phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-10-04 12:07:34 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

feat: Add vector_db_id to chunk metadata (#3304)

Browse source 
# What does this PR do?

When running RAG in a multi vector DB setting, it can be difficult to
trace where retrieved chunks originate from. This PR adds the
`vector_db_id` into each chunk’s metadata, making it easier to
understand which database a given chunk came from. This is helpful for
debugging and for analyzing retrieval behavior of multiple DBs.

Relevant code:

```python
for vector_db_id, result in zip(vector_db_ids, results):
    for chunk, score in zip(result.chunks, result.scores):
        if not hasattr(chunk, "metadata") or chunk.metadata is None:
            chunk.metadata = {}
        chunk.metadata["vector_db_id"] = vector_db_id

        chunks.append(chunk)
        scores.append(score)
```

## Test Plan

* Ran Llama Stack in debug mode.
* Verified that `vector_db_id` was added to each chunk’s metadata.
* Confirmed that the metadata was printed in the console when using the
RAG tool.

---------

Co-authored-by: are-ces <cpompeia@redhat.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>
This commit is contained in:
Cesare Pompeiano 2025-09-10 11:19:21 +02:00 • committed by Sébastien Han
parent ce5885d27c
commit fe517f1ac7
No known key found for this signature in database
2 changed files with 69 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

16
llama_stack/providers/inline/tool_runtime/rag/memory.py
View file

@ -167,8 +167,18 @@ class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, RAGToolRunti
for vector_db_id in vector_db_ids
]
results: list[QueryChunksResponse] = await asyncio.gather(*tasks)
chunks = [c for r in results for c in r.chunks]
scores = [s for r in results for s in r.scores]
chunks = []
scores = []
for vector_db_id, result in zip(vector_db_ids, results, strict=False):
for chunk, score in zip(result.chunks, result.scores, strict=False):
if not hasattr(chunk, "metadata") or chunk.metadata is None:
chunk.metadata = {}
chunk.metadata["vector_db_id"] = vector_db_id
chunks.append(chunk)
scores.append(score)
if not chunks:
return RAGQueryResult(content=None)
@ -203,6 +213,7 @@ class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, RAGToolRunti
metadata_keys_to_exclude_from_context = [
"token_count",
"metadata_token_count",
"vector_db_id",
]
metadata_for_context = {}
for k in chunk_metadata_keys_to_include_from_context:
@ -227,6 +238,7 @@ class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime, RAGToolRunti
"document_ids": [c.metadata["document_id"] for c in chunks[: len(picked)]],
"chunks": [c.content for c in chunks[: len(picked)]],
"scores": scores[: len(picked)],
"vector_db_ids": [c.metadata["vector_db_id"] for c in chunks[: len(picked)]],
},
)