AI-Powered Local Attraction Recommender
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Build a smart, AI-driven local attraction recommender system that leverages a vector database for relevant information retrieval. This workflow dynamically provides personalized suggestions and logs all interactions, perfect for tourism, hospitality, or local businesses.
About This Workflow
This n8n workflow creates a sophisticated AI assistant capable of recommending local attractions. It starts with a Webhook trigger to receive user queries or new attraction data. For data ingestion, it processes text via a Splitter, creates Embeddings using Cohere, and stores them in a Pinecone vector database. For recommendations, it utilizes an Anthropic Chat model, equipped with Memory for conversational context and a Tool to query the Pinecone index. An intelligent Agent orchestrates these components to generate accurate and personalized attraction suggestions. All interactions and recommendations are diligently logged into Google Sheets for analytics and record-keeping, making it a powerful solution for enhanced customer engagement.
Key Features
- AI-Driven Recommendations: Generates intelligent and personalized local attraction suggestions using Anthropic's LLM.
- Vector Database Integration: Utilizes Pinecone for efficient storage and retrieval of attraction data, enhancing recommendation accuracy.
- Conversational Memory: Maintains context throughout user interactions for a seamless and natural recommendation experience.
- Automated Data Ingestion: Easily processes and embeds new attraction data into Pinecone via a webhook trigger.
- Interaction Logging: Automatically records all recommendations and queries to Google Sheets for monitoring and improvement.
How To Use
- Webhook Configuration: Set the
Webhooknode's path to your desired endpoint (e.g.,/local_attraction_recommender) to receive incoming requests. - API Key Setup: Configure your Cohere, Anthropic, and Pinecone API credentials within n8n.
- Pinecone Index: Ensure the
indexNamein both theInsertandQueryPinecone nodes matches your created Pinecone index (local_attraction_recommender). - Google Sheets Integration: Provide your Google Sheets ID and the specific sheet name (
Log) for appending interaction data. - Agent Customization: Adjust the
Agentnode's prompt to define how the AI should respond to queries and utilize its available tools for recommending attractions.
Apps Used
Workflow JSON
{
"id": "2a3489a7-8986-4c73-9bff-18edb563c480",
"name": "AI-Powered Local Attraction Recommender",
"nodes": 6,
"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: 2a3489a7-8986...
About the Author
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