# Integrations Overview Hugging Face Inference Providers works with a growing ecosystem of developer tools, frameworks, and platforms. These integrations let you use state-of-the-art models in your existing workflows and development environments. If a tool doesn't have explicit support for Inference Providers, it is often still compatible via its OpenAI-compatible API support. Check the documentation for your tool to see if it can be configured to use custom endpoints. ## Why Use Integrations? - **Keep your existing tools**: Use Inference Providers with tools you already know - **Access dozens of providers**: Switch between providers without changing your code - **Zero markup pricing**: Get the same rates as going direct to providers - **Single API token**: One HF token for all providers and models ## Overview This table lists _some_ tools, libraries, and applications that work with Hugging Face Inference Providers. For detailed setup instructions, follow the links in the Resources column. | Integration | Description | Resources | | ------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- | | [Claude Code](https://docs.anthropic.com/en/docs/claude-code) | Agentic coding tool for the terminal | [HF docs](./claude-code) | | [CrewAI](https://www.crewai.com/) | Framework for orchestrating AI agent teams | [Official docs](https://docs.crewai.com/en/concepts/llms#hugging-face) | | [NeMo Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner) | Synthetic dataset generation framework | [HF docs](./datadesigner) | | [GitHub Copilot Chat](https://docs.github.com/en/copilot) | AI pair programmer in VS Code | [HF docs](./vscode) | | [fast-agent](https://fast-agent.ai/) | Flexible framework building MCP/ACP powered Agents, Workflows and evals | [Official docs](https://fast-agent.ai/models/llm_providers/#hugging-face) | | [Hermes Agent](https://github.com/NousResearch/hermes-agent) | Open-source AI agent CLI for coding and development | [Official docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration/#hugging-face-inference-providers) / [HF docs](./hermes-agent) | | [Haystack](https://haystack.deepset.ai/) | Open-source LLM framework for building production applications | [Official docs](https://docs.haystack.deepset.ai/docs/huggingfaceapichatgenerator) | | [Inspect](https://inspect.aisi.org.uk/) | AI safety and evaluation framework | [Official docs](https://inspect.aisi.org.uk/providers.html#hugging-face) | | [LangChain](https://www.langchain.com/) | LLM application framework | [Official docs](https://docs.langchain.com/oss/python/integrations/providers/huggingface#huggingfaceendpoint) | | [LiteLLM](https://www.litellm.ai/) | Unified interface for 100+ LLMs | [Official docs](https://docs.litellm.ai/docs/providers/huggingface) | | [LlamaIndex](https://www.llamaindex.ai/) | Data framework for LLM applications | [Official docs](https://developers.llamaindex.ai/python/examples/llm/huggingface/#use-a-model-via-inference-providers) | | [MacWhisper](https://goodsnooze.gumroad.com/l/macwhisper) | Speech-to-text application for macOS | [HF docs](./macwhisper) | | [OpenCode](https://opencode.ai/) | AI coding agent built for the terminal | [Official docs](https://opencode.ai/docs/providers#hugging-face) / [HF docs](./opencode) | | [Pi](https://github.com/badlogic/pi-mono) | Minimalist terminal-based coding assistant | [Official docs](https://github.com/badlogic/pi-mono) / [HF docs](./pi) | | [PydanticAI](https://ai.pydantic.dev/) | Framework for building AI agents with Python | [Official docs](https://ai.pydantic.dev/models/huggingface/) | | [Roo Code](https://roocode.com/) | AI-powered code generation and refactoring | [Official docs](https://docs.roocode.com/providers/huggingface) | | [smolagents](https://huggingface.co/docs/smolagents) | Framework for building LLM agents with tool integration | [Official docs](https://huggingface.co/docs/smolagents/reference/models#smolagents.InferenceClientModel) | | [Vision Agents](https://visionagents.ai/) | SDK for real-time AI with text and vision language models | [Official docs](https://visionagents.ai/integrations/huggingface) / [HF docs](./visionagents) | ## Integrations by Category ### API Clients Client libraries and gateways for simplified LLM access. - [LiteLLM](https://www.litellm.ai/) - Unified interface for calling 100+ LLMs with the same format ([Official docs](https://docs.litellm.ai/docs/providers/huggingface)) ### Applications End-user applications and interfaces powered by LLMs. - [MacWhisper](https://goodsnooze.gumroad.com/l/macwhisper) - Speech-to-text application for macOS ([HF docs](./macwhisper)) ### Developer Tools AI-powered coding assistants and development environments. - [Claude Code](https://docs.anthropic.com/en/docs/claude-code) - Agentic coding tool for the terminal ([HF docs](./claude-code)) - [GitHub Copilot Chat](https://docs.github.com/en/copilot) - AI pair programmer in VS Code ([HF docs](./vscode)) - [Hermes Agent](https://github.com/NousResearch/hermes-agent) - Open-source AI agent CLI for coding and development ([Official docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration/#hugging-face-inference-providers) / [HF docs](./hermes-agent)) - [OpenCode](https://opencode.ai/) - AI coding agent built for the terminal ([Official docs](https://opencode.ai/docs/providers#hugging-face) / [HF docs](./opencode)) - [Pi](https://github.com/badlogic/pi-mono) - Minimalist terminal-based coding assistant ([Official docs](https://github.com/badlogic/pi-mono) / [HF docs](./pi)) - [Roo Code](https://roocode.com/) - AI-powered code generation and refactoring ([Official docs](https://docs.roocode.com/providers/huggingface)) ### Evaluation Frameworks Tools for assessing and ensuring AI safety and performance. - [Inspect](https://inspect.aisi.org.uk/) - AI safety and evaluation framework ([Official docs](https://inspect.aisi.org.uk/providers.html#hugging-face)) ### LLM Frameworks LLM application frameworks and orchestration platforms. - [CrewAI](https://www.crewai.com/) - Framework for orchestrating AI agent teams ([Official docs](https://docs.crewai.com/en/concepts/llms#hugging-face)) - [fast-agent](https://fast-agent.ai/) - Flexible framework building MCP/ACP powered Agents, Workflows and evals ([Official docs](https://fast-agent.ai/models/llm_providers/#hugging-face)) - [Haystack](https://haystack.deepset.ai/) - Open-source framework for building production-ready LLM applications ([Official docs](https://docs.haystack.deepset.ai/docs/huggingfaceapichatgenerator)) - [LangChain](https://www.langchain.com/) - Popular framework for developing LLM applications ([Official docs](https://docs.langchain.com/oss/python/integrations/providers/huggingface#huggingfaceendpoint)) - [LlamaIndex](https://www.llamaindex.ai/) - Data framework for connecting custom data to LLMs ([Official docs](https://developers.llamaindex.ai/python/examples/llm/huggingface/#use-a-model-via-inference-providers)) - [PydanticAI](https://ai.pydantic.dev/) - Framework for building AI agents with Python ([Official docs](https://ai.pydantic.dev/models/huggingface/)) - [smolagents](https://huggingface.co/docs/smolagents) - Framework for building LLM agents with tool integration ([Official docs](https://huggingface.co/docs/smolagents/reference/models#smolagents.InferenceClientModel)) - [Vision Agents](https://visionagents.ai/) - SDK for real-time AI with text and vision language models ([Official docs](https://visionagents.ai/integrations/huggingface) / [HF docs](./visionagents)) ### Synthetic Data Tools for creating synthetic datasets. - [NeMo Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner) - NVIDIA NeMo framework for synthetic data generation ([HF docs](./datadesigner))