diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..97b9354
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,116 @@
+# Python
+**/__pycache__/
+**/*.py[cod]
+**/*$py.class
+*.so
+__init__.py.bak
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+**/*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+env/
+ENV/
+.venv/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Testing
+.coverage
+htmlcov/
+.pytest_cache/
+.tox/
+
+# Distribution
+*.tar.gz
+*.zip
+
+# Logs
+*.log
+
+# Local development
+.env
+.env.local
+.env.*.local
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Virtual environments
+venv/
+env/
+ENV/
+
+# IDEs
+.vscode/
+.idea/
+*.swp
+*.swo 
\ No newline at end of file
diff --git a/README.md b/README.md
index 622810a..7d37d03 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,178 @@
-# cu-playwright-python
\ No newline at end of file
+# Kernel Python Sample App - Computer Use
+
+This is a simple Kernel application that implements a prompt loop using Anthropic Computer Use.
+
+It generally follows the [Anthropic Reference Implementation](https://github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo) but replaces `xodotool` and `gnome-screenshot` with Playwright.
+
+# cu-playwright-python
+
+Computer Use Agent for Python - Browser automation with Claude using Anthropic's Computer Use capabilities.
+
+This library provides a clean, simple interface to Anthropic's Computer Use capabilities, allowing Claude to interact with web pages through Playwright. It's the Python equivalent of [cu-playwright-ts](https://github.com/anthropics/cu-playwright-ts).
+
+## Features
+
+- 🤖 **AI-Powered Browser Automation**: Let Claude control web browsers with natural language
+- 🎯 **Simple API**: Clean, intuitive interface for complex browser interactions
+- 📊 **Structured Responses**: Get validated data back using Pydantic models
+- 🛠️ **Built on Playwright**: Reliable browser automation underneath
+- ⚡ **Async/Await**: Modern Python async support
+
+## Installation
+
+```bash
+pip install cu-playwright-python
+```
+
+You'll also need to install Playwright browsers:
+
+```bash
+playwright install chromium
+```
+
+## Quick Start
+
+```python
+import asyncio
+import os
+from playwright.async_api import async_playwright
+from cu_playwright_python import ComputerUseAgent
+
+async def main():
+    # Set up your Anthropic API key
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    
+    async with async_playwright() as playwright:
+        browser = await playwright.chromium.launch(headless=False)
+        page = await browser.new_page()
+        
+        # Create agent
+        agent = ComputerUseAgent(
+            api_key=api_key,
+            page=page
+        )
+        
+        # Navigate and interact
+        await page.goto("https://example.com")
+        result = await agent.execute("What is the title of this page?")
+        print(result)
+        
+        await browser.close()
+
+asyncio.run(main())
+```
+
+## Usage
+
+### Basic Text Responses
+
+```python
+# Simple queries return text
+result = await agent.execute("Describe what you see on this page")
+print(result)  # "This page contains a header with..."
+```
+
+### Structured Data with Pydantic
+
+```python
+from pydantic import BaseModel
+
+class ProductInfo(BaseModel):
+    name: str
+    price: float
+    in_stock: bool
+
+# Get structured data back
+product = await agent.execute(
+    "Find the main product on this page and extract its details",
+    schema=ProductInfo
+)
+print(f"Product: {product.name}, Price: ${product.price}")
+```
+
+### Advanced Options
+
+```python
+result = await agent.execute(
+    "Fill out the contact form with realistic data",
+    system_prompt_suffix="Be extra careful with form validation",
+    thinking_budget=2048  # More reasoning tokens
+)
+```
+
+## API Reference
+
+### ComputerUseAgent
+
+The main class for browser automation with Claude.
+
+#### Constructor
+
+```python
+ComputerUseAgent(
+    api_key: str,              # Anthropic API key
+    page: Page,                # Playwright page instance
+    model: str = "claude-sonnet-4-20250514"  # Claude model to use
+)
+```
+
+#### execute()
+
+Execute a computer use task with Claude.
+
+```python
+async def execute(
+    query: str,                           # Task description
+    *,
+    schema: Optional[Type[BaseModel]] = None,  # Pydantic model for structured responses
+    system_prompt_suffix: str = "",       # Additional system instructions
+    thinking_budget: int = 1024           # Token budget for Claude's reasoning
+) -> Union[str, BaseModel]
+```
+
+**Parameters:**
+- `query`: Natural language description of what you want Claude to do
+- `schema`: Optional Pydantic model class for structured responses
+- `system_prompt_suffix`: Additional instructions appended to the system prompt
+- `thinking_budget`: Token budget for Claude's internal reasoning process
+
+**Returns:**
+- `str`: When no schema is provided
+- `BaseModel`: Instance of the provided schema class when schema is specified
+
+## Examples
+
+See [example.py](example.py) for comprehensive usage examples including:
+
+- Basic page interactions
+- Structured data extraction with Pydantic models
+- Complex multi-step workflows
+- Custom system prompts
+
+## Requirements
+
+- Python 3.9+
+- An Anthropic API key ([get one here](https://console.anthropic.com/))
+- Playwright browsers installed
+
+## Model Compatibility
+
+This library works with Anthropic's Computer Use compatible models:
+
+- `claude-sonnet-4-20250514` (recommended)
+- Other Computer Use enabled models
+
+See [Anthropic's documentation](https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/computer-use-tool#model-compatibility) for the latest model compatibility information.
+
+## Related Projects
+
+- [cu-playwright-ts](https://github.com/anthropics/cu-playwright-ts) - TypeScript version
+- [Anthropic Computer Use Demo](https://github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo)
+
+## License
+
+MIT - see [LICENSE](LICENSE) for details.
+
+## Contributing
+
+Contributions are welcome! Please feel free to submit a Pull Request.
\ No newline at end of file
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..d562c86
--- /dev/null
+++ b/__init__.py
@@ -0,0 +1,11 @@
+"""
+cu-playwright-python: Computer Use Agent for Python
+
+A Python library for automating browser interactions with Claude using Anthropic's Computer Use capabilities.
+"""
+
+from .agent import ComputerUseAgent
+from .tools import ToolVersion
+
+__version__ = "0.1.0"
+__all__ = ["ComputerUseAgent", "ToolVersion"]
diff --git a/agent.py b/agent.py
new file mode 100644
index 0000000..0d8bd51
--- /dev/null
+++ b/agent.py
@@ -0,0 +1,175 @@
+"""
+Computer Use Agent for automating browser interactions with Claude
+
+This agent provides a clean interface to Anthropic's Computer Use capabilities,
+allowing Claude to interact with web pages through Playwright.
+
+See: https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/computer-use-tool
+"""
+
+import json
+import re
+from typing import Any, Dict, List, Optional, Type, TypeVar, Union
+from playwright.async_api import Page
+from pydantic import BaseModel, ValidationError
+
+from loop import sampling_loop
+
+
+T = TypeVar("T", bound=BaseModel)
+
+
+class ComputerUseAgent:
+    """
+    Computer Use Agent for automating browser interactions with Claude
+
+    This agent provides a clean interface to Anthropic's Computer Use capabilities,
+    allowing Claude to interact with web pages through Playwright.
+
+    See: https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/computer-use-tool
+    """
+
+    def __init__(
+        self, *, api_key: str, page: Page, model: str = "claude-sonnet-4-20250514"
+    ):
+        """
+        Create a new ComputerUseAgent instance
+
+        Args:
+            api_key: Anthropic API key (get one from https://console.anthropic.com/)
+            page: Playwright page instance to control
+            model: Anthropic model to use (defaults to claude-sonnet-4-20250514)
+
+        See: https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/computer-use-tool#model-compatibility
+        """
+        self.api_key = api_key
+        self.model = model
+        self.page = page
+
+    async def execute(
+        self,
+        query: str,
+        schema: Optional[Type[T]] = None,
+        *,
+        system_prompt_suffix: str = "",
+        thinking_budget: int = 1024,
+    ) -> Union[str, T]:
+        """
+        Execute a computer use task with Claude
+
+        This method can return either text responses or structured data validated against a Pydantic schema.
+
+        Args:
+            query: The task description for Claude to execute
+            schema: Optional Pydantic model class for structured responses
+            system_prompt_suffix: Additional instructions appended to the system prompt
+            thinking_budget: Token budget for Claude's internal reasoning (default: 1024)
+
+        Returns:
+            Either a string (when no schema) or validated data of the schema type
+
+        Example:
+            ```python
+            # Text response
+            result = await agent.execute('Tell me the page title')
+
+            # Structured response
+            class UserInfo(BaseModel):
+                name: str
+                age: int
+
+            data = await agent.execute(
+                'Get user info',
+                UserInfo
+            )
+            ```
+
+        See: https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking
+        """
+        # Prepare query with schema instructions if schema is provided
+        final_query = query
+        if schema:
+            schema_json = schema.model_json_schema()
+            final_query = f"""{query}
+
+Please respond with a valid JSON object that matches this JSON Schema:
+```json
+{json.dumps(schema_json, indent=2)}
+```
+
+Respond ONLY with the JSON object, no additional text."""
+
+        # Execute the computer use loop
+        messages = await sampling_loop(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": final_query,
+                }
+            ],
+            api_key=self.api_key,
+            system_prompt_suffix=system_prompt_suffix,
+            thinking_budget=thinking_budget,
+            playwright_page=self.page,
+        )
+
+        if not messages:
+            raise ValueError("No response received")
+
+        last_message = messages[-1]
+        if not last_message:
+            raise ValueError("No response received")
+
+        response = self._extract_text_from_message(last_message)
+
+        # If no schema provided, return string response
+        if not schema:
+            return response
+
+        # Parse and validate structured response
+        parsed_data = self._parse_json_response(response)
+        return schema.model_validate(parsed_data)
+
+    def _extract_text_from_message(self, message: Dict[str, Any]) -> str:
+        """Extract text content from a message"""
+        content = message.get("content", "")
+
+        if isinstance(content, str):
+            return content
+
+        if isinstance(content, list):
+            return "".join(
+                block.get("text", "")
+                for block in content
+                if isinstance(block, dict) and block.get("type") == "text"
+            )
+
+        return ""
+
+    def _parse_json_response(self, response: str) -> Dict[str, Any]:
+        """Parse JSON from response text"""
+        # Example: "Here's the data:\n```json\n{\"name\": \"John\", \"age\": 30}\n```\nHope this helps!"
+        # Example: "```\n{\"status\": \"success\"}\n```"
+        json_match = re.search(r"```(?:json)?\s*\n?([\s\S]*?)\n?```", response)
+        if json_match:
+            try:
+                return json.loads(json_match.group(1).strip())
+            except json.JSONDecodeError:
+                pass
+
+        # Example: "The user data is {\"name\": \"John\", \"age\": 30} as requested."
+        # Example: "Result: {\"items\": [1, 2, 3], \"total\": 3}"
+        object_match = re.search(r"\{[\s\S]*\}", response)
+        if object_match:
+            try:
+                return json.loads(object_match.group(0))
+            except json.JSONDecodeError:
+                pass
+
+        # Example: "{\"name\": \"John\", \"age\": 30}" (clean JSON response)
+        # Example: "  {\"status\": \"ok\"}  " (JSON with whitespace)
+        try:
+            return json.loads(response.strip())
+        except json.JSONDecodeError as e:
+            raise ValueError(f"Could not parse JSON from response: {e}")
diff --git a/example.py b/example.py
new file mode 100644
index 0000000..720db9c
--- /dev/null
+++ b/example.py
@@ -0,0 +1,128 @@
+"""
+Example usage of cu-playwright-python
+
+This example demonstrates how to use the ComputerUseAgent to automate browser interactions.
+"""
+
+import asyncio
+import os
+from typing import List
+from pydantic import BaseModel
+from playwright.async_api import async_playwright
+
+from agent import ComputerUseAgent
+
+
+class HackerNewsStory(BaseModel):
+    """Pydantic model for a Hacker News story"""
+
+    title: str
+    points: int
+    author: str
+    comments: int
+    url: str = ""
+
+
+class PageInfo(BaseModel):
+    """Pydantic model for page information"""
+
+    title: str
+    total_stories: int
+    current_page: int
+
+
+async def text_response_example():
+    """Example of text responses"""
+    ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
+    if not ANTHROPIC_API_KEY:
+        raise ValueError("ANTHROPIC_API_KEY environment variable is required")
+
+    async with async_playwright() as playwright:
+        browser = await playwright.chromium.launch(headless=False)
+        page = await browser.new_page()
+        await page.goto("https://news.ycombinator.com/")
+
+        try:
+            print("\n=== Text Response Examples ===")
+            agent = ComputerUseAgent(
+                api_key=ANTHROPIC_API_KEY,
+                page=page,
+            )
+
+            # Text response with action
+            top_story = await agent.execute(
+                "Tell me the title of the top story on this page"
+            )
+            print("Top story:", top_story)
+
+            # Text response with multiple pieces of information
+            summary = await agent.execute(
+                "Give me a brief summary of the top 3 stories"
+            )
+            print("Summary:", summary)
+
+        except Exception as error:
+            print(f"Error in text response example: {error}")
+        finally:
+            await browser.close()
+
+
+async def structured_response_example():
+    """Example of structured responses with Pydantic models"""
+    ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
+    if not ANTHROPIC_API_KEY:
+        raise ValueError("ANTHROPIC_API_KEY environment variable is required")
+
+    async with async_playwright() as playwright:
+        browser = await playwright.chromium.launch(headless=False)
+        page = await browser.new_page()
+        await page.goto("https://news.ycombinator.com/")
+
+        try:
+            print("\n=== Structured Response Examples ===")
+            agent = ComputerUseAgent(
+                api_key=ANTHROPIC_API_KEY,
+                page=page,
+            )
+
+            # Get multiple stories with structured data
+            class StoriesList(BaseModel):
+                stories: List[HackerNewsStory]
+
+            stories_data = await agent.execute(
+                "Get the top 5 stories with their titles, points, authors, and comment counts",
+                schema=StoriesList,
+            )
+            print("Structured stories:")
+            for story in stories_data.stories[:5]:  # Limit to 5 stories
+                print(
+                    f"  - {story.title} ({story.points} points by {story.author}, {story.comments} comments)"
+                )
+
+            # Get page information with structured data
+            page_info = await agent.execute(
+                "Get information about this page including its title, total number of stories visible, and current page number",
+                schema=PageInfo,
+            )
+            print(
+                f"Page info: {page_info.title}, {page_info.total_stories} stories, page {page_info.current_page}"
+            )
+
+        except Exception as error:
+            print(f"Error in structured response example: {error}")
+        finally:
+            await browser.close()
+
+
+async def run_examples():
+    """Run all examples"""
+    print("Running Computer Use Agent Examples...")
+
+    await text_response_example()
+    await structured_response_example()
+
+    print("\nAll examples completed!")
+
+
+if __name__ == "__main__":
+    asyncio.run(run_examples())
diff --git a/loop.py b/loop.py
new file mode 100644
index 0000000..f575283
--- /dev/null
+++ b/loop.py
@@ -0,0 +1,343 @@
+"""
+Agentic sampling loop that calls the Anthropic API and local implementation of anthropic-defined computer use tools.
+From https://github.com/anthropics/anthropic-quickstarts/blob/main/computer-use-demo/computer_use_demo/loop.py
+"""
+
+import os
+import platform
+from collections.abc import Callable
+from datetime import datetime
+from enum import StrEnum
+from typing import Any, cast
+from playwright.async_api import Page
+
+import httpx
+from anthropic import (
+    Anthropic,
+    AnthropicBedrock,
+    AnthropicVertex,
+    APIError,
+    APIResponseValidationError,
+    APIStatusError,
+)
+from anthropic.types.beta import (
+    BetaCacheControlEphemeralParam,
+    BetaContentBlockParam,
+    BetaImageBlockParam,
+    BetaMessage,
+    BetaMessageParam,
+    BetaTextBlock,
+    BetaTextBlockParam,
+    BetaToolResultBlockParam,
+    BetaToolUseBlockParam,
+)
+
+from tools import (
+    TOOL_GROUPS_BY_VERSION,
+    ToolCollection,
+    ToolResult,
+    ToolVersion,
+)
+
+PROMPT_CACHING_BETA_FLAG = "prompt-caching-2024-07-31"
+
+
+class APIProvider(StrEnum):
+    ANTHROPIC = "anthropic"
+
+
+# This system prompt is optimized for the Docker environment in this repository and
+# specific tool combinations enabled.
+# We encourage modifying this system prompt to ensure the model has context for the
+# environment it is running in, and to provide any additional information that may be
+# helpful for the task at hand.
+SYSTEM_PROMPT = f"""<SYSTEM_CAPABILITY>
+* You are utilising an Ubuntu virtual machine using {os.uname().machine} architecture with internet access.
+* When you connect to the display, CHROMIUM IS ALREADY OPEN. The url bar is not visible but it is there.
+* If you need to navigate to a new page, use ctrl+l to focus the url bar and then enter the url.
+* You won't be able to see the url bar from the screenshot but ctrl-l still works.
+* As the initial step click on the search bar.
+* When viewing a page it can be helpful to zoom out so that you can see everything on the page.
+* Either that, or make sure you scroll down to see everything before deciding something isn't available.
+* When using your computer function calls, they take a while to run and send back to you.
+* Where possible/feasible, try to chain multiple of these calls all into one function calls request.
+* The current date is {datetime.now().strftime("%A, %B %d, %Y")}.
+* After each step, take a screenshot and carefully evaluate if you have achieved the right outcome.
+* Explicitly show your thinking: "I have evaluated step X..." If not correct, try again.
+* Only when you confirm a step was executed correctly should you move on to the next one.
+</SYSTEM_CAPABILITY>
+
+<IMPORTANT>
+* When using Chromium, if a startup wizard appears, IGNORE IT. Do not even click "skip this step".
+* Instead, click on the search bar on the center of the screen where it says "Search or enter address", and enter the appropriate search term or URL there.
+</IMPORTANT>"""
+
+
+async def sampling_loop(
+    *,
+    model: str,
+    messages: list[BetaMessageParam],
+    api_key: str,
+    provider: APIProvider = APIProvider.ANTHROPIC,
+    system_prompt_suffix: str = "",
+    only_n_most_recent_images: int | None = None,
+    max_tokens: int = 4096,
+    tool_version: ToolVersion = "computer_use_20250124",
+    thinking_budget: int | None = None,
+    token_efficient_tools_beta: bool = False,
+    playwright_page: Page,
+):
+    """
+    Agentic sampling loop for the assistant/tool interaction of computer use.
+
+    Args:
+        model: The model to use for the API call
+        messages: The conversation history
+        api_key: The API key for authentication
+        provider: The API provider (defaults to ANTHROPIC)
+        system_prompt_suffix: Additional system prompt text (defaults to empty string)
+        only_n_most_recent_images: Optional limit on number of recent images to keep
+        max_tokens: Maximum tokens for the response (defaults to 4096)
+        tool_version: Version of tools to use (defaults to V20250124)
+        thinking_budget: Optional token budget for thinking
+        token_efficient_tools_beta: Whether to use token efficient tools beta
+        playwright_page: The Playwright page instance for browser automation
+    """
+    tool_group = TOOL_GROUPS_BY_VERSION[tool_version]
+    tool_collection = ToolCollection(
+        *(
+            ToolCls(
+                page=(
+                    playwright_page
+                    if ToolCls.__name__.startswith("ComputerTool")
+                    else None
+                )
+            )
+            for ToolCls in tool_group.tools
+        )
+    )
+    system = BetaTextBlockParam(
+        type="text",
+        text=f"{SYSTEM_PROMPT}{' ' + system_prompt_suffix if system_prompt_suffix else ''}",
+    )
+
+    while True:
+        enable_prompt_caching = False
+        betas = [tool_group.beta_flag] if tool_group.beta_flag else []
+        if token_efficient_tools_beta:
+            betas.append("token-efficient-tools-2025-02-19")
+        image_truncation_threshold = only_n_most_recent_images or 0
+        client = Anthropic(api_key=api_key, max_retries=4)
+        enable_prompt_caching = True
+
+        if enable_prompt_caching:
+            betas.append(PROMPT_CACHING_BETA_FLAG)
+            _inject_prompt_caching(messages)
+            # Because cached reads are 10% of the price, we don't think it's
+            # ever sensible to break the cache by truncating images
+            only_n_most_recent_images = 0
+            # Use type ignore to bypass TypedDict check until SDK types are updated
+            system["cache_control"] = {"type": "ephemeral"}  # type: ignore
+
+        if only_n_most_recent_images:
+            _maybe_filter_to_n_most_recent_images(
+                messages,
+                only_n_most_recent_images,
+                min_removal_threshold=image_truncation_threshold,
+            )
+        extra_body = {}
+        if thinking_budget:
+            # Ensure we only send the required fields for thinking
+            extra_body = {
+                "thinking": {"type": "enabled", "budget_tokens": thinking_budget}
+            }
+
+        # Call the API
+        response = client.beta.messages.create(
+            max_tokens=max_tokens,
+            messages=messages,
+            model=model,
+            system=[system],
+            tools=tool_collection.to_params(),
+            betas=betas,
+            extra_body=extra_body,
+        )
+
+        response_params = _response_to_params(response)
+        messages.append(
+            {
+                "role": "assistant",
+                "content": response_params,
+            }
+        )
+
+        loggable_content = [
+            {
+                "text": block.get("text", "") or block.get("thinking", ""),
+                "input": block.get("input", ""),
+            }
+            for block in response_params
+        ]
+        print("=== LLM RESPONSE ===")
+        print("Stop reason:", response.stop_reason)
+        print(loggable_content)
+        print("===")
+
+        if response.stop_reason == "end_turn":
+            print("LLM has completed its task, ending loop")
+            return messages
+
+        tool_result_content: list[BetaToolResultBlockParam] = []
+        for content_block in response_params:
+            if content_block["type"] == "tool_use":
+                result = await tool_collection.run(
+                    name=content_block["name"],
+                    tool_input=cast(dict[str, Any], content_block["input"]),
+                )
+                tool_result_content.append(
+                    _make_api_tool_result(result, content_block["id"])
+                )
+
+        if not tool_result_content:
+            return messages
+
+        messages.append({"content": tool_result_content, "role": "user"})
+
+
+def _maybe_filter_to_n_most_recent_images(
+    messages: list[BetaMessageParam],
+    images_to_keep: int,
+    min_removal_threshold: int,
+):
+    """
+    With the assumption that images are screenshots that are of diminishing value as
+    the conversation progresses, remove all but the final `images_to_keep` tool_result
+    images in place, with a chunk of min_removal_threshold to reduce the amount we
+    break the implicit prompt cache.
+    """
+    if images_to_keep is None:
+        return messages
+
+    tool_result_blocks = cast(
+        list[BetaToolResultBlockParam],
+        [
+            item
+            for message in messages
+            for item in (
+                message["content"] if isinstance(message["content"], list) else []
+            )
+            if isinstance(item, dict) and item.get("type") == "tool_result"
+        ],
+    )
+
+    total_images = sum(
+        1
+        for tool_result in tool_result_blocks
+        for content in tool_result.get("content", [])
+        if isinstance(content, dict) and content.get("type") == "image"
+    )
+
+    images_to_remove = total_images - images_to_keep
+    # for better cache behavior, we want to remove in chunks
+    images_to_remove -= images_to_remove % min_removal_threshold
+
+    for tool_result in tool_result_blocks:
+        if isinstance(tool_result.get("content"), list):
+            new_content = []
+            for content in tool_result.get("content", []):
+                if isinstance(content, dict) and content.get("type") == "image":
+                    if images_to_remove > 0:
+                        images_to_remove -= 1
+                        continue
+                new_content.append(content)
+            tool_result["content"] = new_content
+
+
+def _response_to_params(
+    response: BetaMessage,
+) -> list[BetaContentBlockParam]:
+    res: list[BetaContentBlockParam] = []
+    for block in response.content:
+        if isinstance(block, BetaTextBlock):
+            if block.text:
+                res.append(BetaTextBlockParam(type="text", text=block.text))
+            elif getattr(block, "type", None) == "thinking":
+                # Handle thinking blocks - include signature field
+                thinking_block = {
+                    "type": "thinking",
+                    "thinking": getattr(block, "thinking", None),
+                }
+                if hasattr(block, "signature"):
+                    thinking_block["signature"] = getattr(block, "signature", None)
+                res.append(cast(BetaContentBlockParam, thinking_block))
+        else:
+            # Handle tool use blocks normally
+            res.append(cast(BetaToolUseBlockParam, block.model_dump()))
+    return res
+
+
+def _inject_prompt_caching(
+    messages: list[BetaMessageParam],
+):
+    """
+    Set cache breakpoints for the 3 most recent turns
+    one cache breakpoint is left for tools/system prompt, to be shared across sessions
+    """
+
+    breakpoints_remaining = 3
+    for message in reversed(messages):
+        if message["role"] == "user" and isinstance(
+            content := message["content"], list
+        ):
+            if breakpoints_remaining:
+                breakpoints_remaining -= 1
+                # Use type ignore to bypass TypedDict check until SDK types are updated
+                content[-1]["cache_control"] = BetaCacheControlEphemeralParam(  # type: ignore
+                    {"type": "ephemeral"}
+                )
+            else:
+                content[-1].pop("cache_control", None)
+                # we'll only every have one extra turn per loop
+                break
+
+
+def _make_api_tool_result(
+    result: ToolResult, tool_use_id: str
+) -> BetaToolResultBlockParam:
+    """Convert an agent ToolResult to an API ToolResultBlockParam."""
+    tool_result_content: list[BetaTextBlockParam | BetaImageBlockParam] | str = []
+    is_error = False
+    if result.error:
+        is_error = True
+        tool_result_content = _maybe_prepend_system_tool_result(result, result.error)
+    else:
+        if result.output:
+            tool_result_content.append(
+                {
+                    "type": "text",
+                    "text": _maybe_prepend_system_tool_result(result, result.output),
+                }
+            )
+        if result.base64_image:
+            tool_result_content.append(
+                {
+                    "type": "image",
+                    "source": {
+                        "type": "base64",
+                        "media_type": "image/png",
+                        "data": result.base64_image,
+                    },
+                }
+            )
+    return {
+        "type": "tool_result",
+        "content": tool_result_content,
+        "tool_use_id": tool_use_id,
+        "is_error": is_error,
+    }
+
+
+def _maybe_prepend_system_tool_result(result: ToolResult, result_text: str):
+    if result.system:
+        result_text = f"<system>{result.system}</system>\n{result_text}"
+    return result_text
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..c907943
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,44 @@
+[project]
+name = "cu-playwright-python"
+version = "0.1.0"
+description = "Computer Use Agent for Python - Browser automation with Claude using Anthropic's Computer Use capabilities"
+requires-python = ">=3.9"
+authors = [
+    { name = "Anthropic Computer Use Team" }
+]
+readme = "README.md"
+license = { text = "MIT" }
+keywords = ["anthropic", "claude", "computer-use", "browser-automation", "playwright", "ai-agent"]
+classifiers = [
+    "Development Status :: 3 - Alpha",
+    "Intended Audience :: Developers",
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+    "Topic :: Internet :: WWW/HTTP :: Browsers",
+]
+dependencies = [
+    "anthropic~=0.52.1",
+    "playwright~=1.52.0",
+    "python-dateutil~=2.8.2",
+    "pydantic~=2.11.5",
+    "typing-extensions~=4.13.2",
+    "httpx~=0.27.0",
+]
+
+[project.urls]
+Homepage = "https://github.com/anthropics/cu-playwright-python"
+Repository = "https://github.com/anthropics/cu-playwright-python"
+Documentation = "https://github.com/anthropics/cu-playwright-python#readme"
+Issues = "https://github.com/anthropics/cu-playwright-python/issues"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["cu_playwright_python"]
diff --git a/tools/__init__.py b/tools/__init__.py
new file mode 100644
index 0000000..3d8ff73
--- /dev/null
+++ b/tools/__init__.py
@@ -0,0 +1,13 @@
+from .base import ToolResult
+from .collection import ToolCollection
+from .computer import ComputerTool20241022, ComputerTool20250124
+from .groups import TOOL_GROUPS_BY_VERSION, ToolVersion
+
+__ALL__ = [
+    ComputerTool20241022,
+    ComputerTool20250124,
+    ToolCollection,
+    ToolResult,
+    ToolVersion,
+    TOOL_GROUPS_BY_VERSION,
+]
diff --git a/tools/base.py b/tools/base.py
new file mode 100644
index 0000000..3d73054
--- /dev/null
+++ b/tools/base.py
@@ -0,0 +1,69 @@
+"""
+From https://github.com/anthropics/anthropic-quickstarts/blob/main/computer-use-demo/computer_use_demo/tools/base.py
+"""
+
+from abc import ABCMeta, abstractmethod
+from dataclasses import dataclass, fields, replace
+from typing import Any
+
+from anthropic.types.beta import BetaToolUnionParam
+
+
+class BaseAnthropicTool(metaclass=ABCMeta):
+    """Abstract base class for Anthropic-defined tools."""
+
+    @abstractmethod
+    def __call__(self, **kwargs) -> Any:
+        """Executes the tool with the given arguments."""
+        ...
+
+    @abstractmethod
+    def to_params(
+        self,
+    ) -> BetaToolUnionParam:
+        raise NotImplementedError
+
+
+@dataclass(kw_only=True, frozen=True)
+class ToolResult:
+    """Represents the result of a tool execution."""
+
+    output: str | None = None
+    error: str | None = None
+    base64_image: str | None = None
+    system: str | None = None
+
+    def __bool__(self):
+        return any(getattr(self, field.name) for field in fields(self))
+
+    def __add__(self, other: "ToolResult"):
+        def combine_fields(
+            field: str | None, other_field: str | None, concatenate: bool = True
+        ):
+            if field and other_field:
+                if concatenate:
+                    return field + other_field
+                raise ValueError("Cannot combine tool results")
+            return field or other_field
+
+        return ToolResult(
+            output=combine_fields(self.output, other.output),
+            error=combine_fields(self.error, other.error),
+            base64_image=combine_fields(self.base64_image, other.base64_image, False),
+            system=combine_fields(self.system, other.system),
+        )
+
+    def replace(self, **kwargs):
+        """Returns a new ToolResult with the given fields replaced."""
+        return replace(self, **kwargs)
+
+
+class ToolFailure(ToolResult):
+    """A ToolResult that represents a failure."""
+
+
+class ToolError(Exception):
+    """Raised when a tool encounters an error."""
+
+    def __init__(self, message):
+        self.message = message
diff --git a/tools/collection.py b/tools/collection.py
new file mode 100644
index 0000000..4691d3e
--- /dev/null
+++ b/tools/collection.py
@@ -0,0 +1,37 @@
+"""
+Collection classes for managing multiple tools.
+From https://github.com/anthropics/anthropic-quickstarts/blob/main/computer-use-demo/computer_use_demo/tools/collection.py
+"""
+
+from typing import Any
+
+from anthropic.types.beta import BetaToolUnionParam
+
+from .base import (
+    BaseAnthropicTool,
+    ToolError,
+    ToolFailure,
+    ToolResult,
+)
+
+
+class ToolCollection:
+    """A collection of anthropic-defined tools."""
+
+    def __init__(self, *tools: BaseAnthropicTool):
+        self.tools = tools
+        self.tool_map = {tool.to_params()["name"]: tool for tool in tools}
+
+    def to_params(
+        self,
+    ) -> list[BetaToolUnionParam]:
+        return [tool.to_params() for tool in self.tools]
+
+    async def run(self, *, name: str, tool_input: dict[str, Any]) -> ToolResult:
+        tool = self.tool_map.get(name)
+        if not tool:
+            return ToolFailure(error=f"Tool {name} is invalid")
+        try:
+            return await tool(**tool_input)
+        except ToolError as e:
+            return ToolFailure(error=e.message)
diff --git a/tools/computer.py b/tools/computer.py
new file mode 100644
index 0000000..406c30e
--- /dev/null
+++ b/tools/computer.py
@@ -0,0 +1,413 @@
+"""
+Modified from https://github.com/anthropics/anthropic-quickstarts/blob/main/computer-use-demo/computer_use_demo/tools/computer.py
+Replaces xdotool and gnome-screenshot with Playwright.
+"""
+
+import asyncio
+import base64
+import os
+from enum import StrEnum
+from typing import Literal, TypedDict, cast, get_args
+
+from playwright.async_api import Page
+
+from anthropic.types.beta import BetaToolComputerUse20241022Param, BetaToolUnionParam
+
+from .base import BaseAnthropicTool, ToolError, ToolResult
+
+TYPING_DELAY_MS = 12
+TYPING_GROUP_SIZE = 50
+
+# Map alternative names to standard Playwright modifier keys
+MODIFIER_KEY_MAP = {
+    "ctrl": "Control",
+    "alt": "Alt",
+    "cmd": "Meta",
+    "command": "Meta",
+    "win": "Meta",
+}
+
+# Essential key mappings for Playwright compatibility
+KEY_MAP = {
+    "return": "Enter",
+    "space": " ",
+    "left": "ArrowLeft",
+    "right": "ArrowRight",
+    "up": "ArrowUp",
+    "down": "ArrowDown",
+    "home": "Home",
+    "end": "End",
+    "pageup": "PageUp",
+    "page_up": "PageUp",
+    "pagedown": "PageDown",
+    "page_down": "PageDown",
+    "delete": "Delete",
+    "backspace": "Backspace",
+    "tab": "Tab",
+    "esc": "Escape",
+    "escape": "Escape",
+    "insert": "Insert",
+    "super_l": "Meta",
+    "f1": "F1",
+    "f2": "F2",
+    "f3": "F3",
+    "f4": "F4",
+    "f5": "F5",
+    "f6": "F6",
+    "f7": "F7",
+    "f8": "F8",
+    "f9": "F9",
+    "f10": "F10",
+    "f11": "F11",
+    "f12": "F12",
+    "minus": "-",
+    "equal": "=",
+    "plus": "+",
+}
+
+Action_20241022 = Literal[
+    "key",
+    "type",
+    "mouse_move",
+    "left_click",
+    "left_click_drag",
+    "right_click",
+    "middle_click",
+    "double_click",
+    "screenshot",
+    "cursor_position",
+]
+
+Action_20250124 = (
+    Action_20241022
+    | Literal[
+        "left_mouse_down",
+        "left_mouse_up",
+        "scroll",
+        "hold_key",
+        "wait",
+        "triple_click",
+    ]
+)
+
+ScrollDirection = Literal["up", "down", "left", "right"]
+
+# Map Playwright mouse buttons to our actions
+MOUSE_BUTTONS = {
+    "left_click": "left",
+    "right_click": "right",
+    "middle_click": "middle",
+}
+
+
+class ComputerToolOptions(TypedDict):
+    display_height_px: int
+    display_width_px: int
+    display_number: int | None
+
+
+def chunks(s: str, chunk_size: int) -> list[str]:
+    return [s[i : i + chunk_size] for i in range(0, len(s), chunk_size)]
+
+
+class BaseComputerTool:
+    """
+    A tool that allows the agent to interact with the screen, keyboard, and mouse using Playwright.
+    The tool parameters are defined by Anthropic and are not editable.
+    """
+
+    name: Literal["computer"] = "computer"
+    width: int = 1280
+    height: int = 720
+    display_num: int | None = None
+    page: Page | None = None
+
+    _screenshot_delay = 2.0
+
+    @property
+    def options(self) -> ComputerToolOptions:
+        return {
+            "display_width_px": self.width,
+            "display_height_px": self.height,
+            "display_number": self.display_num,
+        }
+
+    def __init__(self, page: Page | None = None):
+        super().__init__()
+        self.page = page
+
+    def validate_coordinates(
+        self, coordinate: tuple[int, int] | list[int] | None = None
+    ) -> tuple[int, int] | None:
+        """Validate that coordinates are non-negative integers and convert lists to tuples if needed."""
+        if coordinate is None:
+            return None
+
+        # Convert list to tuple if needed
+        if isinstance(coordinate, list):
+            coordinate = tuple(coordinate)
+
+        if not isinstance(coordinate, tuple) or len(coordinate) != 2:
+            raise ToolError(f"{coordinate} must be a tuple or list of length 2")
+
+        x, y = coordinate
+        if not isinstance(x, int) or not isinstance(y, int) or x < 0 or y < 0:
+            raise ToolError(
+                f"{coordinate} must be a tuple or list of non-negative ints"
+            )
+
+        return coordinate
+
+    def map_key(self, key: str) -> str:
+        """Map a key to its Playwright equivalent."""
+        # Handle modifier keys
+        if key.lower() in MODIFIER_KEY_MAP:
+            return MODIFIER_KEY_MAP[key.lower()]
+
+        # Handle special keys
+        if key.lower() in KEY_MAP:
+            return KEY_MAP[key.lower()]
+
+        # Handle key combinations (e.g. "ctrl+a")
+        if "+" in key:
+            parts = key.split("+")
+            if len(parts) == 2:
+                modifier, main_key = parts
+                mapped_modifier = MODIFIER_KEY_MAP.get(modifier.lower(), modifier)
+                mapped_key = KEY_MAP.get(main_key.lower(), main_key)
+                return f"{mapped_modifier}+{mapped_key}"
+
+        # Return the key as is if no mapping exists
+        return key
+
+    async def __call__(
+        self,
+        *,
+        action: Action_20241022,
+        text: str | None = None,
+        coordinate: tuple[int, int] | list[int] | None = None,
+        **kwargs,
+    ):
+        if not self.page:
+            raise ToolError("Playwright page not initialized")
+
+        if action in ("mouse_move", "left_click_drag"):
+            if coordinate is None:
+                raise ToolError(f"coordinate is required for {action}")
+            if text is not None:
+                raise ToolError(f"text is not accepted for {action}")
+
+            coordinate = self.validate_coordinates(coordinate)
+            x, y = coordinate
+
+            if action == "mouse_move":
+                await self.page.mouse.move(x, y)
+                return await self.screenshot()
+            elif action == "left_click_drag":
+                await self.page.mouse.down(button="left")
+                await self.page.mouse.move(x, y)
+                await self.page.mouse.up(button="left")
+                return await self.screenshot()
+
+        if action in ("key", "type"):
+            if text is None:
+                raise ToolError(f"text is required for {action}")
+            if coordinate is not None:
+                raise ToolError(f"coordinate is not accepted for {action}")
+            if not isinstance(text, str):
+                raise ToolError(output=f"{text} must be a string")
+
+            if action == "key":
+                mapped_key = self.map_key(text)
+                await self.page.keyboard.press(mapped_key)
+                return await self.screenshot()
+            elif action == "type":
+                results: list[ToolResult] = []
+                for chunk in chunks(text, TYPING_GROUP_SIZE):
+                    await self.page.keyboard.type(chunk, delay=TYPING_DELAY_MS)
+                    results.append(await self.screenshot())
+                return ToolResult(
+                    output="".join(result.output or "" for result in results),
+                    error="".join(result.error or "" for result in results),
+                    base64_image=results[-1].base64_image if results else None,
+                )
+
+        if action in (
+            "left_click",
+            "right_click",
+            "double_click",
+            "middle_click",
+            "screenshot",
+            "cursor_position",
+        ):
+            if text is not None:
+                raise ToolError(f"text is not accepted for {action}")
+
+            if action == "screenshot":
+                return await self.screenshot()
+            elif action == "cursor_position":
+                # Playwright doesn't provide a direct way to get cursor position
+                # We'll return a placeholder since this isn't critical functionality
+                return ToolResult(output="Cursor position not available in Playwright")
+            else:
+                if coordinate is not None:
+                    coordinate = self.validate_coordinates(coordinate)
+                    x, y = coordinate
+                    await self.page.mouse.move(x, y)
+
+                if action == "double_click":
+                    await self.page.mouse.dblclick(x, y)
+                else:
+                    await self.page.mouse.click(x, y, button=MOUSE_BUTTONS[action])
+                return await self.screenshot()
+
+        raise ToolError(f"Invalid action: {action}")
+
+    async def screenshot(self):
+        """Take a screenshot using Playwright and return the base64 encoded image."""
+        if not self.page:
+            raise ToolError("Playwright page not initialized")
+
+        # Take screenshot using Playwright and get the buffer directly
+        screenshot_bytes = await self.page.screenshot(type="png")
+        return ToolResult(base64_image=base64.b64encode(screenshot_bytes).decode())
+
+
+class ComputerTool20241022(BaseComputerTool, BaseAnthropicTool):
+    api_type: Literal["computer_20241022"] = "computer_20241022"
+
+    def to_params(self) -> BetaToolComputerUse20241022Param:
+        return {"name": self.name, "type": self.api_type, **self.options}
+
+
+class ComputerTool20250124(BaseComputerTool, BaseAnthropicTool):
+    api_type: Literal["computer_20250124"] = "computer_20250124"
+
+    def to_params(self):
+        return cast(
+            BetaToolUnionParam,
+            {"name": self.name, "type": self.api_type, **self.options},
+        )
+
+    async def __call__(
+        self,
+        *,
+        action: Action_20250124,
+        text: str | None = None,
+        coordinate: tuple[int, int] | list[int] | None = None,
+        scroll_direction: ScrollDirection | None = None,
+        scroll_amount: int | None = None,
+        duration: int | float | None = None,
+        key: str | None = None,
+        **kwargs,
+    ):
+        if not self.page:
+            raise ToolError("Playwright page not initialized")
+
+        if action in ("left_mouse_down", "left_mouse_up"):
+            if coordinate is not None:
+                raise ToolError(f"coordinate is not accepted for {action=}.")
+            if action == "left_mouse_down":
+                await self.page.mouse.down(button="left")
+            else:
+                await self.page.mouse.up(button="left")
+            return await self.screenshot()
+
+        if action == "scroll":
+            if scroll_direction is None or scroll_direction not in get_args(
+                ScrollDirection
+            ):
+                raise ToolError(
+                    f"{scroll_direction=} must be 'up', 'down', 'left', or 'right'"
+                )
+            if not isinstance(scroll_amount, int) or scroll_amount < 0:
+                raise ToolError(f"{scroll_amount=} must be a non-negative int")
+
+            if coordinate is not None:
+                coordinate = self.validate_coordinates(coordinate)
+                x, y = coordinate
+                await self.page.mouse.move(x, y)
+
+            # Map scroll directions to Playwright's wheel events
+            page_dimensions = await self.page.evaluate(
+                "() => Promise.resolve({ h: window.innerHeight, w: window.innerWidth })"
+            )
+            page_partitions = 25
+            scroll_factor = scroll_amount / page_partitions
+            page_width = page_dimensions["w"]
+            page_height = page_dimensions["h"]
+
+            delta_x = 0
+            delta_y = 0
+            if scroll_direction == "up":
+                delta_y = -scroll_factor * page_height
+            elif scroll_direction == "down":
+                delta_y = scroll_factor * page_height
+            elif scroll_direction == "left":
+                delta_x = -scroll_factor * page_width
+            elif scroll_direction == "right":
+                delta_x = scroll_factor * page_width
+
+            print(
+                f"Scrolling {abs(delta_x) if delta_x != 0 else abs(delta_y):.02f} pixels {scroll_direction}"
+            )
+
+            await self.page.mouse.wheel(delta_x=delta_x, delta_y=delta_y)
+            return await self.screenshot()
+
+        if action in ("hold_key", "wait"):
+            if duration is None or not isinstance(duration, (int, float)):
+                raise ToolError(f"{duration=} must be a number")
+            if duration < 0:
+                raise ToolError(f"{duration=} must be non-negative")
+            if duration > 100:
+                raise ToolError(f"{duration=} is too long.")
+
+            if action == "hold_key":
+                if text is None:
+                    raise ToolError(f"text is required for {action}")
+                mapped_key = self.map_key(text)
+                await self.page.keyboard.down(mapped_key)
+                await asyncio.sleep(duration)
+                await self.page.keyboard.up(mapped_key)
+                return await self.screenshot()
+
+            if action == "wait":
+                await asyncio.sleep(duration)
+                return await self.screenshot()
+
+        if action in (
+            "left_click",
+            "right_click",
+            "double_click",
+            "triple_click",
+            "middle_click",
+        ):
+            if text is not None:
+                raise ToolError(f"text is not accepted for {action}")
+
+            if coordinate is not None:
+                coordinate = self.validate_coordinates(coordinate)
+                x, y = coordinate
+                await self.page.mouse.move(x, y)
+
+            if key:
+                mapped_key = self.map_key(key)
+                await self.page.keyboard.down(mapped_key)
+
+            if action == "triple_click":
+                # Playwright doesn't have triple click, so we'll simulate it
+                await self.page.mouse.click(x, y, click_count=3)
+            elif action == "double_click":
+                await self.page.mouse.dblclick(x, y)
+            else:
+                await self.page.mouse.click(x, y, button=MOUSE_BUTTONS[action])
+
+            if key:
+                await self.page.keyboard.up(mapped_key)
+
+            return await self.screenshot()
+
+        return await super().__call__(
+            action=action, text=text, coordinate=coordinate, key=key, **kwargs
+        )
diff --git a/tools/groups.py b/tools/groups.py
new file mode 100644
index 0000000..2fc714b
--- /dev/null
+++ b/tools/groups.py
@@ -0,0 +1,44 @@
+"""
+From https://github.com/anthropics/anthropic-quickstarts/blob/main/computer-use-demo/computer_use_demo/tools/groups.py
+"""
+
+from dataclasses import dataclass
+from typing import Literal
+
+from .base import BaseAnthropicTool
+from .computer import ComputerTool20241022, ComputerTool20250124
+
+ToolVersion = Literal[
+    "computer_use_20250124", "computer_use_20241022", "computer_use_20250429"
+]
+BetaFlag = Literal[
+    "computer-use-2024-10-22", "computer-use-2025-01-24", "computer-use-2025-04-29"
+]
+
+
+@dataclass(frozen=True, kw_only=True)
+class ToolGroup:
+    version: ToolVersion
+    tools: list[type[BaseAnthropicTool]]
+    beta_flag: BetaFlag | None = None
+
+
+TOOL_GROUPS: list[ToolGroup] = [
+    ToolGroup(
+        version="computer_use_20241022",
+        tools=[ComputerTool20241022],
+        beta_flag="computer-use-2024-10-22",
+    ),
+    ToolGroup(
+        version="computer_use_20250124",
+        tools=[ComputerTool20250124],
+        beta_flag="computer-use-2025-01-24",
+    ),
+    ToolGroup(
+        version="computer_use_20250429",
+        tools=[ComputerTool20250124],
+        beta_flag="computer-use-2025-01-24",
+    ),
+]
+
+TOOL_GROUPS_BY_VERSION = {tool_group.version: tool_group for tool_group in TOOL_GROUPS}
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..2e5f693
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,527 @@
+version = 1
+revision = 2
+requires-python = ">=3.9"
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
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+]
+
+[[package]]
+name = "anthropic"
+version = "0.52.1"
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+    { name = "distro" },
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