@Sayak
Setting up a custom LLM (Large Language Model) with VAPI involves several steps. Here's a general guide to get you started:
1. **Prepare Your LLM**: Ensure that your custom LLM is ready for integration. This means it should be trained, hosted, and accessible via an API endpoint.
2. **Gather Required Information**: You'll need the API endpoint URL of your custom LLM and any necessary authentication details such as API keys or tokens.
3. **Access VAPI Dashboard**: Log in to your VAPI account and navigate to the appropriate section for integrating custom models.
4. **Enter LLM Details**: In the custom LLM integration section, you'll be prompted to enter the details of your LLM, including the API endpoint and any authentication required.
5. **Test the Integration**: After entering the details, you should test the integration to ensure that VAPI can successfully communicate with your custom LLM.
6. **Deploy**: Once the test is successful, you can deploy the integration, making your custom LLM available for use with VAPI's services.
If you need specific instructions or if there's a particular step you're unsure about, please let me know, and I can provide more detailed assistance!