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context-llm-pipeline

RAG pipeline, embeddings, LLM interactions, and flow orchestration.

personAuthor: jakexiaohubgithub

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.