> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dappier.com/llms.txt
> Use this file to discover all available pages before exploring further.

# 🕵🏻 Building an AI-Powered Travel Itinerary Assistant using OpenAI Agents SDK and Dappier

You can also check this cookbook in colab [here](https://colab.research.google.com/drive/1HVMyM-O5KviSBXO56H6_ssQLH1C9okFN?usp=sharing)

## Introduction

This notebook provides a **step-by-step guide** to building an **AI-powered travel assistant** using **OpenAI's Agents SDK** and **Dappier**. The assistant generates a **real-time travel itinerary** based on user input, fetching **weather updates, live events, and hotel deals** dynamically.

## Watch the Video Guide

If you prefer a visual walkthrough, check out the accompanying video guide below:

<iframe width="560" height="315" src="https://www.youtube.com/embed/4aU8BK8pfmU?si=bEgCtPqcQmFLZIsu" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen />

## OpenAI Agents SDK

The OpenAI Agents SDK enables you to build **agentic AI applications** with a **lightweight and production-ready** API.

It consists of:

* **Agents** – LLMs equipped with instructions and tools
* **Handoffs** – Delegation of tasks to specialized agents
* **Guardrails** – Input validation for enhanced reliability

The SDK also provides **built-in tracing** for debugging and evaluation, making **AI-powered workflows easy to build and scale**.

***

## Dappier

Dappier is a **real-time AI data platform** that connects **LLMs and AI agents** to **rights-cleared data from trusted sources**.

It specializes in **web search, finance, news, and live events**, ensuring AI applications can **access up-to-date and verified information** without hallucinations.

***

## Install Dependencies

```bash theme={null}
!pip install openai-agents dappier colorama nest-asyncio
```

***

## Import Required Libraries

```python Python theme={null}
import os
import getpass
import nest_asyncio
import asyncio
from agents import Agent, FunctionTool, Runner, function_tool
from colorama import Fore, Style
from dappier import Dappier
from openai.types.responses import ResponseTextDeltaEvent
```

***

## Set Up API Keys Securely

To prevent **exposing API keys in shared environments**, use **getpass** to enter them securely.

```python Python theme={null}
os.environ["DAPPIER_API_KEY"] = getpass.getpass("Enter your Dappier API Key: ")
os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter your OpenAI API Key: ")
```

Initialize Dappier Client:

```python Python theme={null}
dappier_client = Dappier(api_key=os.environ["DAPPIER_API_KEY"])
```

Enable **tracing for OpenAI Agents SDK**:

```python Python theme={null}
from agents import set_tracing_export_api_key

set_tracing_export_api_key(os.environ["OPENAI_API_KEY"])
```

***

## Define AI Functions for Real-Time Data Fetching

### Fetching Real-Time Search Results

This function fetches real-time search results from Dappier based on the user's query.

```python Python theme={null}
# Define Real-Time Search Function
@function_tool
def dappier_real_time_search(query: str, ai_model_id: str) -> str:
    """Fetches real-time search results from Dappier based on the user's query.

    Args:
        query (str): The user's query for real-time data.
        ai_model_id (str): The AI model ID to use for the query, dynamically set by the agent.
            Possible values:
            - "am_01j0rzq4tvfscrgzwac7jv1p4c" (General real-time web search, including news, weather, and events.)
            - "am_01j749h8pbf7ns8r1bq9s2evrh" (Stock market data with real-time financial news and stock prices.)

    Returns:
        str: A response message containing the real-time data results.
    """
    print(Fore.RED + f"CALLING TOOL - dappier_real_time_search: {ai_model_id}\n" + Style.RESET_ALL)
    print(Fore.GREEN + f"Query: {query}\n" + Style.RESET_ALL)
    response = dappier_client.search_real_time_data(query=query, ai_model_id=ai_model_id)
    return response.message if response else "No real-time data found."
```

### Fetching AI-Powered Recommendations

This function fetches AI-powered content recommendations from Dappier based on the user's query

```python Python theme={null}
# Define AI Recommendations Function
@function_tool
def dappier_ai_recommendations(query: str, data_model_id: str) -> str:
    """Fetches AI-powered content recommendations from Dappier based on the user's query.

    Args:
        query (str): The user's query for recommendations.
        data_model_id (str): The Data Model ID to use for the query, dynamically set by the agent.
            Possible values:
            - "dm_01j0pb465keqmatq9k83dthx34" (Sports news)
            - "dm_01j0q82s4bfjmsqkhs3ywm3x6y" (Lifestyle news)
            - "dm_01j1sz8t3qe6v9g8ad102kvmqn" (Dog care advice from iHeartDogs)
            - "dm_01j1sza0h7ekhaecys2p3y0vmj" (Cat care advice from iHeartCats)
            - "dm_01j5xy9w5sf49bm6b1prm80m27" (Eco-friendly content from GreenMonster)
            - "dm_01jagy9nqaeer9hxx8z1sk1jx6" (General news from WISH-TV)
            - "dm_01jhtt138wf1b9j8jwswye99y5" (Local news from 9 and 10 News)

    Returns:
        str: A formatted response containing AI-powered recommendations.
    """
    print(Fore.RED + f"CALLING TOOL: dappier_ai_recommendations: {data_model_id}\n" + Style.RESET_ALL)
    print(Fore.GREEN + f"Query: {query}\n" + Style.RESET_ALL)
    response = dappier_client.get_ai_recommendations(query=query, data_model_id=data_model_id, similarity_top_k=5)
    results = response.response.results
    formatted_text = ""
    for result in results:
        formatted_text += (f"Title: {result.title}\n"
                           f"Author: {result.author}\n"
                           f"Published on: {result.pubdate}\n"
                           f"URL: {result.source_url}\n"
                           f"Image URL: {result.image_url}\n"
                           f"Summary: {result.summary}\n\n")
    return formatted_text or "No recommendations found."
```

***

## Create AI Agent

This AI agent will **determine whether to fetch real-time search results or AI recommendations** based on the user's query.

```python Python theme={null}
agent = Agent(
    name="Dappier Assistant",
    instructions="""
    You analyze the user's query and determine whether to use real-time search or AI recommendations.
    If the query involves stocks, finance, or current events, use `dappier_real_time_search`.
    If the query is about recommendations (e.g., news, lifestyle, sports, pets), use `dappier_ai_recommendations`.
    You MUST provide `ai_model_id` or `data_model_id` as necessary.
    Format responses in structured Markdown.
    """,
    tools=[dappier_real_time_search, dappier_ai_recommendations],
)
```

***

## Generate Task Prompt

A **function to dynamically generate a task prompt** based on the user's travel details.

```python Python theme={null}
def generate_task_prompt(travel_city: str, travel_date: str, num_days: str) -> str:
    return f"""Generate a {num_days}-day travel itinerary for {travel_city}, tailored to the real-time weather forecast for the selected date: {travel_date}. Follow these steps:

        Determine Current Date and Travel Period:
        Use Dappier's real-time search to identify the current date and calculate the trip duration based on user input.

        Fetch LifeStyle News:
        Retrieve LifeStyle news using Dappier AI Recommendations API for the given date and provide insight to the user.

        Fetch Weather Data:
        Retrieve the weather forecast for {travel_city} during the selected dates to understand the conditions for each day.

        Fetch Live Events Data:
        Use Dappier's real-time search to find live events happening in {travel_city} during the trip dates.

        Fetch Hotel Deals Data:
        Use Dappier's real-time search to find the best hotel deals with booking links in {travel_city} during the trip dates.

        Design the Itinerary:
        Use the weather insights, live events, hotel deals to plan activities and destinations that suit the expected conditions. For each suggested location:

        Output:
        Present latest life style news at first then. Present a detailed {num_days}-day itinerary, including timing, activities, booking links, weather information for each day and travel considerations. Ensure the plan is optimized for convenience and enjoyment.
    """
```

***

## Get User Input and Run AI Agent

This function **collects user input dynamically**, generates the **task prompt**, and executes the AI agent **asynchronously**.

```python Python theme={null}
async def main():
    """Asks user for travel details dynamically and executes AI agent"""

    # Ask for travel details dynamically
    travel_city = input("Enter the city you want to travel to: ")
    travel_date = input("Enter the start date of your travel (YYYY-MM-DD): ")
    num_days = input("Enter the number of days for your trip: ")

    # Generate task prompt
    task_prompt = generate_task_prompt(travel_city, travel_date, num_days)

    print(Fore.BLUE + f"\nExecuting AI Agent with prompt:\n{task_prompt}" + Style.RESET_ALL)

    # Execute AI agent with streaming results
    result = Runner.run_streamed(agent, task_prompt)

    print("\n\n=== Streaming Start ===\n\n")

    async for event in result.stream_events():
        if event.type == "raw_response_event" and isinstance(event.data, ResponseTextDeltaEvent):
            print(event.data.delta, end="", flush=True)

    print("\n\n=== Streaming Complete ===")

# Execute main function
asyncio.run(main())
```

```json theme={null}
Enter the city you want to travel to: Paris
Enter the start date of your travel: 01, April 2025
Enter the number of days for your trip: 5

ORIGINAL PROMPT: Generate a 5-day travel itinerary for Paris, tailored to the real-time weather forecast for the selected date: 01, April 2025. Follow these steps:

Determine Current Date and Travel Period:
Use Dappier's real-time search to identify the current date and calculate the trip duration based on user input.

Fetch LifeStyle News:
Retrieve LifeStyle news using Dappier AI Recommendations API for the given date and provide insight to the user.

Fetch Weather Data:
Retrieve the weather forecast for Paris during the selected dates to understand the conditions for each day.

Fetch Live Events Data:
Use Dappier's real-time search to find live events happening in Paris during the trip dates.

Fetch Hotel Deals Data:
Use Dappier's real-time search to find the best hotel deals with booking links in Paris during the trip dates.

Design the Itinerary:
Use the weather insights, live events, hotel deals to plan activities and destinations that suit the expected conditions. For each suggested location:

Output:
Present latest life style news at first then. Present a detailed 5-day itinerary, including timing, activities, booking links, weather information for each day and travel considerations. Ensure the plan is optimized for convenience and enjoyment.



=== Streaming Start ===


CALLING TOOL - dappier_real_time_search: am_01j0rzq4tvfscrgzwac7jv1p4c

Query: current date

CALLING TOOL: dappier_ai_recommendations: dm_01j0q82s4bfjmsqkhs3ywm3x6y

Query: Paris lifestyle news

CALLING TOOL - dappier_real_time_search: am_01j0rzq4tvfscrgzwac7jv1p4c

Query: Paris weather April 1-5, 2025

CALLING TOOL - dappier_real_time_search: am_01j0rzq4tvfscrgzwac7jv1p4c

Query: Paris live events April 1-5, 2025

CALLING TOOL - dappier_real_time_search: am_01j0rzq4tvfscrgzwac7jv1p4c

Query: Paris hotel deals April 1-5, 2025

### Latest Lifestyle News Highlights

#### Justin Bieber's Heartfelt Message
- **Title:** Christian Singer Justin Bieber, 31, Issues Heartbreaking Message To Fans Amidst Concerns For His Wellbeing
- **Summary:** Justin Bieber addresses mental health struggles in a candid message to fans, sharing feelings of inadequacy despite his fame.
- **Link:** [Read more](https://www.themix.net/celebrity/celebrity-news/christian-singer-justin-bieber-31-issues-heartbreaking-message-to-fans-amidst-concerns-for-his-wellbeing/)

#### Controversies in Disney's Live-Action Snow White
- **Title:** Live-Action Snow White Continues to Have Issues as Disney Scales Back Premiere
- **Summary:** Disney's adaptation faces hurdles and mixed reactions due to casting choices and character portrayal.
- **Link:** [Read more](https://www.themix.net/movies/movie-news/live-action-snow-white-continues-to-have-issues-as-disney-scales-back-premiere/)

#### Family-Favorite Baked Ziti Recipe
- **Title:** Family-Favorite Baked Ziti: Simple, Satisfying, and Oh-So-Good
- **Summary:** Discover a delicious and easy-to-make baked ziti recipe that's perfect for family gatherings.
- **Link:** [Read more](https://www.familyproof.com/lifestyle/food-drink/baked-ziti/)

### 5-Day Paris Travel Itinerary (April 1-5, 2025)

#### Weather Overview
- **April 1-5:** Mild temperatures (12-14°C / 54-57°F), partly cloudy. Ideal for outdoor activities and exploration.

#### Day 1: Explore Paris and Join the Marathon
- **Morning:** Breakfast at Café de Flore. Explore Saint-Germain-des-Prés.
- **Afternoon:** Participate or watch the Paris Marathon. Visit Eiffel Tower post-event.
- **Evening:** Dinner at Le Jules Verne with Eiffel Tower views.

#### Day 2: Art and Design Immersion
- **Morning:** Visit Pad Paris - Art + Design Fair.
- **Afternoon:** Explore the Art Paris Art Fair at Grand Palais.
- **Evening:** Candlelight concert at Sainte-Chapelle. Book [here](https://linkparis.com).

#### Day 3: Cultural Experiences
- **Morning:** Tour the Louvre Museum. Don’t miss the Mona Lisa and other major works.
- **Afternoon:** Lunch at Angelina’s. Discover Musée d'Orsay's art.
- **Evening:** Dinner at a local bistro in Montmartre.

#### Day 4: Scenic Views and Relaxation
- **Morning:** Visit Palais Garnier and take a guided tour.
- **Afternoon:** Enjoy a Seine River Cruise with lunch.
- **Evening:** Explore Le Marais district. Dinner at Chez Janou.

#### Day 5: Quirky Fun and Departure
- **Morning:** Participate in International Pillow Fight Day.
- **Afternoon:** Last-minute shopping at Galeries Lafayette.
- **Evening:** Departure preparation. Stay at Mercari Hotel ([Booking Link](https://www.mercari.com/us/item/m11634459421/)).

### Hotel Deals
- **Stay Option:** 5-Day, 4-Night Package at $1,750 from [LinkParis](https://linkparis.com/5-day-trip-to-paris/).
- **Alternative Stay:** Hotel rooms starting at $120 through [Mercari](https://www.mercari.com/us/item/m11634459421/).

Experience a mix of culture, relaxation, and excitement in Paris. Enjoy your trip! 🇫🇷✨

=== Streaming Complete ===
```

***

## Conclusion

This notebook provides a structured guide to building an AI-powered **travel itinerary assistant** using **OpenAI Agents SDK** and **Dappier**.

It covers:

* **Secure API key storage** using `getpass`
* **Real-time data retrieval** for weather, events, and hotels
* **AI-powered recommendations** for lifestyle insights
* **An agent-driven workflow** to generate structured travel plans

This AI assistant can be extended further by integrating **flight search APIs, restaurant recommendations**, and **personalized travel preferences**.