Intelligent Crop Yield Prediction and Analysis
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Leverage AI to predict crop yields with advanced data analysis. This workflow automates the ingestion, processing, and prediction of crucial agricultural data, empowering informed decision-making.
About This Workflow
The Crop Yield Predictor workflow is a powerful solution designed to revolutionize agricultural planning and management. By integrating with your data sources via a webhook, it intelligently processes agricultural information, splits it into manageable chunks, and generates embeddings for semantic understanding. It then stores these embeddings in a Supabase vector database for efficient querying. An AI agent, powered by OpenAI's chat models and equipped with tools for data retrieval and conversational memory, analyzes the data to provide accurate crop yield predictions. Finally, all insights and predictions are logged to a Google Sheet for easy review and further analysis.
Key Features
- Automated Data Ingestion: Seamlessly receive agricultural data through a webhook.
- AI-Powered Prediction: Utilizes advanced AI models for accurate crop yield forecasting.
- Vector Database Integration: Stores and queries data efficiently using Supabase.
- Conversational Analysis: Engages with data through an AI agent with memory.
- Automated Logging: Records all predictions and insights to Google Sheets.
How To Use
- Configure Webhook: Set up an incoming webhook to receive your agricultural data.
- Data Splitting & Embedding: The workflow automatically splits incoming data and generates embeddings using Hugging Face.
- Vector Store Setup: Configure your Supabase credentials and specify the
crop_yield_predictorindex name for storing embeddings. - AI Agent Configuration: Connect your OpenAI API credentials and set up the chat model and memory buffer.
- Tool Integration: Define the Supabase vector store as a tool for the AI agent.
- Google Sheets Logging: Provide your Google Sheets API credentials and specify the
Logsheet name for recording predictions.
Apps Used
Workflow JSON
{
"id": "f09e1aec-0edf-4024-99f3-b49f7d2fc817",
"name": "Intelligent Crop Yield Prediction and Analysis",
"nodes": 9,
"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: f09e1aec-0edf...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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