This n8n workflow streamlines the process of triaging and managing game bug reports by automating data collection, natural language processing, and storage. It begins with a webhook trigger that captures bug reports, then splits and processes textual data. Using AI models, it generates embeddings for semantic understanding and stores them in a Redis vector database for efficient retrieval. The workflow includes a question-answering component that interacts with language models for bug prioritization, and it logs all activities into Google Sheets. This automation is ideal for game developers and QA teams aiming to efficiently organize, evaluate, and track bug reports, reducing manual effort and improving response times.
Automated Game Bug Triage and Logging Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsCohere, @n8n/n8n-nodes-langchain.lmChatHf, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreRedis, googleSheets, stickyNote, webhook |
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