# Replit
Source: https://docs.dappier.com/integrations/replit-integration



Idea to app, fast. Create beautiful, modern web applications at the speed of thought. Describe what you need and Replit's AI Agent builds it for you. Create & deploy websites, automations, internal tools, data pipelines and more in any programming language without setup, downloads or extra tools. All in a single cloud workspace with AI built in.

These below apps provide example projects and pre-built templates to help developers quickly integrate Dappier’s RAG models and build applications with ease in Replit's environment.

## Dappier Python Real Time Data

This template demonstrates how to use Dappier's Real Time Data models in a Python project. You can check out the app on Replit here:

[Check out the app on Replit](https://replit.com/@dappier/Dappier-Python-Real-Time-Data?v=1)

## 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/Gy8z_tlS0Vw?si=m6gggNNtDzQHEVs_" 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 />

## Getting Started

1. **Sign up for a Dappier account:** [https://platform.dappier.com/sign-in](https://platform.dappier.com/sign-in)
2. **Create an API key:**
   * Go to your profile and click "API Keys"
   * Click "Create API key"
3. **Add the API key as a secret in Replit:**
   * Go to the Secrets Tool
   * Add a new secret called `DAPPIER_API_KEY` and paste your API key
4. **Run the code:**
   * Click the "Run" button in the top right corner

## Usage

```python Python theme={null}
response = app.search_real_time_data(
   query="What is the stock price of Apple ?",
   ai_model_id="am_01j06ytn18ejftedz6dyhz2b15"
)
```

## Parameters

#### `query` (str):

* The user-provided query. Examples include:
  * `"How is the weather today in Austin, TX?"`
  * `"What is the latest news for Meta?"`
  * `"What is the stock price for AAPL?"`

#### `ai_model_id` (str):

* The AI model ID to use for the query.
* AI model IDs always start with the prefix `"am_"`.
* Multiple AI model IDs are available, which can be found at [Dappier marketplace.](https://platform.dappier.com/marketplace)

***

## Dappier Python AI Recommendations

This template demonstrates how to use Dappier's AI Recommendations models in a Python project. Check out the app on Replit here:

[Check out the app on Replit](https://replit.com/@dappier/Dappier-Python-AI-Recommendations?v=1)

## 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/M_5qixzR4zI?si=UwXLe3c1TGWNwTTy" 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 />

## Getting Started

1. **Sign up for a Dappier account:** [https://platform.dappier.com/sign-in](https://platform.dappier.com/sign-in)
2. **Create an API key:**
   * Go to your profile and click "API Keys"
   * Click "Create API key"
3. **Add the API key as a secret in Replit:**
   * Go to the Secrets Tool
   * Add a new secret called `DAPPIER_API_KEY` and paste your API key
4. **Run the code:**
   * Click the "Run" button in the top right corner

## Usage

```python Python theme={null}
response = app.get_ai_recommendations(
    query="latest sports news",
    data_model_id="dm_01j0pb465keqmatq9k83dthx34",
    similarity_top_k=5,
    ref="sportsnaut.com",
    num_articles_ref=2,
    search_algorithm="most_recent"
)
```

### Parameters

#### `query` (str):

* The user query for retrieving recommendations.

#### `data_model_id` (str):

* The data model ID to use for recommendations.
* Data model IDs always start with the prefix `"dm_"`.

#### `similarity_top_k` (int) *Optional*:

* The number of top documents to retrieve based on similarity.
* Defaults to `9`.

#### `ref` (str) *Optional*:

* The site domain where AI recommendations should be displayed.
* Defaults to `None`.

#### `num_articles_ref` (int) *Optional*:

* The minimum number of articles to return from the specified reference domain (`ref`).
* The remaining articles will come from other sites in the RAG model.
* Defaults to `0`.

#### `search_algorithm` (str) *Optional*:

* The search algorithm to use for retrieving articles.
* Options:
  * `"most_recent"` (default),
  * `"semantic"`,
  * `"most_recent_semantic"`,
  * `"trending"`.

***