I have a fully coded Python 3.11 / Flask application that extracts, classifies, and archives construction-document metadata through the Gemini and Google Drive APIs. Everything runs locally, but deployment keeps failing in Google Cloud Build. The logs point to configuration errors inside our YAML files, even though the core AI workflow is already solid. Here is what I need within the next 7 days: • Audit the existing Cloud Build and Cloud Functions (2nd Gen) configuration files. • Correct the identified syntax issues so the build pipeline completes without error. • Deploy the working solution to my GCP project and verify that each endpoint functions end-to-end—Gemini calls, Drive writes, and Flask routes. • Document the fixes you applied so I can maintain the pipeline for future feature work. Stack in use: Python 3.11, Flask, Cloud Functions Gen 2, Gemini API, Drive API. You’ll have direct access to the repository and GCP console once an NDA is signed. If you are comfortable troubleshooting GCP configuration, can interpret Cloud Build logs quickly, and can turn around a clean deployment this week, I’d like to hear how you would approach the task and when you can start.