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

# Dappier

> Real-time web and content search for agents

Dappier is a real time search that connects any AI to proprietary, real-time data — including web search, news, sports, stock market data, and premium publisher content.

## Description

Dappier Real-Time Search provides instant access to live web search results and AI-powered recommendations with:

* Real-Time Web Search offering up-to-the-minute results from Google, financial markets, and global news
* Specialized Content Models trained on curated datasets for domains like sports, lifestyle, pet care, sustainability, and multicultural news
* Intelligent Query Routing that automatically selects the appropriate model based on user input

### Core Features:

* Web Search - Perform real-time web lookups across news, stocks, travel, weather, and more
* Stock Market Data - Retrieve live financial news, stock prices, and trades
* Content Recommendations - Get semantically matched articles tailored to user interests
* Domain-Specific Models - Specialized AI trained on lifestyle, pets, sports, and green living

### Output Formats:

* Summarized real-time search results
* Curated lists of recommended articles
* Live financial and stock market insights
* Structured query-to-content responses

## Available Models and Functions

> Explore various AI models and data models available at [Dappier Marketplace](https://marketplace.dappier.com/marketplace).

### AI Models

| Function                   | Model                           | Description                                                                             | Arguments    |
| :------------------------- | :------------------------------ | :-------------------------------------------------------------------------------------- | :----------- |
| `real_time_web_search`     | `am_01j06ytn18ejftedz6dyhz2b15` | Perform a real-time web search across Google, news, weather, and travel data.           | `query: str` |
| `stock_market_data_search` | `am_01j749h8pbf7ns8r1bq9s2evrh` | Perform a real-time stock market data search including stock prices and financial news. | `query: str` |

### Data Models

| Function                  | Model                           | Description                                                                         | Arguments                                                                                                                                                                        |
| :------------------------ | :------------------------------ | :---------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `get_sports_news`         | `dm_01j0pb465keqmatq9k83dthx34` | Get real-time sports news and updates from top sports sources.                      | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |
| `get_lifestyle_news`      | `dm_01j0q82s4bfjmsqkhs3ywm3x6y` | Access real-time lifestyle news and insights from popular publications.             | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |
| `get_iheartdogs_content`  | `dm_01j1sz8t3qe6v9g8ad102kvmqn` | Fetch dog care articles on health, behavior, and grooming from iHeartDogs.          | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |
| `get_iheartcats_content`  | `dm_01j1sza0h7ekhaecys2p3y0vmj` | Fetch cat care content on health, lifestyle, and behavior from iHeartCats.          | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |
| `get_greenmonster_guides` | `dm_01j5xy9w5sf49bm6b1prm80m27` | Access eco-conscious lifestyle articles from GreenMonster.                          | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |
| `get_wishtv_news`         | `dm_01jagy9nqaeer9hxx8z1sk1jx6` | Get news updates on politics, entertainment, and multicultural topics from WISH-TV. | `query: str`, `similarity_top_k: int`, `ref: Optional[str]`, `num_articles_ref: int`, `search_algorithm: Literal["most_recent", "semantic", "most_recent_semantic", "trending"]` |

## Installation

```bash theme={null}
agentstack tools add dappier
```

Set the environment variable

```env theme={null}
DAPPIER_API_KEY=...
```

## Usage

Dappier can be configured for different behaviors by modifying `src/tools/dappier_tool.py`.