diff --git a/README.md b/README.md index 45b94c2..0439d6e 100644 --- a/README.md +++ b/README.md @@ -13,11 +13,23 @@

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# 🌟 Awesome LLM Apps -A curated collection of awesome LLM apps built with RAG and AI agents. This repository features LLM apps that use models from OpenAI, Anthropic, Google, and open-source models like DeepSeek, Qwen or Llama that you can run locally on your computer. +A curated collection of **Awesome LLM apps built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more.** This repository features LLM apps that use models from OpenAI, Anthropic, Google, and open-source models like DeepSeek, Qwen or Llama that you can run locally on your computer.

@@ -28,21 +40,9 @@ A curated collection of awesome LLM apps built with RAG and AI agents. This repo ## 🤔 Why Awesome LLM Apps? - 💡 Discover practical and creative ways LLMs can be applied across different domains, from code repositories to email inboxes and more. -- 🔥 Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with RAG and AI Agents. +- 🔥 Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with AI Agents, Agent Teams, MCP & RAG. - 🎓 Learn from well-documented projects and contribute to the growing open-source ecosystem of LLM-powered applications. -## 🚨 Open Source AI Agent Hackathon - -We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosystem partners — open to all developers, builders, and startups working on agents, RAG, tool use, or multi-agent systems. - -- Win up to **$25,000** in cash by building Agents -- Top 5 projects will be featured in the top trending [Awesome LLM Apps](https://github.com/Shubhamsaboo/awesome-llm-apps) repo. -- **$20,000** worth of API and tool use credits from the partners - -### Participate Now: [Global AI Agent Hackathon](https://github.com/global-agent-hackathon/global-agent-hackathon-may-2025) - -⭐ Star this repo and subscribe to [Unwind AI](https://www.theunwindai.com) for latest updates. - ## 📂 Featured AI Projects ### AI Agents @@ -66,16 +66,19 @@ We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosy ### 🚀 Advanced AI Agents * [🔍 AI Deep Research Agent](advanced_ai_agents/single_agent_apps/ai_deep_research_agent/) +* [🤝 AI Consultant Agent](advanced_ai_agents/single_agent_apps/ai_consultant_agent) * [🏗️ AI System Architect Agent](advanced_ai_agents/single_agent_apps/ai_system_architect_r1/) * [🎯 AI Lead Generation Agent](advanced_ai_agents/single_agent_apps/ai_lead_generation_agent/) * [💰 AI Financial Coach Agent](advanced_ai_agents/multi_agent_apps/ai_financial_coach_agent/) * [🎬 AI Movie Production Agent](advanced_ai_agents/single_agent_apps/ai_movie_production_agent/) * [📈 AI Investment Agent](advanced_ai_agents/single_agent_apps/ai_investment_agent/) * [🏋️‍♂️ AI Health & Fitness Agent](advanced_ai_agents/single_agent_apps/ai_health_fitness_agent/) +* [🚀 AI Product Launch Intelligence Agent](advanced_ai_agents/multi_agent_apps/product_launch_intelligence_agent) * [🗞️ AI Journalist Agent](advanced_ai_agents/single_agent_apps/ai_journalist_agent/) * [🧠 AI Mental Wellbeing Agent](advanced_ai_agents/multi_agent_apps/ai_mental_wellbeing_agent/) * [📑 AI Meeting Agent](advanced_ai_agents/single_agent_apps/ai_meeting_agent/) * [🧬 AI Self-Evolving Agent](advanced_ai_agents/multi_agent_apps/ai_Self-Evolving_agent/) +* [🎧 AI Social Media News and Podcast Agent](advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/) ### 🎮 Autonomous Game Playing Agents @@ -94,6 +97,7 @@ We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosy * [👨‍🏫 AI Teaching Agent Team](advanced_ai_agents/multi_agent_apps/agent_teams/ai_teaching_agent_team/) * [💻 Multimodal Coding Agent Team](advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_coding_agent_team/) * [✨ Multimodal Design Agent Team](advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_design_agent_team/) +* [🌏 AI Travel Planner Agent Team](/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/) ### 🗣️ Voice AI Agents @@ -104,12 +108,14 @@ We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosy ### 🌐 MCP AI Agents -* [♾️ MCP Browser Agent](mcp_ai_agents/browser_mcp_agent/) -* [🐙 MCP GitHub Agent](mcp_ai_agents/github_mcp_agent/) +* [♾️ Browser MCP Agent](mcp_ai_agents/browser_mcp_agent/) +* [🐙 GitHub MCP Agent](mcp_ai_agents/github_mcp_agent/) +* [📑 Notion MCP Agent](mcp_ai_agents/notion_mcp_agent) +* [🌍 AI Travel Planner MCP Agent](mcp_ai_agents/ai_travel_planner_mcp_agent_team) - -### RAG (Retrieval Augmented Generation) +### 📀 RAG (Retrieval Augmented Generation) * [🔗 Agentic RAG](rag_tutorials/agentic_rag/) +* [🧐 Agentic RAG with Reasoning](rag_tutorials/agentic_rag_with_reasoning/) * [📰 AI Blog Search (RAG)](rag_tutorials/ai_blog_search/) * [🔍 Autonomous RAG](rag_tutorials/autonomous_rag/) * [🔄 Corrective RAG (CRAG)](rag_tutorials/corrective_rag/) @@ -125,11 +131,15 @@ We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosy * [📠 RAG with Database Routing](rag_tutorials/rag_database_routing/) * [🖼️ Vision RAG](rag_tutorials/vision_rag/) -### MCP AI Agents -- [🐙 MCP GitHub Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/mcp_ai_agents/github_mcp_agent) -- [♾️ MCP Browser Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/mcp_ai_agents/browser_mcp_agent) +### 💾 LLM Apps with Memory Tutorials + +* [💾 AI ArXiv Agent with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/ai_arxiv_agent_memory/) +* [🛩️ AI Travel Agent with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/ai_travel_agent_memory/) +* [💬 Llama3 Stateful Chat](advanced_llm_apps/llm_apps_with_memory_tutorials/llama3_stateful_chat/) +* [📝 LLM App with Personalized Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/llm_app_personalized_memory/) +* [🗄️ Local ChatGPT Clone with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/local_chatgpt_with_memory/) +* [🧠 Multi-LLM Application with Shared Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/multi_llm_memory/) -### 🧠 Advanced LLM Apps ### 💬 Chat with X Tutorials @@ -140,15 +150,6 @@ We're launching a Global AI Agent Hackathon in collaboration with AI Agent ecosy * [📝 Chat with Substack](advanced_llm_apps/chat_with_X_tutorials/chat_with_substack/) * [📽️ Chat with YouTube Videos](advanced_llm_apps/chat_with_X_tutorials/chat_with_youtube_videos/) -### 💾 LLM Apps with Memory Tutorials - -* [💾 AI ArXiv Agent with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/ai_arxiv_agent_memory/) -* [🛩️ AI Travel Agent with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/ai_travel_agent_memory/) -* [💬 Llama3 Stateful Chat](advanced_llm_apps/llm_apps_with_memory_tutorials/llama3_stateful_chat/) -* [📝 LLM App with Personalized Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/llm_app_personalized_memory/) -* [🗄️ Local ChatGPT Clone with Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/local_chatgpt_with_memory/) -* [🧠 Multi-LLM Application with Shared Memory](advanced_llm_apps/llm_apps_with_memory_tutorials/multi_llm_memory/) - ### 🔧 LLM Fine-tuning Tutorials * [🔧 Llama 3.2 Fine-tuning](advanced_llm_apps/llm_finetuning_tutorials/llama3.2_finetuning/) diff --git a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/README.md b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/README.md index 8ba563e..42f4a7f 100644 --- a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/README.md +++ b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/README.md @@ -23,7 +23,7 @@ This example shows how to build an interactive Tic Tac Toe game where AI agents ```bash # Clone the repository git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd ai_agent_tutorials/ai_tic_tac_toe_agent + cd advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent # Install dependencies pip install -r requirements.txt @@ -35,19 +35,28 @@ This example shows how to build an interactive Tic Tac Toe game where AI agents pip install -r requirements.txt ``` -### 3. Export API Keys +### 3. Setup API Keys -The game supports multiple AI models. Export the API keys for the models you want to use: +The game supports multiple AI models. Create a `.env` file in this directory and add your API keys: -```shell -# Required for OpenAI models -export OPENAI_API_KEY=*** +1. **Create a `.env` file:** + ```bash + # In the ai_tic_tac_toe_agent directory + touch .env + ``` -# Optional - for additional models -export ANTHROPIC_API_KEY=*** # For Claude models -export GOOGLE_API_KEY=*** # For Gemini models -export GROQ_API_KEY=*** # For Groq models -``` +2. **Add your API keys to the `.env` file:** + ```env + # Required for OpenAI models (gpt-4o, o3-mini) + OPENAI_API_KEY=your_actual_openai_api_key_here + + # Optional - for additional models + ANTHROPIC_API_KEY=your_actual_anthropic_api_key_here # For Claude models + GOOGLE_API_KEY=your_actual_google_api_key_here # For Gemini models + GROQ_API_KEY=your_actual_groq_api_key_here # For Groq models + ``` + + > **Note:** Replace the placeholder values with your actual API keys. The app will show helpful error messages if required keys are missing. ### 4. Run the Game diff --git a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/agents.py b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/agents.py index 6be0dc8..615e88e 100644 --- a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/agents.py +++ b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/agents.py @@ -142,14 +142,14 @@ def get_tic_tac_toe_players( - Top-left is (0,0), bottom-right is (2,2) RULES: - - You can only place X in empty spaces (shown as " " on the board) + - You can only place O in empty spaces (shown as " " on the board) - Players take turns placing their marks - First to get 3 marks in a row (horizontal, vertical, or diagonal) wins - If all spaces are filled with no winner, the game is a draw YOUR RESPONSE: - Provide ONLY two numbers separated by a space (row column) - - Example: "1 2" places your X in row 1, column 2 + - Example: "1 2" places your O in row 1, column 2 - Choose only from the valid moves list provided to you STRATEGY TIPS: diff --git a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/app.py b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/app.py index 17faeff..32e0429 100644 --- a/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/app.py +++ b/advanced_ai_agents/autonomous_game_playing_agent_apps/ai_tic_tac_toe_agent/app.py @@ -1,5 +1,11 @@ import nest_asyncio import streamlit as st +from dotenv import load_dotenv +import os + +# Load environment variables from .env file +load_dotenv() + from agents import get_tic_tac_toe_players from agno.utils.log import logger from utils import ( @@ -25,6 +31,20 @@ st.markdown(CUSTOM_CSS, unsafe_allow_html=True) def main(): + #################################################################### + # Check for required API keys + #################################################################### + required_keys_info = { + "gpt-4o": "OPENAI_API_KEY", + "o3-mini": "OPENAI_API_KEY", + "claude-3.5": "ANTHROPIC_API_KEY", + "claude-3.7": "ANTHROPIC_API_KEY", + "claude-3.7-thinking": "ANTHROPIC_API_KEY", + "gemini-flash": "GOOGLE_API_KEY", + "gemini-pro": "GOOGLE_API_KEY", + "llama-3.3": "GROQ_API_KEY", + } + #################################################################### # App header #################################################################### @@ -69,13 +89,40 @@ def main(): key="model_p2", ) + ################################################################ + # API Key validation + ################################################################ + missing_keys = [] + for model in [selected_p_x, selected_p_o]: + required_key = required_keys_info.get(model) + if required_key and not os.getenv(required_key): + missing_keys.append(f"**{model}** requires `{required_key}`") + + if missing_keys: + st.error(f""" + 🔑 **Missing API Keys:** + + {chr(10).join(f"• {key}" for key in missing_keys)} + + **To fix this:** + 1. Create a `.env` file in this directory + 2. Add your API keys: + ``` + OPENAI_API_KEY=your_key_here + ANTHROPIC_API_KEY=your_key_here + GOOGLE_API_KEY=your_key_here + GROQ_API_KEY=your_key_here + ``` + 3. Restart the app + """) + ################################################################ # Game controls ################################################################ col1, col2 = st.columns(2) with col1: if not st.session_state.game_started: - if st.button("▶️ Start Game"): + if st.button("▶️ Start Game", disabled=bool(missing_keys)): st.session_state.player_x, st.session_state.player_o = ( get_tic_tac_toe_players( model_x=model_options[selected_p_x], diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team/README.md index e112f2c..69957f7 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team/README.md @@ -47,7 +47,7 @@ Follow these steps to set up and run the application: 1. **Clone the Repository**: ```bash git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd ai_agent_tutorials/ai_competitors_analysis_team + cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team ``` 2. **Install the dependencies**: diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team/README.md index 9723fba..2a02b0d 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team/README.md @@ -15,7 +15,7 @@ This script demonstrates how to build a team of AI agents that work together as 1. Clone the GitHub repository ```bash git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git -cd awesome-llm-apps/ai_agent_tutorials/ai_finance_agent_team +cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team ``` 2. Install the required dependencies: diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team/README.md index d3566fd..59db7ea 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team/README.md @@ -5,13 +5,15 @@ The AI Game Design Agent Team is a collaborative game design system powered by [ ## Features - **Specialized Game Design Agent Team** - - 🎭 **Story Agent**: Specializes in narrative design and world-building, including character development, plot arcs, dialogue writing, and lore creation - - 🎮 **Gameplay Agent**: Focuses on game mechanics and systems design, including player progression, combat systems, resource management, and balancing - - 🎨 **Visuals Agent**: Handles art direction and audio design, covering UI/UX, character/environment art style, sound effects, and music composition - - ⚙️ **Tech Agent**: Provides technical architecture and implementation guidance, including engine selection, optimization strategies, networking requirements, and development roadmap - - 🎯 **Task Agent**: Coordinates between all specialized agents and ensures cohesive integration of different game aspects + + - 🎭 **Story Agent**: Specializes in narrative design and world-building, including character development, plot arcs, dialogue writing, and lore creation + - 🎮 **Gameplay Agent**: Focuses on game mechanics and systems design, including player progression, combat systems, resource management, and balancing + - 🎨 **Visuals Agent**: Handles art direction and audio design, covering UI/UX, character/environment art style, sound effects, and music composition + - ⚙️ **Tech Agent**: Provides technical architecture and implementation guidance, including engine selection, optimization strategies, networking requirements, and development roadmap + - 🎯 **Task Agent**: Coordinates between all specialized agents and ensures cohesive integration of different game aspects - **Comprehensive Game Design Outputs**: + - Detailed narrative and world-building elements - Core gameplay mechanics and systems - Visual and audio direction @@ -20,38 +22,42 @@ The AI Game Design Agent Team is a collaborative game design system powered by [ - Coherent game design from the team. - **Customizable Input Parameters**: + - Game type and target audience - Art style and visual preferences - Platform requirements - Development constraints (time, budget) - Core mechanics and gameplay features -- **Interactive Results**: - - Quick show of game design ideas from each agent - - Detailed results are presented in expandable sections for easy navigation and reference +- **Interactive Results**: + - Quick show of game design ideas from each agent + - Detailed results are presented in expandable sections for easy navigation and reference ## How to Run Follow these steps to set up and run the application: 1. **Clone the Repository**: + ```bash git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd ai_agent_tutorials/ai_game_design_team + cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team ``` 2. **Install Dependencies**: + ```bash pip install -r requirements.txt ``` 3. **Set Up OpenAI API Key**: + - Obtain an OpenAI API key from [OpenAI's platform](https://platform.openai.com) - You'll input this key in the app's sidebar when running 4. **Run the Streamlit App**: ```bash - streamlit run ai_game_design_agent_team/game_design_agent_team.py + streamlit run game_design_agent_team.py ``` ## Usage diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team/README.md index d97cd99..a8b804f 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team/README.md @@ -26,7 +26,7 @@ A Streamlit application that simulates a full-service legal team using multiple ```bash # Clone the repository git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd awesome-llm-apps/ai_agent_tutorials/ai_legal_agent_team + cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team # Install dependencies pip install -r requirements.txt diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team/README.md index 55c48dd..ba9380b 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team/README.md @@ -36,8 +36,8 @@ A Streamlit application that simulates a full-service recruitment team using mul ```bash # Clone the repository git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd ai_agent_tutorials/ai_recruitment_agent_team - + cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team + # Install dependencies pip install -r requirements.txt ``` diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency/README.md index 4003cea..a11adb3 100644 --- a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency/README.md +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency/README.md @@ -64,7 +64,7 @@ Before anything else, Please get your OpenAI API Key here: https://platform.open 1. **Clone the Repository**: ```bash git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git - cd awesome-llm-apps/ai_agent_tutorials/ai_services_agency + cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency ``` 2. **Install the dependencies**: @@ -74,7 +74,7 @@ Before anything else, Please get your OpenAI API Key here: https://platform.open 3. **Run the Streamlit app**: ```bash - streamlit run ai_services_agency/agency.py + streamlit run agency.py ``` 4. **Enter your OpenAI API Key** in the sidebar when prompted and start analyzing your startup idea! diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/README.md new file mode 100644 index 0000000..c62d4b5 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/README.md @@ -0,0 +1,70 @@ +# ✈️ TripCraft AI + +**Your journey, perfectly crafted with intelligence.** + +Travel planning is overwhelming—juggling dozens of tabs, comparing conflicting info, spending hours just to get started. TripCraft AI makes that disappear. It's a multi-agent AI system that turns simple inputs into complete travel itineraries. Describe your ideal trip, and it handles flights, hotels, activities, and budget automatically. + +## 🎯 Goal + +Make travel planning effortless and personal. No stress, no endless research—just a plan that feels crafted specifically for you. + +--- + +## ⚙️ How It Works + +1. **🎯 Input Your Vision** - Fill out a form with destination, dates, budget, travel style, and preferences +2. **🤖 AI Agents Collaborate** - Specialized agents handle flights, hotels, activities, and budgeting in parallel +3. **🗺️ Get Your Itinerary** - Receive a complete day-by-day plan with bookings, costs, and recommendations + +### Key Features +- **Personalized Planning** - Tailored to your travel style and interests +- **Hidden Gems Discovery** - Beyond typical tourist spots using advanced search +- **Smart Optimization** - Balances cost, time, and experience +- **Complete Packages** - Everything from flights to dining recommendations + +--- + +## 🛠️ Tech Stack + +**Frontend:** Next.js, React, TypeScript +**Backend:** Python, FastAPI, PostgreSQL +**AI:** Agno (agent coordination), Gemini (LLM), Exa (search), Firecrawl (web scraping) +**APIs:** Google Flights, Kayak + +--- + +## 📸 Visuals + +![Image](https://github.com/user-attachments/assets/5fae2938-6d2c-4fc7-86be-d22bb84729a6) +![Image](https://github.com/user-attachments/assets/1bd6e98f-ae32-47be-90a0-23ee6f06c613) +![Image](https://github.com/user-attachments/assets/45db7d19-67ca-4c92-985f-79a7cb976b1c) +![Image](https://github.com/user-attachments/assets/7a06c3de-281d-4820-a517-ea81137289d7) +![Image](https://github.com/user-attachments/assets/523f0d02-8a72-4709-b3d4-5102f1d1b950) +![Image](https://github.com/user-attachments/assets/dbab944a-7678-4eae-9ead-05f15c3de407) + +--- + +## 👥 About + +**Built by**: Amit Wani [@mtwn105](https://github.com/mtwn105) + +Full-stack developer and software engineer passionate about building intelligent systems that solve real-world problems. TripCraft AI represents the intersection of advanced AI capabilities and practical travel planning needs. + +--- + +## 🎬 Demo Video Link + +[https://youtu.be/eTll7EdQyY8](https://youtu.be/eTll7EdQyY8) + +--- + +## 🤖 AI Agents + +Six specialized agents work together to create comprehensive travel plans: + +1. **🏛️ Destination Explorer** - Researches attractions, landmarks, and experiences +2. **🏨 Hotel Search Agent** - Finds accommodations based on location, budget, and amenities +3. **🍽️ Dining Agent** - Recommends restaurants and culinary experiences +4. **💰 Budget Agent** - Handles cost optimization and financial planning +5. **✈️ Flight Search Agent** - Plans air travel routes and comparisons +6. **📅 Itinerary Specialist** - Creates detailed day-by-day schedules with optimal timing diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/.env.example b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/.env.example new file mode 100644 index 0000000..1590d22 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/.env.example @@ -0,0 +1,21 @@ + +# Bright Data credentials +BRIGHT_DATA_API_TOKEN=your_bright_data_api_token +BRIGHT_DATA_BROWSER_AUTH=your_bright_data_browser_auth + +# Database connection URL +DATABASE_URL=your_database_url + +# OpenRouter API key +OPENROUTER_API_KEY=your_openrouter_api_key + +# OpenAI API key +OPENAI_API_KEY=your_openai_api_key + +# Cloudflare R2 configuration +CLOUDFLARE_ACCOUNT_ID=your_cloudflare_account_id +CLOUDFLARE_R2_ACCESS_KEY_ID=your_r2_access_key_id +CLOUDFLARE_R2_SECRET_ACCESS_KEY=your_r2_secret_access_key + +EXA_API_KEY=EXA_API_KEY +FIRECRAWL_API_KEY=FIRECRAWL_API_KEY \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/Dockerfile b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/Dockerfile new file mode 100644 index 0000000..13e1897 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/Dockerfile @@ -0,0 +1,47 @@ +FROM python:3.12-slim-bookworm AS builder + +# Install uv +RUN pip install --no-cache-dir uv + +# Copy dependency files +WORKDIR /app +COPY pyproject.toml uv.lock ./ + +# Install dependencies into the system Python +RUN uv pip install --system -e . + +# Final image - ultra slim +FROM python:3.12-slim-bookworm + +# Install runtime dependencies, Node.js, PNPM, PostgreSQL client libraries, and FFmpeg +RUN apt-get update && \ + apt-get install -y --no-install-recommends ca-certificates curl \ + libpq-dev postgresql-client ffmpeg && \ + curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \ + apt-get install -y --no-install-recommends nodejs && \ + npm install -g pnpm && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* && \ + npm cache clean --force && \ + pip install --no-cache-dir psycopg2-binary gunicorn + +# Copy Python packages from the builder stage +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages + +# Copy application code (only what's needed) +WORKDIR /app +COPY app/ app/ +COPY agents/ agents/ +COPY config/ config/ +COPY models/ models/ +COPY routers/ routers/ +COPY services/ services/ +COPY api.py server.py ./ + +# Create log directory with appropriate permissions +RUN mkdir -p logs && chmod 777 logs + +EXPOSE 8001 + +# Use gunicorn with uvicorn workers +CMD ["gunicorn", "server:app", "--workers", "1", "--worker-class", "uvicorn.workers.UvicornWorker", "--bind", "0.0.0.0:8001", "--timeout", "0", "--keep-alive", "5"] \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/README.md new file mode 100644 index 0000000..f8a0708 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/README.md @@ -0,0 +1,108 @@ +# TripCraft AI - Agent Architecture + +TripCraft AI uses a sophisticated multi-agent system powered by Agno to create personalized travel experiences. This document explains the different agents and their roles in the system. + +## Team Structure + +The system is orchestrated by the "TripCraft AI Team", which coordinates multiple specialized agents to create comprehensive travel plans. The team operates in a coordinated mode, ensuring all aspects of travel planning are handled efficiently. + +### Core Team Members + +1. **Destination Explorer** + - Primary role: Researches and recommends tourist attractions and experiences + - Tools: ExaTools for deep web research + - Focus areas: + - Famous landmarks and monuments + - Popular tourist spots + - Museums and cultural sites + - Shopping areas + - Family-friendly activities + - Provides structured information about attractions including opening hours, fees, and visit duration + +2. **Hotel Search Agent** + - Primary role: Accommodation research and recommendations + - Focuses on finding the perfect stay based on: + - Location preferences + - Budget constraints + - Required amenities + - Room types + - Property features + +3. **Dining Agent** + - Primary role: Restaurant and culinary experience recommendations + - Considers: + - Cuisine types + - Price ranges + - Dietary restrictions + - Ambiance and atmosphere + - Location and accessibility + - Special dining experiences + +4. **Budget Agent** + - Primary role: Financial planning and cost optimization + - Responsibilities: + - Trip cost breakdown + - Budget allocation + - Cost-saving recommendations + - Currency considerations + - Emergency fund planning + +5. **Flight Search Agent** + - Primary role: Air travel planning and optimization + - Handles: + - Flight route research + - Airline comparisons + - Schedule optimization + - Connection planning + - Airport transfer coordination + +6. **Itinerary Specialist** + - Primary role: Creates detailed day-by-day travel schedules + - Expertise: + - Hour-by-hour activity planning + - Optimized timing for attractions + - Transportation scheduling + - Realistic travel times + - Buffer time management + - Weather-adaptive scheduling + - Traveler-specific pacing + +## Team Coordination + +The team works together through a sophisticated coordination system that: +1. Analyzes user preferences and requirements +2. Delegates tasks to specialized agents +3. Combines individual agent outputs into a cohesive travel plan +4. Ensures all aspects of the trip are properly synchronized +5. Maintains budget alignment across all decisions + +## Tools and Technologies + +The agents utilize various tools including: +- **ReasoningTools**: For logical decision-making and plan optimization +- **ExaTools**: For deep web research and information gathering +- **FirecrawlTools**: For real-time data and current information + +## Output Format + +The team produces detailed travel itineraries that include: +- Executive summary of the trip +- Comprehensive travel logistics +- Day-by-day itineraries +- Detailed accommodation information +- Curated experiences and activities +- Complete budget breakdown + +## Best Practices + +The agent system follows these key principles: +1. Thorough analysis of user preferences +2. Detailed research using multiple data sources +3. Practical and implementable recommendations +4. Backup options and contingency plans +5. Clear communication and structured output +6. Budget consciousness across all decisions + +## Integration + +This agent architecture is designed to work seamlessly with the TripCraft AI backend, providing a robust foundation for creating personalized travel experiences that feel both magical and practical. \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/budget.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/budget.py new file mode 100644 index 0000000..a58ef57 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/budget.py @@ -0,0 +1,39 @@ +from agno.agent import Agent +from config.llm import model + +budget_agent = Agent( + name="Budget Optimizer", + role="Calculate costs and optimize travel budgets when asked by team leader", + model=model, + description="You research costs, compare prices, and optimize travel budgets when assigned by the team leader. When plans exceed budget, you suggest strategic adjustments to bring costs in line while preserving the core travel experience.", + instructions=[ + "# Budget Optimization Instructions", + "", + "1. Analyze total budget and cost requirements:", + " - Review total budget limit", + " - Calculate costs for transportation, accommodations, activities, food", + " - Identify any components exceeding budget", + "", + "2. If over budget, suggest cost-saving alternatives:", + " - Alternative accommodations or locations", + " - Different transportation options", + " - Mix of premium and budget experiences", + " - Free or lower-cost activity substitutes", + " - Budget-friendly dining recommendations", + "", + "3. Research and recommend money-saving strategies:", + " - Early booking discounts", + " - Package deals", + " - Off-peak pricing", + " - Local passes and discount cards", + "", + "4. Present clear budget breakdown showing:", + " - Original vs optimized costs", + " - Specific savings per category", + " - Alternative options", + " - Hidden cost warnings", + "", + "Format all amounts in user's preferred currency with clear comparisons between original and optimized budgets.", + ], + markdown=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/destination.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/destination.py new file mode 100644 index 0000000..b82b853 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/destination.py @@ -0,0 +1,68 @@ +from agno.agent import Agent +from agno.tools.exa import ExaTools +from agno.tools.firecrawl import FirecrawlTools +from config.llm import model + +destination_agent = Agent( + name="Destination Explorer", + model=model, + tools=[ + ExaTools( + num_results=10, + ), + ], + description="You are a destination research agent that focuses on recommending mainstream tourist attractions and classic experiences that most travelers would enjoy. You prioritize well-known landmarks and popular activities while keeping recommendations general and widely appealing.", + instructions=[ + "1. Focus on mainstream attractions with thoughtful guidance:", + " - Famous landmarks and monuments", + " - Popular tourist spots", + " - Well-known museums", + " - Classic shopping areas", + " - Common tourist activities", + "", + "2. Guide visitors with simple reasoning:", + " - Suggest crowd-pleasing activities", + " - Focus on family-friendly locations", + " - Recommend proven tourist routes", + " - Include popular photo spots", + "", + "3. Present clear attraction information:", + " - Simple description", + " - General location", + " - Regular opening hours", + " - Standard entrance fees", + " - Typical visit duration", + " - Basic visitor tips", + "", + "4. Organize information logically:", + " - Main attractions first", + " - Common day trips", + " - Standard tourist areas", + " - Popular activities", + "", + "Use tools to find and verify tourist information.", + "Keep suggestions general and widely appealing.", + ], + expected_output=""" + # Tourist Guide + ## Main Attractions + List of most popular tourist spots + + ## Common Activities + Standard tourist activities and experiences + + ## Popular Areas + Well-known districts and neighborhoods + + ## Basic Information + - General visiting tips + - Common transportation options + - Standard tourist advice + """, + markdown=True, + show_tool_calls=True, + add_datetime_to_instructions=True, + retries=3, + delay_between_retries=2, + exponential_backoff=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/flight.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/flight.py new file mode 100644 index 0000000..ea24f15 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/flight.py @@ -0,0 +1,68 @@ +from agno.agent import Agent +from agno.tools.firecrawl import FirecrawlTools +from tools.google_flight import get_google_flights +from config.llm import model + +flight_search_agent = Agent( + name="Flight Search Assistant", + model=model, + tools=[ + # FirecrawlTools(poll_interval=10), + # kayak_flight_url_generator, + get_google_flights, + ], + instructions=[ + "You are a sophisticated flight search and analysis assistant for comprehensive travel planning. For any user query:", + "1. Parse complete flight requirements including:", + " - Origin and destination cities", + " - Travel dates (outbound and return)", + " - Number of travelers (adults, children, infants)", + " - Preferred cabin class", + " - Any specific airlines or routing preferences", + " - Budget constraints if specified", + # "2. Search and analyze multiple flight options:", + "2. Search for flight options:", + # " - Use kayak_url_generator to create appropriate search URLs", + # " - Navigate to and extract data from flight search results", + " - Use get_google_flights to get flight results", + " - Consider both direct and connecting flights", + " - Compare different departure times and airlines", + "3. For each viable flight option, extract:", + " - Complete pricing breakdown (base fare, taxes, total)", + " - Flight numbers and operating airlines", + " - Detailed timing (departure, arrival, duration, layovers)", + " - Aircraft types and amenities when available", + " - Baggage allowance and policies", + "4. Organize and present options with focus on:", + " - Best value for money", + " - Convenient timing and minimal layovers", + " - Reliable airlines with good service records", + " - Flexibility and booking conditions", + "5. Provide practical recommendations considering:", + " - Price trends and booking timing", + " - Alternative dates or nearby airports if beneficial", + " - Loyalty program benefits if applicable", + " - Special requirements (extra legroom, dietary, etc.)", + "6. Include booking guidance:", + " - Direct booking links when available", + " - Fare rules and change policies", + " - Required documents and visa implications", + # "7. Always close browser sessions after completion", + ], + expected_output=""" + All flight details with the following fields: + - flight_number (str): The flight number of the flight + - price (str): The price of the flight + - airline (str): The airline of the flight + - departure_time (str): The departure time of the flight + - arrival_time (str): The arrival time of the flight + - duration (str): The duration of the flight + - stops (int): The number of stops of the flight + """, + markdown=True, + show_tool_calls=True, + debug_mode=True, + retries=3, + delay_between_retries=2, + exponential_backoff=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/food.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/food.py new file mode 100644 index 0000000..d1ad293 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/food.py @@ -0,0 +1,116 @@ +from agno.tools.exa import ExaTools +from config.llm import model +from agno.agent import Agent + +dining_agent = Agent( + name="Culinary Guide", + role="Research dining and food experiences when asked by team leader", + model=model, + tools=[ExaTools()], + description="You research restaurants, food markets, culinary experiences, and dining options when assigned by the team leader.", + instructions=[ + "# Culinary Research and Recommendation Assistant", + "", + "## Task 1: Query Processing", + "- Parse dining preferences from user query", + "- Extract:", + " - Location/area", + " - Cuisine preferences", + " - Dietary restrictions", + " - Budget range", + " - Meal timing", + " - Group size", + " - Special requirements (e.g., family-friendly, romantic)", + "", + "## Task 2: Research & Data Collection", + "- Search for restaurants and food experiences using ExaTools", + "- Gather information about:", + " - Local cuisine specialties", + " - Popular food markets", + " - Culinary experiences", + " - Operating hours", + " - Price ranges", + " - Reservation policies", + "", + "## Task 3: Content Analysis", + "- Analyze restaurant reviews and ratings", + "- Evaluate:", + " - Food quality", + " - Service standards", + " - Ambiance", + " - Value for money", + " - Dietary accommodation", + " - Family-friendliness", + "", + "## Task 4: Data Processing", + "- Filter results based on:", + " - Dietary requirements", + " - Budget constraints", + " - Location preferences", + " - Special requirements", + "- Validate information completeness", + "", + "## Task 5: Results Presentation", + "Present recommendations in a clear, organized format:", + "", + "### Restaurant Recommendations", + "For each restaurant, include:", + "- Name and cuisine type", + "- Price range (e.g., $, $$, $$$)", + "- Rating and brief review summary", + "- Location and accessibility", + "- Operating hours", + "- Dietary options available", + "- Special features (e.g., outdoor seating, view)", + "- Reservation requirements", + "- Popular dishes to try", + "", + "### Food Markets & Culinary Experiences", + "- Market names and specialties", + "- Best times to visit", + "- Must-try local foods", + "- Cultural significance", + "", + "### Additional Information", + "- Local food customs and etiquette", + "- Peak dining hours to avoid", + "- Transportation options", + "- Food safety tips", + "", + "Format the output in clear sections with emojis and bullet points for better readability.", + ], + expected_output=""" + Present dining recommendations in a clear, organized format with the following sections: + + # 🍽️ Restaurant Recommendations + For each recommended restaurant: + - Name and cuisine type + - Price range and value rating + - Location and accessibility + - Operating hours + - Dietary options + - Special features + - Popular dishes + - Reservation info + + # 🛍️ Food Markets & Experiences + - Market names and specialties + - Best visiting times + - Local food highlights + - Cultural significance + + # ℹ️ Additional Information + - Local customs + - Peak hours + - Transportation + - Safety tips + + Use emojis and clear formatting for better readability. + """, + markdown=True, + show_tool_calls=True, + debug_mode=True, + retries=3, + delay_between_retries=2, + exponential_backoff=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/hotel.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/hotel.py new file mode 100644 index 0000000..0deb972 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/hotel.py @@ -0,0 +1,82 @@ +from agno.agent import Agent +from tools.kayak_hotel import kayak_hotel_url_generator +from tools.scrape import scrape_website +from config.llm import model +from models.hotel import HotelResult, HotelResults + +hotel_search_agent = Agent( + name="Hotel Search Assistant", + model=model, + tools=[ + scrape_website, + kayak_hotel_url_generator, + ], + instructions=[ + "# Hotel Search and Data Extraction Assistant", + "", + "## Task 1: Query Processing", + "- Parse hotel search parameters from user query", + "- Extract:", + " - Destination", + " - Check-in/out dates", + " - Number of guests (adults, children)", + " - Room requirements", + " - Budget constraints", + " - Preferred amenities", + " - Location preferences", + "", + "## Task 2: URL Generation & Initial Scraping", + "- Generate Kayak URL using `kayak_hotel_url_generator`", + "- Perform initial content scrape with `scrape_website`", + "- Handle URL encoding for special characters in destination names", + "", + "## Task 3: Data Extraction", + "- Parse hotel listings from scraped content", + "- Extract key details:", + " - Prices (including taxes and fees)", + " - Amenities (especially family-friendly features)", + " - Ratings and reviews", + " - Location details", + " - Room types and availability", + " - Cancellation policies", + "- Handle dynamic loading of results", + "- Navigate multiple pages if needed", + "", + "## Task 4: Data Processing", + "- Structure extracted hotel data according to HotelResult model", + "- Validate data completeness", + "- Filter results based on:", + " - Budget constraints", + " - Required amenities", + " - Location preferences", + " - Family-friendly features", + "", + "## Task 5: Results Presentation", + "- Format results clearly with:", + " - Hotel name and rating", + " - Price breakdown", + " - Location and accessibility", + " - Key amenities", + " - Family-friendly features", + " - Booking policies", + "- Sort results by relevance to user preferences", + "- Include direct booking links", + "", + ], + expected_output=""" + List of hotels with the following fields for each hotel: + - hotel_name (str): The name of the hotel + - price (str): The price of the hotel + - rating (str): The rating of the hotel + - address (str): The address of the hotel + - amenities (List[str]): The amenities of the hotel + - description (str): The description of the hotel + - url (str): The url of the hotel + """, + markdown=True, + show_tool_calls=True, + debug_mode=True, + retries=3, + delay_between_retries=2, + exponential_backoff=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/itinerary.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/itinerary.py new file mode 100644 index 0000000..28e69a0 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/itinerary.py @@ -0,0 +1,127 @@ +from agno.agent import Agent +from agno.tools.exa import ExaTools +from agno.tools.firecrawl import FirecrawlTools +from agno.tools.reasoning import ReasoningTools +from config.llm import model +from typing import Optional +from datetime import datetime, timedelta +from textwrap import dedent + + +itinerary_agent = Agent( + name="Itinerary Specialist", + model=model, + tools=[ + ExaTools(num_results=8), + FirecrawlTools(formats=["markdown"]), + ReasoningTools(add_instructions=True), + ], + markdown=True, + description=dedent( + """\ + You are a master itinerary creator with expertise in crafting detailed, perfectly-timed daily travel plans. + You turn abstract travel details into structured, hour-by-hour plans that maximize enjoyment while maintaining + a realistic pace. You're skilled at adapting schedules to match traveler preferences, weather conditions, + opening hours, and local customs. Your itineraries are practical, thoroughly researched, and full of + insider timing tips that make travel smooth and stress-free.""" + ), + instructions=[ + "1. Create perfectly balanced day-by-day itineraries with meticulous timing:", + " - Structure each day into morning, afternoon, and evening blocks", + " - Include exact timing for each activity (start/end times)", + " - Account for realistic travel times between locations", + " - Balance sightseeing with leisure and rest periods", + " - Adapt pace to match traveler preferences (relaxed, moderate, fast)", + "", + "2. Ensure practical logistics in all schedules:", + " - Verify operating hours for all attractions, restaurants, and services", + " - Account for common delays (security lines, crowds, traffic)", + " - Include buffer time between activities", + " - Check for day-specific closures (weekends, holidays, seasonal)", + " - Consider local transportation options and schedules", + "", + "3. Optimize activity timing with expert knowledge:", + " - Schedule visits during off-peak hours when possible", + " - Plan indoor activities during likely rainy/hot periods", + " - Arrange sunrise/sunset experiences at optimal times", + " - Schedule meals during traditional local dining hours", + " - Time activities to avoid rush hour transportation", + "", + "4. Create custom scheduling for specific traveler types:", + " - Families: Include kid-friendly breaks and early dinners", + " - Seniors: More relaxed pace with ample rest periods", + " - Young adults: Later start times and evening activities", + " - Luxury travelers: Timing for exclusive experiences", + " - Business travelers: Efficient scheduling around work commitments", + "", + "5. Enhance itineraries with practical timing details:", + " - Best arrival times to avoid lines at attractions", + " - Photography timing for optimal lighting", + " - Meal reservations timed around activities", + " - Shopping hours for local markets and stores", + " - Weather-dependent backup plans", + "", + "6. Research tools usage for accurate scheduling:", + " - Use Exa to research location-specific timing information", + " - Employ FirecrawlTools for current operating hours and conditions", + " - Use ReasoningTools to optimize activity sequence and timing", + "", + "7. Format day plans with maximum clarity:", + " - Use clear time blocks (8:00 AM - 9:30 AM)", + " - Include travel method and duration between locations", + " - Highlight reservation times and booking requirements", + " - Note required advance arrival times (security, check-in)", + " - Use emojis for better visual organization", + ], + expected_output=dedent( + """\ + # Detailed Itinerary: {Destination} ({Start Date} - {End Date}) + + ## Trip Overview + - **Dates**: {exact dates with day count} + - **Travelers**: {number and type} + - **Pace**: {relaxed/moderate/fast} + - **Style**: {luxury/mid-range/budget} + - **Priorities**: {key interests and goals} + + ## Day 1: {Day of Week}, {Date} + ### Morning + - **7:00 AM - 8:00 AM**: Breakfast at {location} + - **8:30 AM - 10:30 AM**: {Activity} at {location} + * Notes: {special instructions, timing tips} + * Travel: {transport method, duration} + - **11:00 AM - 12:30 PM**: {Activity} at {location} + * Notes: {special instructions, timing tips} + * Travel: {transport method, duration} + + ### Afternoon + - **1:00 PM - 2:00 PM**: Lunch at {location} + - **2:30 PM - 4:30 PM**: {Activity} at {location} + * Notes: {special instructions, timing tips} + * Travel: {transport method, duration} + - **5:00 PM - 6:00 PM**: Rest/refresh at hotel + + ### Evening + - **7:00 PM - 8:30 PM**: Dinner at {location} + - **9:00 PM - 10:30 PM**: {Activity} at {location} + * Notes: {special instructions, timing tips} + * Travel: {transport method, duration} + + ## Day 2: {Day of Week}, {Date} + [Similar detailed breakdown] + + [Continue for each day of the trip] + + ## Practical Notes + - **Weather Considerations**: {weather-related timing adjustments} + - **Transportation Tips**: {local transport timing advice} + - **Reservation Reminders**: {all pre-booked times} + - **Backup Plans**: {alternative schedules for weather/closures} + """ + ), + add_datetime_to_instructions=True, + show_tool_calls=True, + retries=2, + delay_between_retries=2, + exponential_backoff=True, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/structured_output.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/structured_output.py new file mode 100644 index 0000000..54e31c3 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/structured_output.py @@ -0,0 +1,127 @@ +from typing import TypeVar, Type, Any +from pydantic import BaseModel +from agno.agent import Agent +from loguru import logger +from config.llm import model +import json +import re +from pydantic import ValidationError + +T = TypeVar("T", bound=BaseModel) + + +def clean_json_string(json_str: str) -> str: + """ + Clean a JSON string by removing markdown code blocks and any extra whitespace. + + Args: + json_str (str): The JSON string to clean + + Returns: + str: The cleaned JSON string + """ + # Remove markdown code blocks + json_str = re.sub(r"```(?:json)?\n?(.*?)```", r"\1", json_str, flags=re.DOTALL) + + # If no code blocks found, use the original string + if not json_str.strip(): + json_str = json_str + + # Remove any leading/trailing whitespace + json_str = json_str.strip() + + return json_str + + +async def convert_to_model(input_text: str, target_model: Type[T]) -> str: + """ + Convert input text into a specified Pydantic model using an Agno agent. + + Args: + input_text (str): The input text to convert + target_model (Type[T]): The target Pydantic model class + + Returns: + str: A JSON string that matches the model schema + """ + + logger.info( + f"Converting input text to model: {target_model.__name__} : {input_text}" + ) + + structured_output_agent = Agent( + model=model, + description=( + "You are an expert at extracting structured travel planning information from unstructured, free-form user inputs. " + "Given a detailed user message, travel description, or conversation, your goal is to accurately populate a predefined trip schema. " + ), + instructions=[ + "Your task is to convert the input text into a valid JSON that matches the model schema exactly.", + "You must return ONLY the JSON object that matches the schema exactly - no other output.", + "When formatting text fields, you must:", + "- Use minimal, consistent formatting throughout", + "- Apply appropriate list formatting", + "- Format dates, times and structured data consistently", + "- Structure text concisely and clearly", + ], + markdown=True, + expected_output=""" + A valid JSON object that matches the provided schema. + Text fields should be clean and consistently formatted. + Do not include any explanations or additional text - return only the JSON object. + Without ```json or ``` + """, + ) + + schema = target_model.model_json_schema() + schema_str = json.dumps(schema, indent=2) + + # Create the prompt with model schema and clear instructions + prompt = f""" + Your task is to convert the input text into a valid JSON object that exactly matches the provided schema. + Do not include any explanations or additional text - return only the JSON object. + + Model schema: + {schema_str} + + Rules: + - Output must be valid JSON + - All required fields must be included + - Field types must match schema exactly + - No extra fields allowed + - Validate all constraints (min/max values, regex patterns, etc) + + Text Formatting Requirements: + - Use consistent, clean text formatting throughout all string fields + - For list items, use bullet points (•) instead of asterisks (*) + - Minimize indentation and whitespace in text fields + - Use line breaks sparingly and consistently + - Avoid formatting characters like asterisks (*) in text + - Don't include unnecessary prefixes or labels in text content + - Format times, dates, durations, and prices consistently + - Make sure all fields contain data appropriate for their purpose + + Input text to convert: + {input_text} + """ + + # Get structured response from the agent + try: + response = await structured_output_agent.arun(prompt) + json_string = clean_json_string(response.content) + logger.info(f"Structured output agent response: {json_string}") + + # Parse the JSON string + try: + json.loads(json_string) + return json_string + + except json.JSONDecodeError as json_err: + logger.error(f"JSON parsing error: {str(json_err)}") + raise ValueError(f"Invalid JSON response: {str(json_err)}") + + except Exception as e: + logger.error(f"Failed to parse response into {target_model.__name__}: {str(e)}") + raise ValueError( + f"Failed to parse response into {target_model.__name__}: {str(e)}" + ) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/team.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/team.py new file mode 100644 index 0000000..2c018fa --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/agents/team.py @@ -0,0 +1,334 @@ +from agno.team.team import Team +from config.llm import model, model2 + +from agents.destination import destination_agent +from agents.hotel import hotel_search_agent +from agents.food import dining_agent +from agents.budget import budget_agent +from agents.flight import flight_search_agent +from agents.itinerary import itinerary_agent +from loguru import logger +from agno.tools.reasoning import ReasoningTools + +# def update_team_current_state(team: Team, state: str) -> str: +# """ +# This function is used to set the current state of the team. +# """ +# logger.info(f"The current state of the team is {state}") +# team.session_state["current_state"] = state +# return state + + +trip_planning_team = Team( + name="TripCraft AI Team", + mode="coordinate", + model=model, + tools=[ReasoningTools(add_instructions=True)], + members=[ + destination_agent, + hotel_search_agent, + dining_agent, + budget_agent, + flight_search_agent, + itinerary_agent, + ], + show_tool_calls=True, + markdown=True, + description=( + "You are the lead orchestrator of the TripCraft AI planning team. " + "Your mission is to transform the user's travel preferences into a magical, stress-free itinerary. " + "Based on a single input form, you'll collaborate with expert agents handling flights, stays, dining, activities, and budgeting. " + "The result should be a beautifully crafted, practical, and emotionally resonant travel plan that feels personally designed. " + "Every detail matters - from the exact timing of activities to the ambiance of recommended restaurants. " + "Your goal is to create an itinerary so thorough and thoughtful that it feels like having a personal travel concierge." + ), + instructions=[ + "1. Meticulously analyze the complete travel preferences from the user input:", + " - Primary destination and any secondary locations", + " - Exact travel dates including arrival and departure times", + " - Preferred pace (relaxed, moderate, or fast-paced) with specific timing preferences", + " - Travel style (luxury, mid-range, budget) with detailed expectations", + " - Budget range with currency and flexibility notes", + " - Companion details (solo, couple, family, friends) with group dynamics", + " - Accommodation requirements (room types, amenities, location preferences)", + " - Desired vibes (romantic, adventurous, relaxing, etc.) with specific examples", + " - Top priorities (Instagram spots, local experiences, food, shopping) ranked by importance", + " - Special interests, dietary restrictions, accessibility needs", + " - Previous travel experiences and preferences", + "", + "2. Transportation Planning:", + " - Map out exact routes from start location to all destinations", + " - Research optimal flight/train combinations considering:", + " • Departure/arrival times aligned with check-in/out times", + " • Layover durations and airport transfer times", + " • Airline alliance benefits and baggage policies", + " • Alternative airports and routes for cost optimization", + " - Plan local transportation between all points of interest", + "", + "3. Coordinate with Specialized Agents:", + " - Flight Agent: Detailed air travel options with timing and pricing", + " - Hotel Agent: Accommodation matches for each night with amenity details", + " - Dining Agent: Restaurant recommendations with cuisine, price, and ambiance", + " - Activity Agent: Curated experiences matching interests and pace", + " - Budget Agent: Cost optimization while maintaining experience quality", + "", + "4. Create Detailed Daily Schedules:", + " Morning (6am-12pm):", + " - Breakfast venues with opening hours and signature dishes", + " - Morning activities with exact durations and travel times", + " - Alternative options for weather contingencies", + "", + " Afternoon (12pm-6pm):", + " - Lunch recommendations with peak times and reservation needs", + " - Main sightseeing with entrance fees and skip-the-line options", + " - Rest periods aligned with pace preference", + "", + " Evening (6pm-midnight):", + " - Dinner venues with ambiance descriptions and dress codes", + " - Evening entertainment options", + " - Nightlife suggestions if requested", + "", + "5. Experience Enhancement:", + " - Research and highlight hidden gems matching user interests", + " - Identify unique local experiences with cultural significance", + " - Find Instagram-worthy locations with best photo times", + " - Source exclusive or unusual accommodation options", + " - Map romantic spots for couples or family-friendly venues", + "", + "6. Budget Management:", + " - Break down costs to the smallest detail:", + " • Transportation (flights, trains, taxis, public transit)", + " • Accommodations (nightly rates, taxes, fees)", + " • Activities (tickets, guides, equipment rentals)", + " • Meals (by venue type and meal time)", + " • Shopping allowance", + " • Emergency buffer", + " - Provide cost-saving alternatives while maintaining experience quality", + " - Consider seasonal pricing variations", + "", + "7. Research Tools Usage:", + " - Use Exa for deep destination research including:", + " • Seasonal events and festivals", + " • Local customs and etiquette", + " • Weather patterns and best visit times", + " - Employ Firecrawl for real-time data on:", + " • Venue reviews and ratings", + " • Current pricing and availability", + " • Booking platforms and deals", + "", + "8. Personalization Elements:", + " - Reference and incorporate past travel experiences", + " - Avoid previously visited locations unless requested", + " - Match recommendations to stated preferences", + " - Add personal touches based on special occasions or interests", + "", + "9. Final Itinerary Crafting:", + " - Ensure perfect flow between all elements", + " - Include buffer time for transitions", + " - Add local tips and insider knowledge", + " - Provide backup options for key elements", + " - Format for both inspiration and practical use", + ], + expected_output=""" +A meticulously detailed, day-by-day travel itinerary in Markdown format including: + +**I. Executive Summary** +- 🎯 Trip Purpose & Vision + • Primary goals and desired experiences + • Special occasions or celebrations + • Key preferences and must-haves + +- ✈️ Travel Overview + • Exact dates with day count + • All destinations in sequence + • Group composition and dynamics + • Overall style and pace + • Total budget range and currency + +- 💫 Experience Highlights + • Signature moments and unique experiences + • Special arrangements and exclusives + • Instagram-worthy locations + • Cultural immersion opportunities + +**II. Travel Logistics** +- 🛫 Outbound Journey + • Flight/train details with exact timings + • Carrier information and booking references + • Seat recommendations + • Baggage allowances and restrictions + • Airport/station transfer details + • Check-in instructions + +- 🛬 Return Journey + • Return transportation specifics + • Timing coordination with checkout + • Alternative options if available + +**III. Detailed Daily Itinerary** +For each day (e.g., "Day 1 - Monday, July 1, 2025"): + +- 🌅 Morning (6am-12pm) + • Wake-up time and morning routine + • Breakfast venue with menu highlights + • Morning activities with durations + • Transport between locations + • Tips for timing and crowds + +- ☀️ Afternoon (12pm-6pm) + • Lunch recommendations with price range + • Main activities and experiences + • Rest periods and flexibility + • Photo opportunities + • Indoor/outdoor alternatives + +- 🌙 Evening (6pm-onwards) + • Dinner reservations and details + • Evening entertainment + • Nightlife options if desired + • Transport back to accommodation + +- 🏨 Accommodation + • Property name and room type + • Check-in/out times + • Key amenities and features + • Location benefits + • Booking confirmation details + +- 📝 Daily Notes + • Weather considerations + • Dress code requirements + • Advance bookings needed + • Local customs and tips + • Emergency contacts + +**IV. Accommodation Details** +For each property: +- 📍 Location & Access + • Exact address and coordinates + • Transport options and costs + • Surrounding area highlights + • Distance to key attractions + +- 🛎️ Property Features + • Room types and views + • Included amenities + • Dining options + • Special services + • Unique selling points + +- 💰 Costs & Booking + • Nightly rates and taxes + • Additional fees + • Cancellation policy + • Payment methods + • Booking platform links + +**V. Curated Experiences** +- 🎭 Activities & Attractions + • Name and description + • Operating hours and duration + • Admission fees + • Booking requirements + • Insider tips + • Alternative options + • Accessibility notes + +- 🍽️ Dining Experiences + • Restaurant details and cuisine + • Price ranges and menu highlights + • Ambiance and dress code + • Reservation policies + • Signature dishes + • Dietary accommodation + • View/seating recommendations + +**VI. Comprehensive Budget** +- 💵 Total Trip Cost + • Grand total in user's currency + • Exchange rates used + • Payment timeline + +- 📊 Detailed Breakdown + • Transportation + - Flights/trains + - Local transport + - Airport transfers + • Accommodations + - Nightly rates + - Taxes and fees + - Extra services + • Activities + - Admission fees + - Guide costs + - Equipment rental + • Dining + - Breakfast allowance + - Lunch budget + - Dinner budget + - Drinks/snacks + • Shopping & Souvenirs + • Emergency Fund + • Optional Upgrades + +**VII. Essential Information** +- 📋 Pre-Trip Preparation + • Visa requirements + • Health and insurance + • Packing recommendations + • Weather forecasts + • Currency exchange tips + +- 🗺️ Destination Guide + • Local customs and etiquette + • Language basics + • Emergency contacts + • Medical facilities + • Shopping areas + • Local transport options + +- 📱 Digital Resources + • Useful apps + • Booking confirmations + • Maps and directions + • Restaurant reservations + • Activity tickets + +- ⚠️ Contingency Plans + • Weather alternatives + • Backup restaurants + • Emergency contacts + • Travel insurance details + • Cancellation policies + +Format the entire itinerary with: +• Clear section headers +• Consistent emoji usage +• Bullet points and sub-bullets +• Tables where appropriate +• Highlighted important information +• Links to all bookings and reservations +• Day-specific weather forecasts +• Local emergency numbers +• Relevant photos and maps +""", + success_criteria=[ + "✅ Complete itinerary with all travel days and activities", + "✅ Stays within budget constraints", + "✅ Matches user priorities and travel style", + "✅ Well-structured daily schedule matching user's pace", + "✅ Real flights and accommodations with costs and links", + "✅ Daily activities aligned with selected vibes", + "✅ Clear Markdown format with good visuals", + "✅ Realistic budget breakdown", + "✅ Personalized tips based on user profile", + "✅ Verified, real-world locations only", + ], + enable_agentic_context=True, + share_member_interactions=True, + show_members_responses=True, + add_datetime_to_instructions=True, + add_member_tools_to_system_message=True, + # debug_mode=True, + telemetry=False, +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/__init__.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/__init__.py new file mode 100644 index 0000000..376522a --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/__init__.py @@ -0,0 +1,3 @@ +from .app import app + +__all__ = ["app"] \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/app.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/app.py new file mode 100644 index 0000000..2c682a3 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/api/app.py @@ -0,0 +1,55 @@ +from fastapi import FastAPI, APIRouter +from fastapi.middleware.cors import CORSMiddleware +from loguru import logger +from datetime import datetime, timezone +from contextlib import asynccontextmanager +from services.db_service import initialize_db_pool, close_db_pool +from router.plan import router as plan_router + +router = APIRouter(prefix="/api") + + +@router.get("/health", summary="API Health Check") +async def health_check(): + logger.debug("Health check requested") + return {"status": "healthy", "timestamp": datetime.now(timezone.utc).isoformat()} + + +@asynccontextmanager +async def lifespan(app: FastAPI): + # Startup logic + logger.info("API server started") + + # Initialize database connection pool + logger.info("Initializing database connection pool") + await initialize_db_pool() + logger.info("Database connection pool initialized") + + yield + + # Shutdown logic + # Close database connection pool + logger.info("Closing database connection pool") + await close_db_pool() + + logger.info("API server shutting down") + + +app = FastAPI( + title="TripCraft AI API", + description="API for running intelligent trip planning in the background", + version="0.1.0", + lifespan=lifespan, +) + +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +app.include_router(router) +app.include_router(plan_router) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/broswer.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/broswer.py new file mode 100644 index 0000000..2a0cc55 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/broswer.py @@ -0,0 +1,55 @@ + + +from config.logger import setup_logging +setup_logging(console_level="INFO") +from loguru import logger + +logger.info("Starting the application") +logger.info("Loading environment variables") +from dotenv import load_dotenv +load_dotenv() +logger.info("Loaded environment variables") + +logger.info("Loading agents") +from agents.flight import flight_search_agent +from agents.hotel import hotel_search_agent +logger.info("Loaded agents") + +# structured_output_agent = Agent( +# name="Structured Output Generator", +# model=model2, +# instructions="Generate structured output in the specified schema format. Parse input data and format according to schema requirements. DO NOT include any other text in your response.", +# expected_output=dedent("""\ +# A JSON object with the following fields: +# - status (str): Success or error status of the request (success or error) +# - message (str): Status message or error description +# - data: Object containing the flight results +# - flights: A list of flight results +# Each flight has the following fields: +# - flight_number (str): The flight number of the flight +# - price (str): The price of the flight +# - airline (str): The airline of the flight +# - departure_time (str): The departure time of the flight +# - arrival_time (str): The arrival time of the flight +# - duration (str): The duration of the flight +# - stops (int): The number of stops of the flight + +# **DO NOT include any other text in your response.** +# }"""), +# markdown=True, +# show_tool_calls=True, +# debug_mode=True, +# response_model=FlightResults, +# ) + +# response = flight_search_agent.run(""" +# Give me flights from Mumbai to Singapore for premium economy on 1 july 2025 for 2 adults and 1 child and sort by cheapest +# """) + +# print(response.content) + +response = hotel_search_agent.run(""" + Give me hotels in Singapore for 2 adults and 1 child on 1 july 2025 to 10 july 2025 and sort by cheapest +""") + +print(response.content) \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/llm.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/llm.py new file mode 100644 index 0000000..e7060fc --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/llm.py @@ -0,0 +1,12 @@ +from agno.models.google import Gemini +from agno.models.openai import OpenAIChat +from agno.models.openrouter import OpenRouter + +# model = Gemini(id="gemini-2.0-flash-001", temperature=0.1) +# model2 = OpenAIChat(id="gpt-4o", temperature=0.1) + +model = OpenRouter(id="google/gemini-2.0-flash-001", temperature=0.3, max_tokens=8096) +model2 = OpenRouter(id="openai/gpt-4o", temperature=0.1) +model_zero = OpenRouter( + id="google/gemini-2.0-flash-001", temperature=0.1, max_tokens=8096 +) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/logger.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/logger.py new file mode 100644 index 0000000..1c203ec --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/config/logger.py @@ -0,0 +1,113 @@ +import sys +import logging +import inspect +from typing import Dict, Any, Callable +from loguru import logger +from pathlib import Path + +# Create logs directory if it doesn't exist +# LOGS_DIR = Path("logs") +# LOGS_DIR.mkdir(exist_ok=True) + + +def configure_logger(console_level: str = "INFO", log_format: str = None) -> None: + """Configure loguru logger with console and file outputs + + Args: + console_level: Minimum level for console logs + file_level: Minimum level for file logs + rotation: When to rotate log files (size or time) + retention: How long to keep log files + log_format: Optional custom format string + """ + # Remove default configuration + logger.remove() + + # Use default format if none provided + if log_format is None: + log_format = "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {name}:{function}:{line} - {message}" + + # Add console handler + logger.add( + sys.stderr, + format=log_format, + level=console_level, + colorize=True, + backtrace=True, + diagnose=True, + ) + + # # Add file handler + # logger.add( + # LOGS_DIR / "app.log", + # format=log_format, + # level=console_level, + # ) + + +# Intercept standard library logging to loguru +class InterceptHandler(logging.Handler): + """Intercepts standard library logging and redirects to loguru""" + + def emit(self, record: logging.LogRecord) -> None: + # Get corresponding Loguru level if it exists + try: + level = logger.level(record.levelname).name + except ValueError: + level = record.levelno + + # Find caller from where originated the logged message + frame, depth = inspect.currentframe(), 0 + while frame and frame.f_code.co_filename == logging.__file__: + frame = frame.f_back + depth += 1 + + logger.opt(depth=depth, exception=record.exc_info).log( + level, record.getMessage() + ) + + +def patch_std_logging(): + """Patch all standard library loggers to use loguru""" + # Replace all existing handlers with the InterceptHandler + logging.basicConfig(handlers=[InterceptHandler()], level=0, force=True) + + # Update all existing loggers + for name in logging.root.manager.loggerDict.keys(): + logging_logger = logging.getLogger(name) + logging_logger.handlers = [InterceptHandler()] + logging_logger.propagate = False + + # Update specific common libraries + for logger_name in ("uvicorn", "uvicorn.error", "uvicorn.access", "fastapi"): + logging_logger = logging.getLogger(logger_name) + logging_logger.handlers = [InterceptHandler()] + + +def setup_logging(console_level: str = "INFO", intercept_stdlib: bool = True) -> None: + """Setup logging for the entire application + + Args: + console_level: Minimum level for console output + file_level: Minimum level for file output + intercept_stdlib: Whether to patch standard library logging + """ + # Configure loguru + configure_logger(console_level=console_level) + + # Optionally patch standard library logging + if intercept_stdlib: + patch_std_logging() + + # Add extra context to logger + logger.configure(extra={"app_name": "decipher-research-agent"}) + + logger.info("Logging configured successfully") + + +def logger_hook(function_name: str, function_call: Callable, arguments: Dict[str, Any]): + """Hook function that wraps the tool execution""" + logger.info(f"About to call {function_name} with arguments: {arguments}") + result = function_call(**arguments) + logger.info(f"Function call completed with result: {result}") + return result diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/docker.sh b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/docker.sh new file mode 100644 index 0000000..5ef69fd --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/docker.sh @@ -0,0 +1,24 @@ +#!/bin/bash + +# Exit on any error +set -e + +# Configuration +IMAGE_NAME="decipher-backend" +DOCKER_REGISTRY="mtwn105" +VERSION=$(git describe --tags --always) + +# Build the Docker image +echo "Building Docker image..." +docker build -t $IMAGE_NAME:$VERSION . + +# Tag the image with latest +docker tag $IMAGE_NAME:$VERSION $DOCKER_REGISTRY/$IMAGE_NAME:latest +docker tag $IMAGE_NAME:$VERSION $DOCKER_REGISTRY/$IMAGE_NAME:$VERSION + +# Push the images +echo "Pushing Docker images..." +docker push $DOCKER_REGISTRY/$IMAGE_NAME:latest +docker push $DOCKER_REGISTRY/$IMAGE_NAME:$VERSION + +echo "Successfully built and pushed version $VERSION" diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/main.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/main.py new file mode 100644 index 0000000..73eeb70 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/main.py @@ -0,0 +1,20 @@ +from dotenv import load_dotenv +from loguru import logger + +# Load environment variables +logger.info("Loading environment variables") +load_dotenv() +logger.info("Environment variables loaded") + +# Import and setup logging configuration +from config.logger import setup_logging + +# Configure logging with loguru +setup_logging(console_level="INFO") + +from api.app import app + +if __name__ == "__main__": + logger.info("Starting TripCraft AI API server") + import uvicorn + uvicorn.run(app, host="0.0.0.0", port=8000) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_plan_tasks_table.sql b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_plan_tasks_table.sql new file mode 100644 index 0000000..13df0d1 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_plan_tasks_table.sql @@ -0,0 +1,35 @@ +-- Create enum type for task status +CREATE TYPE plan_task_status AS ENUM ('queued', 'in_progress', 'success', 'error'); + +-- Create plan_tasks table +CREATE TABLE IF NOT EXISTS plan_tasks ( + id SERIAL PRIMARY KEY, + trip_plan_id VARCHAR(50) NOT NULL, + task_type VARCHAR(50) NOT NULL, + status plan_task_status NOT NULL, + input_data JSONB NOT NULL, + output_data JSONB, + error_message VARCHAR(500), + created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP, + updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP +); + +-- Create index on trip_plan_id for faster lookups +CREATE INDEX IF NOT EXISTS idx_plan_tasks_trip_plan_id ON plan_tasks(trip_plan_id); + +-- Create index on status for faster filtering +CREATE INDEX IF NOT EXISTS idx_plan_tasks_status ON plan_tasks(status); + +-- Create trigger to automatically update updated_at timestamp +CREATE OR REPLACE FUNCTION update_updated_at_column() +RETURNS TRIGGER AS $$ +BEGIN + NEW.updated_at = CURRENT_TIMESTAMP; + RETURN NEW; +END; +$$ language 'plpgsql'; + +CREATE TRIGGER update_plan_tasks_updated_at + BEFORE UPDATE ON plan_tasks + FOR EACH ROW + EXECUTE FUNCTION update_updated_at_column(); \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_trip_plan_tables.sql b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_trip_plan_tables.sql new file mode 100644 index 0000000..47ffe56 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/migrations/create_trip_plan_tables.sql @@ -0,0 +1,51 @@ +-- Create trip_plan_status table +CREATE TABLE IF NOT EXISTS trip_plan_status ( + id text NOT NULL, + "tripPlanId" text NOT NULL, + status text NOT NULL DEFAULT 'pending', + "currentStep" text, + error text, + "startedAt" timestamp without time zone, + "completedAt" timestamp without time zone, + "createdAt" timestamp without time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updatedAt" timestamp without time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, + CONSTRAINT trip_plan_status_pkey PRIMARY KEY (id) +); + +-- Create index on tripPlanId for faster lookups +CREATE INDEX IF NOT EXISTS idx_trip_plan_status_trip_plan_id ON trip_plan_status("tripPlanId"); + +-- Create trip_plan_output table +CREATE TABLE IF NOT EXISTS trip_plan_output ( + id text NOT NULL, + "tripPlanId" text NOT NULL, + itinerary text NOT NULL, + summary text, + "createdAt" timestamp without time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updatedAt" timestamp without time zone NOT NULL DEFAULT CURRENT_TIMESTAMP, + CONSTRAINT trip_plan_output_pkey PRIMARY KEY (id) +); + +-- Create index on tripPlanId for faster lookups +CREATE INDEX IF NOT EXISTS idx_trip_plan_output_trip_plan_id ON trip_plan_output("tripPlanId"); + +-- Create trigger to automatically update updated_at timestamp +CREATE OR REPLACE FUNCTION update_updated_at_column() +RETURNS TRIGGER AS $$ +BEGIN + NEW."updatedAt" = CURRENT_TIMESTAMP; + RETURN NEW; +END; +$$ language 'plpgsql'; + +-- Create trigger for trip_plan_status +CREATE TRIGGER update_trip_plan_status_updated_at + BEFORE UPDATE ON trip_plan_status + FOR EACH ROW + EXECUTE FUNCTION update_updated_at_column(); + +-- Create trigger for trip_plan_output +CREATE TRIGGER update_trip_plan_output_updated_at + BEFORE UPDATE ON trip_plan_output + FOR EACH ROW + EXECUTE FUNCTION update_updated_at_column(); \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/flight.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/flight.py new file mode 100644 index 0000000..8a2be55 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/flight.py @@ -0,0 +1,24 @@ +from pydantic import BaseModel, Field +from typing import List, Optional + +class FlightResult(BaseModel): + flight_number: str = Field(description="The flight number of the flight") + price: str = Field(description="The price of the flight") + airline: str = Field(description="The airline of the flight") + departure_time: str = Field(description="The departure time of the flight") + arrival_time: str = Field(description="The arrival time of the flight") + duration: str = Field(description="The duration of the flight") + stops: int = Field(description="The number of stops of the flight") + +class FlightResults(BaseModel): + flights: List[FlightResult] = Field(description="The list of flights") + +class FlightSearchRequest(BaseModel): + departure: str = Field(description="The departure airport") + destination: str = Field(description="The destination airport") + date: str = Field(description="The date of the flight") + return_date: Optional[str] = Field(description="The return date of the flight") + adults: int = Field(description="The number of adults") + children: int = Field(description="The number of children") + cabin_class: str = Field(description="The cabin class") + sort: str = Field(description="The sort order") \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/hotel.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/hotel.py new file mode 100644 index 0000000..d212825 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/hotel.py @@ -0,0 +1,23 @@ +from pydantic import BaseModel, Field +from typing import List + +class HotelResult(BaseModel): + hotel_name: str = Field(description="The name of the hotel") + price: str = Field(description="The price of the hotel") + rating: str = Field(description="The rating of the hotel") + address: str = Field(description="The address of the hotel") + amenities: List[str] = Field(description="The amenities of the hotel") + description: str = Field(description="The description of the hotel") + url: str = Field(description="The url of the hotel") + +class HotelResults(BaseModel): + hotels: List[HotelResult] = Field(description="The list of hotels") + +class HotelSearchRequest(BaseModel): + destination: str = Field(description="The destination city or area") + check_in: str = Field(description="The date of check-in in the format 'YYYY-MM-DD'") + check_out: str = Field(description="The date of check-out in the format 'YYYY-MM-DD'") + adults: int = Field(description="The number of adults") + children: int = Field(description="The number of children") + rooms: int = Field(description="The number of rooms") + sort: str = Field(description="The sort order") \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/plan_task.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/plan_task.py new file mode 100644 index 0000000..72910a3 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/plan_task.py @@ -0,0 +1,49 @@ +from datetime import datetime, timezone +from enum import Enum +from typing import Optional + +from sqlalchemy import String, DateTime, Enum as SQLEnum, JSON +from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column + + +class TaskStatus(str, Enum): + queued = "queued" + in_progress = "in_progress" + success = "success" + error = "error" + + @classmethod + def _missing_(cls, value): + """Handle case-insensitive enum values.""" + for member in cls: + if member.value.lower() == value.lower(): + return member + return None + + +class Base(DeclarativeBase): + pass + + +class PlanTask(Base): + """Model for tracking plan tasks and their states.""" + + __tablename__ = "plan_tasks" + + id: Mapped[int] = mapped_column(primary_key=True) + trip_plan_id: Mapped[str] = mapped_column(String(50), index=True) + task_type: Mapped[str] = mapped_column(String(50)) + status: Mapped[TaskStatus] = mapped_column( + SQLEnum(TaskStatus, name="plan_task_status") + ) + input_data: Mapped[dict] = mapped_column(JSON) + output_data: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True) + error_message: Mapped[Optional[str]] = mapped_column(String(500), nullable=True) + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), default=lambda: datetime.now(timezone.utc) + ) + updated_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), + default=lambda: datetime.now(timezone.utc), + onupdate=lambda: datetime.now(timezone.utc), + ) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/travel_plan.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/travel_plan.py new file mode 100644 index 0000000..fe48a42 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/travel_plan.py @@ -0,0 +1,115 @@ +from pydantic import BaseModel, Field +from typing import List +from models.hotel import HotelResult + + +class TravelDates(BaseModel): + start: str = "" + end: str = "" + + +class TravelPlanRequest(BaseModel): + name: str = "" + destination: str = "" + starting_location: str = "" + travel_dates: TravelDates = TravelDates() + date_input_type: str = "picker" + duration: int = 0 + traveling_with: str = "" + adults: int = 1 + children: int = 0 + age_groups: List[str] = [] + budget: int = 75000 + budget_currency: str = "INR" + travel_style: str = "" + budget_flexible: bool = False + vibes: List[str] = [] + priorities: List[str] = [] + interests: str = "" + rooms: int = 1 + pace: List[int] = [3] + been_there_before: str = "" + loved_places: str = "" + additional_info: str = "" + + +class TravelPlanAgentRequest(BaseModel): + trip_plan_id: str + travel_plan: TravelPlanRequest + + +class TravelPlanResponse(BaseModel): + success: bool + message: str + trip_plan_id: str + + +class DayByDayPlan(BaseModel): + day: int = Field( + default=0, description="The day number in the itinerary, starting from 0" + ) + date: str = Field( + default="", description="The date for this day in YYYY-MM-DD format" + ) + morning: str = Field( + default="", description="Description of morning activities and plans" + ) + afternoon: str = Field( + default="", description="Description of afternoon activities and plans" + ) + evening: str = Field( + default="", description="Description of evening activities and plans" + ) + notes: str = Field( + default="", + description="Additional tips, reminders or important information for the day", + ) + + +class Attraction(BaseModel): + name: str = Field(default="", description="Name of the attraction") + description: str = Field( + default="", description="Detailed description of the attraction" + ) + + +class FlightResult(BaseModel): + duration: str = Field(default="", description="Duration of the flight") + price: str = Field( + default="", description="Price of the flight in the local currency" + ) + departure_time: str = Field(default="", description="Departure time of the flight") + arrival_time: str = Field(default="", description="Arrival time of the flight") + airline: str = Field(default="", description="Airline of the flight") + flight_number: str = Field(default="", description="Flight number of the flight") + url: str = Field(default="", description="Website or booking URL for the flight") + stops: int = Field(default=0, description="Number of stops in the flight") + + +class RestaurantResult(BaseModel): + name: str = Field(default="", description="Name of the restaurant") + description: str = Field(default="", description="Description of the restaurant") + location: str = Field(default="", description="Location of the restaurant") + url: str = Field( + default="", description="Website or booking URL for the restaurant" + ) + + +class TravelPlanTeamResponse(BaseModel): + day_by_day_plan: List[DayByDayPlan] = Field( + description="A list of day-by-day plans for the trip" + ) + hotels: List[HotelResult] = Field(description="A list of hotels for the trip") + attractions: List[Attraction] = Field( + description="A list of recommended attractions for the trip" + ) + flights: List[FlightResult] = Field(description="A list of flights for the trip") + restaurants: List[RestaurantResult] = Field( + description="A list of recommended restaurants for the trip" + ) + budget_insights: List[str] = Field( + description="A list of budget insights for the trip" + ) + tips: List[str] = Field( + description="A list of tips or recommendations for the trip" + ) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/trip_db.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/trip_db.py new file mode 100644 index 0000000..6528134 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/models/trip_db.py @@ -0,0 +1,82 @@ +from sqlalchemy import Column, String, TIMESTAMP, ForeignKey, Text, DateTime +from sqlalchemy.orm import relationship +from sqlalchemy.ext.declarative import declarative_base +from datetime import datetime, timezone +from typing import Optional +from cuid2 import Cuid + +CUID_GENERATOR: Cuid = Cuid() + +from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column + + +class Base(DeclarativeBase): + pass + + +class TripPlan(Base): + __tablename__ = ( + "trip_plan" # Assuming this table exists as per foreign key constraints + ) + id = Column( + String, primary_key=True, default=lambda: str(CUID_GENERATOR.generate()) + ) + # Add other fields for TripPlan if needed for standalone model definition + # For this task, we only need it to satisfy relationship constraints if defined from this end. + + +class TripPlanStatus(Base): + """Model for tracking trip plan status.""" + + __tablename__ = "trip_plan_status" + + id: Mapped[str] = mapped_column( + Text, primary_key=True, default=lambda: CUID_GENERATOR.generate() + ) + tripPlanId: Mapped[str] = mapped_column(Text, index=True) + status: Mapped[str] = mapped_column(Text, default="pending") + currentStep: Mapped[Optional[str]] = mapped_column(Text, nullable=True) + error: Mapped[Optional[str]] = mapped_column(Text, nullable=True) + startedAt: Mapped[Optional[datetime]] = mapped_column( + DateTime(timezone=False), nullable=True + ) + completedAt: Mapped[Optional[datetime]] = mapped_column( + DateTime(timezone=False), nullable=True + ) + createdAt: Mapped[datetime] = mapped_column( + DateTime(timezone=False), + default=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + ) + updatedAt: Mapped[datetime] = mapped_column( + DateTime(timezone=False), + default=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + onupdate=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + ) + + # Relationship (optional, but good practice) + # trip_plan = relationship("TripPlan") # Define TripPlan model if you want to use this relationship + + +class TripPlanOutput(Base): + """Model for storing trip plan output.""" + + __tablename__ = "trip_plan_output" + + id: Mapped[str] = mapped_column( + Text, primary_key=True, default=lambda: CUID_GENERATOR.generate() + ) + tripPlanId: Mapped[str] = mapped_column(Text, index=True) + itinerary: Mapped[str] = mapped_column(Text) + summary: Mapped[Optional[str]] = mapped_column(Text, nullable=True) + createdAt: Mapped[datetime] = mapped_column( + DateTime(timezone=False), + default=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + ) + updatedAt: Mapped[datetime] = mapped_column( + DateTime(timezone=False), + default=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + onupdate=lambda: datetime.now(timezone.utc).replace(tzinfo=None), + ) + + # Relationship (optional) + # trip_plan = relationship("TripPlan") # Define TripPlan model diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/pyproject.toml b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/pyproject.toml new file mode 100644 index 0000000..5794fb4 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/pyproject.toml @@ -0,0 +1,23 @@ +[project] +name = "agno-hackathon" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "agno>=1.5.6", + "asyncpg>=0.30.0", + "boto3>=1.38.27", + "cuid2>=2.0.1", + "exa-py>=1.13.1", + "fast-flights>=2.2", + "fastapi>=0.115.12", + "firecrawl-py>=2.7.1", + "google-genai>=1.18.0", + "loguru>=0.7.3", + "mem0ai>=0.1.102", + "pydantic>=2.11.5", + "python-dotenv>=1.1.0", + "sqlalchemy>=2.0.41", + "uvicorn>=0.34.2", +] diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/plan_task_repository.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/plan_task_repository.py new file mode 100644 index 0000000..c8a0958 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/plan_task_repository.py @@ -0,0 +1,76 @@ +from datetime import datetime, timezone +from typing import Optional, List + +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession + +from models.plan_task import PlanTask, TaskStatus +from services.db_service import get_db_session + + +async def create_plan_task( + trip_plan_id: str, + task_type: str, + input_data: dict, + status: TaskStatus = TaskStatus.queued, +) -> PlanTask: + """Create a new plan task.""" + async with get_db_session() as session: + task = PlanTask( + trip_plan_id=trip_plan_id, + task_type=task_type, + status=status, + input_data=input_data, + ) + session.add(task) + await session.commit() + await session.refresh(task) + return task + + +async def update_task_status( + task_id: int, + status: TaskStatus, + output_data: Optional[dict] = None, + error_message: Optional[str] = None, +) -> Optional[PlanTask]: + """Update the status and output of a plan task.""" + async with get_db_session() as session: + result = await session.execute(select(PlanTask).where(PlanTask.id == task_id)) + task = result.scalar_one_or_none() + + if task: + task.status = status + if output_data is not None: + task.output_data = output_data + if error_message is not None: + task.error_message = error_message + task.updated_at = datetime.now(timezone.utc) + await session.commit() + await session.refresh(task) + return task + + +async def get_task_by_id(task_id: int) -> Optional[PlanTask]: + """Get a plan task by its ID.""" + async with get_db_session() as session: + result = await session.execute(select(PlanTask).where(PlanTask.id == task_id)) + return result.scalar_one_or_none() + + +async def get_tasks_by_trip_plan(trip_plan_id: str) -> List[PlanTask]: + """Get all tasks for a specific trip plan.""" + async with get_db_session() as session: + result = await session.execute( + select(PlanTask).where(PlanTask.trip_plan_id == trip_plan_id) + ) + return list(result.scalars().all()) + + +async def get_tasks_by_status(status: TaskStatus) -> List[PlanTask]: + """Get all tasks with a specific status.""" + async with get_db_session() as session: + result = await session.execute( + select(PlanTask).where(PlanTask.status == status) + ) + return list(result.scalars().all()) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/trip_plan_repository.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/trip_plan_repository.py new file mode 100644 index 0000000..6a98cb7 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/repository/trip_plan_repository.py @@ -0,0 +1,152 @@ +from datetime import datetime, timezone +from typing import Optional, List + +from sqlalchemy import select, delete +from sqlalchemy.ext.asyncio import AsyncSession + +from models.trip_db import TripPlanStatus, TripPlanOutput +from services.db_service import get_db_session + + +async def create_trip_plan_status( + trip_plan_id: str, status: str = "pending", current_step: Optional[str] = None +) -> TripPlanStatus: + """Create a new trip plan status entry.""" + async with get_db_session() as session: + status_entry = TripPlanStatus( + tripPlanId=trip_plan_id, + status=status, + currentStep=current_step, + createdAt=datetime.now().replace(tzinfo=None), + updatedAt=datetime.now().replace(tzinfo=None), + ) + session.add(status_entry) + await session.commit() + await session.refresh(status_entry) + return status_entry + + +async def get_trip_plan_status(trip_plan_id: str) -> Optional[TripPlanStatus]: + """Get the status entry for a trip plan.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanStatus).where(TripPlanStatus.tripPlanId == trip_plan_id) + ) + return result.scalar_one_or_none() + + +async def update_trip_plan_status( + trip_plan_id: str, + status: str, + current_step: Optional[str] = None, + error: Optional[str] = None, + started_at: Optional[datetime] = None, + completed_at: Optional[datetime] = None, +) -> Optional[TripPlanStatus]: + """Update the status of a trip plan.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanStatus).where(TripPlanStatus.tripPlanId == trip_plan_id) + ) + status_entry = result.scalar_one_or_none() + + if status_entry: + status_entry.status = status + if current_step is not None: + status_entry.currentStep = current_step + if error is not None: + status_entry.error = error + if started_at is not None: + status_entry.startedAt = started_at.replace(tzinfo=None) + if completed_at is not None: + status_entry.completedAt = completed_at.replace(tzinfo=None) + status_entry.updatedAt = datetime.now(timezone.utc).replace(tzinfo=None) + + await session.commit() + await session.refresh(status_entry) + return status_entry + + +async def create_trip_plan_output( + trip_plan_id: str, itinerary: str, summary: Optional[str] = None +) -> TripPlanOutput: + """Create a new trip plan output entry.""" + async with get_db_session() as session: + output_entry = TripPlanOutput( + tripPlanId=trip_plan_id, + itinerary=itinerary, + summary=summary, + createdAt=datetime.now(timezone.utc).replace(tzinfo=None), + updatedAt=datetime.now(timezone.utc).replace(tzinfo=None), + ) + session.add(output_entry) + await session.commit() + await session.refresh(output_entry) + return output_entry + + +async def get_trip_plan_output(trip_plan_id: str) -> Optional[TripPlanOutput]: + """Get the output entry for a trip plan.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanOutput).where(TripPlanOutput.tripPlanId == trip_plan_id) + ) + return result.scalar_one_or_none() + + +async def update_trip_plan_output( + trip_plan_id: str, itinerary: Optional[str] = None, summary: Optional[str] = None +) -> Optional[TripPlanOutput]: + """Update the output of a trip plan.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanOutput).where(TripPlanOutput.tripPlanId == trip_plan_id) + ) + output_entry = result.scalar_one_or_none() + + if output_entry: + if itinerary is not None: + output_entry.itinerary = itinerary + if summary is not None: + output_entry.summary = summary + output_entry.updatedAt = datetime.now(timezone.utc).replace(tzinfo=None) + + await session.commit() + await session.refresh(output_entry) + return output_entry + + +async def get_all_pending_trip_plans() -> List[TripPlanStatus]: + """Get all trip plans with pending status.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanStatus).where(TripPlanStatus.status == "pending") + ) + return list(result.scalars().all()) + + +async def get_all_processing_trip_plans() -> List[TripPlanStatus]: + """Get all trip plans with processing status.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanStatus).where(TripPlanStatus.status == "processing") + ) + return list(result.scalars().all()) + + +async def get_trip_plans_by_status(status: str) -> List[TripPlanStatus]: + """Get all trip plans with a specific status.""" + async with get_db_session() as session: + result = await session.execute( + select(TripPlanStatus).where(TripPlanStatus.status == status) + ) + return list(result.scalars().all()) + + +async def delete_trip_plan_outputs(trip_plan_id: str) -> None: + """Delete all output entries for a given trip plan ID.""" + async with get_db_session() as session: + await session.execute( + delete(TripPlanOutput).where(TripPlanOutput.tripPlanId == trip_plan_id) + ) + await session.commit() diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/router/plan.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/router/plan.py new file mode 100644 index 0000000..4f19450 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/router/plan.py @@ -0,0 +1,84 @@ +import asyncio +from fastapi import APIRouter, HTTPException, status +from loguru import logger +from models.travel_plan import TravelPlanAgentRequest, TravelPlanResponse +from models.plan_task import TaskStatus +from services.plan_service import generate_travel_plan +from repository.plan_task_repository import create_plan_task, update_task_status +from typing import List + +router = APIRouter(prefix="/api/plan", tags=["Travel Plan"]) + + +@router.post( + "/trigger", + response_model=TravelPlanResponse, + summary="Trigger Trip Craft Agent", + description="Triggers the travel plan agent with the provided travel details", +) +async def trigger_trip_craft_agent( + request: TravelPlanAgentRequest, +) -> TravelPlanResponse: + """ + Trigger the trip craft agent to create a personalized travel itinerary. + + Args: + request: Travel plan request containing trip details and plan ID + + Returns: + TravelPlanResponse: Success status and trip plan ID + """ + try: + logger.info(f"Triggering travel plan agent for trip ID: {request.trip_plan_id}") + logger.info(f"Travel plan details: {request.travel_plan}") + + # Create initial task + task = await create_plan_task( + trip_plan_id=request.trip_plan_id, + task_type="travel_plan_generation", + input_data=request.travel_plan.model_dump(), + ) + + logger.info(f"Task created: {task.id}") + + # Create background task for plan generation + async def generate_plan_with_tracking(): + try: + # Update task status to in progress when service starts + await update_task_status(task.id, TaskStatus.in_progress) + logger.info(f"Task updated to in progress: {task.id}") + + result = await generate_travel_plan(request) + + # Update task with success status and output + await update_task_status( + task.id, TaskStatus.success, output_data={"travel_plan": result} + ) + logger.info(f"Task updated to success: {task.id}") + except Exception as e: + logger.error(f"Error generating travel plan: {str(e)}") + # Update task with error status + await update_task_status( + task.id, TaskStatus.error, error_message=str(e) + ) + logger.info(f"Task updated to error: {task.id}") + raise + + asyncio.create_task(generate_plan_with_tracking()) + + logger.info( + f"Travel plan agent triggered successfully for trip ID: {request.trip_plan_id}" + ) + + return TravelPlanResponse( + success=True, + message="Travel plan agent triggered successfully", + trip_plan_id=request.trip_plan_id, + ) + + except Exception as e: + logger.error(f"Error triggering travel plan agent: {str(e)}") + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"Failed to trigger travel plan agent: {str(e)}", + ) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/db_service.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/db_service.py new file mode 100644 index 0000000..8c60ee9 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/db_service.py @@ -0,0 +1,131 @@ +""" +Database service module for PostgreSQL connections using SQLAlchemy. + +This module provides utilities for connecting to a PostgreSQL database +with SQLAlchemy, including connection pooling, session management, +and context managers for proper resource management. +""" + +import os +from typing import Any, AsyncGenerator, Dict, Optional +from contextlib import asynccontextmanager + +from sqlalchemy import text +from sqlalchemy.ext.asyncio import ( + AsyncSession, + create_async_engine, + async_sessionmaker, + AsyncEngine +) +from loguru import logger + +# Database connection string from environment variable +# Convert psycopg to SQLAlchemy format if needed +DATABASE_URL = os.getenv("DATABASE_URL", "") +if DATABASE_URL.startswith("postgresql://"): + # Convert to asyncpg format for SQLAlchemy async + DATABASE_URL = DATABASE_URL.replace("postgresql://", "postgresql+asyncpg://") + +# Global engine and session factory +_engine: Optional[AsyncEngine] = None +_session_factory: Optional[async_sessionmaker[AsyncSession]] = None + +async def initialize_db_pool(pool_size: int = 10, max_overflow: int = 20) -> None: + """Initialize the SQLAlchemy engine and session factory. + + Args: + pool_size: Pool size for the connection pool + max_overflow: Maximum number of connections that can be created beyond the pool size + """ + global _engine, _session_factory + if _engine is not None: + return + + logger.info("Initializing SQLAlchemy engine and session factory") + + try: + _engine = create_async_engine( + DATABASE_URL, + echo=False, # Set to True for SQL query logging + pool_size=pool_size, + max_overflow=max_overflow, + pool_pre_ping=True, # Verify connections before using them + ) + + _session_factory = async_sessionmaker( + _engine, + expire_on_commit=False, + autoflush=False, + ) + + # Test the connection + async with _session_factory() as session: + await session.execute(text("SELECT 1")) + + logger.info("SQLAlchemy engine and session factory initialized successfully") + except Exception as e: + logger.error(f"Failed to initialize SQLAlchemy engine and session factory: {e}") + raise + +async def close_db_pool() -> None: + """Close the SQLAlchemy engine and connection pool.""" + global _engine + if _engine is not None: + logger.info("Closing SQLAlchemy engine and connection pool") + await _engine.dispose() + _engine = None + +@asynccontextmanager +async def get_db_session() -> AsyncGenerator[AsyncSession, None]: + """Get a SQLAlchemy session for database operations. + + Returns: + AsyncSession: SQLAlchemy async session + + Example: + ```python + async with get_db_session() as session: + result = await session.execute(text("SELECT * FROM users")) + users = result.fetchall() + ``` + """ + if _session_factory is None: + await initialize_db_pool() + + async with _session_factory() as session: + try: + yield session + except Exception as e: + await session.rollback() + logger.error(f"Database session operation failed: {e}") + raise + +async def execute_query(query: str, params: Optional[Dict[str, Any]] = None) -> list: + """Execute a database query and return results. + + Args: + query: SQL query to execute (raw SQL) + params: Query parameters (for parameterized queries) + + Returns: + list: Query results + + Example: + ```python + results = await execute_query( + "SELECT * FROM users WHERE email = :email", + {"email": "user@example.com"} + ) + ``` + """ + async with get_db_session() as session: + try: + result = await session.execute(text(query), params or {}) + try: + return result.fetchall() + except Exception: + # No results to fetch + return [] + except Exception as e: + logger.error(f"Failed to execute query: {e}") + raise \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/plan_service.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/plan_service.py new file mode 100644 index 0000000..a54944d --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/services/plan_service.py @@ -0,0 +1,413 @@ +from datetime import datetime, timezone +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy import select +from models.trip_db import TripPlanStatus, TripPlanOutput +from models.travel_plan import ( + TravelPlanAgentRequest, + TravelPlanRequest, + TravelPlanTeamResponse, +) +from loguru import logger +from agents.team import trip_planning_team +import json +import time +from agents.structured_output import convert_to_model +from repository.trip_plan_repository import ( + create_trip_plan_status, + update_trip_plan_status, + get_trip_plan_status, + create_trip_plan_output, + delete_trip_plan_outputs, +) +from agents.destination import destination_agent +from agents.itinerary import itinerary_agent +from agents.flight import flight_search_agent +from agents.hotel import hotel_search_agent +from agents.food import dining_agent +from agents.budget import budget_agent + + +def travel_request_to_markdown(data: TravelPlanRequest) -> str: + # Map of travel vibes to their descriptions + travel_vibes = { + "relaxing": "a peaceful retreat focused on wellness, spa experiences, and leisurely activities", + "adventure": "thrilling experiences including hiking, water sports, and adrenaline activities", + "romantic": "intimate experiences with private dining, couples activities, and scenic spots", + "cultural": "immersive experiences with local traditions, museums, and historical sites", + "food-focused": "culinary experiences including cooking classes, food tours, and local cuisine", + "nature": "outdoor experiences with national parks, wildlife, and scenic landscapes", + "photography": "photogenic locations with scenic viewpoints, cultural sites, and natural wonders", + } + + # Map of travel styles to their descriptions + travel_styles = { + "backpacker": "budget-friendly accommodations, local transportation, and authentic experiences", + "comfort": "mid-range hotels, convenient transportation, and balanced comfort-value ratio", + "luxury": "premium accommodations, private transfers, and exclusive experiences", + "eco-conscious": "sustainable accommodations, eco-friendly activities, and responsible tourism", + } + + # Map of pace levels (0-5) to their descriptions + pace_levels = { + 0: "1-2 activities per day with plenty of free time and flexibility", + 1: "2-3 activities per day with significant downtime between activities", + 2: "3-4 activities per day with balanced activity and rest periods", + 3: "4-5 activities per day with moderate breaks between activities", + 4: "5-6 activities per day with minimal downtime", + 5: "6+ activities per day with back-to-back scheduling", + } + + def format_date(date_str: str, is_picker: bool) -> str: + if not date_str: + return "Not specified" + if is_picker: + try: + dt = datetime.fromisoformat(date_str.replace("Z", "+00:00")) + return dt.strftime("%B %d, %Y") + except ValueError: + return date_str + return date_str.strip() + + date_type = data.date_input_type + is_picker = date_type == "picker" + start_date = format_date(data.travel_dates.start, is_picker) + end_date = format_date(data.travel_dates.end, is_picker) + date_range = ( + f"between {start_date} and {end_date}" + if end_date and end_date != "Not specified" + else start_date + ) + + vibes = data.vibes + vibes_descriptions = [travel_vibes.get(v, v) for v in vibes] + + lines = [ + f"# 🧳 Travel Plan Request", + "", + "## 📍 Trip Overview", + f"- **Traveler:** {data.name.title() if data.name else 'Unnamed Traveler'}", + f"- **Route:** {data.starting_location.title()} → {data.destination.title()}", + f"- **Duration:** {data.duration} days ({date_range})", + "", + "## 👥 Travel Group", + f"- **Group Size:** {data.adults} adults, {data.children} children", + f"- **Traveling With:** {data.traveling_with or 'Not specified'}", + f"- **Age Groups:** {', '.join(data.age_groups) or 'Not specified'}", + f"- **Rooms Needed:** {data.rooms or 'Not specified'}", + "", + "## 💰 Budget & Preferences", + f"- **Budget per person:** {data.budget} {data.budget_currency} ({'Flexible' if data.budget_flexible else 'Fixed'})", + f"- **Travel Style:** {travel_styles.get(data.travel_style, data.travel_style or 'Not specified')}", + f"- **Preferred Pace:** {', '.join([pace_levels.get(p, str(p)) for p in data.pace]) or 'Not specified'}", + "", + "## ✨ Trip Preferences", + ] + + if vibes_descriptions: + lines.append("- **Travel Vibes:**") + for vibe in vibes_descriptions: + lines.append(f" - {vibe}") + else: + lines.append("- **Travel Vibes:** Not specified") + + if data.priorities: + lines.append(f"- **Top Priorities:** {', '.join(data.priorities)}") + if data.interests: + lines.append(f"- **Interests:** {data.interests}") + + lines.extend( + [ + "", + "## 🗺️ Destination Context", + f"- **Previous Visit:** {data.been_there_before.capitalize() if data.been_there_before else 'Not specified'}", + f"- **Loved Places:** {data.loved_places or 'Not specified'}", + f"- **Additional Notes:** {data.additional_info or 'Not specified'}", + ] + ) + + return "\n".join(lines) + + +async def generate_travel_plan(request: TravelPlanAgentRequest) -> str: + """Generate a travel plan based on the request and log status/output to database.""" + trip_plan_id = request.trip_plan_id + logger.info(f"Generating travel plan for tripPlanId: {trip_plan_id}") + + # Get or create status entry using repository functions + status_entry = await get_trip_plan_status(trip_plan_id) + if not status_entry: + status_entry = await create_trip_plan_status( + trip_plan_id=trip_plan_id, status="pending" + ) + + # Update status to processing + status_entry = await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Initializing travel plan generation", + started_at=datetime.now(timezone.utc), + ) + + try: + travel_request_md = travel_request_to_markdown(request.travel_plan) + logger.info(f"Travel request markdown: {travel_request_md}") + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Generating plan with TripCraft AI agents", + ) + + last_response_content = "" + time_start = time.time() + + # Team Collaboration + # prompt = f""" + # Below is my travel plan request. Please generate a travel plan for the request. + # {travel_request_md} + # """ + + # time_start = time.time() + # ai_response = await trip_planning_team.arun(prompt) + # time_end = time.time() + # logger.info(f"AI team processing time: {time_end - time_start:.2f} seconds") + + # last_response_content = ai_response.messages[-1].content + # logger.info( + # f"Last AI Response for conversion: {last_response_content[:500]}..." + # ) + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Researching about the destination", + ) + + # Destination Research + destionation_research_response = await destination_agent.arun( + f""" + Please research about the destination {request.travel_plan.destination} + + Below are user's travel request: + {travel_request_md} + + Provide a very detailed research about the destination, its attractions, activities, and other relevant information that user might be interested in. + + Give 10 attractions/activities that user might be interested in. + """ + ) + + logger.info( + f"Destination research response: {destionation_research_response.messages[-1].content}" + ) + + last_response_content = f""" + ## Destination Attractions: + --- + {destionation_research_response.messages[-1].content} + --- +""" + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Searching for the best flights", + ) + # Flight Search + flight_search_response = await flight_search_agent.arun( + f""" + Please find flights according to the user's travel request: + {travel_request_md} + + If user has not specified the exact flight date, please consider it by yourself based on the user's travel request. + + Provide a very detailed research about the flights, its price, duration, and other relevant information that user might be interested in. + + Give top 5 flights. + """ + ) + + logger.info( + f"Flight search response: {flight_search_response.messages[-1].content}" + ) + + last_response_content += f""" + ## Flight recommendations: + --- + {flight_search_response.messages[-1].content} + --- + """ + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Searching for the best hotels", + ) + # Hotel Search + hotel_search_response = await hotel_search_agent.arun( + f""" + Please find hotels according to the user's travel request: + {travel_request_md} + + If user has not specified the exact hotel dates, please consider it by yourself based on the user's travel request. + + Provide a very detailed research about the hotels, its price, amenities, and other relevant information that user might be interested in. + + Give top 5 hotels. + """ + ) + + last_response_content += f""" + ## Hotel recommendations: + --- + {hotel_search_response.messages[-1].content} + --- + """ + + logger.info( + f"Hotel search response: {hotel_search_response.messages[-1].content}" + ) + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Searching for the best restaurants", + ) + # Restaurant Search + restaurant_search_response = await dining_agent.arun( + f""" + Please find restaurants according to the user's travel request: + {travel_request_md} + + If user has not specified the exact restaurant dates, please consider it by yourself based on the user's travel request. + + Provide a very detailed research about the restaurants, its price, menu, and other relevant information that user might be interested in. + + Give top 5 restaurants. + """ + ) + + last_response_content += f""" + ## Restaurant recommendations: + --- + {restaurant_search_response.messages[-1].content} + --- + """ + + logger.info( + f"Restaurant search response: {restaurant_search_response.messages[-1].content}" + ) + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Creating the day-by-day itinerary", + ) + # Itinerary + itinerary_response = await itinerary_agent.arun( + f""" + Please create a detailed day-by-day itinerary for a trip to {request.travel_plan.destination} for user's travel request: + {travel_request_md} + + Based on the following information: + {last_response_content} + """ + ) + + logger.info(f"Itinerary response: {itinerary_response.messages[-1].content}") + + last_response_content += f""" + ## Day-by-day itinerary: + --- + {itinerary_response.messages[-1].content} + --- + """ + + # Update status for AI team generation + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Optimizing the budget", + ) + # Budget + budget_response = await budget_agent.arun( + f""" + Please optimize the budget according to the user's travel request: + {travel_request_md} + + Based on the following information: + {last_response_content} + """ + ) + + logger.info(f"Budget response: {budget_response.messages[-1].content}") + + time_end = time.time() + logger.info(f"Total time taken: {time_end - time_start:.2f} seconds") + + # Update status for response conversion + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="processing", + current_step="Adding finishing touches", + ) + + json_response_output = await convert_to_model( + last_response_content, TravelPlanTeamResponse + ) + logger.info(f"Converted Structured Response: {json_response_output[:500]}...") + + # Delete any existing output entries for this trip plan + await delete_trip_plan_outputs(trip_plan_id=trip_plan_id) + + final_response = json.dumps( + { + "itinerary": json_response_output, + "budget_agent_response": budget_response.messages[-1].content, + "destination_agent_response": destionation_research_response.messages[ + -1 + ].content, + "flight_agent_response": flight_search_response.messages[-1].content, + "hotel_agent_response": hotel_search_response.messages[-1].content, + "restaurant_agent_response": restaurant_search_response.messages[ + -1 + ].content, + "itinerary_agent_response": itinerary_response.messages[-1].content, + }, + indent=2, + ) + + # Create new output entry + await create_trip_plan_output( + trip_plan_id=trip_plan_id, + itinerary=final_response, + summary="", + ) + + # Update status to completed + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="completed", + current_step="Plan generated and saved", + completed_at=datetime.now(timezone.utc), + ) + + return final_response + except Exception as e: + logger.error( + f"Error generating travel plan for {trip_plan_id}: {str(e)}", exc_info=True + ) + # Update status to failed + await update_trip_plan_status( + trip_plan_id=trip_plan_id, + status="failed", + error=str(e), + completed_at=datetime.now(timezone.utc), + ) + raise diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/google_flight.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/google_flight.py new file mode 100644 index 0000000..ea808f2 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/google_flight.py @@ -0,0 +1,52 @@ +from fast_flights import FlightData, Passengers, Result, get_flights +from typing import Literal +from loguru import logger +from agno.tools import tool +from config.logger import logger_hook + + +@tool(name="get_flights", show_result=True, tool_hooks=[logger_hook]) +def get_google_flights( + departure: str, + destination: str, + date: str, + trip: Literal["one-way", "round-trip"] = "one-way", + adults: int = 1, + children: int = 0, + cabin_class: Literal["first", "business", "premium-economy", "economy"] = "economy", +) -> Result: + """ + Get flights from Google Flights + + :param departure: The departure airport code + :param destination: The destination airport code + :param date: The date of the flight in the format 'YYYY-MM-DD' + :param trip: The type of trip (one-way, round-trip) + :param adults: The number of adults (default 1) + :param children: The number of children (default 0) + :param cabin_class: The cabin class (first, business, premium-economy, economy) + :return: Flight Results + + """ + logger.info( + f"Getting flights from Google Flights for {departure} to {destination} on {date}" + ) + + try: + result: Result = get_flights( + flight_data=[ + FlightData(date=date, from_airport=departure, to_airport=destination) + ], + trip=trip, + seat=cabin_class, + passengers=Passengers( + adults=adults, children=children, infants_in_seat=0, infants_on_lap=0 + ), + fetch_mode="fallback", + ) + logger.info(f"Flights found: {result.flights}") + + return result.flights + except Exception as e: + logger.error(f"Error getting flights from Google Flights: {e}") + return [] diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_flight.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_flight.py new file mode 100644 index 0000000..68a457a --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_flight.py @@ -0,0 +1,59 @@ +from config.logger import logger_hook +from typing import Optional +from agno.tools import tool +from models.flight import FlightSearchRequest +from loguru import logger + +@tool( + name="kayak_flight_url_generator", + show_result=True, + tool_hooks=[logger_hook] +) +def kayak_flight_url_generator( + departure: str, destination: str, date: str, return_date: Optional[str] = None, adults: int = 1, children: int = 0, cabin_class: Optional[str] = None, sort: str = "best" +) -> str: + """ + Generates a Kayak URL for flights between departure and destination on the specified date. + + :param departure: The IATA code for the departure airport (e.g., 'SOF' for Sofia) + :param destination: The IATA code for the destination airport (e.g., 'BER' for Berlin) + :param date: The date of the flight in the format 'YYYY-MM-DD' + :return_date: Only for two-way tickets. The date of return flight in the format 'YYYY-MM-DD' + :param adults: The number of adults (default 1) + :param children: The number of children (default 0) + :param cabin_class: The cabin class (first, business, premium, economy) + :param sort: The sort order (best, cheapest) + :return: The Kayak URL for the flight search + """ + request = FlightSearchRequest( + departure=departure, + destination=destination, + date=date, + return_date=return_date, + adults=adults, + children=children, + cabin_class=cabin_class, + sort=sort) + + logger.info(f"Request: {request}") + + logger.info(f"Generating Kayak URL for {departure} to {destination} on {date}") + URL = f"https://www.kayak.com/flights/{departure}-{destination}/{date}" + if return_date: + URL += f"/{return_date}" + if cabin_class and cabin_class.lower() != "economy": + URL += f"/{cabin_class.lower()}" + URL += f"/{adults}adults" + if children > 0: + URL += f"/children" + for _ in range(children): + URL += "-11" + + + URL += "?currency=USD" + if sort.lower() == "cheapest": + URL += "&sort=price_a" + elif sort.lower() == "best": + URL += "&sort=bestflight_a" + logger.info(f"URL: {URL}") + return URL diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_hotel.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_hotel.py new file mode 100644 index 0000000..2225ebd --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/kayak_hotel.py @@ -0,0 +1,56 @@ +from config.logger import logger_hook +from typing import Optional +from agno.tools import tool +from models.hotel import HotelSearchRequest +from loguru import logger + +@tool( + name="kayak_hotel_url_generator", + show_result=True, + tool_hooks=[logger_hook] +) +def kayak_hotel_url_generator( + destination: str, check_in: str, check_out: str, adults: int = 1, children: int = 0, rooms: int = 1, sort: str = "recommended" +) -> str: + """ + Generates a Kayak URL for hotels in the specified destination between check_in and check_out dates. + + :param destination: The destination city or area (e.g. "Berlin", "City Center, Singapore", "Red Fort, Delhi") + :param check_in: The date of check-in in the format 'YYYY-MM-DD' + :param check_out: The date of check-out in the format 'YYYY-MM-DD' + :param adults: The number of adults (default 1) + :param children: The number of children (default 0) + :param rooms: The number of rooms (default 1) + :param sort: The sort order (recommended, distance, price, rating) + :return: The Kayak URL for the hotel search + """ + request = HotelSearchRequest( + destination=destination, + check_in=check_in, + check_out=check_out, + adults=adults, + children=children, + rooms=rooms, + sort=sort) + + logger.info(f"Request: {request}") + + logger.info(f"Generating Kayak URL for {destination} on {check_in} to {check_out}") + URL = f"https://www.kayak.com/hotels/{destination}/{check_in}/{check_out}" + URL += f"/{adults}adults" + if children > 0: + URL += f"/{children}children" + + if rooms > 1: + URL += f"/{rooms}rooms" + + + URL += "?currency=USD" + if sort.lower() == "price": + URL += "&sort=price_a" + elif sort.lower() == "rating": + URL += "&sort=userrating_b" + elif sort.lower() == "distance": + URL += "&sort=distance_a" + logger.info(f"URL: {URL}") + return URL diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/scrape.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/scrape.py new file mode 100644 index 0000000..5252f7d --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/tools/scrape.py @@ -0,0 +1,34 @@ +from firecrawl import FirecrawlApp, ScrapeOptions +import os +from agno.tools import tool +from loguru import logger +from config.logger import logger_hook + +app = FirecrawlApp(api_key=os.getenv("FIRECRAWL_API_KEY")) + + +@tool( + name="scrape_website", + description="Scrape a website and return the markdown content.", + tool_hooks=[logger_hook], +) +def scrape_website(url: str) -> str: + """Scrape a website and return the markdown content. + + Args: + url (str): The URL of the website to scrape. + + Returns: + str: The markdown content of the website. + + Example: + >>> scrape_website("https://www.google.com") + "## Google" + """ + scrape_status = app.scrape_url( + url, + formats=["markdown"], + wait_for=30000, + timeout=60000, + ) + return scrape_status.markdown diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/travel_planning_team.py b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/travel_planning_team.py new file mode 100644 index 0000000..d02a95e --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/travel_planning_team.py @@ -0,0 +1,14 @@ +from fast_flights import FlightData, Passengers, Result, get_flights + +result: Result = get_flights( + flight_data=[FlightData(date="2025-07-01", from_airport="BOM", to_airport="DEL")], + trip="one-way", + seat="economy", + passengers=Passengers(adults=2, children=1, infants_in_seat=0, infants_on_lap=0), + fetch_mode="fallback", +) + +print(result) + +# The price is currently... low/typical/high +print("The price is currently", result.flights) diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/uv.lock b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/uv.lock new file mode 100644 index 0000000..51cda95 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/backend/uv.lock @@ -0,0 +1,1620 @@ +version = 1 +revision = 2 +requires-python = 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"https://files.pythonhosted.org/packages/ea/1f/70c57b3d7278e94ed22d85e09685d3f0a38ebdd8c5c73b65ba4c0d0fe002/yarl-1.20.0-py3-none-any.whl", hash = "sha256:5d0fe6af927a47a230f31e6004621fd0959eaa915fc62acfafa67ff7229a3124", size = 46124, upload-time = "2025-04-17T00:45:12.199Z" }, +] diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/README.md b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/README.md new file mode 100644 index 0000000..e215bc4 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/README.md @@ -0,0 +1,36 @@ +This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). + +## Getting Started + +First, run the development server: + +```bash +npm run dev +# or +yarn dev +# or +pnpm dev +# or +bun dev +``` + +Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. + +You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. + +This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel. + +## Learn More + +To learn more about Next.js, take a look at the following resources: + +- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. +- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. + +You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome! + +## Deploy on Vercel + +The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. + +Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details. diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/auth/[...all]/route.ts b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/auth/[...all]/route.ts new file mode 100644 index 0000000..e4f441a --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/auth/[...all]/route.ts @@ -0,0 +1,4 @@ +import { auth } from "@/lib/auth"; + +export const GET = auth.handler; +export const POST = auth.handler; \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plan/submit/route.ts b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plan/submit/route.ts new file mode 100644 index 0000000..7bab46b --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plan/submit/route.ts @@ -0,0 +1,155 @@ +import { NextRequest, NextResponse } from 'next/server'; +import { prisma } from '@/lib/prisma'; + +interface TripFormData { + name: string; + destination: string; + startingLocation: string; + travelDates: { start: string; end: string }; + dateInputType: "picker" | "text"; + duration: number; + travelingWith: string; + adults: number; + children: number; + ageGroups: string[]; + budget: number; + budgetCurrency: string; + travelStyle: string; + budgetFlexible: boolean; + vibes: string[]; + priorities: string[]; + interests?: string; + rooms: number; + pace: number[]; + beenThereBefore?: string; + lovedPlaces?: string; + additionalInfo?: string; +} + +export async function POST(request: NextRequest) { + try { + const tripData: TripFormData = await request.json(); + + // Log the trip data for debugging + console.log('Received trip planning data:', JSON.stringify(tripData, null, 2)); + + // Validate required fields + if (!tripData.name || !tripData.destination || !tripData.startingLocation) { + return NextResponse.json( + { + success: false, + message: 'Missing required fields: name, destination, or starting location' + }, + { status: 400 } + ); + } + + // Save to database + const savedTripPlan = await prisma.tripPlan.create({ + data: { + name: tripData.name, + destination: tripData.destination, + startingLocation: tripData.startingLocation, + travelDatesStart: tripData.travelDates.start, + travelDatesEnd: tripData.travelDates.end || null, + dateInputType: tripData.dateInputType || "picker", + duration: tripData.duration || null, + travelingWith: tripData.travelingWith, + adults: tripData.adults || 1, + children: tripData.children || 0, + ageGroups: tripData.ageGroups || [], + budget: tripData.budget, + budgetCurrency: tripData.budgetCurrency || "USD", + travelStyle: tripData.travelStyle, + budgetFlexible: tripData.budgetFlexible || false, + vibes: tripData.vibes || [], + priorities: tripData.priorities || [], + interests: tripData.interests || null, + rooms: tripData.rooms || 1, + pace: tripData.pace || [3], + beenThereBefore: tripData.beenThereBefore || null, + lovedPlaces: tripData.lovedPlaces || null, + additionalInfo: tripData.additionalInfo || null, + // userId can be added later when auth is implemented + userId: null + } + }); + + console.log('Trip plan saved to database:', savedTripPlan.id); + + const requestBody = { + trip_plan_id: savedTripPlan.id, + travel_plan: { + name: tripData.name, + destination: tripData.destination, + starting_location: tripData.startingLocation, + travel_dates: { + start: tripData.travelDates.start, + end: tripData.travelDates.end || "" + }, + date_input_type: tripData.dateInputType, + duration: tripData.duration, + traveling_with: tripData.travelingWith, + adults: tripData.adults, + children: tripData.children, + age_groups: tripData.ageGroups, + budget: tripData.budget, + budget_currency: tripData.budgetCurrency, + travel_style: tripData.travelStyle, + budget_flexible: tripData.budgetFlexible, + vibes: tripData.vibes, + priorities: tripData.priorities, + interests: tripData.interests || "", + rooms: tripData.rooms, + pace: tripData.pace, + been_there_before: tripData.beenThereBefore || "", + loved_places: tripData.lovedPlaces || "", + additional_info: tripData.additionalInfo || "" + } + } + + console.log('Request body:', JSON.stringify(requestBody, null, 2)); + + // Call backend API to trigger trip planning + const backendResponse = await fetch(`${process.env.BACKEND_API_URL}/api/plan/trigger`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + }, + body: JSON.stringify(requestBody) + }); + + if (!backendResponse.ok) { + console.error('Backend API error:', await backendResponse.text()); + return NextResponse.json( + { + success: false, + message: 'Failed to trigger trip planning' + }, + { status: 500 } + ); + } + + const responseData = await backendResponse.json(); + console.log('Backend response:', JSON.stringify(responseData, null, 2)); + + return NextResponse.json( + { + success: true, + message: 'Trip planning triggered successfully', + response: responseData, + tripPlanId: savedTripPlan.id + }, + { status: 200 } + ); + } catch (error) { + console.error('Error processing trip submission:', error); + return NextResponse.json( + { + success: false, + message: 'Failed to save trip plan to database' + }, + { status: 500 } + ); + } +} \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/retry/route.ts b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/retry/route.ts new file mode 100644 index 0000000..a9d41dd --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/retry/route.ts @@ -0,0 +1,140 @@ +import { NextRequest, NextResponse } from 'next/server'; +import { prisma } from '@/lib/prisma'; + +export async function POST( + request: NextRequest, + { params }: { params: { id: string } } +) { + try { + const { id } = params; + + // First check if the plan exists + const tripPlan = await prisma.tripPlan.findUnique({ + where: { id }, + include: { + status: true, + output: true, + }, + }); + + if (!tripPlan) { + return NextResponse.json( + { + success: false, + message: 'Trip plan not found' + }, + { status: 404 } + ); + } + + // Update the status to pending/processing + await prisma.tripPlanStatus.upsert({ + where: { tripPlanId: id }, + update: { + status: 'processing', + currentStep: 'Restarting trip plan generation...', + }, + create: { + tripPlanId: id, + status: 'processing', + currentStep: 'Restarting trip plan generation...', + }, + }); + + // Prepare the request body for the backend API + const requestBody = { + trip_plan_id: id, + travel_plan: { + name: tripPlan.name, + destination: tripPlan.destination, + starting_location: tripPlan.startingLocation, + travel_dates: { + start: tripPlan.travelDatesStart, + end: tripPlan.travelDatesEnd || "" + }, + date_input_type: tripPlan.dateInputType, + duration: tripPlan.duration, + traveling_with: tripPlan.travelingWith, + adults: tripPlan.adults, + children: tripPlan.children, + age_groups: tripPlan.ageGroups, + budget: tripPlan.budget, + budget_currency: tripPlan.budgetCurrency, + travel_style: tripPlan.travelStyle, + budget_flexible: tripPlan.budgetFlexible, + vibes: tripPlan.vibes, + priorities: tripPlan.priorities, + interests: tripPlan.interests || "", + rooms: tripPlan.rooms, + pace: tripPlan.pace, + been_there_before: tripPlan.beenThereBefore || "", + loved_places: tripPlan.lovedPlaces || "", + additional_info: tripPlan.additionalInfo || "" + } + }; + + // Call backend API to trigger trip planning again + const backendResponse = await fetch(`${process.env.BACKEND_API_URL}/api/plan/trigger`, { + method: 'POST', + headers: { + 'Content-Type': 'application/json', + }, + body: JSON.stringify(requestBody) + }); + + if (!backendResponse.ok) { + // If backend call fails, update status back to failed + await prisma.tripPlanStatus.update({ + where: { tripPlanId: id }, + data: { + status: 'failed', + currentStep: 'Failed to restart trip plan generation', + }, + }); + + console.error('Backend API error:', await backendResponse.text()); + return NextResponse.json( + { + success: false, + message: 'Failed to retry trip planning' + }, + { status: 500 } + ); + } + + const responseData = await backendResponse.json(); + console.log('Backend retry response:', JSON.stringify(responseData, null, 2)); + + return NextResponse.json( + { + success: true, + message: 'Trip planning retry triggered successfully', + response: responseData + }, + { status: 200 } + ); + } catch (error) { + console.error('Error processing trip retry:', error); + + // Ensure we update the status to failed if there's an error + try { + await prisma.tripPlanStatus.update({ + where: { tripPlanId: params.id }, + data: { + status: 'failed', + currentStep: 'Error occurred while retrying', + }, + }); + } catch (statusError) { + console.error('Failed to update status after error:', statusError); + } + + return NextResponse.json( + { + success: false, + message: 'Failed to retry trip plan' + }, + { status: 500 } + ); + } +} \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/route.ts b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/route.ts new file mode 100644 index 0000000..2485e49 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/[id]/route.ts @@ -0,0 +1,101 @@ +import { NextResponse } from 'next/server'; +import { prisma } from '@/lib/prisma'; + +export async function GET( + request: Request, + { params }: { params: { id: string } } +) { + try { + const { id } = await params; + + const tripPlan = await prisma.tripPlan.findUnique({ + where: { id }, + include: { + status: true, + output: true, + }, + }); + + if (!tripPlan) { + return NextResponse.json( + { + success: false, + message: 'Trip plan not found' + }, + { status: 404 } + ); + } + + return NextResponse.json( + { + success: true, + tripPlan + }, + { status: 200 } + ); + } catch (error) { + console.error('Error fetching trip plan:', error); + return NextResponse.json( + { + success: false, + message: 'Failed to fetch trip plan' + }, + { status: 500 } + ); + } +} + +export async function DELETE( + request: Request, + { params }: { params: { id: string } } +) { + try { + const { id } = params; + + // First check if the plan exists + const tripPlan = await prisma.tripPlan.findUnique({ + where: { id }, + }); + + if (!tripPlan) { + return NextResponse.json( + { + success: false, + message: 'Trip plan not found' + }, + { status: 404 } + ); + } + + // Delete related records first (status and output) + await prisma.tripPlanStatus.deleteMany({ + where: { tripPlanId: id }, + }); + + await prisma.tripPlanOutput.deleteMany({ + where: { tripPlanId: id }, + }); + + // Delete the trip plan + await prisma.tripPlan.delete({ + where: { id }, + }); + + return NextResponse.json( + { + success: true, + message: 'Trip plan deleted successfully' + }, + { status: 200 } + ); + } catch (error) { + console.error('Error deleting trip plan:', error); + return NextResponse.json( + { + success: false, + message: 'Failed to delete trip plan' + }, + { status: 500 } + ); + } +} \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/route.ts b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/route.ts new file mode 100644 index 0000000..23343ec --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/api/plans/route.ts @@ -0,0 +1,29 @@ +import { NextResponse } from 'next/server'; +import { prisma } from '@/lib/prisma'; + +export async function GET() { + try { + const tripPlans = await prisma.tripPlan.findMany({ + orderBy: { + createdAt: 'desc' + } + }); + + return NextResponse.json( + { + success: true, + tripPlans + }, + { status: 200 } + ); + } catch (error) { + console.error('Error fetching trip plans:', error); + return NextResponse.json( + { + success: false, + message: 'Failed to fetch trip plans' + }, + { status: 500 } + ); + } +} \ No newline at end of file diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/auth/page.tsx b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/auth/page.tsx new file mode 100644 index 0000000..0c10770 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/auth/page.tsx @@ -0,0 +1,204 @@ +"use client"; + +import { useState } from "react"; +import { useRouter } from "next/navigation"; +import { authClient } from "@/lib/auth-client"; +import { Button } from "@/components/ui/button"; +import { + Card, + CardContent, + CardDescription, + CardHeader, + CardTitle, +} from "@/components/ui/card"; +import { Input } from "@/components/ui/input"; +import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"; +import { toast } from "sonner"; + +export default function AuthPage() { + const [isLoading, setIsLoading] = useState(false); + const [formData, setFormData] = useState({ + name: "", + email: "", + password: "", + }); + const router = useRouter(); + + function handleInputChange(field: string, value: string) { + setFormData((prev) => ({ ...prev, [field]: value })); + } + + async function handleSignIn(e: React.FormEvent) { + e.preventDefault(); + setIsLoading(true); + + try { + const result = await authClient.signIn.email({ + email: formData.email, + password: formData.password, + }); + + if (result.error) { + toast.error(result.error.message || "Failed to sign in"); + return; + } + + toast.success("Welcome back! Redirecting to your dashboard..."); + router.push("/plan"); + } catch (error) { + toast.error("An unexpected error occurred"); + console.error("Sign in failed:", error); + } finally { + setIsLoading(false); + } + } + + async function handleSignUp(e: React.FormEvent) { + e.preventDefault(); + setIsLoading(true); + + try { + const result = await authClient.signUp.email({ + email: formData.email, + password: formData.password, + name: formData.name, + }); + + if (result.error) { + toast.error(result.error.message || "Failed to create account"); + return; + } + + toast.success("Account created successfully! Redirecting..."); + router.push("/plan"); + } catch (error) { + toast.error("An unexpected error occurred"); + console.error("Sign up failed:", error); + } finally { + setIsLoading(false); + } + } + + return ( +

+ + + + Welcome + + + Sign in to your account or create a new one + + + + + + Sign In + Sign Up + + + +
+
+ + handleInputChange("email", e.target.value)} + required + /> +
+
+ + + handleInputChange("password", e.target.value) + } + required + /> +
+ +
+ + + +
+
+ + handleInputChange("name", e.target.value)} + required + /> +
+
+ + handleInputChange("email", e.target.value)} + required + /> +
+
+ + + handleInputChange("password", e.target.value) + } + required + /> +
+ +
+ + + + +
+ ); +} diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/favicon.ico b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/favicon.ico new file mode 100644 index 0000000..718d6fe Binary files /dev/null and b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/favicon.ico differ diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/globals.css b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/globals.css new file mode 100644 index 0000000..ce0411b --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/globals.css @@ -0,0 +1,198 @@ +@import "tailwindcss"; +@import "tw-animate-css"; + +@custom-variant dark (&:is(.dark *)); + +@theme inline { + --color-background: var(--background); + --color-foreground: var(--foreground); + --font-sans: DM Sans, sans-serif; + --font-mono: Space Mono, monospace; + --color-sidebar-ring: var(--sidebar-ring); + --color-sidebar-border: var(--sidebar-border); + --color-sidebar-accent-foreground: var(--sidebar-accent-foreground); + --color-sidebar-accent: var(--sidebar-accent); + --color-sidebar-primary-foreground: var(--sidebar-primary-foreground); + --color-sidebar-primary: var(--sidebar-primary); + --color-sidebar-foreground: var(--sidebar-foreground); + --color-sidebar: var(--sidebar); + --color-chart-5: var(--chart-5); + --color-chart-4: var(--chart-4); + --color-chart-3: var(--chart-3); + --color-chart-2: var(--chart-2); + --color-chart-1: var(--chart-1); + --color-ring: var(--ring); + --color-input: var(--input); + --color-border: var(--border); + --color-destructive: var(--destructive); + --color-accent-foreground: var(--accent-foreground); + --color-accent: var(--accent); + --color-muted-foreground: var(--muted-foreground); + --color-muted: var(--muted); + --color-secondary-foreground: var(--secondary-foreground); + --color-secondary: var(--secondary); + --color-primary-foreground: var(--primary-foreground); + --color-primary: var(--primary); + --color-popover-foreground: var(--popover-foreground); + --color-popover: var(--popover); + --color-card-foreground: var(--card-foreground); + --color-card: var(--card); + --radius-sm: calc(var(--radius) - 4px); + --radius-md: calc(var(--radius) - 2px); + --radius-lg: var(--radius); + --radius-xl: calc(var(--radius) + 4px); + --font-serif: ui-serif, Georgia, Cambria, "Times New Roman", Times, serif; + --radius: 0px; + --tracking-tighter: calc(var(--tracking-normal) - 0.05em); + --tracking-tight: calc(var(--tracking-normal) - 0.025em); + --tracking-wide: calc(var(--tracking-normal) + 0.025em); + --tracking-wider: calc(var(--tracking-normal) + 0.05em); + --tracking-widest: calc(var(--tracking-normal) + 0.1em); + --tracking-normal: var(--tracking-normal); + --shadow-2xl: var(--shadow-2xl); + --shadow-xl: var(--shadow-xl); + --shadow-lg: var(--shadow-lg); + --shadow-md: var(--shadow-md); + --shadow: var(--shadow); + --shadow-sm: var(--shadow-sm); + --shadow-xs: var(--shadow-xs); + --shadow-2xs: var(--shadow-2xs); + --spacing: var(--spacing); + --letter-spacing: var(--letter-spacing); + --shadow-offset-y: var(--shadow-offset-y); + --shadow-offset-x: var(--shadow-offset-x); + --shadow-spread: var(--shadow-spread); + --shadow-blur: var(--shadow-blur); + --shadow-opacity: var(--shadow-opacity); + --color-shadow-color: var(--shadow-color); + --color-destructive-foreground: var(--destructive-foreground); +} + +:root { + --radius: 0px; + --background: oklch(1 0 0); + --foreground: oklch(0 0 0); + --card: oklch(1 0 0); + --card-foreground: oklch(0 0 0); + --popover: oklch(1 0 0); + --popover-foreground: oklch(0 0 0); + --primary: oklch(0.6489 0.237 26.9728); + --primary-foreground: oklch(1 0 0); + --secondary: oklch(0.968 0.211 109.7692); + --secondary-foreground: oklch(0 0 0); + --muted: oklch(0.9551 0 0); + --muted-foreground: oklch(0.3211 0 0); + --accent: oklch(0.5635 0.2408 260.8178); + --accent-foreground: oklch(1 0 0); + --destructive: oklch(0 0 0); + --border: oklch(0 0 0); + --input: oklch(0 0 0); + --ring: oklch(0.6489 0.237 26.9728); + --chart-1: oklch(0.6489 0.237 26.9728); + --chart-2: oklch(0.968 0.211 109.7692); + --chart-3: oklch(0.5635 0.2408 260.8178); + --chart-4: oklch(0.7323 0.2492 142.4953); + --chart-5: oklch(0.5931 0.2726 328.3634); + --sidebar: oklch(0.9551 0 0); + --sidebar-foreground: oklch(0 0 0); + --sidebar-primary: oklch(0.6489 0.237 26.9728); + --sidebar-primary-foreground: oklch(1 0 0); + --sidebar-accent: oklch(0.5635 0.2408 260.8178); + --sidebar-accent-foreground: oklch(1 0 0); + --sidebar-border: oklch(0 0 0); + --sidebar-ring: oklch(0.6489 0.237 26.9728); + --destructive-foreground: oklch(1 0 0); + --font-sans: DM Sans, sans-serif; + --font-serif: ui-serif, Georgia, Cambria, "Times New Roman", Times, serif; + --font-mono: Space Mono, monospace; + --shadow-color: hsl(0 0% 0%); + --shadow-opacity: 1; + --shadow-blur: 0px; + --shadow-spread: 0px; + --shadow-offset-x: 4px; + --shadow-offset-y: 4px; + --letter-spacing: 0em; + --spacing: 0.25rem; + --shadow-2xs: 4px 4px 0px 0px hsl(0 0% 0% / 0.5); + --shadow-xs: 4px 4px 0px 0px hsl(0 0% 0% / 0.5); + --shadow-sm: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 1px 2px -1px hsl(0 0% 0% / 1); + --shadow: 4px 4px 0px 0px hsl(0 0% 0% / 1), 4px 1px 2px -1px hsl(0 0% 0% / 1); + --shadow-md: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 2px 4px -1px hsl(0 0% 0% / 1); + --shadow-lg: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 4px 6px -1px hsl(0 0% 0% / 1); + --shadow-xl: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 8px 10px -1px hsl(0 0% 0% / 1); + --shadow-2xl: 4px 4px 0px 0px hsl(0 0% 0% / 2.5); + --tracking-normal: 0em; +} + +.dark { + --background: oklch(0 0 0); + --foreground: oklch(1 0 0); + --card: oklch(0.3211 0 0); + --card-foreground: oklch(1 0 0); + --popover: oklch(0.3211 0 0); + --popover-foreground: oklch(1 0 0); + --primary: oklch(0.7044 0.1872 23.1858); + --primary-foreground: oklch(0 0 0); + --secondary: oklch(0.9691 0.2005 109.6228); + --secondary-foreground: oklch(0 0 0); + --muted: oklch(0.3211 0 0); + --muted-foreground: oklch(0.8452 0 0); + --accent: oklch(0.6755 0.1765 252.2592); + --accent-foreground: oklch(0 0 0); + --destructive: oklch(1 0 0); + --border: oklch(1 0 0); + --input: oklch(1 0 0); + --ring: oklch(0.7044 0.1872 23.1858); + --chart-1: oklch(0.7044 0.1872 23.1858); + --chart-2: oklch(0.9691 0.2005 109.6228); + --chart-3: oklch(0.6755 0.1765 252.2592); + --chart-4: oklch(0.7395 0.2268 142.8504); + --chart-5: oklch(0.6131 0.2458 328.0714); + --sidebar: oklch(0 0 0); + --sidebar-foreground: oklch(1 0 0); + --sidebar-primary: oklch(0.7044 0.1872 23.1858); + --sidebar-primary-foreground: oklch(0 0 0); + --sidebar-accent: oklch(0.6755 0.1765 252.2592); + --sidebar-accent-foreground: oklch(0 0 0); + --sidebar-border: oklch(1 0 0); + --sidebar-ring: oklch(0.7044 0.1872 23.1858); + --destructive-foreground: oklch(0 0 0); + --radius: 0px; + --font-sans: DM Sans, sans-serif; + --font-serif: ui-serif, Georgia, Cambria, "Times New Roman", Times, serif; + --font-mono: Space Mono, monospace; + --shadow-color: hsl(0 0% 0%); + --shadow-opacity: 1; + --shadow-blur: 0px; + --shadow-spread: 0px; + --shadow-offset-x: 4px; + --shadow-offset-y: 4px; + --letter-spacing: 0em; + --spacing: 0.25rem; + --shadow-2xs: 4px 4px 0px 0px hsl(0 0% 0% / 0.5); + --shadow-xs: 4px 4px 0px 0px hsl(0 0% 0% / 0.5); + --shadow-sm: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 1px 2px -1px hsl(0 0% 0% / 1); + --shadow: 4px 4px 0px 0px hsl(0 0% 0% / 1), 4px 1px 2px -1px hsl(0 0% 0% / 1); + --shadow-md: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 2px 4px -1px hsl(0 0% 0% / 1); + --shadow-lg: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 4px 6px -1px hsl(0 0% 0% / 1); + --shadow-xl: 4px 4px 0px 0px hsl(0 0% 0% / 1), + 4px 8px 10px -1px hsl(0 0% 0% / 1); + --shadow-2xl: 4px 4px 0px 0px hsl(0 0% 0% / 2.5); +} + +@layer base { + * { + @apply border-border outline-ring/50; + } + body { + @apply bg-background text-foreground; + letter-spacing: var(--tracking-normal); + } +} diff --git a/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/layout.tsx b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/layout.tsx new file mode 100644 index 0000000..4363859 --- /dev/null +++ b/advanced_ai_agents/multi_agent_apps/agent_teams/ai_travel_planner_agent_team/client/app/layout.tsx @@ -0,0 +1,33 @@ +import type { Metadata } from "next"; +import { DM_Sans } from "next/font/google"; +import "./globals.css"; +import Header from "@/components/header"; +import Footer from "@/components/footer"; +import { Toaster } from "@/components/ui/sonner"; + +const dmSans = DM_Sans({ + variable: "--font-dm-sans", + subsets: ["latin"], +}); + +export const metadata: Metadata = { + title: "TripCraft AI", + description: "Your Journey, Perfectly Crafted with Intelligence", +}; + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + +
+ {children} +