mirror/computer
1
0
Fork 0
mirror of https://github.com/trycua/computer.git synced 2026-01-06 05:20:02 -06:00
Code Issues Packages Projects Releases Wiki Activity

added cloud provider to agent ui

Browse Source
This commit is contained in:
Dillon DuPont
2025-05-24 18:59:24 -04:00
parent 658c033a0f
commit b2ecf18a1e
1 changed files with 148 additions and 86 deletions
Download Patch File Download Diff File Expand all files Collapse all files

234
libs/agent/agent/ui/gradio/app.py
View File

@@ -290,7 +290,7 @@ def get_provider_and_model(model_name: str, loop_provider: str) -> tuple:
model_name_to_use = cleaned_model_name
# agent_loop remains AgentLoop.OMNI
elif agent_loop == AgentLoop.UITARS:
# For UITARS, use MLXVLM provider for the MLX models, OAICOMPAT for custom
# For UITARS, use MLXVLM for mlx-community models, OAICOMPAT for custom
if model_name == "Custom model (OpenAI compatible API)":
provider = LLMProvider.OAICOMPAT
model_name_to_use = "tgi"
@@ -333,12 +333,25 @@ def get_ollama_models() -> List[str]:
logging.error(f"Error getting Ollama models: {e}")
return []
def create_computer_instance(verbosity: int = logging.INFO) -> Computer:
def create_computer_instance(
verbosity: int = logging.INFO,
os_type: str = "macos",
provider_type: str = "lume",
name: Optional[str] = None,
api_key: Optional[str] = None
) -> Computer:
"""Create or get the global Computer instance."""
global global_computer
if global_computer is None:
global_computer = Computer(verbosity=verbosity)
global_computer = Computer(
verbosity=verbosity,
os_type=os_type,
provider_type=provider_type,
name=name if name else "",
api_key=api_key
)
return global_computer
@@ -353,12 +366,22 @@ def create_agent(
verbosity: int = logging.INFO,
use_oaicompat: bool = False,
provider_base_url: Optional[str] = None,
computer_os: str = "macos",
computer_provider: str = "lume",
computer_name: Optional[str] = None,
computer_api_key: Optional[str] = None,
) -> ComputerAgent:
"""Create or update the global agent with the specified parameters."""
global global_agent
# Create the computer if not already done
computer = create_computer_instance(verbosity=verbosity)
computer = create_computer_instance(
verbosity=verbosity,
os_type=computer_os,
provider_type=computer_provider,
name=computer_name,
api_key=computer_api_key
)
# Get API key from environment if not provided
if api_key is None:
@@ -401,6 +424,7 @@ def create_agent(
return global_agent
def create_gradio_ui(
provider_name: str = "openai",
model_name: str = "gpt-4o",
@@ -439,6 +463,9 @@ def create_gradio_ui(
# Check if API keys are available
has_openai_key = bool(openai_api_key)
has_anthropic_key = bool(anthropic_api_key)
print("has_openai_key", has_openai_key)
print("has_anthropic_key", has_anthropic_key)
# Get Ollama models for OMNI
ollama_models = get_ollama_models()
@@ -473,7 +500,7 @@ def create_gradio_ui(
elif initial_loop == "ANTHROPIC":
initial_model = anthropic_models[0] if anthropic_models else "No models available"
else: # OMNI
initial_model = omni_models[0] if omni_models else "No models available"
initial_model = omni_models[0] if omni_models else "Custom model (OpenAI compatible API)"
if "Custom model (OpenAI compatible API)" in available_models_for_loop:
initial_model = (
"Custom model (OpenAI compatible API)" # Default to custom if available and no other default fits
@@ -494,7 +521,7 @@ def create_gradio_ui(
]
# Function to generate Python code based on configuration and tasks
def generate_python_code(agent_loop_choice, provider, model_name, tasks, provider_url, recent_images=3, save_trajectory=True):
def generate_python_code(agent_loop_choice, provider, model_name, tasks, provider_url, recent_images=3, save_trajectory=True, computer_os="macos", computer_provider="lume", vm_name="", cua_cloud_api_key=""):
"""Generate Python code for the current configuration and tasks.
Args:
@@ -505,6 +532,10 @@ def create_gradio_ui(
provider_url: The provider base URL for OAICOMPAT providers
recent_images: Number of recent images to keep in context
save_trajectory: Whether to save the agent trajectory
computer_os: Operating system type for the computer
computer_provider: Provider type for the computer
vm_name: Optional VM name
cua_cloud_api_key: Optional CUA Cloud API key
Returns:
Formatted Python code as a string
@@ -515,13 +546,29 @@ def create_gradio_ui(
if task and task.strip():
tasks_str += f' "{task}",\n'
# Create the Python code template
# Create the Python code template with computer configuration
computer_args = []
if computer_os != "macos":
computer_args.append(f'os_type="{computer_os}"')
if computer_provider != "lume":
computer_args.append(f'provider_type="{computer_provider}"')
if vm_name:
computer_args.append(f'name="{vm_name}"')
if cua_cloud_api_key:
computer_args.append(f'api_key="{cua_cloud_api_key}"')
computer_args_str = ", ".join(computer_args)
if computer_args_str:
computer_args_str = f"({computer_args_str})"
else:
computer_args_str = "()"
code = f'''import asyncio
from computer import Computer
from agent import ComputerAgent, LLM, AgentLoop, LLMProvider
async def main():
async with Computer() as macos_computer:
async with Computer{computer_args_str} as macos_computer:
agent = ComputerAgent(
computer=macos_computer,
loop=AgentLoop.{agent_loop_choice},
@@ -660,12 +707,49 @@ if __name__ == "__main__":
LLMProvider.OPENAI,
"gpt-4o",
[],
"https://openrouter.ai/api/v1"
"https://openrouter.ai/api/v1",
3, # recent_images default
True, # save_trajectory default
"macos",
"lume",
"",
""
),
interactive=False,
)
with gr.Accordion("Configuration", open=True):
with gr.Accordion("Computer Configuration", open=True):
# Computer configuration options
computer_os = gr.Dropdown(
choices=["macos", "linux"],
label="Operating System",
value="macos",
info="Select the operating system for the computer",
)
computer_provider = gr.Dropdown(
choices=["cloud", "lume"],
label="Provider",
value="lume",
info="Select the computer provider",
)
vm_name = gr.Textbox(
label="VM Name",
placeholder="Enter VM name (optional)",
value="",
info="Optional name for the virtual machine",
)
cua_cloud_api_key = gr.Textbox(
label="CUA Cloud API Key",
placeholder="Enter your CUA Cloud API key",
value="",
type="password",
info="Required for cloud provider",
)
with gr.Accordion("Agent Configuration", open=True):
# Configuration options
agent_loop = gr.Dropdown(
choices=["OPENAI", "ANTHROPIC", "OMNI", "UITARS"],
@@ -986,6 +1070,10 @@ if __name__ == "__main__":
custom_api_key=None,
openai_key_input=None,
anthropic_key_input=None,
computer_os="macos",
computer_provider="lume",
vm_name="",
cua_cloud_api_key="",
):
if not history:
yield history
@@ -1092,6 +1180,10 @@ if __name__ == "__main__":
"provider_base_url": custom_url_value,
"save_trajectory": save_traj,
"recent_images": recent_imgs,
"computer_os": computer_os,
"computer_provider": computer_provider,
"vm_name": vm_name,
"cua_cloud_api_key": cua_cloud_api_key,
}
save_settings(current_settings)
# --- End Save Settings ---
@@ -1109,6 +1201,10 @@ if __name__ == "__main__":
use_oaicompat=is_oaicompat, # Set flag if custom model was selected
# Pass custom URL only if custom model was selected
provider_base_url=custom_url_value if is_oaicompat else None,
computer_os=computer_os,
computer_provider=computer_provider,
computer_name=vm_name,
computer_api_key=cua_cloud_api_key,
verbosity=logging.DEBUG, # Added verbosity here
)
@@ -1235,6 +1331,10 @@ if __name__ == "__main__":
provider_api_key,
openai_api_key_input,
anthropic_api_key_input,
computer_os,
computer_provider,
vm_name,
cua_cloud_api_key,
],
outputs=[chatbot_history],
queue=True,
@@ -1253,82 +1353,20 @@ if __name__ == "__main__":
# Function to update the code display based on configuration and chat history
def update_code_display(agent_loop, model_choice_val, custom_model_val, chat_history, provider_base_url, recent_images_val, save_trajectory_val):
def update_code_display(agent_loop, model_choice_val, custom_model_val, chat_history, provider_base_url, recent_images_val, save_trajectory_val, computer_os, computer_provider, vm_name, cua_cloud_api_key):
# Extract messages from chat history
messages = []
if chat_history:
for msg in chat_history:
if msg.get("role") == "user":
if isinstance(msg, dict) and msg.get("role") == "user":
messages.append(msg.get("content", ""))
# Determine if this is a custom model selection and which type
is_custom_openai_api = model_choice_val == "Custom model (OpenAI compatible API)"
is_custom_ollama = model_choice_val == "Custom model (ollama)"
is_custom_model_selected = is_custom_openai_api or is_custom_ollama
# Determine provider and model based on current selection
provider, model_name, _ = get_provider_and_model(
model_choice_val or custom_model_val or "gpt-4o",
agent_loop
)
# Determine provider and model name based on agent loop
if agent_loop == "OPENAI":
# For OPENAI loop, always use OPENAI provider with computer-use-preview
provider = LLMProvider.OPENAI
model_name = "computer-use-preview"
elif agent_loop == "ANTHROPIC":
# For ANTHROPIC loop, always use ANTHROPIC provider
provider = LLMProvider.ANTHROPIC
# Extract model name from the UI string
if model_choice_val.startswith("Anthropic: Claude "):
# Extract the model name based on the UI string
model_parts = model_choice_val.replace("Anthropic: Claude ", "").split(" (")
version = model_parts[0] # e.g., "3.7 Sonnet"
date = model_parts[1].replace(")", "") if len(model_parts) > 1 else "" # e.g., "20250219"
# Format as claude-3-7-sonnet-20250219 or claude-3-5-sonnet-20240620
version = version.replace(".", "-").replace(" ", "-").lower()
model_name = f"claude-{version}-{date}"
else:
# Use the model_choice_val directly if it doesn't match the expected format
model_name = model_choice_val
elif agent_loop == "UITARS":
# For UITARS, use MLXVLM for mlx-community models, OAICOMPAT for custom
if model_choice_val == "Custom model (OpenAI compatible API)":
provider = LLMProvider.OAICOMPAT
model_name = custom_model_val
else:
provider = LLMProvider.MLXVLM
model_name = model_choice_val
elif agent_loop == "OMNI":
# For OMNI, provider can be OPENAI, ANTHROPIC, OLLAMA, or OAICOMPAT
if is_custom_openai_api:
provider = LLMProvider.OAICOMPAT
model_name = custom_model_val
elif is_custom_ollama:
provider = LLMProvider.OLLAMA
model_name = custom_model_val
elif model_choice_val.startswith("OMNI: OpenAI "):
provider = LLMProvider.OPENAI
# Extract model name from UI string (e.g., "OMNI: OpenAI GPT-4o" -> "gpt-4o")
model_name = model_choice_val.replace("OMNI: OpenAI ", "").lower().replace(" ", "-")
elif model_choice_val.startswith("OMNI: Claude "):
provider = LLMProvider.ANTHROPIC
# Extract model name from UI string (similar to ANTHROPIC loop case)
model_parts = model_choice_val.replace("OMNI: Claude ", "").split(" (")
version = model_parts[0] # e.g., "3.7 Sonnet"
date = model_parts[1].replace(")", "") if len(model_parts) > 1 else "" # e.g., "20250219"
# Format as claude-3-7-sonnet-20250219 or claude-3-5-sonnet-20240620
version = version.replace(".", "-").replace(" ", "-").lower()
model_name = f"claude-{version}-{date}"
elif model_choice_val.startswith("OMNI: Ollama "):
provider = LLMProvider.OLLAMA
# Extract model name from UI string (e.g., "OMNI: Ollama llama3" -> "llama3")
model_name = model_choice_val.replace("OMNI: Ollama ", "")
else:
# Fallback to get_provider_and_model for any other cases
provider, model_name, _ = get_provider_and_model(model_choice_val, agent_loop)
else:
# Fallback for any other agent loop
provider, model_name, _ = get_provider_and_model(model_choice_val, agent_loop)
# Generate and return the code
return generate_python_code(
agent_loop,
provider,
@@ -1336,38 +1374,62 @@ if __name__ == "__main__":
messages,
provider_base_url,
recent_images_val,
save_trajectory_val
save_trajectory_val,
computer_os,
computer_provider,
vm_name,
cua_cloud_api_key
)
# Update code display when configuration changes
agent_loop.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
model_choice.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
custom_model.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
chatbot_history.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
recent_images.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
save_trajectory.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory],
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
computer_os.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
computer_provider.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
vm_name.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)
cua_cloud_api_key.change(
update_code_display,
inputs=[agent_loop, model_choice, custom_model, chatbot_history, provider_base_url, recent_images, save_trajectory, computer_os, computer_provider, vm_name, cua_cloud_api_key],
outputs=[code_display]
)