dappier-py 0.2.0

Dappier Python SDK for interacting with Dappier APIs

Dappier Python SDK

Python SDK for interacting with Dappier's API's.

Overview

dappier-py provides a straightforward way to interact with Dappier's API's, which allows for real-time data search on the internet and other datamodels from the marketplace. The library is designed to be easy to use and integrate into existing Python projects.

Installation

To install the package, run:

pip install dappier

Alternatively, you can clone the repository and install the dependencies:

git clone https://github.com/DappierAI/dappier-py
cd dappier-py
pip install -r requirements.txt

Initialization

You can get your API key from your Dappier account.

from dappier.dappier import DappierApp

app = DappierApp(api_key='your_api_key')

Real-Time Search

You can perform a real-time search by providing a query. This will search for real-time data related to your query.

result = app.realtime_search_api("When is the next election?")
print(result.response['response']["results"])

AI Recommendations

The AI Recommendations feature allows you to query for articles and other content using a specific data model. You can pick a specific datamodel from marketplace

Default Options:

ai_result = app.ai_recommendations(query="latest tech news", datamodel_id="dm_02hr75e8ate6adr15hjrf3ikol")
print(ai_result.results)

Custom Options:

You can pass custom parameters such as similarity_top_k, ref and num_articles_ref:

ai_custom_result = app.ai_recommendations(
    query="latest tech news", 
    datamodel_id="dm_02hr75e8ate6adr15hjrf3ikol", 
    similarity_top_k=5, 
    ref="techcrunch.com", 
    num_articles_ref=2
)
print(ai_custom_result.results)

Search API

You can also perform a search using a specific datamodel_id. This method allows users to input custom queries and retrieve data based on the datamodel provided.

search_result = app.search(
    query="Latest Microsoft News",
    datamodel_id="dm_01htjq2njgecvah7ncepm8v87y",
    similarity_top_k=6,
    ref="familyproof.com",
    num_articles_ref=3
)
print(search_result.results)

Checkout (example.py)[https://github.com/DappierAI/dappier-py] in this repository for a working example.