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https://github.com/harshit433/resurrectai
ResurrectAI is an AI-driven chat application designed to bring the wisdom and knowledge of great historical personalities to life. Leveraging advanced language models and fine-tuning techniques, ResurrectAI enables users to interact with AI avatars of iconic figures, gaining access to their insights, guidance, and philosophical teaching in realtime
https://github.com/harshit433/resurrectai
artificial-intelligence chatbot conversational-ai finetuning-llms firebase flask flutter html-css-javascript language-model llama3-1 machine-learning ollama python unsloth
Last synced: about 14 hours ago
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ResurrectAI is an AI-driven chat application designed to bring the wisdom and knowledge of great historical personalities to life. Leveraging advanced language models and fine-tuning techniques, ResurrectAI enables users to interact with AI avatars of iconic figures, gaining access to their insights, guidance, and philosophical teaching in realtime
- Host: GitHub
- URL: https://github.com/harshit433/resurrectai
- Owner: harshit433
- Created: 2024-09-08T02:29:31.000Z (18 days ago)
- Default Branch: main
- Last Pushed: 2024-09-08T12:43:13.000Z (17 days ago)
- Last Synced: 2024-09-24T21:38:58.438Z (about 19 hours ago)
- Topics: artificial-intelligence, chatbot, conversational-ai, finetuning-llms, firebase, flask, flutter, html-css-javascript, language-model, llama3-1, machine-learning, ollama, python, unsloth
- Language: Dart
- Homepage:
- Size: 30.3 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ResurrectAI Project Documentation
## Overview
ResurrectAI is a project designed to bring great historical personalities to life through their wisdom by creating a chat application where users can interact with these personalities and seek guidance on almost any topic. The app functions as a 24/7 buddy offering advice in various situations.
### Important Note
- **Linux Machine Required**: The Flask app (`app.py`) requires a Linux machine to run.
- **Alternative**: If you do not have access to a Linux machine, you can try out the code using the training and inference Jupyter notebooks provided in the repository.
## Project Structure
- **app.py**: Flask application to run and interact with the AI model.
- **ResurrectAI_Training.ipynb**: Jupyter notebook for training the AI model.
- **ResurrectAI_Inference.ipynb**: Jupyter notebook for running inference with the AI model.
- **Audio/**: Directory containing audio resources.
- **Books/**: Directory containing text resources.
- **static/styles/**: CSS and styling files for the frontend.
- **templates/**: HTML templates for the web interface.
- **README.md**: Project documentation.
- **requirements.txt**: List of dependencies required to run the project.
- **mobile/resurrectai/**: Flutter app files (not yet connected to the AI model).
- **static/screenshots/**: Directory containing screenshots for documentation.
## Setup Instructions
### 1. Environment Setup
#### Prerequisites
- **Python 3.x**: Ensure that Python 3 is installed on your system.
- **Linux Machine**: Required for running the Flask app (`app.py`).
#### Step-by-Step Guide
1. **Clone the Repository**:
```bash
git clone https://github.com/harshit0414/resurrectai.git
cd resurrectai
```
2. **Create a Virtual Environment**:
```bash
python3 -m venv venv
source venv/bin/activate # Linux
```
3. **Install Dependencies**:
Install the required packages using the `requirements.txt` file:
```bash
pip install -r requirements.txt
```
4. **Install Unsloth and Additional Libraries**:
Run the following commands to install Unsloth and other dependencies required for both the Flask app and the Jupyter notebooks:
```bash
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
pip install --no-deps xformers trl peft accelerate bitsandbytes triton
```
### 2. Running the Flask App (`app.py`)
1. **Start the Flask Application**:
```bash
python app.py
```
2. **Access the Web Interface**:
Once the application is running, open your browser and navigate to `http://localhost:5000` to interact with the AI model.
*Example: Screenshot showing the ResurrectAI web interface.*
### 3. Alternative for Non-Linux Users
If you do not have a Linux machine, you can use the provided Jupyter notebooks:
1. **Training the Model**:
Open the `ResurrectAI_Training.ipynb` notebook in Jupyter and follow the steps to train the AI model.
*Example: Screenshot showing the training process in Jupyter.*
2. **Running Inference**:
Use the `ResurrectAI_Inference.ipynb` notebook to run inference and interact with the model in a non-Linux environment.
### 4. Connecting Firebase to the Flutter Application
To allow users to download and use the ResurrectAI Flutter app with their own Firebase project, follow these steps:
1. **Set up a Firebase Project**:
- Go to the [Firebase Console](https://console.firebase.google.com/) and create a new project.
- Follow the setup instructions for Firebase, and make sure to add your Android/iOS app to the Firebase project.
2. **Modify `google-services.json` (Android)** or `GoogleService-Info.plist` (iOS):
- After setting up Firebase, download the `google-services.json` (for Android) or `GoogleService-Info.plist` (for iOS) file from your Firebase console.
- Place this file in the respective directories in your Flutter app:
- `android/app/` for Android (`google-services.json`)
- `ios/Runner/` for iOS (`GoogleService-Info.plist`)
3. **Install Firebase SDK**:
Ensure you have the necessary Firebase packages installed in your Flutter project by following the official Firebase documentation for Flutter: [Firebase for Flutter](https://firebase.google.com/docs/flutter/setup?platform=android).
```bash
flutter pub add firebase_core
flutter pub add firebase_auth
# Add other Firebase packages as needed
```
4. **Initialize Firebase in Flutter**:
In your `main.dart`, initialize Firebase before running the app:
```dart
void main() async {
WidgetsFlutterBinding.ensureInitialized();
await Firebase.initializeApp();
runApp(MyApp());
}
```
### 5. Flutter Application
The Flutter application is developed but not yet connected to the AI model for interactivity. Once connected, instructions for using the mobile app will be provided in future updates.
*Example: Screenshot showing Android Application developed in Flutter.*
## Contributing
If you'd like to contribute to ResurrectAI, feel free to fork the repository, make your changes, and submit a pull request. Ensure that your code adheres to the project’s coding standards.
## Future Work
- **Connecting Flutter App**: The next step is to connect the Flutter application to the AI model for full interactivity.
- **Cross-Platform Support**: Plans are in place to make the Flask app cross-platform to support non-Linux environments.
## Contact
For any queries or support, please contact [email protected] or open an issue in the repository.