This repository hosts the Minimum Viable Product (MVP) of Qazan AI's future technical analysis tool. Our SaaS platform aims to provide investors with AI-enhanced insights, giving them a competitive edge in financial markets.
Qazan AI leverages cutting-edge artificial intelligence to analyze financial charts and offer actionable insights for investors. This MVP demonstrates our core functionality through a user-friendly web interface built with Flask and served by Nginx. Users can upload graphs of financial asset quotations and receive detailed AI-generated analyses to inform their investment decisions.
Users can upload images of financial asset charts directly through the web interface. AI-Driven Analysis: The application utilizes OpenAI's GPT-4 to analyze uploaded charts and generate investment insights.
Powered by Flask for the web server and PostgreSQL for database management.
Intuitive web design for seamless user experience.
Frontend: HTML, CSS, JavaScript Backend: Python, Flask AI Engine: OpenAI GPT-4 Database: PostgreSQL Server: Nginx Environment Management: Python-dotenv
Follow these instructions to set up and run the project locally.
Python 3.8 or higher PostgreSQL Nginx Pipenv (optional but recommended for environment management)
git clone https://github.com/yourusername/qazan.git
cd qazan
pip install -r requirements.txt
Create a .env file in the root directory and add your environment variables:
OPENAI_ORG_ID=your_openai_org_id
OPENAI_API_KEY=your_openai_api_key
DB_USER=your_db_user
DB_PASS=your_db_password
DB_HOST=your_db_host
DB_NAME=your_db_name
flask db init
flask db migrate -m "Initial migration."
flask db upgrade
flask run
To serve the Flask app through Nginx, configure your Nginx server block as follows:
server {
listen 80;
server_name your_domain.com;
location / {
proxy_pass http://127.0.0.1:5000;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
location /static {
alias /path_to_your_project/static;
}
}
Access the Web Interface Open your browser and navigate to http://your_domain.com.
Click the upload button and select a financial asset chart image (PNG, JPG, or JPEG).
The AI will analyze the uploaded chart and provide investment insights on the results page.
We welcome contributions from the community. To contribute:
Fork the repository. Create a feature branch. Commit your changes. Push to your branch. Create a pull request. Please adhere to the project's Code of Conduct and see CONTRIBUTING.md for detailed guidelines.
For any inquiries or feedback, please contact us at nima@vigilantia.fr
Thank you for being part of Qazan AI's journey to revolutionize financial market analysis with AI!
By Vigilantia - Proudly from Metz
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