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otto
https://github.com/lavanyashukla/otto/assets/12243123/82801fa5-8dbc-4698-ad0b-da751ea30adb
Getting Started
Step 0: Install python, npm, yarn
On linux
sudo apt install python
sudo apt install npm
On mac
brew install python
brew install npm
npm install --global yarn
Step 1: Install whisper and llama
Install llama.cpp
In root directory run
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
make
Download a llama model
Store the model in llama.cpp/models
cd llama.cpp/models
wget https://huggingface.co/TheBloke/Llama-2-7B-GGUF/resolve/main/llama-2-7b.Q4_K_M.gguf
Download a finetuned model
Store the fine-tuned model in llama.cpp/models
wget https://api.wandb.ai/artifactsV2/gcp-us/l2k2/QXJ0aWZhY3Q6NjAyMDE2NzM0/25bd8f78a12839913fd2c4c49c3f9c22/ggml-finetuned-model-q4_0.gguf
Install whisper.cpp
On linux run:
sudo apt-get install libsdl2-dev
On OSX run:
brew install sdl2
In root directory run
git clone https://github.com/ggerganov/whisper.cpp.git
cd whisper.cpp
make
make stream
Download a whisper model
Store the model in whisper.cpp/models
bash ./models/download-ggml-model.sh base.en
Feel free to add more llama or whisper models to play with. If you add a different llm, update llms.json with the model file and correct prompt format.
Step 2: Install python libraries
pip install -r requirements.txt
pip install -r server/skills/requirements_skills.txt
Step 3: Install yarn packages
cd frontend
yarn install
Step 4: Run backend
python server/app.py
Step 5: Run frontend
cd frontend && yarn start