OpenAI MongoDB AI Agent for Movie Recommendations and Favorites
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Automate movie recommendations and favorite storage with this n8n workflow. It leverages OpenAI's Chat Model, MongoDB's aggregation capabilities, and a memory buffer to provide context-aware responses and manage user preferences.
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About This Workflow
Overview
This n8n workflow creates an intelligent AI agent powered by OpenAI and MongoDB, designed for movie enthusiasts. It can process chat messages, query a MongoDB collection for movie data using aggregation pipelines, and store user-favorite movies. The workflow utilizes Langchain nodes for AI interaction and memory management, enabling sophisticated conversational capabilities and personalized movie suggestions.
Key Features
- Dynamically generates MongoDB aggregation pipelines using OpenAI.
- Integrates with OpenAI's Chat Model for natural language processing.
- Utilizes a Window Buffer Memory to maintain conversational context.
- Supports querying movie data from a MongoDB collection.
- Allows storing user-favorite movies back into MongoDB via a dedicated tool workflow.
How To Use
- Configure your OpenAI API credentials and MongoDB connection.
- Ensure your MongoDB database has a 'movies' collection with a schema similar to the example provided.
- Set up the 'When chat message received' node as a webhook to trigger the workflow.
- Interact with the AI agent via the webhook, asking for movie recommendations or specifying favorite movies.
Apps Used
Workflow JSON
{
"id": "1ed3228b-dbbd-4d0a-92f8-26035e216aeb",
"name": "OpenAI MongoDB AI Agent for Movie Recommendations and Favorites",
"nodes": 0,
"category": "AI & Machine Learning",
"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: 1ed3228b-dbbd...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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