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name: context-llm-pipeline description: RAG pipeline, embeddings, LLM interactions, and flow orchestration. tags: [backend, ai, rag]

LLM Pipeline Context

Overview

Core AI logic including RAG flows, LLM service orchestration, and vector retrieval.

Active Files

Orchestration (Flows)

• backend/flows/ingestion_flow.py - Document ingestion
• backend/flows/scraping_flow.py - Scrape orchestration
• backend/flows/template_review_flow.py - LLM review flow

Services

• backend/services/llm/orchestrator.py - Main LLM handler
• backend/services/llm/pipeline.py - Pipeline logic
• backend/services/llm/analyzer.py - Analysis logic
• backend/services/research/zai.py - ZAI research integration
• backend/services/search_pipeline_service.py - Search pipeline

Shared Packages

• packages/llm-common/ - Shared types and utilities (Submodule)

Usage

Use this skill when working on RAG, prompt engineering, or vector search logic.