Automated Neighborhood Safety Insights with AI
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This workflow creates an intelligent AI assistant that ingests neighborhood safety data, processes it using advanced AI models, and provides contextual insights. It leverages a Retrieval-Augmented Generation (RAG) architecture to ensure accurate and relevant responses, logging all interactions for review.
About This Workflow
This powerful n8n workflow establishes a sophisticated AI assistant designed to enhance neighborhood safety. By ingesting unstructured text data—such as incident reports, community feedback, or safety guidelines—via a webhook, it automatically processes and contextualizes this information. Text is intelligently split and converted into vector embeddings using HuggingFace models, then stored in a Redis vector database. A Langchain Agent, powered by Anthropic's advanced language model and equipped with conversational memory, queries this vector store to provide highly relevant and context-aware responses to inquiries about neighborhood safety. All interactions and generated insights are meticulously logged in Google Sheets for auditing and further analysis, empowering communities and organizations to make data-driven safety decisions.
Key Features
- Webhook Trigger: Seamlessly ingest data from any external source with a dedicated API endpoint.
- Advanced Text Processing: Automatically split and embed text using HuggingFace for deep semantic understanding.
- Redis Vector Store (RAG): Efficiently store and retrieve contextual information for accurate, knowledge-grounded AI responses.
- Intelligent Langchain Agent: Orchestrates complex AI interactions, utilizing Anthropic's LLM, custom tools, and conversational memory for natural dialogue.
- Google Sheets Logging: Maintain a comprehensive, auditable record of all AI interactions and generated insights for review and analysis.
How To Use
- Configure Webhook: Set the
pathparameter for your incoming data toneighborhood_safety_insightsin the 'Webhook' node. - Set up HuggingFace Credentials: Add your HuggingFace API key to the 'Embeddings' node's credentials.
- Connect Redis: Provide your Redis API credentials to both the 'Insert' and 'Query' nodes. Ensure the
indexNameis consistent (neighborhood_safety_insights). - Integrate Anthropic: Add your Anthropic API credentials to the 'Chat' node.
- Google Sheets Setup: Connect your Google Sheets OAuth2 API credentials to the 'Sheet' node, specifying your
documentId(SHEET_ID) and desiredsheetName(e.g., "Log"). - Activate Workflow: Once all credentials and parameters are configured, activate the workflow to start processing incoming safety data and generating insights.
Apps Used
Workflow JSON
{
"id": "0ea089fa-9b7b-4ae7-bbd6-4b33d254f2ea",
"name": "Automated Neighborhood Safety Insights with AI",
"nodes": 11,
"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: 0ea089fa-9b7b...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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