dreamlink-analysis-pipeline

An automated dream analysis pipeline coordinates validation, OpenAI reasoning, and multi-table Supabase storage. It processes dream submissions end-to-end, applying user profile personalization and extracting biblical citations before persisting results.

Caching AI dream interpretations uses TTL-based cache lookups to prevent redundant OpenAI API calls. The pipeline checks for cache misses, retrieves cached analysis if available, and gracefully degrades to a fresh API call if the cache fails.

Extracting and storing biblical citations from OpenAI analysis involves parsing structured JSON outputs and persisting the verse references. The pipeline saves these extracted references into dedicated database tables alongside the main dream entries.

Yes, you can trigger asynchronous image generation after storing dream analysis results. The pipeline initiates non-blocking visualizations via the dreamlink-image-gen workflow once the analysis is successfully persisted to the database.

Error recovery in a dream processing workflow handles cache and OpenAI failures with graceful degradation. It ensures the pipeline continues operating with actionable telemetry for monitoring, rather than crashing during transient service disruptions.

User profiles are required to personalize AI-generated dream interpretations. The pipeline fetches user data to adjust the reading level and tailor the OpenAI prompts, ensuring the final analysis matches the submitter's specific context.