A step-by-step guide to building a self-hosted AI code review pipeline using Ollama and Qwen2.5-Coder 7B. The system listens for GitHub pull request webhooks via a Flask server, fetches PR diffs, sends them to a locally running LLM for analysis, and posts structured review comments back to the PR. Covers HMAC-SHA256 webhook signature verification, diff parsing, prompt engineering for JSON-structured output, GitHub Reviews API integration, ngrok tunneling for local development, GitLab adaptation, and production considerations including background job queues (RQ/Celery), Gunicorn deployment, and rate limiting. Emphasizes data sovereignty and elimination of per-seat cloud AI costs.
Table of contents
How to Set Up AI Code Review With a Local LLMTable of ContentsWhy Self-Host Your AI Code Review?Architecture OverviewSetting Up Ollama and Qwen2.5-CoderBuilding the Webhook ServerIntegrating the Local LLM for Code ReviewPosting Review Comments to GitHubTesting and Running LocallyAdapting for GitLabTips for Production UseWhat Comes NextSort: