The Canary 🐦

AI Market Monitor for the "AI Bubble"

A serverless, zero-maintenance AI agent that tracks the health of the AI financial market. It runs daily on GitHub Actions, analyzes market data and news using an LLM, and publishes a risk score to a public dashboard.

🚀 Features

• Zero Infrastructure: Runs entirely on GitHub Actions and GitHub Pages.
• AI Analyst: Publishes a versioned editorial opinion about how fragile the AI investment boom is to a meaningful correction over the next 6–12 months. Confidence is the model's judgment; data quality is an independent collection measure.
• Data-Driven: Tracks volatility of major AI stocks (NVDA, MSFT, GOOGL) and global news sentiment.
• Visual Dashboard: Beautiful, dark-mode UI to visualize the "Risk Score" trend.

🛠️ Setup & Deployment

1. Fork & Clone

Fork this repository to your GitHub account and clone it locally.

2. Get an API Key

You need an API key from OpenRouter to access the LLM.

3. Local Usage

1. Install Dependencies:

   pip install -r requirements.txt

2. Run the Agent:

   export OPENROUTER_API_KEY="your_key_here"
   python src/agent.py

   This will generate a new entry in data/status_history.json. The default requested model is OpenRouter's ~openai/gpt-latest alias: it means the newest eligible OpenAI GPT model selected by OpenRouter, not a fixed model name. Set OPENROUTER_MODEL to an exact slug for controlled testing or rollback. Each v2 entry records both requested and concrete resolved model identities and the canary-opinion-v2 methodology.

   A score is an editorial opinion, not a calibrated probability or investment recommendation. Status is derived from score (0–30 GREEN, 31–69 YELLOW, 70–100 RED). Evidence quality is reported separately: articles published within the 48-hour freshness window count as fresh; missing collection inputs are marked degraded. A completely empty evidence packet is rejected.

3. View Dashboard: Because of browser security (CORS), checking index.html directly from the file system won't work. Serve it locally:

   python -m http.server

   Then open http://localhost:8000 in your browser.

4. GitHub Deployment (Automated)

To enable the daily automatic updates:

1. Add Secret:

   • Go to your repo Settings -> Secrets and variables -> Actions.
   • Click New repository secret.
   • Name: OPENROUTER_API_KEY
   • Value: sk-or-v1-... (your actual key).

2. Enable GitHub Pages:

   • Go to Settings -> Pages.
   • Under Build and deployment -> Source, select Deploy from a branch.
   • Select Branch: main, Folder: /(root).
   • Click Save.

3. Permissions (Important!):

   • Go to Settings -> Actions -> General.
   • Scroll to Workflow permissions.
   • Select Read and write permissions.
   • Click Save.

4. Test It:

   • Go to the Actions tab.
   • Select "Daily Market Check".
   • Click Run workflow.

Once the workflow finishes, your dashboard will be live at https://<your-username>.github.io/ai-bubble/.