feat: enable specifiy database and collection name in local api with neo4j(enterprise)#1245
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nuoxiichn wants to merge 3 commits intoMemTensor:mainfrom
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feat: enable specifiy database and collection name in local api with neo4j(enterprise)#1245nuoxiichn wants to merge 3 commits intoMemTensor:mainfrom
nuoxiichn wants to merge 3 commits intoMemTensor:mainfrom
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Pull request overview
This PR adds multi-tenant routing support for Neo4j Enterprise multi-database deployments and optional external vector DB (Qdrant) syncing, allowing per-user/per-cube isolation across both graph and vector storage.
Changes:
- Add per-user/per-cube component initialization + caching for Neo4j multi-db mode in API handlers.
- Add optional external VecDB sync path for Neo4j graph writes and use the external VecDB for embedding search when configured.
- Add Qdrant per-scope collection routing (via
user_id/user_name) and update API Neo4j config generation to support these modes.
Reviewed changes
Copilot reviewed 9 out of 9 changed files in this pull request and generated 10 comments.
Show a summary per file
| File | Description |
|---|---|
src/memos/vec_dbs/qdrant.py |
Routes operations to user-scoped Qdrant collections; adds collection auto-create/indexing helpers and multi-collection fallback reads/deletes. |
src/memos/graph_dbs/neo4j.py |
Adds optional Qdrant sync on writes and prefers external VecDB for search_by_embedding when configured. |
src/memos/configs/graph_db.py |
Extends Neo4jGraphDBConfig with optional vec_config for external vector syncing/search. |
src/memos/api/handlers/search_handler.py |
Adds per-db component caching/creation for Neo4j multi-db search flows. |
src/memos/api/handlers/component_init.py |
Introduces create_per_db_components to build isolated per-db graph/memory/search components. |
src/memos/api/handlers/add_handler.py |
Adds per-user component caching/creation for Neo4j multi-db add flows. |
src/memos/api/config.py |
Updates Neo4j config generation for multi-db naming and optional Qdrant sync configuration. |
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| payload = { | ||
| "memory": memory, | ||
| "vector_sync": "success", | ||
| **metadata, |
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| "user": os.getenv("NEO4J_USER", "neo4j"), | ||
| "db_name": f"memos{user_id.replace('-', '')}", | ||
| "db_name": f"{user_id.replace('_', '-')}", | ||
| "password": os.getenv("NEO4J_PASSWORD", "12345678"), | ||
| "auto_create": True, | ||
| "use_multi_db": True, |
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| # Shallow-copy the shared mem_reader and point its searcher at the new database | ||
| # so deduplication reads target the correct graph store. | ||
| new_mem_reader = copy.copy(base_components["mem_reader"]) |
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| if user_id not in self._per_user_cube_cache: | ||
| with self._cache_lock: | ||
| if user_id not in self._per_user_cube_cache: | ||
| self.logger.info( | ||
| f"[AddHandler] Creating per-user components for user_id={user_id!r}" | ||
| ) | ||
| self._per_user_cube_cache[user_id] = create_per_db_components( | ||
| db_name=user_id, | ||
| base_components=vars(self.deps), | ||
| ) | ||
| return self._per_user_cube_cache[user_id] |
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| point_ids: list[str | int] = ids | ||
| self.client.delete( | ||
| collection_name=self.config.collection_name, | ||
| points_selector=models.PointIdsList(points=point_ids), | ||
| ) | ||
| for collection_name in self._all_candidate_collections(): | ||
| self.client.delete( | ||
| collection_name=collection_name, | ||
| points_selector=models.PointIdsList(points=point_ids), | ||
| ) |
| vec_filter["user_name"] = user_name | ||
|
|
||
| if search_filter: | ||
| vec_filter.update(search_filter) |
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| def _get_per_db_components(self, db_name: str) -> dict[str, Any]: | ||
| """Return cached per-db components, creating them on first access.""" | ||
| if db_name not in self._per_db_cube_cache: | ||
| with self._cache_lock: | ||
| if db_name not in self._per_db_cube_cache: | ||
| self.logger.info( | ||
| f"[SearchHandler] Creating per-db components for db_name={db_name!r}" | ||
| ) | ||
| per_db = create_per_db_components( | ||
| db_name=db_name, | ||
| base_components=vars(self.deps), | ||
| ) | ||
| per_db["deepsearch_agent"] = DeepSearchMemAgent( | ||
| llm=self.llm, | ||
| memory_retriever=per_db["text_mem"], | ||
| ) | ||
| self._per_db_cube_cache[db_name] = per_db | ||
| return self._per_db_cube_cache[db_name] |
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Description
This commit fixes the limitation where the local API could not target a specific database and collection, which is required for Neo4j Enterprise and multi-DB setups. It introduces new configuration fields and threads the db/collection parameters through API handlers and initialization flow. The Neo4j and Qdrant adapters are updated accordingly to create/use the specified database and collection.
Type of change
Please delete options that are not relevant.
How Has This Been Tested?
Run test with
uv run --with pytest pytest -q test_multidb_handlers.py test_qdrant.py. Also, you can change different user_id in current examples and see new database/collection created at qdrant dashboard and neo4j browser.Checklist
Reviewer Checklist