Next-Generation
RAG Pull Request Engineering

Eliminate code review bottlenecks. ReviewFlow AI intelligently parses AST structures, clusters modified files into cohesive logical chapters, and performs RAG analysis across complex pull requests.

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Architectural Blueprint

The 9-Stage Intelligent Review Engine

Every pull request passes through an exhaustive multi-module pipeline balancing speed and accuracy.

Module 01

GitHub Connector

Securely ingests pull requests, commits, and diff payloads.

Module 02

Diff Parser

Analyzes modified hunks, file types, and token limits.

Module 03

Static AST Engine

Parses Python AST syntax trees for complexity and hazards.

Module 04

Chapter Decomposition

Partitions large PRs into cohesive reviewable logical chapters.

Module 05

RAG Ingestion

Tokenizes code hunks and chunks for contextual embedding.

Module 06

Vector Store (ChromaDB)

Stores embeddings for semantic nearest-neighbor retrieval.

Module 07

Knowledge Graph

Maps cross-module dependencies and entity relationships.

Module 08

Dual LLM Engine

Groq & Gemini fallbacks evaluate engineering trade-offs.

Module 09

Review Presenter

Delivers actionable, line-level feedback and risk metrics.

Next-Generation RAG Pull Request Engineering