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

# LangDB Structured Output

> Generate MovieScript objects with LangDB via JSON mode and structured outputs.

```python structured_output.py theme={null}
"""
Langdb Structured Output
========================

Cookbook example for `langdb/structured_output.py`.
"""

from typing import List

from agno.agent import Agent, RunOutput  # noqa
from agno.models.langdb import LangDB
from pydantic import BaseModel, Field
from rich.pretty import pprint  # noqa

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


class MovieScript(BaseModel):
    setting: str = Field(
        ..., description="Provide a nice setting for a blockbuster movie."
    )
    ending: str = Field(
        ...,
        description="Ending of the movie. If not available, provide a happy ending.",
    )
    genre: str = Field(
        ...,
        description="Genre of the movie. If not available, select action, thriller or romantic comedy.",
    )
    name: str = Field(..., description="Give a name to this movie")
    characters: List[str] = Field(..., description="Name of characters for this movie.")
    storyline: str = Field(
        ..., description="3 sentence storyline for the movie. Make it exciting!"
    )


# Agent that uses JSON mode
json_mode_agent = Agent(
    model=LangDB(id="llama3-1-70b-instruct-v1.0"),
    description="You write movie scripts.",
    output_schema=MovieScript,
    use_json_mode=True,
)

# Agent that uses structured outputs
structured_output_agent = Agent(
    model=LangDB(id="llama3-1-70b-instruct-v1.0"),
    description="You write movie scripts.",
    output_schema=MovieScript,
)

# Get the response in a variable
# json_mode_response: RunOutput = json_mode_agent.run("New York")
# pprint(json_mode_response.content)
# structured_output_response: RunOutput = structured_output_agent.run("New York")
# pprint(structured_output_response.content)

json_mode_agent.print_response("New York")
structured_output_agent.print_response("New York")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**2. Export environment variables**

```bash Mac/Linux theme={null}
export LANGDB_API_KEY="your_langdb_api_key_here"
export LANGDB_PROJECT_ID="your_langdb_project_id_here"
```

```bash Windows theme={null}
$Env:LANGDB_API_KEY="your_langdb_api_key_here"
$Env:LANGDB_PROJECT_ID="your_langdb_project_id_here"
```

**3. Run the example**

Save the code above as `structured_output.py`, then run:

```bash theme={null}
python structured_output.py
```

Full source: [cookbook/90\_models/langdb/structured\_output.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/90_models/langdb/structured_output.py)


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