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SockPulse App

Portfolio Analysis Contributions Welcome License

A comprehensive stock market portfolio analysis tool that helps users identify undervalued & overvalued stocks, track performance, and leverage AI-powered insights.

📜 Project Overview

  • 📊 Portfolio Management: Users can create stock lists, track investments, and analyze stock fundamentals.
  • 🤖 AI-Powered Insights: ML models predict stock valuations, detect trends, and assess risk.
  • 🏛 Company Earnings Call Summaries: LLMs extract key takeaways and financial indicators.
  • 🔍 Stock Screening: Identify undervalued & overvalued stocks based on financial history.
  • 📈 Custom KPI Calculations: Users define custom ratios and financial indicators.

✨ What Will You Learn?

By contributing to this project, you will gain hands-on experience with:

  • ✅ Best coding practices (structured repo, Python packaging, modular code design)
  • ✅ End-to-end ML project setup (data ingestion, feature engineering, model training & deployment)
  • ✅ Collaboration (GitHub PRs, issue tracking, code reviews, forks, branching strategies)
  • ✅ Python packaging (pyproject.toml, setup.py, requirements.txt, pip install -e .)
  • ✅ ML & LLMs (financial modeling, company earnings call summarization, AI-driven KPI indicators)
  • ✅ Data Analysis (fundamental analysis, feature engineering, valuation models)
  • ✅ Databases (PostgreSQL, MongoDB, MinIO for storage, MLflow for experiments)
  • ✅ MLOps & CI/CD (model tracking, automation, Dockerized services, API deployment)

🔧 Tools & Technologies Used

Category Technologies
Frontend Dash
Backend FastAPI
Databases PostgreSQL, MongoDB, MinIO (Object Storage)
ML Models Scikit-learn, PyTorch, TensorFlow
Experiment Tracking MLflow (for local experiments only)
Deployment Docker, Docker Compose
CI/CD GitHub Actions
Data Processing Pandas, NumPy, SQLAlchemy
NLP for Summarization OpenAI GPT, NLTK, Hugging Face

❓ How do we maintain the repository?

We follow a Git branching strategy for organized development:

  • main → Stable production branch
  • develop → Active development branch
  • feature/* → Individual feature branches
  • hotfix/* → Quick bug fixes
  • docs → Documentation updates

💡 Contributors should fork the repo & create pull requests for merging!

📌 How to Run the Project Locally

🚀 1️⃣ Clone the Repository

git clone https://github.com/RaghavaAlajangi/StockPulse.git

cd stockpluse

🐍 2️⃣ Create Virtual Environment and Install Dependencies

python -m venv venv

pip install -r requirements.txt

🐳 3️⃣ Start the App locally

python -m src.app --local

🌍 4️⃣ Access the App

  • Frontend (Dash): http://localhost:8050

🤝 Contributing Guidelines

Want to contribute? 🎉 Follow these steps:

  1. Fork the repository.
  2. Create a new feature branch.
  3. Commit your changes with descriptive messages.
  4. Submit a pull request.

🚀 Let’s build an amazing stock analysis tool together!

💡 After your first PR, your name will be added to the contributers list!

📜 License

This project is licensed under the MIT License 📜.