---
title: PDF to Form Automation
description: Enhance and Automate Interactions Between Form Filling and Local File Systems
---

import { Step, Steps } from 'fumadocs-ui/components/steps';
import { Tab, Tabs } from 'fumadocs-ui/components/tabs';

## Overview

Cua can be used to automate interactions between form filling and local file systems over any operating system. Cua let's you interact with all the elements of a web page and local file systems to integrate between the two.

This preset usecase uses [Cua Computer](/computer-sdk/computers) to interact with a web page and local file systems along with [Agent Loops](/agent-sdk/agent-loops) to run the agent in a loop with message history.

---

<Steps>

<Step>

### Set Up Your Environment

First, install the required dependencies:

Create a `requirements.txt` file:

```text
cua-agent
cua-computer
python-dotenv>=1.0.0
```

Install the dependencies:

```bash
pip install -r requirements.txt
```

Create a `.env` file with your API keys:

```text
ANTHROPIC_API_KEY=your-anthropic-api-key
CUA_API_KEY=sk_cua-api01...
```

</Step>

<Step>

### Create Your Form Filling Script

Create a Python file (e.g., `form_filling.py`) and select your environment:

<Tabs items={['Cloud Sandbox', 'Linux on Docker', 'macOS Sandbox', 'Windows Sandbox']}>
  <Tab value="Cloud Sandbox">

```python
import asyncio
import logging
import os
import signal
import traceback

from agent import ComputerAgent
from computer import Computer, VMProviderType
from dotenv import load_dotenv

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def handle_sigint(sig, frame):
    print("\n\nExecution interrupted by user. Exiting gracefully...")
    exit(0)

async def fill_application():
    try:
        async with Computer(
            os_type="linux",
            provider_type=VMProviderType.CLOUD,
            name="your-sandbox-name",  # Replace with your sandbox name
            api_key=os.environ["CUA_API_KEY"],
            verbosity=logging.INFO,
        ) as computer:

            agent = ComputerAgent(
                model="cua/anthropic/claude-sonnet-4.5",
                tools=[computer],
                only_n_most_recent_images=3,
                verbosity=logging.INFO,
                trajectory_dir="trajectories",
                use_prompt_caching=True,
                max_trajectory_budget=5.0,
            )

            tasks = [
                "Visit https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs.pdf and download the pdf.",
                "Visit https://form.jotform.com/252881246782264 and fill the form from the information in the pdf."
            ]

            history = []

            for i, task in enumerate(tasks, 1):
                print(f"\n[Task {i}/{len(tasks)}] {task}")

                # Add user message to history
                history.append({"role": "user", "content": task})

                # Run agent with conversation history
                async for result in agent.run(history, stream=False):
                    history += result.get("output", [])

                    # Print output for debugging
                    for item in result.get("output", []):
                        if item.get("type") == "message":
                            content = item.get("content", [])
                            for content_part in content:
                                if content_part.get("text"):
                                    logger.info(f"Agent: {content_part.get('text')}")
                        elif item.get("type") == "computer_call":
                            action = item.get("action", {})
                            action_type = action.get("type", "")
                            logger.debug(f"Computer Action: {action_type}")

                print(f"✅ Task {i}/{len(tasks)} completed")

            print("\n🎉 All tasks completed successfully!")

    except Exception as e:
        logger.error(f"Error in fill_application: {e}")
        traceback.print_exc()
        raise

def main():
    try:
        load_dotenv()

        if "ANTHROPIC_API_KEY" not in os.environ:
            raise RuntimeError(
                "Please set the ANTHROPIC_API_KEY environment variable.\n"
                "You can add it to a .env file in the project root."
            )

        if "CUA_API_KEY" not in os.environ:
            raise RuntimeError(
                "Please set the CUA_API_KEY environment variable.\n"
                "You can add it to a .env file in the project root."
            )

        signal.signal(signal.SIGINT, handle_sigint)

        asyncio.run(fill_application())

    except Exception as e:
        logger.error(f"Error running automation: {e}")
        traceback.print_exc()

if __name__ == "__main__":
    main()
```

  </Tab>
  <Tab value="Linux on Docker">

```python
import asyncio
import logging
import os
import signal
import traceback

from agent import ComputerAgent
from computer import Computer, VMProviderType
from dotenv import load_dotenv

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def handle_sigint(sig, frame):
    print("\n\nExecution interrupted by user. Exiting gracefully...")
    exit(0)

async def fill_application():
    try:
        async with Computer(
            os_type="linux",
            provider_type=VMProviderType.DOCKER,
            image="trycua/cua-xfce:latest",  # or "trycua/cua-ubuntu:latest"
            verbosity=logging.INFO,
        ) as computer:

            agent = ComputerAgent(
                model="cua/anthropic/claude-sonnet-4.5",
                tools=[computer],
                only_n_most_recent_images=3,
                verbosity=logging.INFO,
                trajectory_dir="trajectories",
                use_prompt_caching=True,
                max_trajectory_budget=5.0,
            )

            tasks = [
                "Visit https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs.pdf and download the pdf.",
                "Visit https://form.jotform.com/252881246782264 and fill the form from the information in the pdf."
            ]

            history = []

            for i, task in enumerate(tasks, 1):
                print(f"\n[Task {i}/{len(tasks)}] {task}")

                # Add user message to history
                history.append({"role": "user", "content": task})

                # Run agent with conversation history
                async for result in agent.run(history, stream=False):
                    history += result.get("output", [])

                    # Print output for debugging
                    for item in result.get("output", []):
                        if item.get("type") == "message":
                            content = item.get("content", [])
                            for content_part in content:
                                if content_part.get("text"):
                                    logger.info(f"Agent: {content_part.get('text')}")
                        elif item.get("type") == "computer_call":
                            action = item.get("action", {})
                            action_type = action.get("type", "")
                            logger.debug(f"Computer Action: {action_type}")

                print(f"✅ Task {i}/{len(tasks)} completed")

            print("\n🎉 All tasks completed successfully!")

    except Exception as e:
        logger.error(f"Error in fill_application: {e}")
        traceback.print_exc()
        raise

def main():
    try:
        load_dotenv()

        if "ANTHROPIC_API_KEY" not in os.environ:
            raise RuntimeError(
                "Please set the ANTHROPIC_API_KEY environment variable.\n"
                "You can add it to a .env file in the project root."
            )

        signal.signal(signal.SIGINT, handle_sigint)

        asyncio.run(fill_application())

    except Exception as e:
        logger.error(f"Error running automation: {e}")
        traceback.print_exc()

if __name__ == "__main__":
    main()
```

  </Tab>
  <Tab value="macOS Sandbox">

```python
import asyncio
import logging
import os
import signal
import traceback

from agent import ComputerAgent
from computer import Computer, VMProviderType
from dotenv import load_dotenv

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def handle_sigint(sig, frame):
    print("\n\nExecution interrupted by user. Exiting gracefully...")
    exit(0)

async def fill_application():
    try:
        async with Computer(
            os_type="macos",
            provider_type=VMProviderType.LUME,
            name="macos-sequoia-cua:latest",
            verbosity=logging.INFO,
        ) as computer:

            agent = ComputerAgent(
                model="cua/anthropic/claude-sonnet-4.5",
                tools=[computer],
                only_n_most_recent_images=3,
                verbosity=logging.INFO,
                trajectory_dir="trajectories",
                use_prompt_caching=True,
                max_trajectory_budget=5.0,
            )

            tasks = [
                "Visit https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs.pdf and download the pdf.",
                "Visit https://form.jotform.com/252881246782264 and fill the form from the information in the pdf."
            ]

            history = []

            for i, task in enumerate(tasks, 1):
                print(f"\n[Task {i}/{len(tasks)}] {task}")

                # Add user message to history
                history.append({"role": "user", "content": task})

                # Run agent with conversation history
                async for result in agent.run(history, stream=False):
                    history += result.get("output", [])

                    # Print output for debugging
                    for item in result.get("output", []):
                        if item.get("type") == "message":
                            content = item.get("content", [])
                            for content_part in content:
                                if content_part.get("text"):
                                    logger.info(f"Agent: {content_part.get('text')}")
                        elif item.get("type") == "computer_call":
                            action = item.get("action", {})
                            action_type = action.get("type", "")
                            logger.debug(f"Computer Action: {action_type}")

                print(f"✅ Task {i}/{len(tasks)} completed")

            print("\n🎉 All tasks completed successfully!")

    except Exception as e:
        logger.error(f"Error in fill_application: {e}")
        traceback.print_exc()
        raise

def main():
    try:
        load_dotenv()

        if "ANTHROPIC_API_KEY" not in os.environ:
            raise RuntimeError(
                "Please set the ANTHROPIC_API_KEY environment variable.\n"
                "You can add it to a .env file in the project root."
            )

        signal.signal(signal.SIGINT, handle_sigint)

        asyncio.run(fill_application())

    except Exception as e:
        logger.error(f"Error running automation: {e}")
        traceback.print_exc()

if __name__ == "__main__":
    main()
```

  </Tab>
  <Tab value="Windows Sandbox">

```python
import asyncio
import logging
import os
import signal
import traceback

from agent import ComputerAgent
from computer import Computer, VMProviderType
from dotenv import load_dotenv

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def handle_sigint(sig, frame):
    print("\n\nExecution interrupted by user. Exiting gracefully...")
    exit(0)

async def fill_application():
    try:
        async with Computer(
            os_type="windows",
            provider_type=VMProviderType.WINDOWS_SANDBOX,
            verbosity=logging.INFO,
        ) as computer:

            agent = ComputerAgent(
                model="cua/anthropic/claude-sonnet-4.5",
                tools=[computer],
                only_n_most_recent_images=3,
                verbosity=logging.INFO,
                trajectory_dir="trajectories",
                use_prompt_caching=True,
                max_trajectory_budget=5.0,
            )

            tasks = [
                "Visit https://www.overleaf.com/latex/templates/jakes-resume/syzfjbzwjncs.pdf and download the pdf.",
                "Visit https://form.jotform.com/252881246782264 and fill the form from the information in the pdf."
            ]

            history = []

            for i, task in enumerate(tasks, 1):
                print(f"\n[Task {i}/{len(tasks)}] {task}")

                # Add user message to history
                history.append({"role": "user", "content": task})

                # Run agent with conversation history
                async for result in agent.run(history, stream=False):
                    history += result.get("output", [])

                    # Print output for debugging
                    for item in result.get("output", []):
                        if item.get("type") == "message":
                            content = item.get("content", [])
                            for content_part in content:
                                if content_part.get("text"):
                                    logger.info(f"Agent: {content_part.get('text')}")
                        elif item.get("type") == "computer_call":
                            action = item.get("action", {})
                            action_type = action.get("type", "")
                            logger.debug(f"Computer Action: {action_type}")

                print(f"✅ Task {i}/{len(tasks)} completed")

            print("\n🎉 All tasks completed successfully!")

    except Exception as e:
        logger.error(f"Error in fill_application: {e}")
        traceback.print_exc()
        raise

def main():
    try:
        load_dotenv()

        if "ANTHROPIC_API_KEY" not in os.environ:
            raise RuntimeError(
                "Please set the ANTHROPIC_API_KEY environment variable.\n"
                "You can add it to a .env file in the project root."
            )

        signal.signal(signal.SIGINT, handle_sigint)

        asyncio.run(fill_application())

    except Exception as e:
        logger.error(f"Error running automation: {e}")
        traceback.print_exc()

if __name__ == "__main__":
    main()
```

  </Tab>
</Tabs>

</Step>

<Step>

### Run Your Script

Execute your form filling automation:

```bash
python form_filling.py
```

The agent will:
1. Download the PDF resume from Overleaf
2. Extract information from the PDF
3. Fill out the JotForm with the extracted information

Monitor the output to see the agent's progress through each task.

</Step>

</Steps>

---

## Next Steps

- Learn more about [Cua computers](/computer-sdk/computers) and [computer commands](/computer-sdk/commands)
- Read about [Agent loops](/agent-sdk/agent-loops), [tools](/agent-sdk/custom-tools), and [supported model providers](/agent-sdk/supported-model-providers/)
- Experiment with different [Models and Providers](/agent-sdk/supported-model-providers/)
- Join our [Discord community](https://discord.com/invite/mVnXXpdE85) for help
