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metadata
title: LifeFlow AI - Intelligent Trip Planning System
emoji: 🗺️
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: mit
short_description: Your journey, in perfect rhythm
tags:
  - mcp-in-action-track-enterprise
  - mcp-in-action-track-consumer
  - mcp-in-action-track-creative

✨ LifeFlow AI: Intelligent Trip Planning System

Your journey, in perfect rhythm. > An enterprise-grade, multi-agent system that orchestrates your daily schedule using real-world data, hybrid AI architecture, and mathematical optimization.

📖 Overview

LifeFlow AI is not just a chatbot; it's a State Machine for Real-World Operations. It solves the complexity of daily travel planning—considering traffic, weather, opening hours, and route optimization—by coordinating a team of specialized AI agents.

Unlike traditional AI planners that hallucinate locations, LifeFlow grounds every decision in Real-Time Data (Google Maps & OpenWeather) and uses Mathematical Optimization (TSP/OR-Tools) for routing.

🚀 Key Innovation: Hybrid AI Architecture

We solve the "Trilemma" of AI Agents: Cost vs. Speed vs. Intelligence.

1. Dual-Brain System 🧠 + ⚡

Instead of using one expensive model for everything, LifeFlow uses a tiered approach:

  • Primary Brain (The Leader): Uses high-reasoning models (e.g., GPT-5, Gemini 2.5 Pro) for complex intent understanding, team orchestration, and final report generation.
  • Acceleration Layer (The Muscle): Uses ultra-fast, low-cost models (e.g., Groq/Llama-3, Qwen 2.5, Gemini Flash-lite, GPT mini) for high-volume tool execution (searching POIs, checking weather).

2. Context-Offloading Protocol 📉

Traditional agents paste massive JSON search results into the chat context, burning thousands of tokens.

  • LifeFlow's Approach: Agents treat data like "Hot Potatoes."
  • Mechanism: Raw data (reviews, photos, coordinates) is offloaded to a structured database immediately. Agents only pass Reference IDs (e.g., scout_result_123) to the next agent.
  • Result: Token consumption reduced by 75% (from ~80k to ~20k per run).

🤖 The Agent Team

LifeFlow orchestrates 6 specialized agents working in a strict pipeline:

  1. 📋 Planner: Analyzes vague user requests (e.g., "I need to buy coffee and visit the bank") and converts them into structured JSON tasks.
  2. 👨‍✈️ Team Leader: The State Machine orchestrator. Enforces SOPs and handles error recovery.
  3. 🗺️ Scout (Fast Mode): Interacts with Google Places API to verify locations and retrieve coordinates.
  4. ⚡ Optimizer (Fast Mode): Uses routing algorithms to solve the Traveling Salesperson Problem (TSP) with time windows.
  5. 🧭 Navigator (Fast Mode): Calculates precise traffic impacts and generates polyline routes.
  6. 🌤️ Weatherman (Fast Mode): Checks hyper-local weather forecasts for specific arrival times.
  7. 📊 Presenter: Compiles all data (from the DB) into a human-readable, formatted report.

🛠️ Features

  • BYOK (Bring Your Own Key): Secure client-side key management for Google Maps, OpenWeather, and LLMs.
  • Zero-Cost Validation: Smart API testing mechanism that checks key validity without incurring charges.
  • Interactive Map: Visualizes routes, stops, and alternative POIs using Folium.
  • Graceful Cancellation: Cooperative signal handling to terminate background agents instantly.
  • Reactive UI: Modern Gradio interface with real-time streaming and responsive layouts.

⚙️ Configuration

LifeFlow AI allows deep customization via the Settings panel:

Supported Providers

  • Google Gemini: 2.5 Pro, 2.5 Flash, 2.0 Flash.
  • OpenAI: GPT-5, GPT-5-mini, GPT-4o-mini.
  • Groq: Llama 3.3 70B, Qwen 2.5 32B (for Acceleration).

Fast Mode (Hybrid)

Enable Fast Mode in settings to offload search and routing tasks to Groq. This significantly reduces latency and API costs while maintaining high-quality reasoning for the final output.

📦 Tech Stack

  • Framework: Agno (formerly Phidata) for Agent Orchestration.
  • UI/UX: Gradio 5.x with custom CSS themes. (update to Gradio 6.x soon)
  • Services: Google Maps Platform (Places, Routes), OpenWeatherMap.
  • Infrastructure: Python 3.11, Docker.

💻 Local Installation

To run LifeFlow AI locally:

TODO

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference