YouTube Comment Summarizer Using RAG Agent and Pinecone
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Automate the summarization of YouTube comments using a RAG Agent and Pinecone vector database. This workflow processes incoming comments via a webhook, splits them, embeds them for storage, and then retrieves relevant information to generate concise summaries.
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About This Workflow
Overview
This n8n workflow automates the summarization of YouTube comments. It leverages a Retrieval-Augmented Generation (RAG) approach, integrating Langchain nodes with a webhook trigger to receive comment data. The comments are then split into manageable chunks, embedded using OpenAI's embeddings model, and stored in a Pinecone vector database for efficient retrieval. A Pinecone query node retrieves context, which is then fed into a RAG Agent along with chat history (managed by Window Memory) and an OpenAI chat model to generate a summary. The results are logged to a Google Sheet, with Slack alerts for any errors. This workflow is ideal for content creators or social media managers who need to quickly understand the sentiment and key themes within their YouTube comments without manual review.
Key Features
- Webhook Trigger: Accepts incoming YouTube comment data via HTTP POST.
- Text Splitting: Divides comments into smaller, processable chunks.
- OpenAI Embeddings: Converts text into vector representations for semantic search.
- Pinecone Vector Store: Stores and retrieves comment embeddings efficiently.
- RAG Agent: Utilizes Langchain's RAG capabilities for context-aware summarization.
- Window Memory: Manages chat history for more coherent agent responses.
- Google Sheets Logging: Records processing status for tracking and analysis.
- Slack Alerts: Notifies users of any workflow errors.
How To Use
- Set up Credentials: Configure OpenAI API and Pinecone API credentials within n8n.
- Configure Webhook Trigger: Set the HTTP method to POST and the path to 'youtube-comment-summarizer' or a custom path.
- Adjust Text Splitter: Modify
chunkSizeandchunkOverlapparameters as needed for your comment volume and length. - Set OpenAI Model and Pinecone Index: Ensure the correct OpenAI embedding model and Pinecone index name ('youtube_comment_summarizer') are selected.
- Configure Google Sheets Append: Provide your Google Sheets API credentials, the
SHEET_IDfor your document, and theLogsheet name. - Configure Slack Alert: Add your Slack API credentials and the target channel ('#alerts').
- Trigger the workflow: Send comment data to the configured webhook URL to initiate the summarization process.
Apps Used
Workflow JSON
{
"id": "a3f29ddd-cad6-44f6-9f64-a7e9fa508d78",
"name": "YouTube Comment Summarizer Using RAG Agent and Pinecone",
"nodes": 0,
"category": "Social Media Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: a3f29ddd-cad6...
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