# Integrations

Ragas is a framework and can be integrated with a host of different frameworks and tools so that you can use Ragas with your own toolchain. If any tool you want is not supported feel free to raise an [issue](https://github.com/vibrantlabsai/ragas/issues/new) and we'll be more than happy to look into it 🙂

## Frameworks

- [Amazon Bedrock](https://docs.ragas.io/en/stable/howtos/integrations/amazon_bedrock/index.md) - Amazon Bedrock is a managed framework for building, deploying, and scaling intelligent agents and integrated AI solutions; more information can be found [here](https://aws.amazon.com/bedrock/).
- [Haystack](https://docs.ragas.io/en/stable/howtos/integrations/haystack/index.md) - Haystack is a LLM orchestration framework to build customizable, production-ready LLM applications, more information can be found [here](https://haystack.deepset.ai/).
- [Griptape](https://docs.ragas.io/en/stable/howtos/integrations/griptape/index.md) - Griptape framework simplifies generative AI application development through flexible abstractions for LLMs, RAG, and more, additional information can be found [here](https://docs.griptape.ai/stable/griptape-framework/).
- [Langchain](https://docs.ragas.io/en/stable/howtos/integrations/langchain/index.md) - Langchain is a framework for building LLM applications, more information can be found [here](https://www.langchain.com/).
- [LlamaIndex for RAG](https://docs.ragas.io/en/stable/howtos/integrations/_llamaindex/index.md) - LlamaIndex is a framework for building RAG applications, more information can be found [here](https://www.llamaindex.ai/).
- [LlamaIndex for Agents](https://docs.ragas.io/en/stable/howtos/integrations/llamaindex_agents/index.md) - LlamaIndex enables building intelligent, semi-autonomous agents, more information can be found [here](https://www.llamaindex.ai/).
- [LlamaStack](https://docs.ragas.io/en/stable/howtos/integrations/llama_stack/index.md) – A unified framework by Meta for building and deploying generative AI apps across local, cloud, and mobile; [docs](https://llama-stack.readthedocs.io/en/latest/)
- [OCI Gen AI](https://docs.ragas.io/en/stable/howtos/integrations/oci_genai/index.md) - Oracle Cloud Infrastructure Generative AI provides access to various LLM models including Cohere, Meta, and Mistral models for RAG evaluation.
- [R2R](https://docs.ragas.io/en/stable/howtos/integrations/r2r/index.md) - R2R is an all-in-one solution for AI Retrieval-Augmented Generation (RAG) with production-ready features, more information can be found [here](https://r2r-docs.sciphi.ai/introduction)
- [Swarm](https://docs.ragas.io/en/stable/howtos/integrations/swarm_agent_evaluation/index.md) - Swarm is a framework for orchestrating multiple AI agents, more information can be found [here](https://github.com/openai/swarm).

## Tracing Tools

Tools that help you trace the LLM calls can be integrated with Ragas to get the traces of the evaluator LLMs.

- [Arize Phoenix](https://docs.ragas.io/en/stable/howtos/integrations/_arize/index.md) - Arize is a platform for observability and debugging of LLMs, more information can be found [here](https://phoenix.arize.com/).
- [LangSmith](https://docs.ragas.io/en/stable/howtos/integrations/langsmith/index.md) - LangSmith is a platform for observability and debugging of LLMs from LangChain, more information can be found [here](https://www.langchain.com/langsmith).