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* Removed Python backend files that are no longer used (everything in `promptengine`) * Added `providers` subdomain, with `CustomProviderProtocol`, `provider` decorator, and global singleton `ProviderRegistry` * Added a tab for custom providers, and a dropzone, in ChainForge global settings UI * List custom providers in the Global Settings screen once added. * Added ability to remove custom providers by clicking X. * Make custom funcs sync but call them async'ly. * Add Cohere custom provider example in examples/ *Cache the custom provider scripts and load them upon page load * Rebuild react and update package version * Bug fix when custom provider is deleted and settings screen is opened on the deleted custom provider
2.1 KiB
2.1 KiB
dalaipy
A Python Wrapper for 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
- Go to Dalai, and set up your model of choice on your system (either Mac, Windows, or Linux). The readme provides clear explanations!
- Once you can run
npx dalai serve
, run the server and test out your model of choice. - 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 - the owner of Dalai
@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 stringmodel
: (required) the model that should be used, in the form of a stringalpaca.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 64repeat_penalty
: default is 1.3seed
: 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 40top_p
: default is 0.9
-
request() -
model.request(prompt)
prompt
: (required) the prompt stringprettify
: whether or not to clean and output just the string, or the whole request dictionary (default isTrue
)