AI powered chatbot with interactive UI
Join us in revolutionizing Namami Gange! This project is a crucial part of the Namami Gange initiative, blending the power of the Rasa framework and a user-friendly React app to create an intelligent chatbot system. By harnessing the prowess of GPT-4-Free, our goal is to enhance Namami Gange's outreach by providing an interactive and informative conversational interface. Imagine chatting with an AI assistant dedicated to answering queries and guiding you through the Namami Gange project.
An interactive AI-ML chatbot with the personality and animation of Cha-cha Chaudary ( The mascot of Namami Gange project) that educates the users about the components of Namami Gange and quizzes them.
- Ensure you have Python version 3.8 installed
- Additionally, Node.js and npm need to be installed
git clone https://github.com/heyysiri/NamamiGange.gitThis guide provides step-by-step instructions for installing Rasa without using a conda environment. You will use Python's virtual environments to set up and install Rasa on your system.
- Python (Make sure you have Python installed on your system. You can download python 3.8 version from the official Python website).
Open a terminal or command prompt and navigate to the repository cloned to create your virtual environment. Run the following commands:
python -m venv venvThis will create a virtual environment named "venv" in the current directory.
Activate the virtual environment using the appropriate command for your operating system:
venv\Scripts\activateAfter activation, your command prompt or terminal should show the virtual environment's name.
With the virtual environment activated, install Rasa using the following command:
pip install rasaThis will install the latest version of Rasa and its dependencies within the virtual environment.
Verify the installation by checking the Rasa version:
rasa --versionThis command should display the installed Rasa version.
Remember, using a virtual environment is a good practice to isolate project dependencies. Adjustments might be necessary based on your specific project setup or any specific libraries you're using.
In terminal navigate to the my-react-app directory. Make sure to have Node.js and npm installed beforehand.
# Navigate to the React app directory
cd my-react-app
# Install dependencies
npm installTo clone G4f in action folder, run:
Activate the venv
activate the venv
venv/Scripts/Activate
Change the directory
cd actions
Cloning the repository
git clone https://github.com/xtekky/gpt4free.git
Installing requirements
cd gpt4free
pip install -r requirements.txt
For any doubts, refer https://github.com/xtekky/gpt4free/blob/main/README.md?plain=1
- Open the following link and sign in https://home.openweathermap.org/users/sign_in
- Enter an API keyname and click generate.
- Copy the API key and enter it in the actions.py file inside the ActionWeatherEnglish and ActionWeatherHindi class.
- Train the Rasa chatbot:
rasa train
- Start the Rasa server:
rasa run -m models --enable-api --cors "*" --debug - Running the actions:
Split the terminal and navigate to the rasa-env directory and then run rasa bot.
cd rasa-env rasa run actions
- Start the React app:
# Navigate to the React app directory cd react_app # Run the app npm start
- Rasa Configuration: Find configuration files for Rasa NLU and Core in the
NamamiGangedirectory. - React App Configuration: Configuration files for the React app can be found in the
my-react-appdirectory. - OpenWeather API Configuration: You can find the cofiguration for the API in actions.py
- Rasa: The brain behind conversational AI.
- React: Creates the interactive chat interface.
- GPT-4-Free: Powers realistic and engaging conversations.
Manogna @manognavadla
Pranava @pranRV
Shresta @Shresta-Voruganti
Shriani @shrianireddy
Siri @heyysiri