📧 Smart Email Digest (RAG + Streamlit)

A modern, agentic email digest and Q&A app using Retrieval-Augmented Generation (RAG) with LangGraph, ChromaDB, and OpenAI. Process your Gmail inbox, get executive and market summaries, and ask questions about your emails—all in a beautiful Streamlit UI.

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Features

• Automated Email Categorization: Action Required, High-Priority, Market News, Newsletters
• Executive & Market Summaries: LLM-powered, concise, and actionable
• Q&A Chat: Ask questions about your emails using RAG (ChromaDB + OpenAI)
• Streamlit UI: Easy to use, interactive, and beautiful

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Setup Instructions

1. Clone the repository

git clone <your-repo-url>
cd EmailDigest

2. Install dependencies

We recommend using a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -r requirements.txt

3. Set up environment variables

Create a .env file in the root directory with the following:

OPENAI_API_KEY=your-openai-api-key
GMAIL_CREDENTIALS_PATH=credentials.json  # Path to your Gmail OAuth credentials

• OpenAI API Key: Get one at https://platform.openai.com/account/api-keys
• Gmail Credentials: Follow Google's guide to create OAuth credentials and download credentials.json.

4. (Optional) Set up Google API credentials

• Place your credentials.json in the project root or specify the path in .env as GMAIL_CREDENTIALS_PATH.

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Running the App

streamlit run src/app.py

• Use the sidebar to process your emails.
• View summaries and categories.
• Use the Q&A chat to ask questions about your inbox!

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Notes

• ChromaDB will store embeddings in a .chroma/ directory by default.
• Token/Rate Limits: The app batches and/or truncates data to avoid OpenAI rate limits, but very large inboxes may still require patience.
• Supported Models: Uses OpenAI's GPT-4.1 and text-embedding-3-large by default, with fallbacks.

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Contributing

Pull requests and issues are welcome!

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License

MIT