Production-Ready Gmail to Jobber Request Automation (AI & GraphQL)

Overview: We require a production-grade automation service that monitors an incoming Gmail inbox, reliably extracts structured work-order data using an LLM, and creates fully populated Jobber Requests via Jobber's GraphQL API. Key Functional Requirements: 1. Ingestion: - Real-time email capture using Gmail API via Google Cloud Pub/Sub webhooks (no inefficient polling). - Robust handling of forwarded/nested email threads to extract the original requester's details, not the forwarder. 2. AI Extraction & Validation: - LLM pipeline (OpenAI/Anthropic) using strict JSON schemas (Structured Outputs / Tool Calling). - Extracted fields: Client Name, Phone, Email, Property Address, Job Title, Work Overview, and Job Notes. 3. Media & Snapshot Engine: - Generate a clean PDF snapshot of the original raw email (HTML-to-PDF via Puppeteer or Playwright). - Extract and forward incoming media/documents (JPEGs, PNGs, PDFs). 4. Jobber Sync: - Query existing clients via GraphQL (`clients` query); match by email or phone. - If not found, execute `clientCreate` mutation. - Create a Jobber Request (`requestCreate` mutation) with all extracted fields, attaching the raw email PDF and media files via Jobber's file upload flow. 5. Reliability & Security: - Deduplication / Idempotency check via a lightweight database (Redis, SQLite, or PostgreSQL) to prevent duplicate requests on webhook retries. - Comprehensive error handling, structured logging, and fallback alerts (e.g., webhook to Discord/Slack or admin email on unparseable threads). Deliverables: - Clean, documented codebase (Node.js or Python). - Setup documentation covering OAuth 2.0 configuration, Pub/Sub provisioning, and environment variables. - Dockerfile / deployment configuration for standard cloud hosting (e.g., Railway, Render, or VPS). Bot Filter: Start your proposal with the keyword "PIPELINE". Bids lacking this keyword or displaying generic AI-generated filler will be archived immediately.