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https://github.com/simular-ai/Agent-S.git
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lyon
64 lines
1.7 KiB
Python
64 lines
1.7 KiB
Python
import asyncio
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import platform
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from fastapi import FastAPI
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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from gui_agents.core.AgentS import GraphSearchAgent
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from gui_agents.aci.LinuxOSACI import LinuxACI
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from gui_agents.aci.MacOSACI import MacOSACI
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from gui_agents.aci.WindowsOSACI import WindowsOSACI
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app = FastAPI()
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engine_params = {
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"engine_type": "openai",
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"model": "gpt-4o",
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}
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# Determine the operating system and select appropriate ACI
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os_name = platform.system().lower()
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if os_name == "linux":
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grounding_agent = LinuxACI()
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platform_name = "ubuntu"
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elif os_name == "darwin":
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grounding_agent = MacOSACI()
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platform_name = "macos"
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elif os_name == "windows":
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grounding_agent = WindowsOSACI()
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platform_name = "windows"
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else:
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raise ValueError(f"Unsupported operating system: {os_name}")
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agent = GraphSearchAgent(
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engine_params,
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grounding_agent,
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platform=platform_name,
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action_space="pyautogui",
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observation_type="mixed",
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)
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class InstructionData(BaseModel):
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screenshot: str
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accessibility_tree: str
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class CommandRequest(BaseModel):
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obs: InstructionData
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instruction: str
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async def stream_code(code: str):
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for line in code.splitlines(keepends=True):
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yield line
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await asyncio.sleep(0.1)
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@app.post("/execute")
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async def execute_command_stream(cmd: CommandRequest):
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obs = {
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"screenshot": cmd.obs.screenshot,
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"accessibility_tree": cmd.obs.accessibility_tree,
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}
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instruction = cmd.instruction
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info, code = agent.predict(instruction=instruction, observation=obs)
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return StreamingResponse(stream_code(code), media_type="text/plain")
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