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# 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>
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| .. | ||
| agents | ||
| batches | ||
| datasetio | ||
| eval | ||
| files/localfs | ||
| inference | ||
| ios/inference | ||
| post_training | ||
| safety | ||
| scoring | ||
| telemetry | ||
| tool_runtime | ||
| vector_io | ||
| __init__.py | ||