Web Search

@register_tool('web_search', allow_overwrite=True)
class WebSearch(BaseTool):
    ...

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    }
  },
  "required": ["query"]
}

# Linux/Mac
export SERPER_API_KEY="your-api-key-here"

# Windows (Command Prompt)
set SERPER_API_KEY=your-api-key-here

# Windows (PowerShell)
$env:SERPER_API_KEY="your-api-key-here"

import os
os.environ['SERPER_API_KEY'] = 'your-api-key-here'

from qwen_agent.tools import WebSearch
import json

# Initialize the tool
web_search = WebSearch()

# Perform a search
result = web_search.call(params=json.dumps({'query': 'latest AI news'}))
print(result)

from qwen_agent.agents import Assistant

bot = Assistant(
    llm={'model': 'qwen-max'},
    function_list=['web_search']
)

messages = [
    {
        'role': 'user',
        'content': 'What are the latest developments in quantum computing?'
    }
]

for response in bot.run(messages=messages):
    print(response)

web_search = WebSearch()

queries = [
    'Python best practices 2024',
    'machine learning tutorials',
    'latest tech trends'
]

for query in queries:
    print(f"\n=== Searching: {query} ===")
    result = web_search.call(params=json.dumps({'query': query}))
    print(result)

[1]"Title of first result
Snippet text from the page..."Date

[2]"Title of second result
Snippet text from the page..."Date

[3]"Title of third result
Snippet text from the page..."

from qwen_agent.agents import Assistant

def create_research_assistant():
    """Create an agent that can search the web for information."""
    bot = Assistant(
        llm={'model': 'qwen-max'},
        name='Research Assistant',
        description='I can search the web to find current information and help answer your questions.',
        system_message=(
            'You are a helpful research assistant. When users ask questions, '
            'use web search to find current information. Always cite your sources '
            'and provide the most recent and relevant information.'
        ),
        function_list=['web_search']
    )
    return bot

# Create and use the assistant
bot = create_research_assistant()

messages = []
while True:
    query = input('\nAsk a question (or "quit"): ')
    if query.lower() in ['quit', 'exit', 'q']:
        break
    
    messages.append({'role': 'user', 'content': query})
    
    response = []
    for response in bot.run(messages=messages):
        pass  # Wait for complete response
    
    # Print assistant's response
    print(f"\nAssistant: {response[-1]['content']}")
    messages.extend(response)

{
    'organic': [
        {
            'title': 'Page title',
            'snippet': 'Page description or excerpt',
            'link': 'https://example.com/page',
            'date': '2024-03-15',  # Optional
            'position': 1
        },
        # ... more results
    ],
    'searchParameters': {
        'q': 'search query',
        'type': 'search'
    }
}

from qwen_agent.tools import WebSearch

# Use the static search method directly
raw_results = WebSearch.search('AI research papers')

# raw_results is a list of dicts
for result in raw_results:
    print(f"Title: {result['title']}")
    print(f"Link: {result['link']}")
    print(f"Snippet: {result['snippet']}")
    if 'date' in result:
        print(f"Date: {result['date']}")
    print()

from qwen_agent.tools import WebSearch

class CustomWebSearch(WebSearch):
    @staticmethod
    def _format_results(search_results):
        """Custom result formatting."""
        formatted = []
        for i, doc in enumerate(search_results, 1):
            formatted.append(
                f"{i}. {doc['title']}\n"
                f"   {doc.get('snippet', 'No description')}\n"
                f"   {doc.get('link', '')}\n"
            )
        return '\n'.join(formatted)

# Use custom formatter
custom_search = CustomWebSearch()
result = custom_search.call(params='{"query": "Python tips"}')
print(result)

from qwen_agent.tools import WebSearch
import json

web_search = WebSearch()

try:
    result = web_search.call(
        params=json.dumps({'query': 'test search'})
    )
    print(result)
except ValueError as e:
    if 'SERPER_API_KEY' in str(e):
        print("Error: API key not set. Please set SERPER_API_KEY environment variable.")
    else:
        print(f"Error: {e}")
except Exception as e:
    print(f"Search failed: {e}")

from qwen_agent.tools import WebSearch
import json
import time
from datetime import datetime

def monitor_news_topic(topic, interval_minutes=60):
    """Monitor a topic and report new results periodically."""
    web_search = WebSearch()
    seen_titles = set()
    
    print(f"Monitoring: {topic}")
    print(f"Checking every {interval_minutes} minutes...\n")
    
    while True:
        try:
            result = web_search.call(
                params=json.dumps({'query': f'{topic} latest news'})
            )
            
            # Parse results (simplified)
            lines = result.split('\n')
            current_titles = [line for line in lines if line.startswith('[')]
            
            # Check for new articles
            new_articles = [t for t in current_titles if t not in seen_titles]
            
            if new_articles:
                print(f"\n[{datetime.now().strftime('%Y-%m-%d %H:%M')}] New articles:")
                for article in new_articles:
                    print(article)
                seen_titles.update(new_articles)
            
            time.sleep(interval_minutes * 60)
            
        except KeyboardInterrupt:
            print("\nStopping monitor...")
            break
        except Exception as e:
            print(f"Error: {e}")
            time.sleep(60)

# Monitor AI news
if __name__ == '__main__':
    monitor_news_topic('artificial intelligence', interval_minutes=30)