Setting Up Local Language Models for Your App

Your app relies on two essential models: Embeddings and Text Generation. While OpenAI's default models work seamlessly, you have the flexibility to switch providers or even run the models locally.

Step 1: Configure Environment Variables

Navigate to the .env file or set the following environment variables:

LLM_NAME=<your Text Generation model>
API_KEY=<API key for Text Generation>
EMBEDDINGS_NAME=<LLM for Embeddings>
EMBEDDINGS_KEY=<API key for Embeddings>
VITE_API_STREAMING=<true or false>

You can omit the keys if users provide their own. Ensure you set LLM_NAME and EMBEDDINGS_NAME.

Step 2: Choose Your Models

Options for LLM_NAME:

• OpenAI (More details (opens in a new tab))
• manifest (More details (opens in a new tab))
• cohere (More details (opens in a new tab))
• Arc53/docsgpt-14b (More details (opens in a new tab))
• Arc53/docsgpt-7b-falcon (More details (opens in a new tab))
• llama.cpp (More details (opens in a new tab))

Options for EMBEDDINGS_NAME:

• openai_text-embedding-ada-002
• huggingface_sentence-transformers/all-mpnet-base-v2
• huggingface_hkunlp/instructor-large
• cohere_medium

If using Llama, set EMBEDDINGS_NAME to huggingface_sentence-transformers/all-mpnet-base-v2. Download the required model and place it in the models/ folder.

Alternatively, for local Llama setup, run setup.sh and choose option 1. The script handles the DocsGPT model addition.

Step 3: Local Hosting for Privacy

If working with sensitive data, host everything locally by setting SELF_HOSTED_MODEL to true in your .env. For LLM_NAME, use any model available on Hugging Face. That's it! Your app is now configured for local and private hosting, ensuring optimal security for critical data.