# dalaipy A Python Wrapper for [Dalai](https://github.com/cocktailpeanut/dalai)! Dalai is a simple, and easy way to run LLaMa and Alpaca locally. ## Installation `pip install dalaipy==2.0.2` https://pypi.org/project/dalaipy/2.0.2/ ## Instructions 1. Go to [Dalai](https://github.com/cocktailpeanut/dalai), and set up your model of choice on your system (either Mac, Windows, or Linux). The readme provides clear explanations! 2. Once you can run `npx dalai serve`, run the server and test out your model of choice. 3. Install dalaipy per the instructions above, and make your first request: ``` from dalaipy.src import Dalai model = Dalai() # your_model can be one of the following, "alpaca.7B", "alpaca.13B", "llama.7B", "llama.13B", "llama.30B", or "llama.65B", and is dictated by which model you installed request_dict = model.generate_request("What is the capital of the United States?", your_model) print(model.request(request_dict)) ``` ## Credits [@cocktailpeanut](https://github.com/cocktailpeanut) - the owner of Dalai [@quadrismegistus](https://github.com/quadrismegistus) - made a notebook with the original idea of using python-socketio to communicate with the web server ## Docs ### Dalai Class - generate_request() - `model.generate_request(prompt, model)` - `prompt`: **(required)** the prompt string - `model`: **(required)** the model that should be used, in the form of a string - `alpaca.7B` - `alpaca.13B` - `llama.7B` - `llama.13B` - `llama.30B` - `llama.65B` - `id`: the request ID (defaut is '0') - `n_predict`: the number of tokens to return (default is 128) - `repeat_last_n`: default is 64 - `repeat_penalty`: default is 1.3 - `seed`: the seed (default is -1) - `temp`: the temperature of the request (default is 0.5) - `threads`: the number of threads to use (default is 4) - `top_k`: default is 40 - `top_p`: default is 0.9 - request() - `model.request(prompt)` - `prompt`: **(required)** the prompt string - `prettify`: whether or not to clean and output just the string, or the whole request dictionary (default is `True`)