> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-docs-scavio-google-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Parallel

> Give agents Parallel's Search, Task (deep research), and Monitor APIs for grounded web lookups, cited research, and scheduled web tracking.

Enable Agno agents with web search and extraction infrastructure from Parallel that prioritizes token efficiency and multi-hop reasoning.

## Search

Natural-language web search that returns LLM-optimized excerpts. Use when the model needs current facts, specific entities, or web data to ground a response.

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[ParallelTools(
        max_results=10,
        include_domains=["techcrunch.com", "wired.com"],
    )],
    markdown=True,
)

agent.print_response("What are the latest developments in AI agents?", stream=True)
```

## Task

Deep research that takes a plain-language input and returns comprehensive, cited results. Choose the processor by complexity and latency. `base` typically completes in 15 to 100 seconds, while higher tiers can take minutes.

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools

enrichment_tools = ParallelTools(
    enable_search=False,
    enable_extract=False,
    enable_task=True,
    default_processor="base",
    default_output_schema={
        "type": "json",
        "json_schema": {
            "type": "object",
            "properties": {
                "company_name": {"type": "string"},
                "headquarters": {"type": "string"},
                "total_funding": {"type": "string"},
                "key_investors": {"type": "array", "items": {"type": "string"}},
            },
            "required": ["company_name"],
        },
    },
)

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[enrichment_tools],
    markdown=True,
    instructions="Use create_task() to research, then get_task_result() to retrieve.",
)

agent.print_response("Research Anthropic and return structured company data", stream=True)
```

## Monitor

Continuously track the web for changes relevant to a natural-language query, on a schedule you control. Use for news tracking, regulatory watchlists, or competitor monitoring.

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.parallel import ParallelTools

monitor_tools = ParallelTools(
    enable_search=False,
    enable_extract=False,
    enable_monitor=True,
    default_monitor_frequency="1d",
)

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[monitor_tools],
    markdown=True,
)

# Create monitors
agent.print_response("Create a monitor to track OpenAI product launches", stream=True)

# Later: check for events
agent.print_response("List my monitors and fetch recent events", stream=True)
```

## Run the Examples

<Steps>
  <Step title="Clone and set up">
    ```bash theme={null}
    git clone https://github.com/agno-agi/agno.git
    cd agno
    ```
  </Step>

  <Step title="Create virtual environment">
    ```bash theme={null}
    ./scripts/demo_setup.sh
    source .venvs/demo/bin/activate
    ```
  </Step>

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

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

  <Step title="Run an example">
    ```bash theme={null}
    # Search
    python cookbook/91_tools/parallel/news_search.py

    # Task (deep research)
    python cookbook/91_tools/parallel/company_enrichment.py

    # Monitor (continuous tracking)
    python cookbook/91_tools/parallel/competitor_tracker.py
    ```
  </Step>
</Steps>

For more examples, see the [Parallel cookbook](https://github.com/agno-agi/agno/tree/main/cookbook/91_tools/parallel).