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[Docs] v1.72.2.rc (#11519)
* v1-72-2.rc * docs v1.72.2.rc * docs 1.72.2.rc * docs update * docs Bug Fixes * add TLDR section * add table * docs release notes * docs v1-72-2-stable * docs /v1/messages * docs hf rerank
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docs/my-website/docs/providers/huggingface_rerank.md
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docs/my-website/docs/providers/huggingface_rerank.md
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@ -0,0 +1,263 @@
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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import Image from '@theme/IdealImage';
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# HuggingFace Rerank
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HuggingFace Rerank allows you to use reranking models hosted on Hugging Face infrastructure or your custom endpoints to reorder documents based on their relevance to a query.
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| Property | Details |
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|----------|---------|
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| Description | HuggingFace Rerank enables semantic reranking of documents using models hosted on Hugging Face infrastructure or custom endpoints. |
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| Provider Route on LiteLLM | `huggingface/` in model name |
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| Provider Doc | [Hugging Face Hub ↗](https://huggingface.co/models?pipeline_tag=sentence-similarity) |
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## Quick Start
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### LiteLLM Python SDK
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```python showLineNumbers title="Example using LiteLLM Python SDK"
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import litellm
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import os
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# Set your HuggingFace token
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os.environ["HF_TOKEN"] = "hf_xxxxxx"
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# Basic rerank usage
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response = litellm.rerank(
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model="huggingface/BAAI/bge-reranker-base",
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query="What is the capital of the United States?",
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documents=[
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"Carson City is the capital city of the American state of Nevada.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
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"Washington, D.C. is the capital of the United States.",
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"Capital punishment has existed in the United States since before it was a country.",
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],
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top_n=3,
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)
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print(response)
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```
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### Custom Endpoint Usage
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```python showLineNumbers title="Using custom HuggingFace endpoint"
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import litellm
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response = litellm.rerank(
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model="huggingface/BAAI/bge-reranker-base",
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query="hello",
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documents=["hello", "world"],
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top_n=2,
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api_base="https://my-custom-hf-endpoint.com",
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api_key="test_api_key",
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)
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print(response)
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```
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### Async Usage
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```python showLineNumbers title="Async rerank example"
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import litellm
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import asyncio
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import os
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os.environ["HF_TOKEN"] = "hf_xxxxxx"
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async def async_rerank_example():
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response = await litellm.arerank(
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model="huggingface/BAAI/bge-reranker-base",
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query="What is the capital of the United States?",
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documents=[
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"Carson City is the capital city of the American state of Nevada.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
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"Washington, D.C. is the capital of the United States.",
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"Capital punishment has existed in the United States since before it was a country.",
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],
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top_n=3,
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)
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print(response)
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asyncio.run(async_rerank_example())
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```
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## LiteLLM Proxy
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### 1. Configure your model in config.yaml
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<Tabs>
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<TabItem value="config-yaml" label="config.yaml">
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```yaml
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model_list:
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- model_name: bge-reranker-base
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litellm_params:
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model: huggingface/BAAI/bge-reranker-base
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api_key: os.environ/HF_TOKEN
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- model_name: bge-reranker-large
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litellm_params:
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model: huggingface/BAAI/bge-reranker-large
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api_key: os.environ/HF_TOKEN
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- model_name: custom-reranker
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litellm_params:
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model: huggingface/BAAI/bge-reranker-base
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api_base: https://my-custom-hf-endpoint.com
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api_key: your-custom-api-key
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```
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</TabItem>
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</Tabs>
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### 2. Start the proxy
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```bash
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export HF_TOKEN="hf_xxxxxx"
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litellm --config /path/to/config.yaml
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# RUNNING on http://0.0.0.0:4000
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```
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### 3. Make rerank requests
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<Tabs>
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<TabItem value="curl" label="Curl">
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```bash
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curl http://localhost:4000/rerank \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer $LITELLM_API_KEY" \
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-d '{
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"model": "bge-reranker-base",
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"query": "What is the capital of the United States?",
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"documents": [
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"Carson City is the capital city of the American state of Nevada.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
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"Washington, D.C. is the capital of the United States.",
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"Capital punishment has existed in the United States since before it was a country."
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],
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"top_n": 3
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}'
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```
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</TabItem>
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<TabItem value="python-sdk" label="Python SDK">
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```python
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import litellm
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# Initialize with your LiteLLM proxy URL
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response = litellm.rerank(
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model="bge-reranker-base",
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query="What is the capital of the United States?",
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documents=[
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"Carson City is the capital city of the American state of Nevada.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
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"Washington, D.C. is the capital of the United States.",
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"Capital punishment has existed in the United States since before it was a country.",
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],
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top_n=3,
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api_base="http://localhost:4000",
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api_key="your-litellm-api-key"
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)
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print(response)
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```
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</TabItem>
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<TabItem value="requests" label="Using requests library">
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```python
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import requests
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url = "http://localhost:4000/rerank"
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headers = {
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"Authorization": "Bearer your-litellm-api-key",
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"Content-Type": "application/json"
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}
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data = {
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"model": "bge-reranker-base",
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"query": "What is the capital of the United States?",
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"documents": [
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"Carson City is the capital city of the American state of Nevada.",
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"The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
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"Washington, D.C. is the capital of the United States.",
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"Capital punishment has existed in the United States since before it was a country."
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],
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"top_n": 3
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}
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response = requests.post(url, headers=headers, json=data)
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print(response.json())
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```
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</TabItem>
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</Tabs>
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## Configuration Options
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### Authentication
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#### Using HuggingFace Token (Serverless)
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```python
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import os
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os.environ["HF_TOKEN"] = "hf_xxxxxx"
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# Or pass directly
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litellm.rerank(
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model="huggingface/BAAI/bge-reranker-base",
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api_key="hf_xxxxxx",
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# ... other params
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)
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```
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#### Using Custom Endpoint
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```python
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litellm.rerank(
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model="huggingface/BAAI/bge-reranker-base",
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api_base="https://your-custom-endpoint.com",
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api_key="your-custom-key",
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# ... other params
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)
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```
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## Response Format
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The response follows the standard rerank API format:
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```json
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{
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"results": [
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{
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"index": 3,
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"relevance_score": 0.999071
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},
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{
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"index": 4,
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"relevance_score": 0.7867867
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},
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{
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"index": 0,
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"relevance_score": 0.32713068
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}
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],
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"id": "07734bd2-2473-4f07-94e1-0d9f0e6843cf",
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"meta": {
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"api_version": {
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"version": "2",
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"is_experimental": false
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},
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"billed_units": {
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"search_units": 1
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}
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}
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}
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```
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@ -116,4 +116,5 @@ curl http://0.0.0.0:4000/rerank \
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| Azure AI| [Usage](../docs/providers/azure_ai) |
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| Jina AI| [Usage](../docs/providers/jina_ai) |
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| AWS Bedrock| [Usage](../docs/providers/bedrock#rerank-api) |
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| HuggingFace| [Usage](../docs/providers/huggingface_rerank) |
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| Infinity| [Usage](../docs/providers/infinity) |
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BIN
docs/my-website/img/release_notes/v1_messages_perf.png
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BIN
docs/my-website/img/release_notes/v1_messages_perf.png
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Binary file not shown.
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After Width: | Height: | Size: 515 KiB |
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@ -19,15 +19,6 @@ import Image from '@theme/IdealImage';
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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:::info
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The release candidate is live now.
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The production release will be live on Wednesday.
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:::
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## Deploy this version
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<Tabs>
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240
docs/my-website/release_notes/v1.72.2/index.md
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240
docs/my-website/release_notes/v1.72.2/index.md
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@ -0,0 +1,240 @@
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---
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title: "[Pre Release] v1.72.2-stable"
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slug: "v1-72-2-stable"
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date: 2025-06-07T10:00:00
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authors:
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- name: Krrish Dholakia
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title: CEO, LiteLLM
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url: https://www.linkedin.com/in/krish-d/
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image_url: https://media.licdn.com/dms/image/v2/D4D03AQGrlsJ3aqpHmQ/profile-displayphoto-shrink_400_400/B4DZSAzgP7HYAg-/0/1737327772964?e=1749686400&v=beta&t=Hkl3U8Ps0VtvNxX0BNNq24b4dtX5wQaPFp6oiKCIHD8
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- name: Ishaan Jaffer
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title: CTO, LiteLLM
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url: https://www.linkedin.com/in/reffajnaahsi/
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image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
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hide_table_of_contents: false
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---
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import Image from '@theme/IdealImage';
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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:::info
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The release candidate is live now.
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The production release will be live on Wednesday.
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:::
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## Deploy this version
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<Tabs>
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<TabItem value="docker" label="Docker">
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``` showLineNumbers title="docker run litellm"
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docker run
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-e STORE_MODEL_IN_DB=True
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-p 4000:4000
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ghcr.io/berriai/litellm:main-v1.72.2.rc
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```
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</TabItem>
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<TabItem value="pip" label="Pip">
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``` showLineNumbers title="pip install litellm"
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pip install litellm==1.72.2
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```
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</TabItem>
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</Tabs>
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## TLDR
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* **Why Upgrade**
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- /v1/messages API performance improvements (lower latency, higher RPS)
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- Multi instance rate limiting support
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- Full Claude-4 cost tracking & Gemini 2.5 Pro preview
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* **Who Should Read**
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- Teams using `/v1/messages` API (Claude Code), LiteLLM Rate Limiting
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* **Risk of Upgrade**
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- **Medium**
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- Upgraded `ddtrace==3.8.0`, if you use DataDog tracing this is a medium level risk. We recommend monitoring logs for any issues.
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---
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## `/v1/messages` Performance Improvements
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This release brings significant performance improvements to the `/v1/messages` API. For large streaming requests LiteLLM overhead latency is now 50ms and can handle 250 RPS per instance.
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<Image
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img={require('../../img/release_notes/v1_messages_perf.png')}
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style={{width: '100%', display: 'block', margin: '2rem auto'}}
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/>
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## New Models / Updated Models
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**Newly Added Models**
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| Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) |
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| ----------- | -------------------------------------- | -------------- | ------------------- | -------------------- |
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| Anthropic | `claude-4-opus-20250514` | 200K | $15.00 | $75.00 |
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| Anthropic | `claude-4-sonnet-20250514` | 200K | $3.00 | $15.00 |
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| VertexAI, Google AI Studio | `gemini-2.5-pro-preview-06-05` | 1M | $1.25 | $10.00 |
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| OpenAI | `codex-mini-latest` | 200K | $1.50 | $6.00 |
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| Cerebras | `qwen-3-32b` | 128K | $0.40 | $0.80 |
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| SambaNova | `DeepSeek-R1` | 32K | $5.00 | $7.00 |
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| SambaNova | `DeepSeek-R1-Distill-Llama-70B` | 131K | $0.70 | $1.40 |
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### Model Updates
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- **[Anthropic](../../docs/providers/anthropic)**
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- Cost tracking added for new Claude models - [PR](https://github.com/BerriAI/litellm/pull/11339)
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- `claude-4-opus-20250514`
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- `claude-4-sonnet-20250514`
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- **[Google AI Studio](../../docs/providers/gemini)**
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- Google Gemini 2.5 Pro Preview 06-05 support - [PR](https://github.com/BerriAI/litellm/pull/11447)
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- Gemini streaming thinking content parsing with `reasoning_content` - [PR](https://github.com/BerriAI/litellm/pull/11298)
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- Support for no reasoning option for Gemini models - [PR](https://github.com/BerriAI/litellm/pull/11393)
|
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- URL context support for Gemini models - [PR](https://github.com/BerriAI/litellm/pull/11351)
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- Gemini embeddings-001 model prices and context window - [PR](https://github.com/BerriAI/litellm/pull/11332)
|
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- **[OpenAI](../../docs/providers/openai)**
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- Cost tracking for `codex-mini-latest` - [PR](https://github.com/BerriAI/litellm/pull/11492)
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- **[Vertex AI](../../docs/providers/vertex)**
|
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- Cache token tracking on streaming calls - [PR](https://github.com/BerriAI/litellm/pull/11387)
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- Return response_id matching upstream response ID for stream and non-stream - [PR](https://github.com/BerriAI/litellm/pull/11456)
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- **[Cerebras](../../docs/providers/cerebras)**
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- Cerebras/qwen-3-32b model pricing and context window - [PR](https://github.com/BerriAI/litellm/pull/11373)
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- **[HuggingFace](../../docs/providers/huggingface)**
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- Fixed embeddings using non-default `input_type` - [PR](https://github.com/BerriAI/litellm/pull/11452)
|
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- **[DataRobot](../../docs/providers/datarobot)**
|
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- New provider integration for enterprise AI workflows - [PR](https://github.com/BerriAI/litellm/pull/10385)
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- **[DeepSeek](../../docs/providers/together_ai)**
|
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- DeepSeek R1 family model configuration via Together AI - [PR](https://github.com/BerriAI/litellm/pull/11394)
|
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- DeepSeek R1 pricing and context window configuration - [PR](https://github.com/BerriAI/litellm/pull/11339)
|
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|
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---
|
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|
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## LLM API Endpoints
|
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|
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- **[Images API](../../docs/image_generation)**
|
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- Azure endpoint support for image endpoints - [PR](https://github.com/BerriAI/litellm/pull/11482)
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- **[Anthropic Messages API](../../docs/completion/chat)**
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- Support for ALL LiteLLM Providers (OpenAI, Azure, Bedrock, Vertex, DeepSeek, etc.) on /v1/messages API Spec - [PR](https://github.com/BerriAI/litellm/pull/11502)
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- Performance improvements for /v1/messages route - [PR](https://github.com/BerriAI/litellm/pull/11421)
|
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- Return streaming usage statistics when using LiteLLM with Bedrock models - [PR](https://github.com/BerriAI/litellm/pull/11469)
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- **[Embeddings API](../../docs/embedding/supported_embedding)**
|
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- Provider-specific optional params handling for embedding calls - [PR](https://github.com/BerriAI/litellm/pull/11346)
|
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- Proper Sagemaker request attribute usage for embeddings - [PR](https://github.com/BerriAI/litellm/pull/11362)
|
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- **[Rerank API](../../docs/rerank/supported_rerank)**
|
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- New HuggingFace rerank provider support - [PR](https://github.com/BerriAI/litellm/pull/11438)
|
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|
||||
---
|
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|
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## Spend Tracking
|
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|
||||
- Added token tracking for anthropic batch calls via /anthropic passthrough route- [PR](https://github.com/BerriAI/litellm/pull/11388)
|
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|
||||
---
|
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|
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## Management Endpoints / UI
|
||||
|
||||
|
||||
- **SSO/Authentication**
|
||||
- SSO configuration endpoints and UI integration with persistent settings - [PR](https://github.com/BerriAI/litellm/pull/11417)
|
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- Update proxy admin ID role in DB + Handle SSO redirects with custom root path - [PR](https://github.com/BerriAI/litellm/pull/11384)
|
||||
- Support returning virtual key in custom auth - [PR](https://github.com/BerriAI/litellm/pull/11346)
|
||||
- User ID validation to ensure it is not an email or phone number - [PR](https://github.com/BerriAI/litellm/pull/10102)
|
||||
- **Teams**
|
||||
- Fixed Create/Update team member API 500 error - [PR](https://github.com/BerriAI/litellm/pull/10479)
|
||||
- Enterprise feature gating for RegenerateKeyModal in KeyInfoView - [PR](https://github.com/BerriAI/litellm/pull/11400)
|
||||
- **SCIM**
|
||||
- Fixed SCIM running patch operation case sensitivity - [PR](https://github.com/BerriAI/litellm/pull/11335)
|
||||
- **General**
|
||||
- Converted action buttons to sticky footer action buttons - [PR](https://github.com/BerriAI/litellm/pull/11293)
|
||||
- Custom Server Root Path improvements - don't require reserving `/litellm` route - [PR](https://github.com/BerriAI/litellm/pull/11460)
|
||||
---
|
||||
|
||||
## Logging / Guardrails Integrations
|
||||
|
||||
#### Logging
|
||||
- **[S3](../../docs/proxy/logging#s3)**
|
||||
- Async + Batched S3 Logging for improved performance - [PR](https://github.com/BerriAI/litellm/pull/11340)
|
||||
- **[DataDog](../../docs/observability/datadog_integration)**
|
||||
- Add instrumentation for streaming chunks - [PR](https://github.com/BerriAI/litellm/pull/11338)
|
||||
- Add DD profiler to monitor Python profile of LiteLLM CPU% - [PR](https://github.com/BerriAI/litellm/pull/11375)
|
||||
- Bump DD trace version - [PR](https://github.com/BerriAI/litellm/pull/11426)
|
||||
- **[Prometheus](../../docs/proxy/prometheus)**
|
||||
- Pass custom metadata labels in litellm_total_token metrics - [PR](https://github.com/BerriAI/litellm/pull/11414)
|
||||
- **[GCS](../../docs/proxy/logging#google-cloud-storage)**
|
||||
- Update GCSBucketBase to handle GSM project ID if passed - [PR](https://github.com/BerriAI/litellm/pull/11409)
|
||||
|
||||
#### Guardrails
|
||||
- **[Presidio](../../docs/proxy/guardrails/presidio)**
|
||||
- Add presidio_language yaml configuration support for guardrails - [PR](https://github.com/BerriAI/litellm/pull/11331)
|
||||
|
||||
---
|
||||
|
||||
## Performance / Reliability Improvements
|
||||
|
||||
- **Performance Optimizations**
|
||||
- Don't run auth on /health/liveliness endpoints - [PR](https://github.com/BerriAI/litellm/pull/11378)
|
||||
- Don't create 1 task for every hanging request alert - [PR](https://github.com/BerriAI/litellm/pull/11385)
|
||||
- Add debugging endpoint to track active /asyncio-tasks - [PR](https://github.com/BerriAI/litellm/pull/11382)
|
||||
- Make batch size for maximum retention in spend logs controllable - [PR](https://github.com/BerriAI/litellm/pull/11459)
|
||||
- Expose flag to disable token counter - [PR](https://github.com/BerriAI/litellm/pull/11344)
|
||||
- Support pipeline redis lpop for older redis versions - [PR](https://github.com/BerriAI/litellm/pull/11425)
|
||||
---
|
||||
|
||||
## Bug Fixes
|
||||
|
||||
- **LLM API Fixes**
|
||||
- **Anthropic**: Fix regression when passing file url's to the 'file_id' parameter - [PR](https://github.com/BerriAI/litellm/pull/11387)
|
||||
- **Vertex AI**: Fix Vertex AI any_of issues for Description and Default. - [PR](https://github.com/BerriAI/litellm/issues/11383)
|
||||
- Fix transcription model name mapping - [PR](https://github.com/BerriAI/litellm/pull/11333)
|
||||
- **Image Generation**: Fix None values in usage field for gpt-image-1 model responses - [PR](https://github.com/BerriAI/litellm/pull/11448)
|
||||
- **Responses API**: Fix _transform_responses_api_content_to_chat_completion_content doesn't support file content type - [PR](https://github.com/BerriAI/litellm/pull/11494)
|
||||
- **Fireworks AI**: Fix rate limit exception mapping - detect "rate limit" text in error messages - [PR](https://github.com/BerriAI/litellm/pull/11455)
|
||||
- **Spend Tracking/Budgets**
|
||||
- Respect user_header_name property for budget selection and user identification - [PR](https://github.com/BerriAI/litellm/pull/11419)
|
||||
- **MCP Server**
|
||||
- Remove duplicate server_id MCP config servers - [PR](https://github.com/BerriAI/litellm/pull/11327)
|
||||
- **Function Calling**
|
||||
- supports_function_calling works with llm_proxy models - [PR](https://github.com/BerriAI/litellm/pull/11381)
|
||||
- **Knowledge Base**
|
||||
- Fixed Knowledge Base Call returning error - [PR](https://github.com/BerriAI/litellm/pull/11467)
|
||||
|
||||
---
|
||||
|
||||
## New Contributors
|
||||
* [@mjnitz02](https://github.com/mjnitz02) made their first contribution in [#10385](https://github.com/BerriAI/litellm/pull/10385)
|
||||
* [@hagan](https://github.com/hagan) made their first contribution in [#10479](https://github.com/BerriAI/litellm/pull/10479)
|
||||
* [@wwells](https://github.com/wwells) made their first contribution in [#11409](https://github.com/BerriAI/litellm/pull/11409)
|
||||
* [@likweitan](https://github.com/likweitan) made their first contribution in [#11400](https://github.com/BerriAI/litellm/pull/11400)
|
||||
* [@raz-alon](https://github.com/raz-alon) made their first contribution in [#10102](https://github.com/BerriAI/litellm/pull/10102)
|
||||
* [@jtsai-quid](https://github.com/jtsai-quid) made their first contribution in [#11394](https://github.com/BerriAI/litellm/pull/11394)
|
||||
* [@tmbo](https://github.com/tmbo) made their first contribution in [#11362](https://github.com/BerriAI/litellm/pull/11362)
|
||||
* [@wangsha](https://github.com/wangsha) made their first contribution in [#11351](https://github.com/BerriAI/litellm/pull/11351)
|
||||
* [@seankwalker](https://github.com/seankwalker) made their first contribution in [#11452](https://github.com/BerriAI/litellm/pull/11452)
|
||||
* [@pazevedo-hyland](https://github.com/pazevedo-hyland) made their first contribution in [#11381](https://github.com/BerriAI/litellm/pull/11381)
|
||||
* [@cainiaoit](https://github.com/cainiaoit) made their first contribution in [#11438](https://github.com/BerriAI/litellm/pull/11438)
|
||||
* [@vuanhtu52](https://github.com/vuanhtu52) made their first contribution in [#11508](https://github.com/BerriAI/litellm/pull/11508)
|
||||
|
||||
---
|
||||
|
||||
## Demo Instance
|
||||
|
||||
Here's a Demo Instance to test changes:
|
||||
|
||||
- Instance: https://demo.litellm.ai/
|
||||
- Login Credentials:
|
||||
- Username: admin
|
||||
- Password: sk-1234
|
||||
|
||||
## [Git Diff](https://github.com/BerriAI/litellm/releases)
|
||||
|
|
@ -340,7 +340,14 @@ const sidebars = {
|
|||
"providers/codestral",
|
||||
"providers/cohere",
|
||||
"providers/anyscale",
|
||||
"providers/huggingface",
|
||||
{
|
||||
type: "category",
|
||||
label: "HuggingFace",
|
||||
items: [
|
||||
"providers/huggingface",
|
||||
"providers/huggingface_rerank",
|
||||
]
|
||||
},
|
||||
"providers/databricks",
|
||||
"providers/deepgram",
|
||||
"providers/watsonx",
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue