* fix(hosted_vllm): route through base_llm_http_handler to support ssl_verify
The hosted_vllm provider was falling through to the OpenAI catch-all path
which doesn't pass ssl_verify to the HTTP client. This adds an explicit
elif branch that routes hosted_vllm through base_llm_http_handler.completion()
which properly passes ssl_verify to the httpx client.
- Add explicit hosted_vllm branch in main.py completion()
- Add ssl_verify tests for sync and async completion
- Update existing audio_url test to mock httpx instead of OpenAI client
* feat(hosted_vllm): add embedding support with ssl_verify
- Add HostedVLLMEmbeddingConfig for embedding transformations
- Register hosted_vllm embedding config in utils.py
- Add lazy import for embedding transformation module
- Add unit test for ssl_verify parameter handling
Adds support for Anthropic-style 'thinking' parameter in hosted_vllm,
converting it to OpenAI-style 'reasoning_effort' since vLLM is
OpenAI-compatible.
This enables users to use Claude Code CLI with hosted vLLM models
like GLM-4.6/4.7 through the /v1/messages endpoint.
Mapping (same as Anthropic adapter):
- budget_tokens >= 10000 -> "high"
- budget_tokens >= 5000 -> "medium"
- budget_tokens >= 2000 -> "low"
- budget_tokens < 2000 -> "minimal"
Fixes#19761
* Vllm rerank (#12737)
* Add Hosted VLLM rerank provider integration
This commit implements the Hosted VLLM rerank provider integration for LiteLLM. The integration includes:
Adding Hosted VLLM as a supported rerank provider in the main rerank function
Implementing the HostedVLLMRerank handler class for making API requests
Creating a transformation class to convert Hosted VLLM responses to LiteLLM's standardized format
The integration supports both synchronous and asynchronous rerank operations. API credentials can be provided directly or through environment variables (HOSTED_VLLM_API_KEY and HOSTED_VLLM_API_BASE).
Notable features:
Proper error handling for missing credentials
Standard response transformation
Support for common rerank parameters (top_n, return_documents, etc.)
Proper token usage tracking
This expands LiteLLM's rerank provider ecosystem to include Hosted VLLM alongside existing providers like Cohere, Together AI, Azure AI, and Bedrock.
* refactor(rerank): use base_llm_http_handler for hosted_vllm rerank
- Replace custom HostedVLLMRerank handler with base_llm_http_handler
- Implement proper HostedVLLMRerankConfig inheriting from BaseRerankConfig
- Follow Cohere-compatible implementation pattern
- Clean up unnecessary comments
* Fix lint errors in hosted_vllm rerank transformer: remove unused imports
* Fix linting errors in rerank transformation modules
* fix: resolve type errors in Hosted VLLM rerank module
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Co-authored-by: Philip D'Souza <philip.dsouza@macro4.com>
Co-authored-by: Philip D'Souza <philip.a.dsouza@gmail.com>
* added a few tests
---------
Co-authored-by: Philip D'Souza <philip.dsouza@macro4.com>
Co-authored-by: Philip D'Souza <philip.a.dsouza@gmail.com>
