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Integration Types
Phoenix offers several types of integrations to support your AI development workflow:Tracing Integrations
Automatically capture traces from your AI applications built with popular frameworks and LLM providers.
Eval Model Integrations
Use any LLM provider to power Phoenix’s evaluation capabilities for scoring and classifying your traces.
Eval Library Integrations
Integrate with external evaluation libraries like Ragas and Cleanlab to visualize results in Phoenix.
Vector Database Integrations
Connect with vector databases for embedding analysis and retrieval debugging.
Span Processors
Convert traces from other instrumentation libraries to the OpenInference format.
Tracing Integrations
Phoenix captures detailed traces from your AI applications, giving you visibility into every step of your LLM pipeline.By Language
- Python
- TypeScript
- Java
LLM Providers
Phoenix provides native tracing support for all major LLM providers:
Platforms
Integrate Phoenix with AI development platforms and infrastructure:
Eval Model Integrations
Phoenix’s evaluation library (phoenix-evals) can use any LLM provider to power evaluations. These models score, classify, and analyze your traces.