Domain

JourneyForge AI

JourneyForge coordinates six specialist agents to build a comprehensive travel plan: 1. **Destination Agent** — attractions, culture, weather, and local insights 2. **Flight Agent** — routes, timing, layovers, and transfers 3. **Hotel Agent** — accommodation matching style and budget 4. **Dining Agent** — restaurant recommendations and food experiences 5. **Budget Agent** — itemized cost breakdown and optimization 6. **Itinerary Agent** — day-by-day schedules with logistics Enter your trip preferences and receive a full markdown itinerary.

Python Streamlit

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JourneyForge AI

AI travel planning team by Sharad Khare.

JourneyForge AI is a six-agent Agno team that plans complete trips — destinations, flights, hotels, dining, budgets, and day-by-day itineraries — from your preferences in a Streamlit interface.

Built and maintained by Sharad Khare — AI strategist, full-stack developer, and creator of practical agent workflows.

What this project does

JourneyForge coordinates six specialist agents to build a comprehensive travel plan:

1. Destination Agent — attractions, culture, weather, and local insights

2. Flight Agent — routes, timing, layovers, and transfers

3. Hotel Agent — accommodation matching style and budget

4. Dining Agent — restaurant recommendations and food experiences

5. Budget Agent — itemized cost breakdown and optimization

6. Itinerary Agent — day-by-day schedules with logistics

Enter your trip preferences and receive a full markdown itinerary.

Why Sharad Khare built JourneyForge AI

Trip planning spans flights, lodging, dining, budgeting, and scheduling — domains that overwhelm a single prompt. JourneyForge demonstrates how an Agno coordinate team with DuckDuckGo research produces thorough, practical itineraries from structured user input.

How it works

Trip Preferences Form
   │
   ▼
Coordinator Team (JourneyForge AI Team)
   │
   ├─ Destination Agent → attractions & culture
   ├─ Flight Agent → routing & timing
   ├─ Hotel Agent → accommodation options
   ├─ Dining Agent → restaurant curation
   ├─ Budget Agent → cost breakdown
   └─ Itinerary Agent → daily schedule
   │
   ▼
Comprehensive Markdown Itinerary

Features

Six-agent Agno coordinate team with reasoning tools
DuckDuckGo web search for current travel data
Streamlit form for dates, budget, style, and priorities
Day-by-day itinerary with budget breakdown
Modular package layout for agent customization

Quick start

cd journeyforge-ai
pip install -r requirements.txt
streamlit run app.py

Required API key

OpenAI API key — enter in the sidebar when running the app

Example inputs

Destination: Kyoto, Japan
Dates: 7-day spring trip from Mumbai
Style: Mid-range · Pace: Moderate
Companions: Couple
Budget: $3,000–$5,000 USD
Priorities: Food & Dining, Culture, Photography

Project structure

journeyforge-ai/
├── app.py
├── journeyforge/
│   ├── config.py
│   ├── agents.py
│   └── team.py
├── requirements.txt
├── pyproject.toml
└── README.md

Topics

Sharad KhareJourneyForge AIAI travel plannerAgno multi-agent trip planningitinerary generator Streamlitflight hotel dining budget agentsvacation planning AIday-by-day travel itineraryDuckDuckGo travel research agent.

Who this is for

Travelers planning detailed multi-day trips
Digital nomads prototyping AI concierge workflows
Travel bloggers generating itinerary drafts
Developers learning Agno coordinate team patterns

Use cases

Generate a full trip itinerary from preference inputs
Get budget breakdowns across flights, hotels, and dining
Research destinations with web-backed agent search
Learn how coordinate teams orchestrate domain specialists

Author

Website: sharadkhare.in

License

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bash

cd journeyforge-ai
pip install -r requirements.txt
streamlit run app.py