Admin Overview

Welcome to the operator’s manual for Digest Engine. This guide is assuming you are running the system, not writing code for it.

Component Map

• Django (API & Workers): Python core running the REST API.
• Celery Worker: Asynchronous task runner for LangGraph skills and entity extraction.
• Celery Beat: Cron scheduler for trend gathering and fetching RSS/Reddit plugins.
• PostgreSQL: Holds all standard application state and configuration.
• Redis: Acts as the message broker for Celery and the WebSockets channel layer.
• Qdrant: The Vector Database storing the high-dimensional embeddings for Cosine relevance calculations.
• Ollama (Optional): A containerized local LLM server for generating embeddings locally without paying OpenAI/OpenRouter.
• Nginx: Reverse proxy to route /api/ traffic to Django and / traffic to Next.js.
• Next.js: The frontend App Router.

Request Path

Browser -> Nginx -> Next.js (for HTML) -> Nginx -> Django Gunicorn -> Postgres.

Ingestion Path

Beat triggers fetch -> Celery Worker -> Fetches RSS array -> Django DB -> Triggers Embedding -> Saves to Qdrant -> Enqueues LangGraph Pipeline -> Celery Worker Executes Skills.

AI Pipeline Path

Orchestrated by LangGraph inside a Celery task. Calls out to the specific OPENROUTER_API_BASE or Local Ollama instance. State transitions are saved continuously to Postgres mapping to SkillResults.

Realtime Path

Browser -> Nginx (WebSocket Upgrade) -> Django Daphne ASGI -> Redis CHANNEL_LAYER -> Broadcast to users.