forked from phoenix-oss/llama-stack-mirror
dd7be274b9
# What does this PR do?
This PR fixes the behavior of the `/tool-runtime/rag-tool/query`
endpoint when invoked with an empty `vector_db_ids` parameter.
As of now, it simply returns an empty result, which leads to a
misleading error message from the server and makes it difficult and
time-consuming to detect the problem with the input parameter.
The proposed fix is to return an indicative error message in this case.
## Test Plan
Running the following script:
```
agent = Agent(
client,
model=MODEL_ID,
instructions=SYSTEM_PROMPT,
tools=[
dict(
name="builtin::rag/knowledge_search",
args={
"vector_db_ids": [],
},
)
],
)
response = agent.create_turn(
messages=[
{
"role": "user",
"content": "How to install OpenShift?",
}
],
session_id=agent.create_session(f"rag-session")
)
```
results in the following error message in the non-patched version:
```
{"type": "function", "name": "knowledge_search", "parameters": {"query": "installing OpenShift"}}400: Invalid value: Tool call result (id: 494b8020-90bb-449b-aa76-10960d6b2cc2, name: knowledge_search) does not have any content
```
and in the following one in the patched version:
```
{"type": "function", "name": "knowledge_search", "parameters": {"query": "installing OpenShift"}}400: Invalid value: No vector DBs were provided to the RAG tool. Please provide at least one DB.
```
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| .. | ||
| client-sdk/post_training | ||
| external-provider/llama-stack-provider-ollama | ||
| integration | ||
| unit | ||
| verifications | ||
| __init__.py | ||