README.md•1.52 kB
# Overview
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## Request or Contribute an Integration
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Don't see an integration you were looking for? We'd love to [hear from you!](https://github.com/Arize-ai/openinference/issues/new/choose)
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## Integration Types
Phoenix has a wide range of integrations. Generally these fall into a few categories:
1. **Tracing integrations** - where Phoenix will capture traces of applications built using a specific library.
1. _E.g._ [_OpenAI_](llm-providers/openai/)_,_ [_LangChain_](frameworks-and-platforms/langchain/)_,_ [_Vercel AI SDK_](frameworks-and-platforms/vercel/vercel-ai-sdk-tracing-js.md)_,_ [_Amazon Bedrock_](llm-providers/amazon-bedrock/)_,_ [_Hugging Face smolagents_](frameworks-and-platforms/hugging-face-smolagents/)
2. **Eval Model integrations** - where Phoenix's eval Python package will make calls to a specific model.
1. _E.g._ [_OpenAI_](llm-providers/openai/)_,_ [_Anthropic_](llm-providers/anthropic/)_,_ [_Google VertexAI_](llm-providers/vertexai/)_,_ [_Mistral_](llm-providers/mistralai/)
3. **Eval Library integrations** - where Phoenix traces can be evaluated using an outside eval library, instead of Phoenix's eval library, and visualized in Phoenix.
1. _E.g._ [_Ragas_](evaluation-integrations/ragas.md)_,_ [_Cleanlab_](evaluation-integrations/cleanlab.md)
Each partner listing in this section contains **integration docs** and **relevant tutorials.**