AgentCloud

AgentCloud is an open-source platform enabling companies to build and deploy private LLM chat apps (like ChatGPT), empowering teams to securely interact with their data.

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Quickstart with AgentCloud · Run Locally · Tutorial - RAG Google Bigquery · Start Reading Blog

Introduction

Welcome to agentcloud. This project comprises three main components:

1. Agent Backend: A Python application running crewai, communicating LLM messages through socket.io
2. Webapp: A UI built using next.js, tailwind, and an express custom server.
3. Vector Proxy: A Rust application which communicates with Qdrant vector Database

Getting Started

To run this project locally, follow these steps:

1. Clone the repository: git clone https://github.com/rnadigital/agentcloud.git
2. Install Docker: Install Docker
3. Start Services:

   • For Mac & Linux: Run the following command:

     chmod +x install.sh && ./install.sh
     

   • Follow the prompts or provide command-line arguments as needed.

~$ ./install.sh --help

Usage: ./install.sh [options]

Note: By default, vector-db-proxy `cargo build`'s without the `--release` flag, for faster builds during development.
      To change this, set RELEASE=true` in your env before running install i.e `RELEASE=true ./install.sh ...`.

Options:

    -h, --help                       Display this help message.

    --kill-webapp-next               Kill webapp after startup (for developers)
    --kill-vector-db-proxy           Kill vector-db-proxy after startup (for developers)
    --kill-agent-backend             Kill agent-backend after startup (for developers)

    --project-id ID                  (OPTIONAL) Specify a GCP project ID (for Secret Manager, GCS, etc)
    --service-account-json PATH      (OPTIONAL) Specify the file path of your GCP service account json.
    --gcs-bucket-name NAME           (OPTIONAL) Specify the GCS bucket name to use.
    --gcs-bucket-location LOCATION   (OPTIONAL) Specify the GCS bucket location.

• For Windows: (Coming soon...)

Tutorials

How to Build a RAG Chatbot Using Agent Cloud and PostgreSQL
How to Build a RAG Chatbot Using Agent Cloud and BigQuery
How to Build a RAG Chatbot Using Agent Cloud and MongoDB

Comparisons

Agent Cloud vs CrewAI
Agent Cloud VS OpenAI
Agent Cloud VS Google Cloud Agents

Documentation

Documentation is available at Agent Cloud - Talk to Your Data

• Introduction
  
• Data sources
  
• RAG Examples

Public Roadmap

Check out our roadmap to stay updated on recently released features and learn about what's coming next.

License

This project is licensed under the GNU Affero General Public License, version 3 only.

Changelog

See CHANGELOG.md for the list of changes in each version.

Contributions & Feedback

If you wish to contribute or provide feedback, please follow the contribution guidelines in CONTRIBUTING.md.

We welcome contributions and feedback from the community. Thank you for exploring agentcloud!

And If you find AgentCloud useful, please consider giving us a star ⭐ on GitHub. Your support helps us continue to innovate and deliver exciting features.