awesome-llm-apps/advanced_ai_agents/multi_agent_apps/devpulse_ai

🧠 DevPulseAI - Multi-Agent Signal Intelligence Pipeline

A reference implementation demonstrating a multi-agent system for aggregating, analyzing, and synthesizing technical signals from multiple developer-focused sources.

Features

• Multi-Source Signal Collection - Aggregates data from GitHub, ArXiv, HackerNews, Medium, and HuggingFace
• LLM-Powered Analysis - Four specialized agents working in concert
• Structured Intelligence Output - Prioritized digest with actionable recommendations

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                    Signal Intelligence Pipeline                  │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  ┌────────┐ ┌────────┐ ┌────────┐ ┌────────┐ ┌────────┐         │
│  │ GitHub │ │ ArXiv  │ │  HN    │ │ Medium │ │   HF   │ ← Data  │
│  └───┬────┘ └───┬────┘ └───┬────┘ └───┬────┘ └───┬────┘         │
│      └──────────┴──────────┼──────────┴──────────┘               │
│       │             │             │                              │
│       └─────────────┼─────────────┘                              │
│                     ▼                                            │
│           ┌─────────────────┐                                    │
│           │ Signal Collector│   ← Agent 1: Ingestion            │
│           └────────┬────────┘                                    │
│                    ▼                                             │
│           ┌─────────────────┐                                    │
│           │ Relevance Agent │   ← Agent 2: Scoring (0-100)      │
│           └────────┬────────┘                                    │
│                    ▼                                             │
│           ┌─────────────────┐                                    │
│           │   Risk Agent    │   ← Agent 3: Security Assessment  │
│           └────────┬────────┘                                    │
│                    ▼                                             │
│           ┌─────────────────┐                                    │
│           │ Synthesis Agent │   ← Agent 4: Final Digest         │
│           └────────┬────────┘                                    │
│                    ▼                                             │
│           ┌─────────────────┐                                    │
│           │ Intelligence    │   ← Prioritized Output            │
│           │ Digest          │                                    │
│           └─────────────────┘                                    │
└─────────────────────────────────────────────────────────────────┘

Agent Responsibilities

Agent	Role	Output
SignalCollectorAgent	Aggregates & normalizes signals	Unified signal list
RelevanceAgent	Scores developer relevance (0-100)	Score + reasoning
RiskAgent	Identifies security/breaking changes	Risk level + concerns
SynthesisAgent	Produces final intelligence digest	Prioritized recommendations

How to Get Started

1. Clone the repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/multi_agent_apps/devpulse_ai

1. Install dependencies

pip install -r requirements.txt

1. Set your OpenAI API key (optional for live mode)

export OPENAI_API_KEY=your_api_key

1. Run the verification script (no API key needed)

python verify.py

1. Run the full pipeline (requires API key for LLM agents)

python main.py

Verification Script

The verify.py script tests the entire pipeline using mock data only - no network calls or API keys required:

python verify.py

Expected output:

[OK] DevPulseAI reference pipeline executed successfully

Optional: n8n Automation

An n8n workflow is included for those who want to automate the pipeline:

• Location: workflows/signal-intelligence-pipeline.json
• Import: n8n → Settings → Import from File
• Requires: n8n instance + configured credentials

This is entirely optional - the Python implementation works standalone.

Directory Structure

devpulse_ai/
├── adapters/
│   ├── github.py       # GitHub trending repos
│   ├── arxiv.py        # AI/ML research papers
│   ├── hackernews.py   # Tech news stories
│   ├── medium.py       # Tech blog RSS feeds
│   └── huggingface.py  # HuggingFace models
├── agents/
│   ├── __init__.py
│   ├── signal_collector.py
│   ├── relevance_agent.py
│   ├── risk_agent.py
│   └── synthesis_agent.py
├── workflows/
│   └── signal-intelligence-pipeline.json
├── main.py             # Full pipeline demo
├── verify.py           # Mock data verification
├── requirements.txt
└── README.md

How It Works

1. Signal Collection: Adapters fetch data from GitHub, ArXiv, HackerNews, Medium, and HuggingFace
2. Normalization: SignalCollectorAgent unifies signals to a common schema
3. Relevance Scoring: RelevanceAgent rates each signal 0-100 for developer relevance
4. Risk Assessment: RiskAgent flags security issues and breaking changes
5. Synthesis: SynthesisAgent produces a prioritized intelligence digest

Built With

• Agno - Multi-agent framework
• OpenAI GPT-4o-mini - LLM backbone
• httpx - Async HTTP client