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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)
- manifest (More details)
- cohere (More details)
- Arc53/docsgpt-14b (More details)
- Arc53/docsgpt-7b-falcon (More details)
- llama.cpp (More details)
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.