📈 VentureView

A smart forecasting assistant for small businesses. Upload a CSV, describe your forecast needs in plain English, and get predictions powered by machine learning and natural language understanding.

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🚀 Features

• 🔐 Email-based login system (FastAPI + PostgreSQL)
• 📁 CSV upload with per-user storage in the database
• 🧠 Natural language parsing using Gemini LLM
• 📊 Time-series forecasting with Facebook Prophet
• 📉 Dynamic graph generation with confidence intervals
• 🗣 AI-generated explanation of the forecast
• 🌐 Clean frontend built with React (Vite)

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🧰 Tech Stack

Layer	Tools
Frontend	React (Vite), Vanilla CSS
Backend	FastAPI, SQLAlchemy, PostgreSQL, Gemini
Forecast	Facebook Prophet, Pandas, Matplotlib
Auth	Email-based login

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📄 How It Works

1. Login with your email

2. Upload a CSV file containing date, product, and revenue

3. Type a prompt like:

   Forecast revenue for notebooks for the next 14 days
   

4. The app:

   • Parses your prompt using Gemini
   • Validates and filters your uploaded CSV
   • Runs a Prophet forecast
   • Returns a graph + natural language explanation

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⚙️ .env Template

Create a .env file in the project root with:

LLM_API_KEY=your-gemini-api-key
DATABASE_URL=postgresql://username:password@localhost:5432/yourdbname

Replace username, password, and yourdbname with your actual PostgreSQL credentials.

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🛠 Setup Instructions

1. Backend (Python)

# From the project root
python -m venv venv
source venv/bin/activate

pip install -r requirements.txt

# Run the backend server
python backend/main.py

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2. Frontend (React)

cd frontend
npm install
npm run dev

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🧪 Sample CSV Format

date,product,revenue
2024-01-01,Notebooks,100
2024-01-02,Notebooks,120
...

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👨‍💻 Author

Sajal Sabat