https://github.com/wahidpanda/querry.ai
Querry.ai is a web application for data analysis and management at querry, utilizing AI, chatbots, custom dashboards, and advanced analytics tools.
https://github.com/wahidpanda/querry.ai
Last synced: 3 months ago
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Querry.ai is a web application for data analysis and management at querry, utilizing AI, chatbots, custom dashboards, and advanced analytics tools.
- Host: GitHub
- URL: https://github.com/wahidpanda/querry.ai
- Owner: wahidpanda
- Created: 2024-08-22T03:38:57.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-26T09:29:31.000Z (7 months ago)
- Last Synced: 2025-02-26T10:31:39.418Z (7 months ago)
- Language: Python
- Homepage:
- Size: 1.09 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# querry.ai
querry.ai is a web application for data analysis and management at Felicity Internet Data Center, utilizing AI, chatbots, custom dashboards, and advanced analytics tools.
# querry.ai
querry.ai is an advanced data analysis and interactive application for querry.ai It integrates various features including data analysis, chatbot interaction, custom dashboards, and advanced analytics.
## Project Structure
querry.ai/
├── .gitignore
├── README.md
├── requirements.txt
├── app/
│ ├── __init__.py
│ ├── main.py
│ ├── pages/
│ │ ├── __init__.py
│ │ ├── eda_page.py
│ │ ├── chat_pdf.py
│ │ ├── dashboard_page.py
│ │ ├── login_page.py
│ │ ├── chatbot_page.py
│ │ ├── advanced_analytics_page.py
│ ├── utils/
│ │ ├── __init__.py
│ │ ├── auth.py
│ │ ├── pdf_processing.py
│ │ ├── gtts_speech.py
│ │ ├── vector_store.py
│ │ ├── custom_plots.py
├── static/
│ ├── css/
│ │ └── custom_style.css
│ ├── images/
│ ├── idc.jpg
│ ├── idc2.jpeg
├── .env.example
└── LICENSE
## Features
- **User Authentication**: Secure login and account creation system.
- **Advanced Data Analysis**: Upload and analyze datasets with custom visualizations.
- **Chat with Document**: Interact with PDF documents using Google's Gemini API.
- **Custom Dashboard Creation**: Build and save dashboards based on your data analysis preferences.
- **Chatbot Integration**: Query querry's systems using an AI-powered chatbot.
- **Advanced Analytics**: Perform predictive modeling and advanced statistical analysis.
## Installation
1. Clone the repository:
```sh
git clone https://github.com/wahidpanda/Felicity-IDC.ai.git
cd querry.ai
```
2. Create a virtual environment and activate it:
```sh
python3 -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
```
3. Install the required packages:
```sh
pip install -r requirements.txt
```
4. Set up your environment variables by copying `.env.example` to `.env` and updating with your credentials:
```sh
cp .env.example .env
```
5. Run the application:
```sh
streamlit run app/main.py
```
## Dependencies
- `Streamlit`: Web framework for creating interactive applications.
- `pandas`, `ydata-profiling`: Data manipulation and analysis.
- `Google Generative AI`: API for interacting with PDF documents.
- `FAISS`: Vector search engine for text embeddings.
- `PyPDF2`: PDF processing library.
- `gTTS`: Text-to-speech conversion.
- `seaborn`, `matplotlib`, `plotly`: Data visualization libraries.
##Steps to Use the Dockerfile:
1. Replace "your_app.py" with the actual name of your Streamlit Python script.
2. Build the Docker Image: Navigate to your project directory where the Dockerfile is located and run:
```sh
docker build -t streamlit-app .
```
3. Run the Docker Container: Once the image is built, you can run it using
```sh
docker run -p 8501:8501 streamlit-app
```
This will start your Streamlit app in a Docker container, and you can access it by navigating to http://localhost:8501 in your web browser.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Contribution
This is not for contribuiton purpose !!!
## COntact
Email me: islamoahidul12@gmail.com