> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Search API: Fast Web Lookup

> Quick web search for recent information.

```python news_search.py theme={null}
"""
Search API — Fast Web Lookup
============================

Quick web search for recent information.

USE CASES:
- Find recent news articles
- Quick factual lookups
- Gather sources for research
- Check current events

Search API is fast (1-5 seconds) but returns raw results.
Your agent synthesizes the answer from the snippets.

For deep research with citations, use Task API instead.

Prerequisites:
- pip install parallel-web
- export PARALLEL_API_KEY=<your-api-key>
"""

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools

# =============================================================================
# SEARCH CONFIGURATIONS
# =============================================================================

# General search
general_search = ParallelTools(
    max_results=10,
)

# Tech news — filtered sources
tech_search = ParallelTools(
    include_domains=["techcrunch.com", "wired.com", "arstechnica.com", "theverge.com"],
    max_results=10,
)

# Financial news
finance_search = ParallelTools(
    include_domains=["reuters.com", "bloomberg.com", "wsj.com", "ft.com"],
    max_results=10,
)

# Quick lookup — concise results
quick_search = ParallelTools(
    max_results=5,
    max_chars_per_result=300,
)

# =============================================================================
# SEARCH AGENTS
# =============================================================================

# General news agent
news_agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[general_search],
    markdown=True,
)

# Tech news specialist
tech_agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[tech_search],
    markdown=True,
    instructions="You search tech news for the latest developments in technology.",
)

# Financial news specialist
finance_agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[finance_search],
    markdown=True,
    instructions="You search financial news for market updates and company news.",
)

# =============================================================================
# RUN
# =============================================================================
if __name__ == "__main__":
    # Quick news search
    news_agent.print_response(
        "What are the latest developments in AI agents?",
        stream=True,
    )
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai parallel-web
    ```
  </Step>

  <Step title="Export your API keys">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      export PARALLEL_API_KEY="your_parallel_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      $Env:PARALLEL_API_KEY="your_parallel_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run the example">
    Save the code above as `news_search.py`, then run:

    ```bash theme={null}
    python news_search.py
    ```
  </Step>
</Steps>

Full source: [cookbook/91\_tools/parallel/news\_search.py](https://github.com/agno-agi/agno/blob/main/cookbook/91_tools/parallel/news_search.py)