Bridging AI models
Project description
OmniBridge
OmniBridge wrap and connects different AI models. It helps access different AI models in a centralized place.
Install
pip install omnibridge
Now you can start using OmniBridge!
NOTE: Once installed, you can use omnibridge with both
omnibridgeandobrcommands.
Usage
Add your key
obr create key --name open_ai --value <value>
Add your model
obr create model chatgpt --name gpt3.5 --key open_ai
You can now run chatGPT from your cli!
obr run model --name gpt3.5 --prompt "tell me a joke"
You can also use the model you created to build flows (aka Auto-GPT), passing the output of one model to several others!
obr create flow --name chef --model gpt3.5 -i "what ingridients do I need for the dishes?"
"what wine would you suggest to pair with the dishes" "how much time does it take to prepare?"
This command set up four instances of your model, the first instance will handle your prompt as you would expect regularly, however, instead of returning the output, it will pass it to the other three, adding a specific instruction for each!
Understand it best with an example - (Notice it may take a short while to generate a response.)
obr run flow --name chef --prompt "suggest two dishes for a romantic date"
This should return
1. Filet Mignon with Roasted Vegetables: <description>
2. Lobster Risotto: <description>
******************************************************************
Ingridients:
< a list of ingridients>
******************************************************************
1. Filet Mignon with Roasted Vegetables: A red wine like a Cabernet Sauvignon or a Merlot...
2. Lobster Risotto: A white wine like a Chardonnay or a Sauvignon Blanc...
******************************************************************
Typical cooking times for a filet mignon can range from 8 to 12 minutes, and for lobster risotto,
it can take around 30-40 minutes.
Combining two models in a sequential flow
Add your key
obr create key --name open_ai --value <value>
Create two models
obr create model chatgpt --name gpt_model -k open_ai
obr create model dalle --name dalle_model -k open_ai
Now combine both models in a sequential flow
obr create flow --name image_flow --multi gpt_model dalle_model -t seq
Finally, run the flow with a prompt
obr run flow --name image_flow -i "create a prompt to an image that will amaze me"
NOTE: As of now, we will create the images in your current working directory and print the paths. Tell us if you would want to receive the output of image creation models differently!
We are working on more cool stuff!
Community
Come share your ideas, usage, and suggestions!
Join our discord server and share your feedback and ideas with us!
Contribute:
Join us in shaping the future of A.I!
For information on how to contribute, see here.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file OmniBridge-0.1.73.tar.gz.
File metadata
- Download URL: OmniBridge-0.1.73.tar.gz
- Upload date:
- Size: 24.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
771481245e697a718f0c8226a1f9912941b12dfd8855985b074b8b0dd963be13
|
|
| MD5 |
91999e64391aaf2375c050493c9b41d7
|
|
| BLAKE2b-256 |
c2d642cb600e34bc1901bc8e59baff3674cf32c815a7733c1b6c58541e297692
|