OpenAI MongoDB AI Agent for Movie Recommendations and Favorites

Name: OpenAI MongoDB AI Agent for Movie Recommendations and Favorites
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Author: Free N8N

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AI & Machine Learningai agentautomationlangchainmongodbmovie recommendationopenai

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

ai agent

automation

langchain

mongodb

movie recommendation

openai

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.