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https://github.com/edgar971/open-chat

A self-hosted, offline, ChatGPT-like chatbot with different LLM support. 100% private, with no data leaving your device.
https://github.com/edgar971/open-chat

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A self-hosted, offline, ChatGPT-like chatbot with different LLM support. 100% private, with no data leaving your device.

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README

        



OpenLLM




A self-hosted, offline, ChatGPT-like chatbot with different LLM support. 100% private, with no data leaving your device.

## How to install

---

### Install OpenLLM anywhere else with Docker

You can run OpenLLM on any x86 system. Make sure you have Docker installed.

Then, clone this repo and `cd` into it:

```
git clone https://github.com/edgar971/open-chat.git
cd open-chat
```

You can now run OpenLLM with any of the following models depending upon your hardware:

| Model size | Model used | Minimum RAM required | How to start OpenLLM |
| ---------- | ----------------------------------- | -------------------- | ------------------------------------------------ |
| 7B | Nous Hermes Llama 2 7B (GGML q4_0) | 8GB | `docker compose up -d` |
| 13B | Nous Hermes Llama 2 13B (GGML q4_0) | 16GB | `docker compose -f docker-compose-13b.yml up -d` |
| 70B | Meta Llama 2 70B Chat (GGML q4_0) | 48GB | `docker compose -f docker-compose-70b.yml up -d` |

You can access OpenLLM at `http://localhost:3000`.

To stop OpenLLM, run:

```
docker compose down
```

---

## API Configuration

Additional settings can be found [here](https://github.com/abetlen/llama-cpp-python/blob/main/llama_cpp/server/app.py#L23) and added as env variables or arguments to the run.sh (--n_ctx 12) script.

Example:

```yml
version: '3'
services:
api:
image: ghcr.io/edgar971/open-chat-cuda:latest
environment:
- MODEL=/path/to/your/model
- N_CTX=4096
ports:
```

## Acknowledgements

A massive thank you to the following developers and teams for making OpenLLM possible:

- [Mckay Wrigley](https://github.com/mckaywrigley) for building [Chatbot UI](https://github.com/mckaywrigley).
- [Georgi Gerganov](https://github.com/ggerganov) for implementing [llama.cpp](https://github.com/ggerganov/llama.cpp).
- [Andrei](https://github.com/abetlen) for building the [Python bindings for llama.cpp](https://github.com/abetlen/llama-cpp-python).
- [NousResearch](https://nousresearch.com) for [fine-tuning the Llama 2 7B and 13B models](https://huggingface.co/NousResearch).
- [Tom Jobbins](https://huggingface.co/TheBloke) for [quantizing the Llama 2 models](https://huggingface.co/TheBloke/Nous-Hermes-Llama-2-7B-GGML).
- [Meta](https://ai.meta.com/llama) for releasing Llama 2 under a permissive license.