support use existing sandbox by id

2025-07-20 16:02:18 +08:00
parent 398ae434ed
commit 3301d54625
4 changed files with 178 additions and 16 deletions
@@ -17,7 +17,8 @@ from app.tool.python_execute import PythonExecute
 from app.tool.str_replace_editor import StrReplaceEditor

 from app.tool.sb_browser_tool import SandboxBrowserTool
-from app.daytona.sandbox import create_sandbox
+from app.daytona.sandbox import create_sandbox,get_or_start_sandbox
+import daytona

 class SandboxManus(ToolCallAgent):
    """A versatile general-purpose agent with support for both local and MCP tools."""
@@ -53,6 +54,7 @@ class SandboxManus(ToolCallAgent):
        default_factory=dict
    )  # server_id -> url/command
    _initialized: bool = False
+    sandbox_link: Optional[dict[str, dict[str, str]]] = Field(default_factory=dict)

    @model_validator(mode="after")
    def initialize_helper(self) -> "SandboxManus":
@@ -65,16 +67,67 @@ class SandboxManus(ToolCallAgent):
        """Factory method to create and properly initialize a Manus instance."""
        instance = cls(**kwargs)
        await instance.initialize_mcp_servers()
-        instance.initialize_sandbox_tools()
+        await instance.initialize_sandbox_tools()
        instance._initialized = True
        return instance

-    def initialize_sandbox_tools(self,password="123456") -> None:
-        sandbox = create_sandbox(password=password)
-        print(f"VNC link: {sandbox.get_preview_link(6080)}")
-        computer_tool = SandboxBrowserTool.create_with_sandbox(sandbox)
-        sandbox_tools=[computer_tool]
-        self.available_tools.add_tools(*sandbox_tools)
+    async def initialize_sandbox_tools(self, sandbox_id: str = config.daytona.sandbox_id, password:str = config.daytona.VNC_password) -> None:
+        try:
+            if sandbox_id:
+                sandbox = await get_or_start_sandbox(sandbox_id)
+
+                # Initialize sandbox_link if not exists
+                if not self.sandbox_link:
+                    self.sandbox_link = {}
+
+                # Check if URLs are already cached
+                if sandbox_id in self.sandbox_link:
+                    vnc_url = self.sandbox_link[sandbox_id]["vnc"]
+                    website_url = self.sandbox_link[sandbox_id]["website"]
+                    logger.info(f"Using cached URLs - VNC: {vnc_url}, Website: {website_url}")
+                else:
+                    # Get URLs from sandbox and cache them
+                    vnc_link = sandbox.get_preview_link(6080)
+                    website_link = sandbox.get_preview_link(8080)
+                    vnc_url = vnc_link.url if hasattr(vnc_link, 'url') else str(vnc_link)
+                    website_url = website_link.url if hasattr(website_link, 'url') else str(website_link)
+
+                    # Cache the URLs
+                    self.sandbox_link[sandbox_id] = {
+                        "vnc": str(vnc_url),
+                        "website": str(website_url)
+                    }
+                    logger.info(f"Cached new URLs - VNC: {vnc_url}, Website: {website_url}")
+
+                logger.info(f"VNC URL: {vnc_url}")
+                logger.info(f"Website URL: {website_url}")
+            else:
+                # 创建新沙箱
+                if password:
+                    sandbox = create_sandbox(password=password)
+                else:
+                    raise ValueError("Sandbox ID or password must be provided")
+                vnc_link = sandbox.get_preview_link(6080)
+                website_link = sandbox.get_preview_link(8080)
+                vnc_url = vnc_link.url if hasattr(vnc_link, 'url') else str(vnc_link)
+                website_url = website_link.url if hasattr(website_link, 'url') else str(website_link)
+
+                # Get the actual sandbox_id from the created sandbox
+                actual_sandbox_id = sandbox.id if hasattr(sandbox, 'id') else 'new_sandbox'
+                if not self.sandbox_link:
+                    self.sandbox_link = {}
+                self.sandbox_link[actual_sandbox_id] = {
+                    "vnc": vnc_url,
+                    "website": website_url,
+                }
+                logger.info(f"VNC URL: {vnc_url}")
+                logger.info(f"Website URL: {website_url}")
+            computer_tool = SandboxBrowserTool.create_with_sandbox(sandbox)
+            self.available_tools.add_tools(computer_tool)
+
+        except Exception as e:
+            logger.error(f"Error initializing sandbox tools: {e}")
+            raise

    async def initialize_mcp_servers(self) -> None:
        """Initialize connections to configured MCP servers."""
@@ -111,6 +111,8 @@ class DaytonaSettings(BaseModel):
    daytona_target: Optional[str] = Field("us", description="enum ['asia', 'eu', 'us']")
    sandbox_image_name: Optional[str]= Field("kortix/suna:0.1.3", description="")
    sandbox_entrypoint: Optional[str]= Field("/usr/bin/supervisord -n -c /etc/supervisor/conf.d/supervisord.conf", description="")
+    sandbox_id: Optional[str] = Field(None, description="ID of the daytona sandbox to use, if any")
+    VNC_password: Optional[str] = Field("123456", description="VNC password for the vnc service in sandbox")

 class MCPServerConfig(BaseModel):
    """Configuration for a single MCP server"""
@@ -0,0 +1,115 @@
+# Global LLM configuration
+[llm]
+model = "claude-3-7-sonnet-20250219"       # The LLM model to use
+base_url = "https://api.anthropic.com/v1/" # API endpoint URL
+api_key = "YOUR_API_KEY"                   # Your API key
+max_tokens = 8192                          # Maximum number of tokens in the response
+temperature = 0.0                          # Controls randomness
+
+# [llm] # Amazon Bedrock
+# api_type = "aws"                                       # Required
+# model = "us.anthropic.claude-3-7-sonnet-20250219-v1:0" # Bedrock supported modelID
+# base_url = "bedrock-runtime.us-west-2.amazonaws.com"   # Not used now
+# max_tokens = 8192
+# temperature = 1.0
+# api_key = "bear"                                       # Required but not used for Bedrock
+
+# [llm] #AZURE OPENAI:
+# api_type= 'azure'
+# model = "YOUR_MODEL_NAME" #"gpt-4o-mini"
+# base_url = "{YOUR_AZURE_ENDPOINT.rstrip('/')}/openai/deployments/{AZURE_DEPLOYMENT_ID}"
+# api_key = "AZURE API KEY"
+# max_tokens = 8096
+# temperature = 0.0
+# api_version="AZURE API VERSION" #"2024-08-01-preview"
+
+# [llm] #OLLAMA:
+# api_type = 'ollama'
+# model = "llama3.2"
+# base_url = "http://localhost:11434/v1"
+# api_key = "ollama"
+# max_tokens = 4096
+# temperature = 0.0
+
+# Optional configuration for specific LLM models
+[llm.vision]
+model = "claude-3-7-sonnet-20250219"       # The vision model to use
+base_url = "https://api.anthropic.com/v1/" # API endpoint URL for vision model
+api_key = "YOUR_API_KEY"                   # Your API key for vision model
+max_tokens = 8192                          # Maximum number of tokens in the response
+temperature = 0.0                          # Controls randomness for vision model
+
+# [llm.vision] #OLLAMA VISION:
+# api_type = 'ollama'
+# model = "llama3.2-vision"
+# base_url = "http://localhost:11434/v1"
+# api_key = "ollama"
+# max_tokens = 4096
+# temperature = 0.0
+
+# Optional configuration for specific browser configuration
+# [browser]
+# Whether to run browser in headless mode (default: false)
+#headless = false
+# Disable browser security features (default: true)
+#disable_security = true
+# Extra arguments to pass to the browser
+#extra_chromium_args = []
+# Path to a Chrome instance to use to connect to your normal browser
+# e.g. '/Applications/Google Chrome.app/Contents/MacOS/Google Chrome'
+#chrome_instance_path = ""
+# Connect to a browser instance via WebSocket
+#wss_url = ""
+# Connect to a browser instance via CDP
+#cdp_url = ""
+
+# Optional configuration, Proxy settings for the browser
+# [browser.proxy]
+# server = "http://proxy-server:port"
+# username = "proxy-username"
+# password = "proxy-password"
+
+# Optional configuration, Search settings.
+# [search]
+# Search engine for agent to use. Default is "Google", can be set to "Baidu" or "DuckDuckGo" or "Bing".
+#engine = "Google"
+# Fallback engine order. Default is ["DuckDuckGo", "Baidu", "Bing"] - will try in this order after primary engine fails.
+#fallback_engines = ["DuckDuckGo", "Baidu", "Bing"]
+# Seconds to wait before retrying all engines again when they all fail due to rate limits. Default is 60.
+#retry_delay = 60
+# Maximum number of times to retry all engines when all fail. Default is 3.
+#max_retries = 3
+# Language code for search results. Options: "en" (English), "zh" (Chinese), etc.
+#lang = "en"
+# Country code for search results. Options: "us" (United States), "cn" (China), etc.
+#country = "us"
+
+
+## Sandbox configuration
+#[sandbox]
+#use_sandbox = false
+#image = "python:3.12-slim"
+#work_dir = "/workspace"
+#memory_limit = "1g"  # 512m
+#cpu_limit = 2.0
+#timeout = 300
+#network_enabled = true
+
+# Daytona configuration
+#[daytona]
+#daytona_api_key = ""
+#daytona_server_url = "https://app.daytona.io/api"
+#daytona_target = "us"
+#sandbox_image_name = "kortix/suna:0.1.3"
+#sandbox_entrypoint =
+#sandbox_id =
+#VNC_password =
+
+# MCP (Model Context Protocol) configuration
+[mcp]
+server_reference = "app.mcp.server" # default server module reference
+
+# Optional Runflow configuration
+# Your can add additional agents into run-flow workflow to solve different-type tasks.
+[runflow]
+use_data_analysis_agent = false     # The Data Analysi Agent to solve various data analysis tasks
@@ -95,14 +95,6 @@ temperature = 0.0                          # Controls randomness for vision mode
 #timeout = 300
 #network_enabled = true

-# Daytona configuration
-[daytona]
-daytona_api_key = ""
-daytona_server_url = "https://app.daytona.io/api"
-daytona_target = "us"
-#sandbox_image_name =
-#sandbox_entrypoint =
-
 # MCP (Model Context Protocol) configuration
 [mcp]
 server_reference = "app.mcp.server" # default server module reference