Newspaper Agent

News article extraction tools for AI agents.

from praisonaiagents import Agent
from praisonaiagents import extract_article

agent = Agent(
    name="News Reader",
    instructions="Extract and summarise news articles from URLs.",
    tools=[extract_article],
)
agent.start("Summarise the main points from this article URL")

The user pastes a news link; the agent extracts article text and returns a brief summary.

Prerequisites

• Python 3.10 or higher
• PraisonAI Agents package installed
• PraisonAI Tools package installed
• newspaper3k package installed

Newspaper Tools

Use Newspaper Tools to extract and analyze news articles with AI agents.

1. Install Dependencies

   First, install the required packages:

   pip install praisonaiagents praisonai-tools newspaper3k
   
2. Import Components

   Import the necessary components:

   from praisonaiagents import Agent, Task, AgentTeam
   from praisonai_tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics
   
3. Create Agent

   Create a news agent:

   news_agent = Agent(
       name="NewsAgent",
       role="News Analyst",
       goal="Collect and analyze news articles from various sources.",
       backstory="Expert in news gathering and content analysis.",
       tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics],
       reflection=False
   )
   
4. Define Task

   Define the news task:

   news_task = Task(
       description="Analyze news articles about 'AI developments' from major tech news sources.",
       expected_output="Summary of key AI developments with source articles.",
       agent=news_agent,
       name="ai_news"
   )
   
5. Run Agent

   Initialize and run the agent:

   agents = AgentTeam(
       agents=[news_agent],
       tasks=[news_task],
       process="sequential"
   )
   agents.start()
   

Understanding Newspaper Tools

What are Newspaper Tools?

Newspaper Tools provide news article processing capabilities for AI agents:

• Article extraction
• Source management
• Content analysis
• Trend detection
• Multi-language support

Key Components

News Agent

Create specialized news agents:

Agent(tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics])

News Task

Define news tasks:

Task(description="news_query")

Process Types

Sequential or parallel processing:

process="sequential"

Article Options

Customize article retrieval:

language="en", limit=10

Available Functions

from praisonai_tools import get_article
from praisonai_tools import get_news_sources
from praisonai_tools import get_articles_from_source
from praisonai_tools import get_trending_topics

Examples

Basic News Agent

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics

# Create news agent
news_agent = Agent(
    name="NewsExpert",
    role="News Analyst",
    goal="Gather and analyze news content efficiently.",
    backstory="Expert in news analysis and content curation.",
    tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics],
    reflection=False
)

# Define news task
news_task = Task(
    description="Analyze tech news trends.",
    expected_output="Tech news analysis report.",
    agent=news_agent,
    name="tech_news_analysis"
)

# Run agent
agents = AgentTeam(
    agents=[news_agent],
    tasks=[news_task],
    process="sequential"
)
agents.start()

Advanced News Analysis with Multiple Agents

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics

# Create news collection agent
collector_agent = Agent(
    name="Collector",
    role="News Collector",
    goal="Gather comprehensive news coverage.",
    tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics],
    reflection=False
)

# Create analysis agent
analysis_agent = Agent(
    name="Analyzer",
    role="Content Analyst",
    goal="Analyze news content and identify trends.",
    backstory="Expert in news analysis and trend identification.",
    reflection=False
)

# Define tasks
collection_task = Task(
    description="Collect news articles about renewable energy developments.",
    agent=collector_agent,
    name="energy_news"
)

analysis_task = Task(
    description="Analyze the articles and identify key trends and breakthroughs.",
    agent=analysis_agent,
    name="news_analysis"
)

# Run agents
agents = AgentTeam(
    agents=[collector_agent, analysis_agent],
    tasks=[collection_task, analysis_task],
    process="sequential"
)
agents.start()

Best Practices

Agent Configuration

Configure agents with clear news focus:

from praisonai_tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics

Agent(
    name="NewsAnalyst",
    role="News Specialist",
    goal="Analyze news content effectively",
    tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics]
)

Task Definition

Define specific news objectives:

Task(
    description="Analyze tech news from major sources for AI developments",
    expected_output="Trend analysis with key findings"
)

Common Patterns

News Monitoring

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics

# News monitor agent
monitor = Agent(
    name="Monitor",
    role="News Monitor",
    tools=[get_article, get_news_sources, get_articles_from_source, get_trending_topics]
)

# Analysis agent
analyst = Agent(
    name="Analyst",
    role="News Analyst"
)

# Define tasks
monitor_task = Task(
    description="Monitor tech news sources",
    agent=monitor
)

analysis_task = Task(
    description="Analyze news trends",
    agent=analyst
)

# Run workflow
agents = AgentTeam(
    agents=[monitor, analyst],
    tasks=[monitor_task, analysis_task]
)

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Tools Overview

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