PromptWatchDog - Real-Time Insights Metric Powered by Gemini

[g-emarco]

This PR introduces PromptWatchDog, a serverless, event-driven framework designed to monitor data streams using natural language prompts evaluated by Gemini Pro on Google Cloud. Instead of rigid code-based metrics, users define conditions in English (e.g., "Check if message sentiment is negative"), and Gemini interprets the data in real-time.

Architecture & Flow

• Event Ingestion: Listens to messages on Pub/Sub.
• AI Analysis Engine: Uses Gemini Pro (via LangChain) to evaluate unstructured payloads against natural language metric definitions.
• Dynamic Monitoring: Emits structured JSON logs to aggregate Log-Based Metrics in Cloud Monitoring.
• Local Dashboard: A Next.js UI for managing prompt definitions stored in Firestore.

Key Components Included:

• Watchdog Service (Python 3.11): Deployed on Cloud Run (Functions Framework or Gen2) using uv for dependencies.
• Next.js Dashboard (Local Only): Secure management UI for Firestore prompts (adheres to the Principle of Least Privilege).
• Unified Monitoring Setup: Patterns for using watchdog_id and watchdog_name labels to scale without schema changes.