Chat with GitHub issues using OpenAI and Redis vector search
Ready for 3.0What this workflow does
This AI workflow has 11 nodes and runs manually, when you click “Execute workflow” (plus 1 other trigger). Along the way it connects Embeddings OpenAI, OpenAI Chat Model, Redis Chat Memory and Redis Vector Store.
How it runs
Trigger: Manually, when you click “Execute workflow” (plus 1 other trigger).
- Fetch issues from GitHub (HTTP Request): calls an HTTP API
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; 1 tool (Augment with results from Redis); memory: Redis Chat Memory
- Vectorize and store in Redis (Redis Vector Store): stores documents in the Redis vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (9)
- Manual Trigger
n8n-nodes-base.manualTrigger - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Redis Chat Memory
@n8n/n8n-nodes-langchain.memoryRedisChat - HTTP Request
n8n-nodes-base.httpRequest - Redis Vector Store
@n8n/n8n-nodes-langchain.vectorStoreRedis - AI Agent
@n8n/n8n-nodes-langchain.agent
From the author
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…