📖 Chat with GitHub issues using OpenAI and Redis vector search

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💡 Pro Tip — If you need GitHub data beyond what the REST API gives you, ScraperNode has a repository scraper that extracts metadata at scale without token rate limits.

Description

Chat with Your GitHub Issues Using AI 🤖

Ever wanted to just ask your repository what’s going on instead of scrolling through endless issue lists? This workflow lets you do exactly that.

What Does It Do?

Turn any GitHub repo into a conversational knowledge base. Ask questions in plain English, get smart answers powered by AI and vector search.

• “Show me recent authentication bugs” → AI finds and explains them
• “What issues are blocking the release?” → Instant context-aware answers
• “Are there any similar problems to #247?” → Semantic search finds connections you’d miss

The Magic ✨

1. Slurp up issues from your GitHub repo (with all the metadata goodness)
2. Vectorize everything using OpenAI embeddings and store in Redis
3. Chat naturally with an AI agent that searches your issue database
4. Get smart answers with full conversation memory

Quick Start

You’ll need:

• OpenAI API key (for the AI brain)
• Redis 8.x (for vector search magic)
• GitHub repo URL (optional: API token for speed)

Get it running:

1. Drop in your credentials
2. Point it at your repo (edit the owner and repository params)
3. Run the ingestion flow once to populate the database
4. Start chatting!

Tinker Away 🔧

This is your playground. Here are some ideas:

• Swap the data source: Jira tickets? Linear issues? Notion docs? Go wild.
• Change the AI model: Try different GPT models or even local LLMs
• Add custom filters: Filter by labels, assignees, or whatever matters to you
• Tune the search: Adjust how many results come back, tweak relevance scores
• Make it public: Share the chat interface with your team or users
• Auto-update: Hook it up to webhooks for real-time issue indexing

Built with n8n, Redis, and OpenAI. No vendor lock-in, fully hackable, 100% yours to customize.

🔗 Nodes Used

HTTP Request, AI Agent, Embeddings OpenAI, OpenAI Chat Model, Redis Chat Memory, Default Data Loader

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup