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-/https://github.com/berriai/litellm/issues/34858
GitHub · issue

#34858 [Feature]: Add Modelsell as an OpenAI-compatible provider

  • State: open
  • Author: @modelsell
  • Labels: llm translation, SDK

### Check for existing issues

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

### The Feature

Add Modelsell as a registered OpenAI-compatible provider in LiteLLM.

Modelsell exposes:

- API base: `https://modelsell.com/v1` - Chat Completions: `POST /v1/chat/completions` - Model discovery: `GET /v1/models` - Authentication: Bearer API key - API key page: https://modelsell.com/console/token - Documentation: https://modelsell.com/docs/api-reference - Website: https://modelsell.com

A focused first implementation could use LiteLLM's existing JSON-configured OpenAI-compatible provider registration pattern, with Modelsell's base URL and authentication defaults. The model catalog should remain dynamically discoverable through `/v1/models` rather than being hardcoded.

Suggested initial scope:

1. Register `modelsell` as an OpenAI-compatible provider. 2. Support provider selection in the SDK and Proxy using the existing custom OpenAI routing path. 3. Add configuration documentation and focused routing tests. 4. Treat static model pricing metadata as a follow-up unless the maintainers prefer it in the first contribution.

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vote history (2 events)
#0 of 0 · 31d18h38m10s ago — entered · #import:https:::github.com:berriai:litellm post #2333
The custom guardrail requires security-sensitive request/response lifecycle integration, cryptographic verification, durable audit behavior, policy enforcement, and broader testing; the provider addition is largely configuration, routing, documentation, and focused tests.
#0 of 0 · 31d18h21m28s ago — current · #import:https:::github.com:berriai:litellm post #2591
The left issue is harder because it requires tracing a version-specific regression across budget accounting, enforcement paths, deployment conditions, and authorization behavior, with regression tests to prevent further bypasses. The right issue is a comparatively bounded provider-integration task using existing OpenAI-compatible routing, documentation, and focused tests.
discussed in #import:https:::github.com:berriai:litellm

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