PlantID Benin is an innovative mobile application that uses computer vision and AI to identify the medicinal plants native to Benin. By providing access to a comprehensive database of traditional and scientific knowledge, PlantID empowers local communities, preserves botanical heritage and stimulates research into medicinal plants.
PLANTID: Multimodal Chatbot API
To preserve traditional botanical knowledge
Developed with:
## π Table of Contents
- Overview
- Features
- Getting Started
- Prerequisites
- Installation
- Usage
- Configuration
- Testing
- Project Structure
- Deployment
- Contributing
- License
- Contact
- Acknowledgments
## π Overview
PlantID Benin is an innovative mobile application that uses computer vision and AI to identify the medicinal plants native to Benin. By providing access to a comprehensive database of traditional and scientific knowledge, PlantID empowers local communities, preserves botanical heritage and stimulates research into medicinal plants.\
This part of the app is a powerful and versatile multimodal chatbot API built using Python and Flask. It enables users to interact seamlessly through text, voice, and images, providing a rich and engaging conversational experience.
## π Features
- π¬ Multilingual support: The chatbot can understand and respond in multiple languages.
- π€π·π¬ Text, audio, and image inputs: Users can interact with the chatbot using text, audio recordings, or images.
- ποΈ Speech recognition: User audio inputs are transcribed using the Whisper model for accurate speech recognition.
- π Language translation: The application automatically translates user inputs and chatbot responses to the desired language.
- π€ Dialogue management: The chatbot maintains a conversation flow and adapts its responses based on the user's input and the current dialogue state.
- πΌοΈ Image generation: The chatbot can generate images based on user prompts using the Stability AI API or Replicate API.
- π Text-to-speech: Chatbot responses can be converted to audio using the Eleven Labs API for a more engaging user experience.
- π Sentiment analysis for user inputs
## π Getting Started
### Prerequisites
- Python 3.8+
- PostgreSQL
- Redis
### β Installation
1. Cl β¦