Hi, I was chatting with the Vapi Support Chat on the Vapi Website and it was extremely helpful with talking through my current startup project that my team is working on, more helpful than any other LLM (which makes sense given that the support chat is trained on the Vapi System/DOCs). Is is possible to have access to the support chat to run locally or how would you recommend prompting/training my LLM to help me through my coding development step by step? When I am currently talking with the AI support chat agent, if I were to leave the site or temporarily click on a new tab, the chat stops and I am no longer able to use it after prompting and explaining it everything about what I am working on. I would love to be able to use this chat locally or in a stable manner and better yet, have an LLM trained on it so that way I can also use/copy text & code that it would output to me. Any thoughts or suggestions?

Hi quantquant12, For accessing Vapi documentation via a local setup or training a custom LLM with these documents, here’s a concise approach you might consider: 1. **Local Access to Vapi Support Chat**: - Vapi's support chat, being an integrated feature, is not designed for local access. However, you could replicate its functionality by integrating a custom LLM with access to Vapi's documentation. 2. **Training a Custom LLM**: - **Create a Dataset**: Extract necessary information from the [Vapi documentation](https://docs.vapi.ai/customization/custom-llm/using-your-server) to form a training dataset. - **Training Process**: Utilize an LLM library like OpenAI’s GPT, and fine-tune it using your curated dataset. - **Local Server Setup**: Use a local environment (e.g., Flask with Ngrok) to set up your server and integrate your trained model. Follow the process outlined in [this guide](https://docs.vapi.ai/customization/custom-llm/using-your-server). 3. **Integration**: - Use an existing API like OpenAI’s to connect your LLM to a user interface where you can input queries and receive guidance based on your training data. This setup will allow your custom LLM to assist you step-by-step through your coding development, leveraging information from the Vapi documentation.