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src/utils/__init__.py

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+# -*- coding: utf-8 -*-
+# @Time    : 2025/1/1
+# @Author  : wenshao
+# @Email   : wenshaoguo1026@gmail.com
+# @Project : browser-use-webui
+# @FileName: __init__.py.py

src/utils/agent_state.py

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+import asyncio
+
+class AgentState:
+    _instance = None
+
+    def __init__(self):
+        if not hasattr(self, '_stop_requested'):
+            self._stop_requested = asyncio.Event()
+            self.last_valid_state = None  # store the last valid browser state
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(AgentState, cls).__new__(cls)
+        return cls._instance
+
+    def request_stop(self):
+        self._stop_requested.set()
+
+    def clear_stop(self):
+        self._stop_requested.clear()
+        self.last_valid_state = None
+
+    def is_stop_requested(self):
+        return self._stop_requested.is_set()
+
+    def set_last_valid_state(self, state):
+        self.last_valid_state = state
+
+    def get_last_valid_state(self):
+        return self.last_valid_state

src/utils/utils.py

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+# -*- coding: utf-8 -*-
+# @Time    : 2025/1/1
+# @Author  : wenshao
+# @Email   : wenshaoguo1026@gmail.com
+# @Project : browser-use-webui
+# @FileName: utils.py
+import base64
+import os
+import time
+from pathlib import Path
+from typing import Dict, Optional
+
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_ollama import ChatOllama
+from langchain_openai import AzureChatOpenAI, ChatOpenAI
+import gradio as gr
+
+def get_llm_model(provider: str, **kwargs):
+    """
+    获取LLM 模型
+    :param provider: 模型类型
+    :param kwargs:
+    :return:
+    """
+    if provider == "anthropic":
+        if not kwargs.get("base_url", ""):
+            base_url = "https://api.anthropic.com"
+        else:
+            base_url = kwargs.get("base_url")
+
+        if not kwargs.get("api_key", ""):
+            api_key = os.getenv("ANTHROPIC_API_KEY", "")
+        else:
+            api_key = kwargs.get("api_key")
+
+        return ChatAnthropic(
+            model_name=kwargs.get("model_name", "claude-3-5-sonnet-20240620"),
+            temperature=kwargs.get("temperature", 0.0),
+            base_url=base_url,
+            api_key=api_key,
+        )
+    elif provider == "openai":
+        if not kwargs.get("base_url", ""):
+            base_url = os.getenv("OPENAI_ENDPOINT", "https://api.openai.com/v1")
+        else:
+            base_url = kwargs.get("base_url")
+
+        if not kwargs.get("api_key", ""):
+            api_key = os.getenv("OPENAI_API_KEY", "")
+        else:
+            api_key = kwargs.get("api_key")
+
+        return ChatOpenAI(
+            model=kwargs.get("model_name", "gpt-4o"),
+            temperature=kwargs.get("temperature", 0.0),
+            base_url=base_url,
+            api_key=api_key,
+        )
+    elif provider == "deepseek":
+        if not kwargs.get("base_url", ""):
+            base_url = os.getenv("DEEPSEEK_ENDPOINT", "")
+        else:
+            base_url = kwargs.get("base_url")
+
+        if not kwargs.get("api_key", ""):
+            api_key = os.getenv("DEEPSEEK_API_KEY", "")
+        else:
+            api_key = kwargs.get("api_key")
+
+        return ChatOpenAI(
+            model=kwargs.get("model_name", "deepseek-chat"),
+            temperature=kwargs.get("temperature", 0.0),
+            base_url=base_url,
+            api_key=api_key,
+        )
+    elif provider == "gemini":
+        if not kwargs.get("api_key", ""):
+            api_key = os.getenv("GOOGLE_API_KEY", "")
+        else:
+            api_key = kwargs.get("api_key")
+        return ChatGoogleGenerativeAI(
+            model=kwargs.get("model_name", "gemini-2.0-flash-exp"),
+            temperature=kwargs.get("temperature", 0.0),
+            google_api_key=api_key,
+        )
+    elif provider == "ollama":
+        return ChatOllama(
+            model=kwargs.get("model_name", "qwen2.5:7b"),
+            temperature=kwargs.get("temperature", 0.0),
+            num_ctx=128000,
+            base_url=kwargs.get("base_url", "http://localhost:11434"),
+        )
+    elif provider == "azure_openai":
+        if not kwargs.get("base_url", ""):
+            base_url = os.getenv("AZURE_OPENAI_ENDPOINT", "")
+        else:
+            base_url = kwargs.get("base_url")
+        if not kwargs.get("api_key", ""):
+            api_key = os.getenv("AZURE_OPENAI_API_KEY", "")
+        else:
+            api_key = kwargs.get("api_key")
+        return AzureChatOpenAI(
+            model=kwargs.get("model_name", "gpt-4o"),
+            temperature=kwargs.get("temperature", 0.0),
+            api_version="2024-05-01-preview",
+            azure_endpoint=base_url,
+            api_key=api_key,
+        )
+    else:
+        raise ValueError(f"Unsupported provider: {provider}")
+    
+# Predefined model names for common providers
+model_names = {
+    "anthropic": ["claude-3-5-sonnet-20240620", "claude-3-opus-20240229"],
+    "openai": ["gpt-4o", "gpt-4", "gpt-3.5-turbo"],
+    "deepseek": ["deepseek-chat"],
+    "gemini": ["gemini-2.0-flash-exp", "gemini-2.0-flash-thinking-exp", "gemini-1.5-flash-latest", "gemini-1.5-flash-8b-latest", "gemini-2.0-flash-thinking-exp-1219" ],
+    "ollama": ["qwen2.5:7b", "llama2:7b"],
+    "azure_openai": ["gpt-4o", "gpt-4", "gpt-3.5-turbo"]
+}
+
+# Callback to update the model name dropdown based on the selected provider
+def update_model_dropdown(llm_provider, api_key=None, base_url=None):
+    """
+    Update the model name dropdown with predefined models for the selected provider.
+    """
+    # Use API keys from .env if not provided
+    if not api_key:
+        api_key = os.getenv(f"{llm_provider.upper()}_API_KEY", "")
+    if not base_url:
+        base_url = os.getenv(f"{llm_provider.upper()}_BASE_URL", "")
+
+    # Use predefined models for the selected provider
+    if llm_provider in model_names:
+        return gr.Dropdown(choices=model_names[llm_provider], value=model_names[llm_provider][0], interactive=True)
+    else:
+        return gr.Dropdown(choices=[], value="", interactive=True, allow_custom_value=True)
+        
+def encode_image(img_path):
+    if not img_path:
+        return None
+    with open(img_path, "rb") as fin:
+        image_data = base64.b64encode(fin.read()).decode("utf-8")
+    return image_data
+
+
+def get_latest_files(directory: str, file_types: list = ['.webm', '.zip']) -> Dict[str, Optional[str]]:
+    """Get the latest recording and trace files"""
+    latest_files: Dict[str, Optional[str]] = {ext: None for ext in file_types}
+    
+    if not os.path.exists(directory):
+        os.makedirs(directory, exist_ok=True)
+        return latest_files
+
+    for file_type in file_types:
+        try:
+            matches = list(Path(directory).rglob(f"*{file_type}"))
+            if matches:
+                latest = max(matches, key=lambda p: p.stat().st_mtime)
+                # Only return files that are complete (not being written)
+                if time.time() - latest.stat().st_mtime > 1.0:
+                    latest_files[file_type] = str(latest)
+        except Exception as e:
+            print(f"Error getting latest {file_type} file: {e}")
+            
+    return latest_files
+async def capture_screenshot(browser_context):
+    """Capture and encode a screenshot"""
+    # Extract the Playwright browser instance
+    playwright_browser = browser_context.browser.playwright_browser  # Ensure this is correct.
+
+    # Check if the browser instance is valid and if an existing context can be reused
+    if playwright_browser and playwright_browser.contexts:
+        playwright_context = playwright_browser.contexts[0]
+    else:
+        return None
+
+    # Access pages in the context
+    pages = None
+    if playwright_context:
+        pages = playwright_context.pages
+
+    # Use an existing page or create a new one if none exist
+    if pages:
+        active_page = pages[0]
+        for page in pages:
+            if page.url != "about:blank":
+                active_page = page
+    else:
+        return None
+
+    # Take screenshot
+    try:
+        screenshot = await active_page.screenshot(
+            type='jpeg',
+            quality=75,
+            scale="css"
+        )
+        encoded = base64.b64encode(screenshot).decode('utf-8')
+        return encoded
+    except Exception as e:
+        return None