Welcome to agentcloud
repository! This project comprises three main components:
- Agent Backend: A Python application running crewai, communicating LLM messages through socket.io
- Webapp: A UI built using next.js, tailwind, and an express custom server.
- Vector Proxy: A Rust application which communicates with Qdrant vector Database
To run this project up locally, clone this repo and run Docker. For now there is a reliance on GCP for Bucket storage to store files. (We will add AWS S3, Local Disk in future releases.) Follow the steps below to get started:
- Start Services: Simply run the following command:
Mac & Linux:
chmod +x install.sh && ./install.sh
The script will prompt for some details, or you can pass them as command line arguments:
~$ ./install.sh --help
Usage: ./install.sh [options]
Options:
--project-id ID Specify the GCP project ID.
--service-account-json PATH Specify the file path of your GCP service account json.
--gcs-bucket-name NAME Specify the GCS bucket name to use.
--gcs-bucket-location LOCATION Specify the GCS bucket location.
--openai-api-key KEY Specify your OpenAI API key.
-h, --help Display this help message.
Windows:
(Coming soon...)
This project is licensed under the GNU Affero General Public License, version 3 only.
See CHANGELOG.md.
If you wish to contribute or provide feedback, please follow the contribution guidelines in CONTRIBUTING.md.
Thank you for exploring agentcloud
!