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fix: raise an error when no vector DB IDs are provided to the RAG tool (#1911)

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# 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.
```
This commit is contained in:
Ilya Kolchinsky 2025-05-12 11:25:13 +02:00 • committed by GitHub
parent f2b83800cc
commit dd7be274b9
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2 changed files with 22 additions and 1 deletions
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4
llama_stack/providers/inline/tool_runtime/rag/memory.py
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@ -105,7 +105,9 @@ class MemoryToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime, RAGToolRuntime):
query_config: RAGQueryConfig | None = None,
) -> RAGQueryResult:
if not vector_db_ids:
return RAGQueryResult(content=None)
raise ValueError(
"No vector DBs were provided to the knowledge search tool. Please provide at least one vector DB ID."
)
query_config = query_config or RAGQueryConfig()
query = await generate_rag_query(