## Cross-Framework LLM Tool Integration with AG2

Tool Interoperability: Use LangChain, CrewAI & PydanticAI Tools in AG2 | v0.6 - YouTube

**TL;DR** AG2 lets you bring in **Tools** from different frameworks like **LangChain** and **PydanticAI**.

- [LangChain Tools](https://python.langchain.com/v0.1/docs/modules/tools): Useful for tasks like API querying and web scraping.
- [PydanticAI Tools](https://ai.pydantic.dev/tools/): Adds context-driven tools and structured data processing.

## Enhanced Support for Non-OpenAI Models

### TL;DR

- **AutoGen has expanded integrations with a variety of cloud-based model providers beyond OpenAI.**
- **Leverage models and platforms from Gemini, Anthropic, Mistral AI, Together.AI, and Groq for your AutoGen agents.**
- **Utilise models specifically for chat, language, image, and coding.**
- **LLM provider diversification can provide cost and resilience benefits.**

In addition to the recently released AutoGen [Google Gemini](https://ai.google.dev/) client, new client classes for [Mistral AI](https://mistral.ai/), [Anthropic](https://www.anthropic.com/), [Together.AI](https://www.together.ai/), and [Groq](https://groq.com/) enable you to utilize over 75 different large language models in your AutoGen agent workflow.

These new client classes tailor AutoGen's underlying messages to each provider's unique requirements and remove that complexity from the developer, who can then focus on building their AutoGen workflow.

Using them is as simple as installing the client-specific library and updating your LLM config with the relevant `api_type` and `model`. We'll demonstrate how to use them below.

The community is continuing to enhance and build new client classes as cloud-based inference providers arrive. So, watch this space, and feel free to [discuss](https://discord.gg/pAbnFJrkgZ) or [develop](https://github.com/ag2ai/ag2/pulls) another one.