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

# Pydantic Input

> Pass Pydantic model instances as workflow input.

Demonstrates passing a Pydantic model instance directly as workflow input.

```python pydantic_input.py theme={null}
"""
Pydantic Input
==============

Demonstrates passing a Pydantic model instance directly as workflow input.
"""

from typing import List

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from agno.workflow.step import Step
from agno.workflow.workflow import Workflow
from pydantic import BaseModel, Field


# ---------------------------------------------------------------------------
# Define Input Model
# ---------------------------------------------------------------------------
class ResearchTopic(BaseModel):
    topic: str
    focus_areas: List[str] = Field(description="Specific areas to focus on")
    target_audience: str = Field(description="Who this research is for")
    sources_required: int = Field(description="Number of sources needed", default=5)


# ---------------------------------------------------------------------------
# Create Agents
# ---------------------------------------------------------------------------
hackernews_agent = Agent(
    name="Hackernews Agent",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[HackerNewsTools()],
    role="Extract key insights and content from Hackernews posts",
)

web_agent = Agent(
    name="Web Agent",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[WebSearchTools()],
    role="Search the web for the latest news and trends",
)

content_planner = Agent(
    name="Content Planner",
    model=OpenAIChat(id="gpt-4o"),
    instructions=[
        "Plan a content schedule over 4 weeks for the provided topic and research content",
        "Ensure that I have posts for 3 posts per week",
    ],
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
research_team = Team(
    name="Research Team",
    members=[hackernews_agent, web_agent],
    instructions="Research tech topics from Hackernews and the web",
)

# ---------------------------------------------------------------------------
# Define Steps
# ---------------------------------------------------------------------------
research_step = Step(
    name="Research Step",
    team=research_team,
)

content_planning_step = Step(
    name="Content Planning Step",
    agent=content_planner,
)

# ---------------------------------------------------------------------------
# Create Workflow
# ---------------------------------------------------------------------------
content_creation_workflow = Workflow(
    name="Content Creation Workflow",
    description="Automated content creation from blog posts to social media",
    db=SqliteDb(
        session_table="workflow_session",
        db_file="tmp/workflow.db",
    ),
    steps=[research_step, content_planning_step],
)

# ---------------------------------------------------------------------------
# Run Workflow
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    print("=== Example: Research with Structured Topic ===")
    research_topic = ResearchTopic(
        topic="AI trends in 2024",
        focus_areas=[
            "Machine Learning",
            "Natural Language Processing",
            "Computer Vision",
            "AI Ethics",
        ],
        target_audience="Tech professionals and business leaders",
        sources_required=8,
    )
    content_creation_workflow.print_response(
        input=research_topic,
        markdown=True,
    )
```

## Run the Example

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

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

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

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

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

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

Full source: [cookbook/04\_workflows/06\_advanced\_concepts/structured\_io/pydantic\_input.py](https://github.com/agno-agi/agno/blob/main/cookbook/04_workflows/06_advanced_concepts/structured_io/pydantic_input.py)