Automated Fleet Fuel Efficiency Reporting with AI Agent
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This workflow automates the generation of fleet fuel efficiency reports by processing incoming data via a Webhook, splitting it, embedding it into a vector store, and querying it with an AI agent. The results are then logged to Google Sheets.
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About This Workflow
Overview
This n8n workflow automates the process of generating and reporting on fleet fuel efficiency. It leverages a combination of n8n's core nodes and Langchain integrations to create an intelligent reporting system. The workflow starts by receiving data through a Webhook. This data is then split into manageable chunks using the Splitter node. These chunks are embedded using HuggingFace embeddings and stored in a Weaviate vector store. When a query is made (implicitly through the agent), the workflow retrieves relevant information from the vector store, utilizes an AI agent with memory and chat capabilities (Anthropic), and finally logs the generated report to a Google Sheet. This is particularly useful for fleet managers and operational analysts who need to track and analyze fuel consumption patterns efficiently.
Key Features
- Webhook Integration: Accepts incoming fleet data via a customizable webhook.
- Text Splitting & Embedding: Processes raw data into embeddings for efficient storage and retrieval.
- Vector Store Persistence: Utilizes Weaviate for storing and querying vector embeddings.
- AI Agent with Memory: Employs Langchain's agent with chat and memory capabilities for intelligent data analysis and report generation.
- Google Sheets Logging: Automatically logs the generated reports to a specified Google Sheet for easy access and further analysis.
How To Use
- Configure Webhook: Set up the Webhook node with your desired path (e.g.,
fleet_fuel_efficiency_report) to receive incoming fleet data. - Set up Langchain Nodes: Configure the Splitter, Embeddings (HuggingFace), and Vector Store (Weaviate) nodes with appropriate parameters.
- Connect Weaviate: Ensure your Weaviate instance is correctly configured with credentials and the
indexNamematches. - Configure AI Agent: Set up the Memory, Tool (Weaviate vector store), Chat (Anthropic), and Agent nodes. Define the prompt for the Agent to generate the fuel efficiency report.
- Google Sheets Integration: Configure the Google Sheets node with your
SHEET_IDandsheetNameto log the generated reports. - Activate Workflow: Trigger the workflow by sending data to the configured Webhook.
Apps Used
Workflow JSON
{
"id": "647e3c90-c010-4ade-86ad-a3eb62efe5fd",
"name": "Automated Fleet Fuel Efficiency Reporting with AI Agent",
"nodes": 0,
"category": "Automotive 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: 647e3c90-c010...
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