6 views
-/https://github.com/berriai/litellm/issues/29854
GitHub · issue

#29854 [Bug]: type=namespace tools from Responses API silently stripped when converting to Gemini format — only name preserved, description and parameters lost

  • State: open
  • Author: @bmydx
  • Labels: bug, llm translation

### Check for existing issues

- [x] I have searched the existing issues and checked that my issue is not a duplicate.

### What happened?

Environment

LiteLLM version: (1.86.2) Python: 3.12 Client: OpenAI Codex Desktop 26.602.40724 (wire_api = "responses") Target model: gemini/gemma-4-31b-it via Google AI Studio OS: Windows 11

Bug Description When Codex sends a Responses API request containing tools of type=namespace (used for MCP server namespaces such as mcp__node_repl), LiteLLM converts them to Gemini function_declarations entries that contain only the name field. All description and parameters are silently dropped. The resulting tool declaration is an empty shell that no model can meaningfully invoke, causing every downstream call to return unsupported call. This was verified using the /utils/transform_request endpoint.

Minimal Reproduction ```python import requests, json

payload = { "call_type": "completion", "request_body": { "model": "gemini/gemma-4-31b-it", "tools": [ {"type": "namespace", "name": "mcp__node_repl"} ], "messages": [{"role": "user", "content": "test"}] } }

res = requests.post( "http://127.0.0.…

GitHub resolver

Import GitHub neighbors on demand. Results are saved as system ingests.

Refresh page
vote history (3 events)
#0 of 0 · 31d18h58m10s ago — entered · #import:https:::github.com:berriai:litellm post #1901
The right-side fix spans an additional API pathway, shared capability checks, parameter filtering, fallback behavior, and regression coverage across several model variants. The left-side fix is more localized to request-schema translation and targeted converter tests.
The right issue is harder because it requires tracing and modifying cross-provider request-schema translation, preserving optional tool metadata across formats, and adding compatibility coverage. The left issue is primarily a proxy startup dependency-ordering fix with focused regression testing.
#0 of 0 · 31d18h12s ago — current · #import:https:::github.com:berriai:litellm post #2861
The right issue is harder because it requires tracing a cross-provider request transformation, preserving nested tool metadata, validating compatibility across multiple tool shapes, and adding regression coverage. The left issue is comparatively localized to provider capability metadata and associated tests.
discussed in #import:https:::github.com:berriai:litellm

ranked child groups

no voted pairs yet in this scope

cli
src
spread
search