content_meta.get("topic", ""),
"domain": content_meta.get("domain", ""),
"created_at": p.created_time.isoformat() if p.created_time else None,
"summary_embedding": summary_embedding,
})
result = await connector.execute_query(
PERCEPTUAL_NODE_SAVE,
perceptuals=flattened,
)
created_uuids = [record.get("uuid") for record in result]
print(f"Successfully saved {len(created_uuids)} Perceptual nodes to Neo4j")
return created_uuids
except Exception as e:
print(f"Failed to save Perceptual nodes to Neo4j: {e}")
return None
async def add_perceptual_dialogue_edges(
perceptuals: list,
dialog_id: str,
connector: Neo4jConnector,
) -> Optional[List[str]]:
"""Add edges between Perceptual nodes and Dialogue nodes.
Args:
perceptuals: List of MemoryPerceptualModel objects
dialog_id: The dialogue ID (or ref_id) to link to
connector: Neo4j connector instance
Returns:
List of created edge element IDs or None if failed
"""
if not perceptuals or not dialog_id:
return []
try:
edges = []
for p in perceptuals:
edges.append({
"perceptual_id": str(p.id),
"dialog_id": dialog_id,
"end_user_id": str(p.end_user_id),
"created_at": p.created_time.isoformat() if p.created_time else None,
})
result = await connector.execute_query(
PERCEPTUAL_DIALOGUE_EDGE_SAVE,
edges=edges,
)
created_ids = [record.get("uuid") for record in result]
print(f"Successfully saved {len(created_ids)} Perceptual-Dialogue edges to Neo4j")
return created_ids
except Exception as e:
print(f"Failed to save Perceptual-Dialogue edges: {e}")
return None

33
api/app/repositories/neo4j/cypher_queries.py
View File

@@ -1323,3 +1323,36 @@ RETURN s.statement AS statement,
ORDER BY COALESCE(s.activation_value, 0) DESC
LIMIT $limit
"""
# 感知记忆节点保存
PERCEPTUAL_NODE_SAVE = """
UNWIND $perceptuals AS p
MERGE (n:Perceptual {id: p.id})
SET n += {
id: p.id,
end_user_id: p.end_user_id,
perceptual_type: p.perceptual_type,
file_path: p.file_path,
file_name: p.file_name,
file_ext: p.file_ext,
summary: p.summary,
keywords: p.keywords,
topic: p.topic,
domain: p.domain,
created_at: p.created_at,
summary_embedding: p.summary_embedding
}
RETURN n.id AS uuid
"""
# 感知记忆与对话的关联边
PERCEPTUAL_DIALOGUE_EDGE_SAVE = """
UNWIND $edges AS edge
MATCH (p:Perceptual {id: edge.perceptual_id, end_user_id: edge.end_user_id})
MATCH (d:Dialogue {end_user_id: edge.end_user_id})
WHERE d.id = edge.dialog_id OR d.ref_id = edge.dialog_id
MERGE (d)-[r:HAS_PERCEPTUAL]->(p)
SET r.end_user_id = edge.end_user_id,
r.created_at = edge.created_at
RETURN elementId(r) AS uuid
"""