Automate code reviews for GitLab MRs with Gemini AI and JIRA context

What it does Automates code review by listening for a comment trigger on GitLab merge requests, summarising the diff, and using an LLM to post constructive, line‑specific feedback. If a JIRA ticket ID is found in the MR description, the ticket’s summary is used to inform the AI review. Use cases - Quickly obtain high‑quality feedback on MRs without waiting for peers. - Highlight logic, security or performance issues that might slip through cursory reviews. - Incorporate project context by pulling in related JIRA ticket summaries. Good to know - Triggered by commenting ai-review on a merge request. - The LLM returns only high‑value findings; if nothing critical is detected, the workflow posts an “all clear” message. - You can swap out the LLM (Gemini, OpenAI, etc.) or adjust the prompt to fit your team’s guidelines. - AI usage may incur costs or be geo‑restricted depending on your provider n8n.io. How it works - Webhook listener: A Webhook node captures GitLab note events and filters for the trigger phrase. - Fetch & parse: The workflow retrieves MR details and diffs, splitting each change into “original” and “new” code blocks. - Optional JIRA context: If your MR description includes a JIRA key (e.g., PROJ-123), the workflow fetches the ticket (and parent ticket for subtasks) and composes a brief context summary. - LLM review: The parsed diff and optional context are sent to an LLM with instructions to identify logic, security or performance issues and suggest improvements. - Post results: Inline comments are posted back to the MR at the appropriate file/line positions; if no issues are found, a single “all clear” note is posted. How to use - Import the template JSON and open the Webhook node. Replace the REPLACEWITHUNIQUEPATH placeholder with your desired path and configure a GitLab project webhook to send MR comments to that URL. - Select your LLM credentials in the Gemini (or other LLM) node, and optionally add JIRA credentials in the JIRA nodes. - Activate the workflow and comment ai-review on any merge request to test it. - For each review, the workflow posts status updates (“AI review initiated…”) and final comments. Requirements - A GitLab project with a generate Personal Access Token (PAT) stored as an environment variable (GITLABTOKEN). - LLM credentials (e.g., Google Gemini) and optional JIRA credentials. Customising this workflow - Change the trigger phrase in the Trigger Phrase Filter node. - Modify the LLM prompt to focus on different aspects (e.g., style, documentation). - Filter out certain file types or directories before sending diffs to the LLM. - Integrate other services (Slack, email) to notify teams when reviews are complete.