AI & GenAI Signal Digest 🤖

An autonomous multi-agent system to digest AI signals and deliver insights via WhatsApp.

Overview

This system is designed to help busy professionals stay on top of the rapidly evolving AI landscape. It autonomously:

1. Acquires research papers (arXiv) and news.
2. Filters content using LLMs (Relevance Decision).
3. Enriches data with embeddings and topics.
4. Prioritizes high-signal items.
5. Synthesizes concise summaries (TL;DR).
6. Validates quality with guardrails.
7. Delivers a digest via WhatsApp.

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Architecture

The system is composed of 7 Autonomous Agents orchestrated by a central scheduler:

• Agent 1: Acquisition - Fetches raw data.
• Agent 2: Relevance - Classifies content (LLM-based).
• Agent 3: Enrichment - Generates embeddings.
• Agent 4: Prioritization - Ranks content.
• Agent 5: Synthesis - Generates summaries.
• Agent 6: Guardrail - Validates output quality.
• Agent 7: Delivery - Sends via Twilio/WhatsApp.

Plus a Flask Dashboard for monitoring and manual control.

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Quick Start

Prerequisites

• Python 3.11+
• API Keys: OpenAI/Gemini, Twilio (Optional for delivery)

Installation

1. Clone the repository:

   git clone https://github.com/piconnnie/-ai-signal-digest.git
   cd -ai-signal-digest

2. Setup Virtual Environment:

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Mac/Linux
   source venv/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Configuration: Create a .env file in the root directory:

   OPENAI_API_KEY=sk-your-key-here
   TWILIO_ACCOUNT_SID=your-sid
   TWILIO_AUTH_TOKEN=your-token
   TWILIO_FROM_NUMBER=whatsapp:+14155238886
   DATABASE_URL=sqlite:///data/signal_digest.db

Usage

Run the Pipeline (Background Service):

python -m src.main

Run the Dashboard (UI):

python -m src.ui.app

Open http://localhost:5000 to view the dashboard.

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License

MIT