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feat: Add rerank models and rerank API change (#3831)

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# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
- Extend the model type to include rerank models.
- Implement `rerank()` method in inference router.
- Add `rerank_model_list` to `OpenAIMixin` to enable providers to
register and identify rerank models
- Update documentation.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->
```
pytest tests/unit/providers/utils/inference/test_openai_mixin.py
```
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Jiayi Ni 2025-10-22 12:02:28 -07:00 • committed by GitHub
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docs/docs/providers/inference/index.mdx
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@ -3,9 +3,10 @@ description: "Inference
Llama Stack Inference API for generating completions, chat completions, and embeddings.
This API provides the raw interface to the underlying models. Two kinds of models are supported:
This API provides the raw interface to the underlying models. Three kinds of models are supported:
- LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
- Embedding models: these models generate embeddings to be used for semantic search."
- Embedding models: these models generate embeddings to be used for semantic search.
- Rerank models: these models reorder the documents based on their relevance to a query."
sidebar_label: Inference
title: Inference
---
@ -18,8 +19,9 @@ Inference
Llama Stack Inference API for generating completions, chat completions, and embeddings.
This API provides the raw interface to the underlying models. Two kinds of models are supported:
This API provides the raw interface to the underlying models. Three kinds of models are supported:
- LLM models: these models generate "raw" and "chat" (conversational) completions.
- Embedding models: these models generate embeddings to be used for semantic search.
- Rerank models: these models reorder the documents based on their relevance to a query.
This section contains documentation for all available providers for the **inference** API.