Aimengpt
A self-hosted, offline, ChatGPT-like chatbot that allows document uploads, powered by Llama 2, chromadb and Langchain. 100% private, with no data leaving your device. New: Support for Code Llama models.
Install / Use
/learn @aietal/AimengptREADME
Demo
<div align="center"> <img src="./ui/public/ui-screenshot.png" alt="UI" /> </div>Supported models
Currently, AimenGPT supports the following models. Support for running custom models is on the roadmap.
| Model name | Model size | Model download size | Memory required | | ---------------------------------------- | ---------- | ------------------- | --------------- | | Nous Hermes Llama 2 7B Chat (GGML q4_0) | 7B | 3.79GB | 6.29GB | | Nous Hermes Llama 2 13B Chat (GGML q4_0) | 13B | 7.32GB | 9.82GB | | Nous Hermes Llama 2 70B Chat (GGML q4_0) | 70B | 38.87GB | 41.37GB | | Code Llama 7B Chat (GGUF Q4_K_M) | 7B | 4.24GB | 6.74GB | | Code Llama 13B Chat (GGUF Q4_K_M) | 13B | 8.06GB | 10.56GB | | Phind Code Llama 34B Chat (GGUF Q4_K_M) | 34B | 20.22GB | 22.72GB |
How to install
Install AimenGPT on your server or local machine
You can run AimenGPT on any x86 or arm64 system. Make sure you have Docker installed.
First, clone the Chroma repo:
git clone https://github.com/chroma-core/chroma.git
Then, clone this repo and cd into it:
git clone https://github.com/aietal/aimengpt.git
cd aimengpt
Run AimenGPT with the following command:
./run.sh --model 7b
You can access AimenGPT at http://localhost:3000.
To run 13B or 70B chat models, replace
7bwith13bor70brespectively. To run Code Llama 7B, 13B or 34B models, replace7bwithcode-7b,code-13borcode-34brespectively.
To stop AimenGPT, do Ctrl + C in Terminal.
Note: On the first run, it may take a while for the model to be downloaded to the
/modelsdirectory. You may also see lots of output like this for a few minutes, which is normal:aimengpt-aimengpt-ui-1 | [INFO wait] Host [aimengpt-api-13b:8000] not yet available...After the model has been automatically downloaded and loaded, and the API server is running, you'll see an output like:
aimengpt-ui_1 | ready - started server on 0.0.0.0:3000, url: http://localhost:3000You can then access AimentGPT at http://localhost:3000.
Install AimenGPT on M1/M2 Mac
Make sure your have Docker and Xcode installed.
First, clone the Chroma repo:
git clone https://github.com/chroma-core/chroma.git
Then, clone this repo and cd into it:
git clone https://github.com/aietal/aimengpt.git
cd aimengpt
Run AimenGPT with the following command:
./run-mac.sh --model 7b
You can access AimenGPT at http://localhost:3000.
To run 13B or 70B chat models, replace
7bwith13bor70brespectively. To run 7B, 13B or 34B Code Llama models, replace7bwithcode-7b,code-13borcode-34brespectively.
To stop AimenGPT, do Ctrl + C in Terminal.
OpenAI compatible API
Thanks to llama-cpp-python, a drop-in replacement for OpenAI API is available at http://localhost:3001. Open http://localhost:3001/docs to see the API documentation.
Benchmarks
Umbrel has tested AimenGPT models on the following hardware with the default system prompt, and user prompt: "How does the universe expand?" at temperature 0 to guarantee deterministic results. Generation speed is averaged over the first 10 generations.
Feel free to add your own benchmarks to this table by opening a pull request.
Nous Hermes Llama 2 7B Chat (GGML q4_0)
| Device | Generation speed | | ----------------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 54 tokens/sec | | GCP c2-standard-16 vCPU (64 GB RAM) | 16.7 tokens/sec | | GCP c2-standard-4 vCPU (16 GB RAM) | 4.3 tokens/sec | | Umbrel Home (16GB RAM) | 2.7 tokens/sec | | Raspberry Pi 4 (8GB RAM) | 0.9 tokens/sec |
Nous Hermes Llama 2 13B Chat (GGML q4_0)
| Device | Generation speed | | ----------------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 20 tokens/sec | | GCP c2-standard-16 vCPU (64 GB RAM) | 8.6 tokens/sec | | GCP c2-standard-4 vCPU (16 GB RAM) | 2.2 tokens/sec | | Umbrel Home (16GB RAM) | 1.5 tokens/sec |
Nous Hermes Llama 2 70B Chat (GGML q4_0)
| Device | Generation speed | | ----------------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 4.8 tokens/sec | | GCP e2-standard-16 vCPU (64 GB RAM) | 1.75 tokens/sec | | GCP c2-standard-16 vCPU (64 GB RAM) | 1.62 tokens/sec |
Code Llama 7B Chat (GGUF Q4_K_M)
| Device | Generation speed | | ----------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 41 tokens/sec |
Code Llama 13B Chat (GGUF Q4_K_M)
| Device | Generation speed | | ----------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 25 tokens/sec |
Phind Code Llama 34B Chat (GGUF Q4_K_M)
| Device | Generation speed | | ----------------------------- | ---------------- | | M1 Max MacBook Pro (64GB RAM) | 10.26 tokens/sec |
Roadmap and contributing
We're looking to add more features to AimenGPT. The highest priorities are:
- Enable support for Nvidia GPUs
- Enable upload of different file types
- Enable the creation of several document collection and allowing to select between them
- Updating the front-end to show model download progress, and to allow users to switch between models.
- Making it easy to run custom models.
If you're a developer who'd like to help with any of these, please open an issue to discuss the best way to tackle the challenge. If you're looking to help but not sure where to begin, feel free to message us on Twitter/X
Acknowledgements
A massive thank you to the following developers and teams for making AimenGPT possible:
- Umbrel for building AimenGPT
- Mckay Wrigley for building Chatbot UI.
- Georgi Gerganov for implementing llama.cpp.
- Andrei for building the Python bindings for llama.cpp.
- NousResearch for fine-tuning the Llama 2 7B and 13B models.
- Phind for fine-tuning the Code Llama 34B model.
- Tom Jobbins for quantizing the Llama 2 models.
- Meta for releasing Llama 2 and Code Llama under a permissive license.
