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"""
Entrypoint for Gradio, see https://gradio.app/
"""
import platform
import asyncio
import base64
import os
from datetime import datetime
from enum import StrEnum
from functools import partial
from pathlib import Path
from typing import cast, Dict
import gradio as gr
from anthropic import APIResponse
from anthropic.types import TextBlock
from anthropic.types.beta import BetaMessage, BetaTextBlock, BetaToolUseBlock
from anthropic.types.tool_use_block import ToolUseBlock
from computer_use_demo.loop import (
PROVIDER_TO_DEFAULT_MODEL_NAME,
APIProvider,
sampling_loop,
sampling_loop_sync,
)
from computer_use_demo.tools import ToolResult
CONFIG_DIR = Path("~/.anthropic").expanduser()
API_KEY_FILE = CONFIG_DIR / "api_key"
WARNING_TEXT = "⚠️ Security Alert: Never provide access to sensitive accounts or data, as malicious web content can hijack Claude's behavior"
class Sender(StrEnum):
USER = "user"
BOT = "assistant"
TOOL = "tool"
def setup_state(state):
if "messages" not in state:
state["messages"] = []
if "api_key" not in state:
# Try to load API key from file first, then environment
state["api_key"] = load_from_storage("api_key") or os.getenv("ANTHROPIC_API_KEY", "")
if not state["api_key"]:
print("API key not found. Please set it in the environment or storage.")
if "provider" not in state:
state["provider"] = os.getenv("API_PROVIDER", "anthropic") or APIProvider.ANTHROPIC
if "provider_radio" not in state:
state["provider_radio"] = state["provider"]
if "model" not in state:
_reset_model(state)
if "auth_validated" not in state:
state["auth_validated"] = False
if "responses" not in state:
state["responses"] = {}
if "tools" not in state:
state["tools"] = {}
if "only_n_most_recent_images" not in state:
state["only_n_most_recent_images"] = 3 # 10
if "custom_system_prompt" not in state:
state["custom_system_prompt"] = load_from_storage("system_prompt") or ""
# remove if want to use default system prompt
device_os_name = "Windows" if platform.platform == "Windows" else "Mac" if platform.platform == "Darwin" else "Linux"
state["custom_system_prompt"] += f"\n\nNOTE: you are operating a {device_os_name} machine"
if "hide_images" not in state:
state["hide_images"] = False
def _reset_model(state):
state["model"] = PROVIDER_TO_DEFAULT_MODEL_NAME[cast(APIProvider, state["provider"])]
async def main(state):
"""Render loop for Gradio"""
setup_state(state)
return "Setup completed"
def validate_auth(provider: APIProvider, api_key: str | None):
if provider == APIProvider.ANTHROPIC:
if not api_key:
return "Enter your Anthropic API key to continue."
if provider == APIProvider.BEDROCK:
import boto3
if not boto3.Session().get_credentials():
return "You must have AWS credentials set up to use the Bedrock API."
if provider == APIProvider.VERTEX:
import google.auth
from google.auth.exceptions import DefaultCredentialsError
if not os.environ.get("CLOUD_ML_REGION"):
return "Set the CLOUD_ML_REGION environment variable to use the Vertex API."
try:
google.auth.default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
except DefaultCredentialsError:
return "Your google cloud credentials are not set up correctly."
def load_from_storage(filename: str) -> str | None:
"""Load data from a file in the storage directory."""
try:
file_path = CONFIG_DIR / filename
if file_path.exists():
data = file_path.read_text().strip()
if data:
return data
except Exception as e:
print(f"Debug: Error loading {filename}: {e}")
return None
def save_to_storage(filename: str, data: str) -> None:
"""Save data to a file in the storage directory."""
try:
CONFIG_DIR.mkdir(parents=True, exist_ok=True)
file_path = CONFIG_DIR / filename
file_path.write_text(data)
# Ensure only user can read/write the file
file_path.chmod(0o600)
except Exception as e:
print(f"Debug: Error saving {filename}: {e}")
def _api_response_callback(response: APIResponse[BetaMessage], response_state: dict):
response_id = datetime.now().isoformat()
response_state[response_id] = response
def _tool_output_callback(tool_output: ToolResult, tool_id: str, tool_state: dict):
tool_state[tool_id] = tool_output
def _render_message(sender: Sender, message: str | BetaTextBlock | BetaToolUseBlock | ToolResult, state):
is_tool_result = not isinstance(message, str) and (
isinstance(message, ToolResult)
or message.__class__.__name__ == "ToolResult"
or message.__class__.__name__ == "CLIResult"
)
if not message or (
is_tool_result
and state["hide_images"]
and not hasattr(message, "error")
and not hasattr(message, "output")
):
return
if is_tool_result:
message = cast(ToolResult, message)
if message.output:
return message.output
if message.error:
return f"Error: {message.error}"
if message.base64_image and not state["hide_images"]:
return base64.b64decode(message.base64_image)
elif isinstance(message, BetaTextBlock) or isinstance(message, TextBlock):
return message.text
elif isinstance(message, BetaToolUseBlock) or isinstance(message, ToolUseBlock):
return f"Tool Use: {message.name}\nInput: {message.input}"
else:
return message
# open new tab, open google sheets inside, then create a new blank spreadsheet
def process_input(user_input, state):
# Ensure the state is properly initialized
setup_state(state)
# Append the user input to the messages in the state
state["messages"].append(
{
"role": Sender.USER,
"content": [TextBlock(type="text", text=user_input)],
}
)
# Run the sampling loop synchronously and yield messages
for message in sampling_loop(state):
yield message
def accumulate_messages(*args, **kwargs):
"""
Wrapper function to accumulate messages from sampling_loop_sync.
"""
accumulated_messages = []
for message in sampling_loop_sync(*args, **kwargs):
# Check if the message is already in the accumulated messages
if message not in accumulated_messages:
accumulated_messages.append(message)
# Yield the accumulated messages as a list
yield accumulated_messages
def sampling_loop(state):
# Ensure the API key is present
if not state.get("api_key"):
raise ValueError("API key is missing. Please set it in the environment or storage.")
# Call the sampling loop and yield messages
for message in accumulate_messages(
system_prompt_suffix=state["custom_system_prompt"],
model=state["model"],
provider=state["provider"],
messages=state["messages"],
output_callback=partial(_render_message, Sender.BOT, state=state),
tool_output_callback=partial(_tool_output_callback, tool_state=state["tools"]),
api_response_callback=partial(_api_response_callback, response_state=state["responses"]),
api_key=state["api_key"],
only_n_most_recent_images=state["only_n_most_recent_images"],
):
yield message
with gr.Blocks() as demo:
state = gr.State({}) # Use Gradio's state management
gr.Markdown("# Claude Computer Use Demo")
if not os.getenv("HIDE_WARNING", False):
gr.Markdown(WARNING_TEXT)
with gr.Row():
provider = gr.Dropdown(
label="API Provider",
choices=[option.value for option in APIProvider],
value="anthropic",
interactive=True,
)
model = gr.Textbox(label="Model", value="claude-3-5-sonnet-20241022")
api_key = gr.Textbox(
label="Anthropic API Key",
type="password",
value="",
interactive=True,
)
only_n_images = gr.Slider(
label="Only send N most recent images",
minimum=0,
value=3, # 10
interactive=True,
)
custom_prompt = gr.Textbox(
label="Custom System Prompt Suffix",
value="",
interactive=True,
)
hide_images = gr.Checkbox(label="Hide screenshots", value=False)
api_key.change(fn=lambda key: save_to_storage(API_KEY_FILE, key), inputs=api_key)
chat_input = gr.Textbox(label="Type a message to send to Claude...")
# chat_output = gr.Textbox(label="Chat Output", interactive=False)
chatbot = gr.Chatbot(label="Chatbot History", autoscroll=True)
# Pass state as an input to the function
chat_input.submit(process_input, [chat_input, state], chatbot)
demo.launch(share=True)