A workflow demonstrating how the Web Search Agent can perform intelligent searches and process web content.

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Quick Start

1

Install Package

First, install the PraisonAI Agents package:

pip install praisonaiagents
2

Set API Key

Set your OpenAI API key as an environment variable:

export OPENAI_API_KEY=your_api_key_here
3

Create Script

Create a new file web_search.py:

from praisonaiagents import Agent, Tools
from praisonaiagents.tools import duckduckgo

# Create Web Search Agent
search_agent = Agent(
    name="WebSearcher",
    role="Web Search Specialist",
    goal="Perform intelligent web searches and gather information",
    instructions="You are a Web Search Agent",
    tools=[duckduckgo]
)

# Perform search
response = search_agent.start(
    "Search about AI developments in 2024"
)

# Save search results
with open('search_results.md', 'w') as f:
    f.write(response)

The Web Search Agent employs sophisticated search strategies:

  1. Query Processing: Optimizes search queries
  2. Content Filtering: Filters relevant results
  3. Information Extraction: Extracts key information
  4. Result Summarization: Summarizes findings

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Features

Smart Search

Intelligent query processing.

Content Filtering

Relevance-based filtering.

Information Extraction

Key information extraction.

Result Summary

Concise result summaries.

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Example Usage

# Example: Perform topic research
from praisonaiagents import Agent, Tools
from praisonaiagents.tools import duckduckgo

agent = Agent(
    instructions="You are a Web Search Agent",
    tools=[duckduckgo]
)

# Research specific topic
response = agent.start("""
    Search for information about quantum computing:
    - Recent breakthroughs
    - Leading companies
    - Current applications
    - Future predictions
""")

# Save research results
with open('quantum_computing_research.md', 'w') as f:
    f.write(response)

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Next Steps