Automated Patch Note Summarizer for Instant Insights
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Streamline your update process with the Patch Note Summarizer. This n8n workflow automatically processes incoming patch notes, extracts key information, and generates concise summaries for easy review and logging.
About This Workflow
The Patch Note Summarizer is an intelligent n8n workflow designed to ingest raw patch notes and transform them into easily digestible summaries. It leverages powerful AI models through Langchain to process text, embed information into a vector store (Weaviate), and generate coherent summaries. This workflow is triggered via a webhook, making it ideal for real-time integration with various game or software update systems. The summarized output is then logged to a Google Sheet, providing a centralized and organized record of all update changes. Reduce manual effort and gain instant clarity on software or game updates with this efficient automation.
Key Features
- Automated Ingestion: Accepts patch notes via a webhook for seamless integration.
- AI-Powered Summarization: Utilizes advanced AI models to condense lengthy patch notes into concise summaries.
- Intelligent Data Chunking: Effectively processes large texts by splitting them into manageable chunks for analysis.
- Vector Store Integration: Leverages Weaviate for efficient storage and retrieval of embedded patch note information.
- Automated Logging: Logs all processed summaries to a Google Sheet for easy tracking and historical reference.
How To Use
- Webhook Trigger: Configure the
Webhooknode to receive incoming patch note data via a POST request to thepatch_note_summarizerendpoint. - Text Splitting: The
Splitternode automatically breaks down the incoming text into smaller, manageable chunks for AI processing (configured with a chunk size of 400 and overlap of 40). - Embedding Generation: The
Embeddingsnode (using Cohere) generates vector embeddings for each text chunk, preparing them for storage and retrieval. - Data Ingestion: The
Insertnode stores these embeddings in a Weaviate vector database under thepatch_note_summarizerindex. - Query and Retrieval: The
Querynode retrieves relevant information from the Weaviate database. - AI Agent and Chat: The
ToolandAgentnodes orchestrate the AI conversation, using the retrieved data, memory (Memorynode), and a chat model (Chatnode) to generate a summary. - Logging: The
Sheetnode appends the generated summary to a designated Google Sheet (specified bySHEET_IDandLogsheet name).
Apps Used
Workflow JSON
{
"id": "d857c0fb-0ca2-4229-91db-1012da3ef7fd",
"name": "Automated Patch Note Summarizer for Instant Insights",
"nodes": 7,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: d857c0fb-0ca2...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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