feat(memory, model): update multi-modal memory write and model list API
- Adjust multi-modal memory write behavior for text and visual data - Mask API keys in model list response to prevent exposure - Add capability-based filtering to the model list API
This commit is contained in:
Eternity
@@ -1,16 +1,19 @@
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from typing import List, Optional
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from app.core.logging_config import get_logger
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from app.core.memory.models.graph_models import DialogueNode, StatementNode, ChunkNode, MemorySummaryNode
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from app.repositories.neo4j.cypher_queries import DIALOGUE_NODE_SAVE, STATEMENT_NODE_SAVE, CHUNK_NODE_SAVE, \
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MEMORY_SUMMARY_NODE_SAVE, PERCEPTUAL_NODE_SAVE, PERCEPTUAL_DIALOGUE_EDGE_SAVE
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MEMORY_SUMMARY_NODE_SAVE
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# 使用新的仓储层
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from app.repositories.neo4j.neo4j_connector import Neo4jConnector
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logger = get_logger(__name__)
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async def delete_all_nodes(end_user_id: str, connector: Neo4jConnector):
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"""Delete all nodes in the database."""
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result = await connector.execute_query(f"MATCH (n {{end_user_id: '{end_user_id}'}}) DETACH DELETE n")
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print(f"All end_user_id: {end_user_id} node and edge deleted successfully")
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logger.warning(f"All end_user_id: {end_user_id} node and edge deleted successfully")
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return result
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@@ -25,7 +28,7 @@ async def add_dialogue_nodes(dialogues: List[DialogueNode], connector: Neo4jConn
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List of created node UUIDs or None if failed
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"""
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if not dialogues:
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print("No dialogues to save")
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logger.info("No dialogues to save")
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return []
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try:
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@@ -50,11 +53,11 @@ async def add_dialogue_nodes(dialogues: List[DialogueNode], connector: Neo4jConn
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)
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created_uuids = [record["uuid"] for record in result]
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print(f"Successfully created {len(created_uuids)} dialogue nodes: {created_uuids}")
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logger.info(f"Successfully created {len(created_uuids)} dialogue nodes: {created_uuids}")
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return created_uuids
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except Exception as e:
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print(f"Error creating dialogue nodes: {e}")
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logger.info(f"Error creating dialogue nodes: {e}")
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return None
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@@ -69,7 +72,7 @@ async def add_statement_nodes(statements: List[StatementNode], connector: Neo4jC
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List of created node UUIDs or None if failed
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"""
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if not statements:
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print("No statements to save")
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logger.info("No statements to save")
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return []
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try:
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@@ -122,11 +125,11 @@ async def add_statement_nodes(statements: List[StatementNode], connector: Neo4jC
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)
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created_uuids = [record["uuid"] for record in result]
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print(f"Successfully created {len(created_uuids)} statement nodes")
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logger.info(f"Successfully created {len(created_uuids)} statement nodes")
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return created_uuids
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except Exception as e:
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print(f"Error creating statement nodes: {e}")
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logger.info(f"Error creating statement nodes: {e}")
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return None
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@@ -141,7 +144,7 @@ async def add_chunk_nodes(chunks: List[ChunkNode], connector: Neo4jConnector) ->
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List of created chunk UUIDs or None if failed
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"""
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if not chunks:
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print("No chunk nodes to add")
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logger.info("No chunk nodes to add")
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return []
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try:
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@@ -174,16 +177,18 @@ async def add_chunk_nodes(chunks: List[ChunkNode], connector: Neo4jConnector) ->
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)
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created_uuids = [record["uuid"] for record in result]
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print(f"Successfully created {len(created_uuids)} chunk nodes")
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logger.info(f"Successfully created {len(created_uuids)} chunk nodes")
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return created_uuids
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except Exception as e:
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print(f"Error creating chunk nodes: {e}")
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logger.info(f"Error creating chunk nodes: {e}")
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return None
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async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector: Neo4jConnector) -> Optional[
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List[str]]:
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async def add_memory_summary_nodes(
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summaries: List[MemorySummaryNode],
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connector: Neo4jConnector
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) -> Optional[List[str]]:
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"""Add memory summary nodes to Neo4j in batch.
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Args:
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@@ -194,7 +199,7 @@ async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector
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List of created summary node ids or None if failed
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"""
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if not summaries:
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print("No memory summary nodes to add")
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logger.info("No memory summary nodes to add")
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return []
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try:
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@@ -220,110 +225,8 @@ async def add_memory_summary_nodes(summaries: List[MemorySummaryNode], connector
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summaries=flattened
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)
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created_ids = [record.get("uuid") for record in result]
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print(f"Successfully saved {len(created_ids)} MemorySummary nodes to Neo4j")
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logger.info(f"Successfully saved {len(created_ids)} MemorySummary nodes to Neo4j")
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return created_ids
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except Exception as e:
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print(f"Failed to save MemorySummary nodes to Neo4j: {e}")
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return None
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async def add_perceptual_nodes(
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perceptuals: list,
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connector: Neo4jConnector,
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embedder_client=None,
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) -> Optional[List[str]]:
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"""Add perceptual memory nodes to Neo4j in batch.
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Args:
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perceptuals: List of MemoryPerceptualModel objects from PostgreSQL
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connector: Neo4j connector instance
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embedder_client: Optional embedder client for generating summary embeddings
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Returns:
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List of created node UUIDs or None if failed
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"""
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if not perceptuals:
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print("No perceptual nodes to add")
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return []
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try:
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flattened = []
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for p in perceptuals:
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meta = p.meta_data or {}
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content_meta = meta.get("content", {})
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# 生成 summary embedding（如果有 embedder_client）
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summary_embedding = None
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if embedder_client and p.summary:
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try:
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summary_embedding = (await embedder_client.response([p.summary]))[0]
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except Exception as emb_err:
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print(f"Failed to embed perceptual summary: {emb_err}")
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flattened.append({
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"id": str(p.id),
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"end_user_id": str(p.end_user_id),
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"perceptual_type": p.perceptual_type,
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"file_path": p.file_path or "",
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"file_name": p.file_name or "",
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"file_ext": p.file_ext or "",
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"summary": p.summary or "",
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"keywords": content_meta.get("keywords", []),
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"topic": content_meta.get("topic", ""),
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"domain": content_meta.get("domain", ""),
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"created_at": p.created_time.isoformat() if p.created_time else None,
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"summary_embedding": summary_embedding,
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})
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result = await connector.execute_query(
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PERCEPTUAL_NODE_SAVE,
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perceptuals=flattened,
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)
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created_uuids = [record.get("uuid") for record in result]
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print(f"Successfully saved {len(created_uuids)} Perceptual nodes to Neo4j")
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return created_uuids
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except Exception as e:
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print(f"Failed to save Perceptual nodes to Neo4j: {e}")
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return None
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async def add_perceptual_dialogue_edges(
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perceptuals: list,
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dialog_id: str,
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connector: Neo4jConnector,
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) -> Optional[List[str]]:
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"""Add edges between Perceptual nodes and Dialogue nodes.
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Args:
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perceptuals: List of MemoryPerceptualModel objects
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dialog_id: The dialogue ID (or ref_id) to link to
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connector: Neo4j connector instance
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Returns:
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List of created edge element IDs or None if failed
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"""
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if not perceptuals or not dialog_id:
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return []
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try:
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edges = []
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for p in perceptuals:
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edges.append({
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"perceptual_id": str(p.id),
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"dialog_id": dialog_id,
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"end_user_id": str(p.end_user_id),
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"created_at": p.created_time.isoformat() if p.created_time else None,
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})
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result = await connector.execute_query(
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PERCEPTUAL_DIALOGUE_EDGE_SAVE,
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edges=edges,
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)
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created_ids = [record.get("uuid") for record in result]
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print(f"Successfully saved {len(created_ids)} Perceptual-Dialogue edges to Neo4j")
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return created_ids
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except Exception as e:
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print(f"Failed to save Perceptual-Dialogue edges: {e}")
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logger.info(f"Failed to save MemorySummary nodes to Neo4j: {e}")
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return None
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