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WhatsAppBot

This is the bot that can. Powered by FastAPI and WhatsApp Business Cloud API.

Features

  • Intelligent Text and Image Input: Ask complex questions, get creative prompts answered, and explore different styles with Google's cutting-edge language models.
  • Seamless WhatsApp Integration: Send and receive messages through WhatsApp, making AI accessible and convenient right at your fingertips.
  • Huggingface Inference Support (Beta): Access a broad range of pre-trained models for diverse text tasks while exploring the potential of Huggingface's powerful ecosystem.

Getting Started

Prerequisites

  • Python 3.10.13
  • FastAPI
  • WhatsApp Business Cloud API credentials
  • Google Cloud Platform (GCP) credentials/service account with access to Vertex AI (for Google LLMs)
  • (Optional) Additional APIs specific to your desired functionality

Installation

Option 1: Easy Setup (Recommended)

  1. Download the repository

    git clone https://github.com/so-dipe/WhatsAppBot.git
cd WhatsAppBot

  2. Run the installation script:

    ./install.sh

Option 2: Manual Setup:,

  1. Create a Python Virtual Environment in the repository:

    python -m venv venv

  2. Install dependencies in the virtual environment:

    source venv/bin/activate
pip install -r requirements.txt

  3. Configure settings and Environment Variables

    1. Copy the sample_config.env file

      cp sample_config.env .env

    2. Open .env and replace the placeholder values with your credentials

    3. If you plan on using google's models, paste a copy of your service account at service_account_key.json

    alternatively, run the configure.sh script

    ./configure.sh

Usage

  1. Run run_app.sh bash script 
    ./run_app.sh

OR Manually start FastAPI and Redis servers.

  1. Run FastAPI server

    uvicorn app.main:app

    in developement mode, use

    uvicorn app.main:app --reload

    by default, a port is opened on 8000.

  2. Run Redis Server

    redis-server config/redis.conf

    config/redis.conf contains the default config file used.

  3. Set up ngrok (if needed) to expose your local server to the internet:

    ngrok http 8000

    Note: WhatsApp Business API requires a webhook callback URL that must be accessible from the internet. Explore ngrok for a permanent domain if you prefer.

Contributing

Roadmap

  • Seamless Huggingface Inference API Integration: Empower users with a vast library of pre-trained models and a user-friendly model selection interface.
  • Expand LLM Hosting Platform Support: Welcome DeepInfra, AnyScale, and potentially more to offer diverse LLM hosting options.
  • Unleash Speech-to-Text Capabilities: Enable voice-based interactions for a more natural and accessible experience.
  • Unlock the Power of Documents: Facilitate conversations around PDFs and document files for enriched knowledge sharing.

License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.