> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Capture Reasoning Content with Reasoning Tools

<Steps>
  <Step title="Add the following code to your Python file">
    ```python capture_reasoning_content_reasoning_tools.py theme={null}
    from textwrap import dedent

    from agno.agent import Agent
    from agno.models.openai import OpenAIResponses
    from agno.tools.reasoning import ReasoningTools

    """Test function to verify reasoning_content is populated in RunOutput."""
    print("\n=== Testing reasoning_content generation ===\n")

    # Create an agent with ReasoningTools
    agent = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[ReasoningTools(add_instructions=True)],
        instructions=dedent("""\
            You are an expert problem-solving assistant with strong analytical skills! 🧠
            Use step-by-step reasoning to solve the problem.
            \
        """),
    )

    # Test 1: Non-streaming mode
    print("Running with stream=False...")
    response = agent.run("What is the sum of the first 10 natural numbers?", stream=False)

    # Check reasoning_content
    if hasattr(response, "reasoning_content") and response.reasoning_content:
        print("✅ reasoning_content FOUND in non-streaming response")
        print(f"   Length: {len(response.reasoning_content)} characters")
        print("\n=== reasoning_content preview (non-streaming) ===")
        preview = response.reasoning_content[:1000]
        if len(response.reasoning_content) > 1000:
            preview += "..."
        print(preview)
    else:
        print("❌ reasoning_content NOT FOUND in non-streaming response")

    # Process streaming responses to find the final one
    print("\n\n=== Test 2: Processing stream to find final response ===\n")

    # Create another fresh agent
    streaming_agent_alt = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[ReasoningTools(add_instructions=True)],
        instructions=dedent("""\
            You are an expert problem-solving assistant with strong analytical skills! 🧠
            Use step-by-step reasoning to solve the problem.
            \
        """),
    )

    # Process streaming responses and look for the final RunOutput
    final_response = None
    for event in streaming_agent_alt.run(
        "What is the value of 3! (factorial)?",
        stream=True,
        stream_events=True,
    ):
        # The final event in the stream should be a RunOutput object
        if hasattr(event, "reasoning_content"):
            final_response = event

    print("--- Checking reasoning_content from final stream event ---")
    if (
        final_response
        and hasattr(final_response, "reasoning_content")
        and final_response.reasoning_content
    ):
        print("✅ reasoning_content FOUND in final stream event")
        print(f"   Length: {len(final_response.reasoning_content)} characters")
        print("\n=== reasoning_content preview (final stream event) ===")
        preview = final_response.reasoning_content[:1000]
        if len(final_response.reasoning_content) > 1000:
            preview += "..."
        print(preview)
    else:
        print("❌ reasoning_content NOT FOUND in final stream event")
    ```
  </Step>

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

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

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

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

  <Step title="Run Agent">
    ```bash theme={null}
    python capture_reasoning_content_reasoning_tools.py
    ```
  </Step>
</Steps>