Dappier Tools
Dappier is a platform that connects LLMs and Agentic AI agents to real-time, rights-cleared data from trusted sources, including web search, finance, and news. By providing enriched, prompt-ready data, Dappier empowers AI with verified and up-to-date information for a wide range of applications. Explore a wide range of data models in our marketplace at marketplace.dappier.com.
Overview
This package provides two tool specs:
-
DappierRealTimeSearchToolSpec: A powerful API-driven tool designed to fetch up-to-the-minute information from various sources, including real-time web search results, stock market data, news, weather, travel deals and much more.
-
DappierAIRecommendationsToolSpec: Provides AI-powered content recommendations across a range of domains including sports news, lifestyle news, pet care content from iHeartDogs and iHeartCats, compassionate living from GreenMonster, and local news from WISH-TV and 9&10 News.
Key Features
Real Time Search Tool
-
Real-Time Web Search: Fetches the latest news, weather updates, travel deals, and other relevant web content through AI-powered search.
-
Stock Market Insights: Retrieves real-time stock prices, financial news, and trade data from Polygon.io, enriched with AI-driven insights.
-
AI-Powered Queries: Uses pre-defined AI models to refine and enhance search results for better accuracy and relevance.
-
Seamless Integration: Works with the Dappier API, requiring a valid API key to access search functionalities.
AI Recommendations Tool
-
Domain-specific recommendations: Tailors AI-powered content suggestions across verticals like sports, lifestyle, pet care and news.
-
Smart search algorithms: Supports modes like semantic, trending, and most recent to deliver the most relevant and timely results.
-
Reference domain targeting: Lets you prioritize results from a specific site or domain for more context-aware recommendations.
-
Readable, structured output: Returns responses with clear formatting, including title, summary, author, publish date, source, and links.
Installation
pip install llama-index-tools-dappier
Setup
You'll need to set up your API keys for OpenAI and Dappier.
You can go to here to get API Key from Open AI.
os.environ["OPENAI_API_KEY"] = "openai_api_key"
You can go to here to get API Key from Dappier with free credits.
os.environ["DAPPIER_API_KEY"] = "dappier_api_key"
Usage
Real Time Search Tool
This tool has a more extensive example usage documented in a Jupyter notebook here
Here's an example usage of the DappierRealTimeSearchToolSpec.
from llama_index.tools.dappier import (
DappierRealTimeSearchToolSpec,
)
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
dappier_tool = DappierRealTimeSearchToolSpec()
agent = FunctionAgent(
tools=dappier_tool.to_tool_list(),
llm=OpenAI(model="gpt-4o"),
)
await agent.run(
"How is the weather in Boston today ? Create a detailed analysis in markdown format."
)
The tools available in are:
search_real_time_data: A tool that performs a real-time web search to retrieve the latest information, including news, weather, travel deals, and more.search_stock_market_data: A tool that fetches real-time stock market data, including stock prices, financial news, and trade updates, with AI-powered insights.
AI Recommendations Tool
This tool has a more extensive example usage documented in a Jupyter notebook here
Here's an example usage of the DappierAIRecommendationsToolSpec.
from llama_index.tools.dappier import (
DappierAIRecommendationsToolSpec,
)
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
dappier_tool = DappierAIRecommendationsToolSpec()
agent = FunctionAgent(
tools=dappier_tool.to_tool_list(),
llm=OpenAI(model="gpt-4o"),
)
await agent.run(
"Get latest sports news, lifestyle news, breaking news, dog care advice and summarize it into different sections, with source links."
)
The tools available in are:
-
get_sports_news_recommendations: A tool that fetches real-time news, updates, and personalized content from top sports sources like Sportsnaut, Forever Blueshirts, Minnesota Sports Fan, LAFB Network, Bounding Into Sports, and Ringside Intel. -
get_lifestyle_news_recommendations: A tool that fetches Real-time updates, analysis, and personalized content from top sources like The Mix, Snipdaily, Nerdable, and Familyproof. -
get_iheartdogs_recommendations: A tool that fetches articles on health, behavior, lifestyle. grooming, ownership and more from iheartdogs.com -
get_iheartcats_recommendations: A tool that fetches articles on health, behavior, lifestyle. grooming, ownership and more from iheartcats.com -
get_greenmonster_recommendations: A tool that fetches guides to making conscious and compassionate choices that help people, animals, and the planet. -
get_wishtv_recommendations: A tool that fetches politics, breaking news, multicultural news, Hispanic language content, Entertainment, Health, Education and many more. -
get_nine_and_ten_news_recommendations: A tool that fetches up-to-date local news, weather forecasts, sports coverage, and community stories for Northern Michigan, including the Cadillac and Traverse City areas.
This loader is designed to be used as a way to load data as a Tool in an Agent.
Metadata
Release files for llama-index-tools-dappier 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| llama_index_tools_dappier-0.6.0.tar.gz | 7.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llama_index_tools_dappier-0.6.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.1 kB
Release files / llama_index_tools_dappier-0.6.0.tar.gz
| Download URL | llama_index_tools_dappier-0.6.0.tar.gz |
|---|---|
| Size | 7.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
351279c5e19fe560212f78006beb1cd0a1fd7788990598fd969c8f9ef77413c4
|
|
BLAKE2b-256 checksum How to use checksums |
cc0b7067a22e29fa1ee4ac23a714f4acffa53ee8d6b82981fefb78b7b8d87e9e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / llama_index_tools_dappier-0.6.0-py3-none-any.whl
| Download URL | llama_index_tools_dappier-0.6.0-py3-none-any.whl |
|---|---|
| Size | 8.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
5510d0ae238f1197aabcfb534efe2e5956407ab064a4a5db091257152bf17255
|
|
BLAKE2b-256 checksum How to use checksums |
a5f0dbe8b4ac5a30459397c22936d318a43c0de881d4f1f1cc0620166e295656
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.12.7 {"installer":{"name":"uv","version":"0.12.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|