# 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:

```env
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](https://platform.openai.com/docs/models))
- manifest ([More details](https://python.langchain.com/docs/integrations/llms/manifest))
- cohere ([More details](https://docs.cohere.com/docs/llmu))
- Arc53/docsgpt-14b ([More details](https://huggingface.co/Arc53/docsgpt-14b))
- Arc53/docsgpt-7b-falcon ([More details](https://huggingface.co/Arc53/docsgpt-7b-falcon))
- llama.cpp ([More details](https://python.langchain.com/docs/integrations/llms/llamacpp))

**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.