AI DIAL Generic RAG Backend version
latest
What is the problem this feature will solve?
SearchTool.__call__ (src/generic_rag/app/mcp.py:337-374) runs a generation step per call, but:
- No usage tracking of any kind — no callback, no aggregation.
- Returns a plain
TextContent(type="text", text=text), with no usage signal.
- A caller invoking
rag_search has no way to learn its LLM cost or which model produced the answer.
What is the feature you are proposing to solve the problem?
- Track usage per model during
rag_search's generation step (e.g. a callback recording
model/deployment alongside each call's token counts).
- Expose it on the tool result via MCP's
_meta field (CallToolResult.meta, mcp.types) — the
field designed for this kind of extension data.
What alternatives have you considered?
No response
AI DIAL Generic RAG Backend version
latest
What is the problem this feature will solve?
SearchTool.__call__(src/generic_rag/app/mcp.py:337-374) runs a generation step per call, but:TextContent(type="text", text=text), with no usage signal.rag_searchhas no way to learn its LLM cost or which model produced the answer.What is the feature you are proposing to solve the problem?
rag_search's generation step (e.g. a callback recordingmodel/deploymentalongside each call's token counts)._metafield (CallToolResult.meta,mcp.types) — thefield designed for this kind of extension data.
What alternatives have you considered?
No response