llama-stack-mirror/llama_stack/providers/inline/tool_runtime
Cesare Pompeiano 1c23aeb937
feat: Add vector_db_id to chunk metadata (#3304)
# 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>
2025-09-10 11:19:21 +02:00
..
rag feat: Add vector_db_id to chunk metadata (#3304) 2025-09-10 11:19:21 +02:00
__init__.py agents to use tools api (#673) 2025-01-08 19:01:00 -08:00