Private Local Ollama + Dynamic LLM Router for Reviews

This workflow enables privacy-focused automation for Travel & Hospitality review management using self-hosted Ollama LLMs. It intelligently analyzes incoming prompts—such as customer reviews, sentiment analysis requests, or image-based feedback—and dynamically routes them to the best local model: text models (qwq, llama3.2, phi4) for reasoning and summarization, qwen2.5-coder for extracting insights via code, and vision models (granite3.2-vision, llama3.2-vision) for photo reviews.

Benefits include zero data leakage to external APIs, optimal model performance per task, and seamless conversation history for contextual review handling. Ideal for hotels, airlines, or tour operators processing sensitive guest feedback locally without cloud costs or compliance risks.

Use cases: Automate review sentiment scoring, generate response templates, analyze review images for issues like cleanliness, or code custom metrics—all processed on your hardware. Setup is straightforward: install Ollama, pull models, configure local API, and activate for instant chat-based review management.