workshop_gallery.json

{
  "id": "gallery_default",
  "name": "Multi-agent Workshop Gallery",
  "url": null,
  "metadata": {
    "author": "Jacob Albrecht",
    "created_at": "2025-02-21T20:43:06.400850",
    "updated_at": "2025-03-21T20:43:07.501068",
    "version": "0.0.2",
    "description": "A demo gallery containing basic components for human-in-loop conversations",
    "tags": ["human-in-loop", "assistant", "web agents"],
    "license": "MIT",
    "homepage": null,
    "category": "conversation",
    "last_synced": null
  },
  "components": {
    "agents": [
      {
        "provider": "autogen_agentchat.agents.UserProxyAgent",
        "component_type": "agent",
        "version": 1,
        "component_version": 1,
        "description": "An agent that can represent a human user through an input function.",
        "label": "UserProxyAgent",
        "config": {
          "name": "user_proxy",
          "description": "a human user that should be consulted only when the assistant_agent is unable to verify the information provided by the websurfer_agent"
        }
      },
      {
        "provider": "autogen_agentchat.agents.AssistantAgent",
        "component_type": "agent",
        "version": 1,
        "component_version": 1,
        "description": "An agent that provides assistance with tool use.",
        "label": "AssistantAgent",
        "config": {
          "name": "weather_agent",
          "model_client": {
            "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
            "component_type": "model",
            "version": 1,
            "component_version": 1,
            "description": "Chat completion client for OpenAI hosted models.",
            "label": "OpenAIChatCompletionClient",
            "config": {
              "model": "deepseek/deepseek-r1:free",
              "api_key": "**********",
              "model_info": {
                "vision": false,
                "function_calling": true,
                "json_output": true,
                "family": "unknown"
              },
              "base_url": "https://openrouter.ai/api/v1"
            }
          },
          "tools": [],
          "model_context": {
            "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
            "component_type": "chat_completion_context",
            "version": 1,
            "component_version": 1,
            "description": "An unbounded chat completion context that keeps a view of the all the messages.",
            "label": "UnboundedChatCompletionContext",
            "config": {}
          },
          "description": "An agent that provides assistance with ability to use tools.",
          "system_message": "You are a helpful AI assistant. Solve tasks using your tools. Reply with TERMINATE when the task has been completed.",
          "model_client_stream": false,
          "reflect_on_tool_use": false,
          "tool_call_summary_format": "{result}"
        }
      },
      {
        "provider": "autogen_ext.agents.web_surfer.MultimodalWebSurfer",
        "component_type": "agent",
        "version": 1,
        "component_version": 1,
        "description": "MultimodalWebSurfer is a multimodal agent that acts as a web surfer that can search the web and visit web pages.",
        "label": "MultimodalWebSurfer",
        "config": {
          "name": "WebSurfer",
          "model_client": {
            "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
            "component_type": "model",
            "version": 1,
            "component_version": 1,
            "description": "Chat completion client for OpenAI hosted models.",
            "label": "OpenAIChatCompletionClient",
            "config": {
              "model": "google/gemini-2.0-flash-exp:free",
              "api_key": "**********",
              "model_info": {
                "vision": true,
                "function_calling": true,
                "json_output": true,
                "family": "unknown"
              },
              "base_url": "https://openrouter.ai/api/v1"
            }
          },
          "description": "A helpful assistant with access to a web browser.",
          "headless": true,
          "start_page": "https://www.bing.com/",
          "animate_actions": false,
          "to_save_screenshots": false,
          "use_ocr": false,
          "to_resize_viewport": true
        }
      }
    ],
    "models": [
      {
        "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
        "component_type": "model",
        "version": 1,
        "component_version": 1,
        "description": "UI-TARS 72B is an open-source multimodal AI model designed specifically for automating browser and desktop tasks through visual interaction and control. The model is built with a specialized vision architecture enabling accurate interpretation and manipulation of on-screen visual data. It supports automation tasks within web browsers as well as desktop applications, including Microsoft Office and VS Code.",
        "label": "bytedance-research/ui-tars-72b:free",
        "config": {
          "model": "bytedance-research/ui-tars-72b:free",
          "api_key": "**********",
          "model_info": {
            "vision": true,
            "function_calling": true,
            "json_output": true,
            "family": "unknown"
          },
          "base_url": "https://openrouter.ai/api/v1"
        }
      },
      {
        "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
        "component_type": "model",
        "version": 1,
        "component_version": 1,
        "description": "Chat completion client for Deepseek-R1, free tier hosted by OpenRouter.io.",
        "label": "deepseek-r1",
        "config": {
          "model": "deepseek/deepseek-r1:free",
          "api_key": "**********",
          "model_info": {
            "vision": false,
            "function_calling": true,
            "json_output": true,
            "family": "unknown"
          },
          "base_url": "https://openrouter.ai/api/v1"
        }
      },
      {
        "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
        "component_type": "model",
        "version": 1,
        "component_version": 1,
        "description": "Chat completion client for Deepseek-R1, Uses search engine Exa.AI",
        "label": "deepseek-r1 - Web Search",
        "config": {
          "model": "deepseek/deepseek-r1:exa",
          "api_key": "**********",
          "model_info": {
            "vision": false,
            "function_calling": true,
            "json_output": true,
            "family": "unknown"
          },
          "base_url": "https://openrouter.ai/api/v1"
        }
      },
      {
        "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
        "component_type": "model",
        "version": 1,
        "component_version": 1,
        "description": "Chat completion client for Google Gemini",
        "label": "gemini-2.0-flash",
        "config": {
          "model": "google/gemini-2.0-flash-exp:free",
          "api_key": "**********",
          "model_info": {
            "vision": true,
            "function_calling": true,
            "json_output": true,
            "family": "unknown"
          },
          "base_url": "https://openrouter.ai/api/v1"
        }
      }
    ],
    "tools": [
      {
        "provider": "autogen_core.tools.FunctionTool",
        "component_type": "tool",
        "version": 1,
        "component_version": 1,
        "description": "A tool that performs basic arithmetic operations (addition, subtraction, multiplication, division).",
        "label": "Calculator Tool",
        "config": {
          "source_code": "def calculator(a: float, b: float, operator: str) -> str:\n    try:\n        if operator == \"+\":\n            return str(a + b)\n        elif operator == \"-\":\n            return str(a - b)\n        elif operator == \"*\":\n            return str(a * b)\n        elif operator == \"/\":\n            if b == 0:\n                return \"Error: Division by zero\"\n            return str(a / b)\n        else:\n            return \"Error: Invalid operator. Please use +, -, *, or /\"\n    except Exception as e:\n        return f\"Error: {str(e)}\"\n",
          "name": "calculator",
          "description": "A simple calculator that performs basic arithmetic operations",
          "global_imports": [],
          "has_cancellation_support": false
        }
      },
      {
        "provider": "autogen_core.tools.FunctionTool",
        "component_type": "tool",
        "version": 1,
        "component_version": 1,
        "description": "A tool that generates images based on a text description using OpenAI's DALL-E model. Note: Requires OpenAI API key to function.",
        "label": "Image Generation Tool",
        "config": {
          "source_code": "async def generate_image(\n    query: str, output_dir: Optional[Path] = None, image_size: Literal[\"1024x1024\", \"512x512\", \"256x256\"] = \"1024x1024\"\n) -> List[str]:\n    \"\"\"\n    Generate images using OpenAI's DALL-E model based on a text description.\n\n    Args:\n        query: Natural language description of the desired image\n        output_dir: Directory to save generated images (default: current directory)\n        image_size: Size of generated image (1024x1024, 512x512, or 256x256)\n\n    Returns:\n        List[str]: Paths to the generated image files\n    \"\"\"\n    # Initialize the OpenAI client\n    client = OpenAI()\n\n    # Generate images using DALL-E 3\n    response = client.images.generate(model=\"dall-e-3\", prompt=query, n=1, response_format=\"b64_json\", size=image_size)\n\n    saved_files = []\n\n    # Process the response\n    if response.data:\n        for image_data in response.data:\n            # Generate a unique filename\n            file_name = f\"{uuid.uuid4()}.png\"\n\n            # Use output_dir if provided, otherwise use current directory\n            file_path = Path(output_dir) / file_name if output_dir else Path(file_name)\n\n            base64_str = image_data.b64_json\n            img = Image.open(io.BytesIO(base64.decodebytes(bytes(base64_str, \"utf-8\"))))\n\n            # Save the image to a file\n            img.save(file_path)\n\n            saved_files.append(str(file_path))\n\n    return saved_files\n",
          "name": "generate_image",
          "description": "Generate images using DALL-E based on text descriptions.",
          "global_imports": [
            "io",
            "uuid",
            "base64",
            {
              "module": "typing",
              "imports": ["List", "Optional", "Literal"]
            },
            {
              "module": "pathlib",
              "imports": ["Path"]
            },
            {
              "module": "openai",
              "imports": ["OpenAI"]
            },
            {
              "module": "PIL",
              "imports": ["Image"]
            }
          ],
          "has_cancellation_support": false
        }
      },
      {
        "provider": "autogen_core.tools.FunctionTool",
        "component_type": "tool",
        "version": 1,
        "component_version": 1,
        "description": "A tool that generates a PDF file from a list of images.Requires the PyFPDF and pillow library to function.",
        "label": "PDF Generation Tool",
        "config": {
          "source_code": "async def generate_pdf(\n    sections: List[Dict[str, Optional[str]]], output_file: str = \"report.pdf\", report_title: str = \"PDF Report\"\n) -> str:\n    \"\"\"\n    Generate a PDF report with formatted sections including text and images.\n\n    Args:\n        sections: List of dictionaries containing section details with keys:\n            - title: Section title\n            - level: Heading level (title, h1, h2)\n            - content: Section text content\n            - image: Optional image URL or file path\n        output_file: Name of output PDF file\n        report_title: Title shown at top of report\n\n    Returns:\n        str: Path to the generated PDF file\n    \"\"\"\n\n    def normalize_text(text: str) -> str:\n        \"\"\"Normalize Unicode text to ASCII.\"\"\"\n        return unicodedata.normalize(\"NFKD\", text).encode(\"ascii\", \"ignore\").decode(\"ascii\")\n\n    def get_image(image_url_or_path):\n        \"\"\"Fetch image from URL or local path.\"\"\"\n        if image_url_or_path.startswith((\"http://\", \"https://\")):\n            response = requests.get(image_url_or_path)\n            if response.status_code == 200:\n                return BytesIO(response.content)\n        elif Path(image_url_or_path).is_file():\n            return open(image_url_or_path, \"rb\")\n        return None\n\n    def add_rounded_corners(img, radius=6):\n        \"\"\"Add rounded corners to an image.\"\"\"\n        mask = Image.new(\"L\", img.size, 0)\n        draw = ImageDraw.Draw(mask)\n        draw.rounded_rectangle([(0, 0), img.size], radius, fill=255)\n        img = ImageOps.fit(img, mask.size, centering=(0.5, 0.5))\n        img.putalpha(mask)\n        return img\n\n    class PDF(FPDF):\n        \"\"\"Custom PDF class with header and content formatting.\"\"\"\n\n        def header(self):\n            self.set_font(\"Arial\", \"B\", 12)\n            normalized_title = normalize_text(report_title)\n            self.cell(0, 10, normalized_title, 0, 1, \"C\")\n\n        def chapter_title(self, txt):\n            self.set_font(\"Arial\", \"B\", 12)\n            normalized_txt = normalize_text(txt)\n            self.cell(0, 10, normalized_txt, 0, 1, \"L\")\n            self.ln(2)\n\n        def chapter_body(self, body):\n            self.set_font(\"Arial\", \"\", 12)\n            normalized_body = normalize_text(body)\n            self.multi_cell(0, 10, normalized_body)\n            self.ln()\n\n        def add_image(self, img_data):\n            img = Image.open(img_data)\n            img = add_rounded_corners(img)\n            img_path = Path(f\"temp_{uuid.uuid4().hex}.png\")\n            img.save(img_path, format=\"PNG\")\n            self.image(str(img_path), x=None, y=None, w=190 if img.width > 190 else img.width)\n            self.ln(10)\n            img_path.unlink()\n\n    # Initialize PDF\n    pdf = PDF()\n    pdf.add_page()\n    font_size = {\"title\": 16, \"h1\": 14, \"h2\": 12, \"body\": 12}\n\n    # Add sections\n    for section in sections:\n        title = section.get(\"title\", \"\")\n        level = section.get(\"level\", \"h1\")\n        content = section.get(\"content\", \"\")\n        image = section.get(\"image\")\n\n        pdf.set_font(\"Arial\", \"B\" if level in font_size else \"\", font_size.get(level, font_size[\"body\"]))\n        pdf.chapter_title(title)\n\n        if content:\n            pdf.chapter_body(content)\n\n        if image:\n            img_data = get_image(image)\n            if img_data:\n                pdf.add_image(img_data)\n                if isinstance(img_data, BytesIO):\n                    img_data.close()\n\n    pdf.output(output_file)\n    return output_file\n",
          "name": "generate_pdf",
          "description": "Generate PDF reports with formatted sections containing text and images",
          "global_imports": [
            "uuid",
            "requests",
            "unicodedata",
            {
              "module": "typing",
              "imports": ["List", "Dict", "Optional"]
            },
            {
              "module": "pathlib",
              "imports": ["Path"]
            },
            {
              "module": "fpdf",
              "imports": ["FPDF"]
            },
            {
              "module": "PIL",
              "imports": ["Image", "ImageDraw", "ImageOps"]
            },
            {
              "module": "io",
              "imports": ["BytesIO"]
            }
          ],
          "has_cancellation_support": false
        }
      },
      {
        "provider": "autogen_core.tools.FunctionTool",
        "component_type": "tool",
        "version": 1,
        "component_version": 1,
        "description": "A tool that fetches the content of a webpage and converts it to markdown. Requires the requests and beautifulsoup4 library to function.",
        "label": "Fetch Webpage Tool",
        "config": {
          "source_code": "async def fetch_webpage(\n    url: str, include_images: bool = True, max_length: Optional[int] = None, headers: Optional[Dict[str, str]] = None\n) -> str:\n    \"\"\"Fetch a webpage and convert it to markdown format.\n\n    Args:\n        url: The URL of the webpage to fetch\n        include_images: Whether to include image references in the markdown\n        max_length: Maximum length of the output markdown (if None, no limit)\n        headers: Optional HTTP headers for the request\n\n    Returns:\n        str: Markdown version of the webpage content\n\n    Raises:\n        ValueError: If the URL is invalid or the page can't be fetched\n    \"\"\"\n    # Use default headers if none provided\n    if headers is None:\n        headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n    try:\n        # Fetch the webpage\n        async with httpx.AsyncClient() as client:\n            response = await client.get(url, headers=headers, timeout=10)\n            response.raise_for_status()\n\n            # Parse HTML\n            soup = BeautifulSoup(response.text, \"html.parser\")\n\n            # Remove script and style elements\n            for script in soup([\"script\", \"style\"]):\n                script.decompose()\n\n            # Convert relative URLs to absolute\n            for tag in soup.find_all([\"a\", \"img\"]):\n                if tag.get(\"href\"):\n                    tag[\"href\"] = urljoin(url, tag[\"href\"])\n                if tag.get(\"src\"):\n                    tag[\"src\"] = urljoin(url, tag[\"src\"])\n\n            # Configure HTML to Markdown converter\n            h2t = html2text.HTML2Text()\n            h2t.body_width = 0  # No line wrapping\n            h2t.ignore_images = not include_images\n            h2t.ignore_emphasis = False\n            h2t.ignore_links = False\n            h2t.ignore_tables = False\n\n            # Convert to markdown\n            markdown = h2t.handle(str(soup))\n\n            # Trim if max_length is specified\n            if max_length and len(markdown) > max_length:\n                markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n            return markdown.strip()\n\n    except httpx.RequestError as e:\n        raise ValueError(f\"Failed to fetch webpage: {str(e)}\") from e\n    except Exception as e:\n        raise ValueError(f\"Error processing webpage: {str(e)}\") from e\n",
          "name": "fetch_webpage",
          "description": "Fetch a webpage and convert it to markdown format, with options for including images and limiting length",
          "global_imports": [
            "os",
            "html2text",
            {
              "module": "typing",
              "imports": ["Optional", "Dict"]
            },
            "httpx",
            {
              "module": "bs4",
              "imports": ["BeautifulSoup"]
            },
            {
              "module": "html2text",
              "imports": ["HTML2Text"]
            },
            {
              "module": "urllib.parse",
              "imports": ["urljoin"]
            }
          ],
          "has_cancellation_support": false
        }
      }
    ],
    "terminations": [
      {
        "provider": "autogen_agentchat.conditions.TextMentionTermination",
        "component_type": "termination",
        "version": 1,
        "component_version": 1,
        "description": "Terminate the conversation if a specific text is mentioned.",
        "label": "TextMentionTermination",
        "config": {
          "text": "TERMINATE"
        }
      },
      {
        "provider": "autogen_agentchat.conditions.MaxMessageTermination",
        "component_type": "termination",
        "version": 1,
        "component_version": 1,
        "description": "Terminate the conversation after a maximum number of messages have been exchanged.",
        "label": "MaxMessageTermination",
        "config": {
          "max_messages": 10,
          "include_agent_event": false
        }
      },
      {
        "provider": "autogen_agentchat.base.OrTerminationCondition",
        "component_type": "termination",
        "version": 1,
        "component_version": 1,
        "description": "Termination condition that ends the conversation when either a message contains 'TERMINATE' or the maximum number of messages is reached.",
        "label": "OR Termination",
        "config": {
          "conditions": [
            {
              "provider": "autogen_agentchat.conditions.TextMentionTermination",
              "component_type": "termination",
              "version": 1,
              "component_version": 1,
              "description": "Terminate the conversation if a specific text is mentioned.",
              "label": "TextMentionTermination",
              "config": {
                "text": "TERMINATE"
              }
            },
            {
              "provider": "autogen_agentchat.conditions.MaxMessageTermination",
              "component_type": "termination",
              "version": 1,
              "component_version": 1,
              "description": "Terminate the conversation after a maximum number of messages have been exchanged.",
              "label": "MaxMessageTermination",
              "config": {
                "max_messages": 10,
                "include_agent_event": false
              }
            }
          ]
        }
      }
    ],
    "teams": [
      {
        "provider": "autogen_agentchat.teams.RoundRobinGroupChat",
        "component_type": "team",
        "version": 1,
        "component_version": 1,
        "description": "A single AssistantAgent (with a calculator tool) in a RoundRobinGroupChat team. ",
        "label": "RoundRobin Team",
        "config": {
          "participants": [
            {
              "provider": "autogen_ext.agents.web_surfer.MultimodalWebSurfer",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "MultimodalWebSurfer is a multimodal agent that acts as a web surfer that can search the web and visit web pages.",
              "label": "MultimodalWebSurfer",
              "config": {
                "name": "WebSurfer",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "google/gemini-2.0-flash-exp:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": true,
                      "function_calling": true,
                      "json_output": true,
                      "family": "unknown"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "description": "A helpful assistant with access to a web browser.",
                "headless": true,
                "start_page": "https://www.bing.com/",
                "animate_actions": false,
                "to_save_screenshots": false,
                "use_ocr": false,
                "to_resize_viewport": true
              }
            },
            {
              "provider": "autogen_agentchat.agents.AssistantAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that provides assistance with tool use.",
              "label": "AssistantAgent",
              "config": {
                "name": "assistant_agent",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "deepseek/deepseek-r1:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "unknown"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "An agent that provides assistance with ability to use tools.",
                "system_message": "You are a helpful AI assistant. Solve tasks using your tools. Reply with TERMINATE when the task has been completed.",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            }
          ],
          "termination_condition": {
            "provider": "autogen_agentchat.base.OrTerminationCondition",
            "component_type": "termination",
            "version": 1,
            "component_version": 1,
            "label": "OrTerminationCondition",
            "config": {
              "conditions": [
                {
                  "provider": "autogen_agentchat.conditions.TextMentionTermination",
                  "component_type": "termination",
                  "version": 1,
                  "component_version": 1,
                  "description": "Terminate the conversation if a specific text is mentioned.",
                  "label": "TextMentionTermination",
                  "config": {
                    "text": "TERMINATE"
                  }
                },
                {
                  "provider": "autogen_agentchat.conditions.MaxMessageTermination",
                  "component_type": "termination",
                  "version": 1,
                  "component_version": 1,
                  "description": "Terminate the conversation after a maximum number of messages have been exchanged.",
                  "label": "MaxMessageTermination",
                  "config": {
                    "max_messages": 10,
                    "include_agent_event": false
                  }
                }
              ]
            }
          }
        }
      },
      {
        "provider": "autogen_agentchat.teams.SelectorGroupChat",
        "component_type": "team",
        "version": 1,
        "component_version": 1,
        "description": "A team with 3 agents - a Research Assistant that performs web searches and analyzes information, a Verifier that ensures research quality and completeness, and a Summary Agent that provides a detailed markdown summary of the research as a report to the user.",
        "label": "Deep Research Team",
        "config": {
          "participants": [
            {
              "provider": "autogen_agentchat.agents.AssistantAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that provides assistance with tool use.",
              "label": "AssistantAgent",
              "config": {
                "name": "research_assistant",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "google/gemini-2.0-flash-exp:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "unknown"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [
                  {
                    "provider": "autogen_core.tools.FunctionTool",
                    "component_type": "tool",
                    "version": 1,
                    "component_version": 1,
                    "description": "Create custom tools by wrapping standard Python functions.",
                    "label": "FunctionTool",
                    "config": {
                      "source_code": "async def fetch_webpage(\n    url: str, include_images: bool = True, max_length: Optional[int] = None, headers: Optional[Dict[str, str]] = None\n) -> str:\n    \"\"\"Fetch a webpage and convert it to markdown format.\n\n    Args:\n        url: The URL of the webpage to fetch\n        include_images: Whether to include image references in the markdown\n        max_length: Maximum length of the output markdown (if None, no limit)\n        headers: Optional HTTP headers for the request\n\n    Returns:\n        str: Markdown version of the webpage content\n\n    Raises:\n        ValueError: If the URL is invalid or the page can't be fetched\n    \"\"\"\n    # Use default headers if none provided\n    if headers is None:\n        headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n    try:\n        # Fetch the webpage\n        async with httpx.AsyncClient() as client:\n            response = await client.get(url, headers=headers, timeout=10)\n            response.raise_for_status()\n\n            # Parse HTML\n            soup = BeautifulSoup(response.text, \"html.parser\")\n\n            # Remove script and style elements\n            for script in soup([\"script\", \"style\"]):\n                script.decompose()\n\n            # Convert relative URLs to absolute\n            for tag in soup.find_all([\"a\", \"img\"]):\n                if tag.get(\"href\"):\n                    tag[\"href\"] = urljoin(url, tag[\"href\"])\n                if tag.get(\"src\"):\n                    tag[\"src\"] = urljoin(url, tag[\"src\"])\n\n            # Configure HTML to Markdown converter\n            h2t = html2text.HTML2Text()\n            h2t.body_width = 0  # No line wrapping\n            h2t.ignore_images = not include_images\n            h2t.ignore_emphasis = False\n            h2t.ignore_links = False\n            h2t.ignore_tables = False\n\n            # Convert to markdown\n            markdown = h2t.handle(str(soup))\n\n            # Trim if max_length is specified\n            if max_length and len(markdown) > max_length:\n                markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n            return markdown.strip()\n\n    except httpx.RequestError as e:\n        raise ValueError(f\"Failed to fetch webpage: {str(e)}\") from e\n    except Exception as e:\n        raise ValueError(f\"Error processing webpage: {str(e)}\") from e\n",
                      "name": "fetch_webpage",
                      "description": "Fetch a webpage and convert it to markdown format, with options for including images and limiting length",
                      "global_imports": [
                        "os",
                        "html2text",
                        {
                          "module": "typing",
                          "imports": ["Optional", "Dict"]
                        },
                        "httpx",
                        {
                          "module": "bs4",
                          "imports": ["BeautifulSoup"]
                        },
                        {
                          "module": "html2text",
                          "imports": ["HTML2Text"]
                        },
                        {
                          "module": "urllib.parse",
                          "imports": ["urljoin"]
                        }
                      ],
                      "has_cancellation_support": false
                    }
                  }
                ],
                "handoffs": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "A research assistant that performs web searches and analyzes information",
                "system_message": "You are a research assistant focused on finding accurate information.\n        Use the google_search tool to find relevant information.\n        Break down complex queries into specific search terms.\n        Always verify information across multiple sources when possible.\n        When you find relevant information, explain why it's relevant and how it connects to the query. When you get feedback from the a verifier agent, use your tools to act on the feedback and make progress.",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            },
            {
              "provider": "autogen_agentchat.agents.AssistantAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that provides assistance with tool use.",
              "label": "AssistantAgent",
              "config": {
                "name": "verifier",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "google/gemini-2.0-flash-exp:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "unknown"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [],
                "handoffs": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "A verification specialist who ensures research quality and completeness",
                "system_message": "You are a research verification specialist.\n        Your role is to:\n        1. Verify that search queries are effective and suggest improvements if needed\n        2. Explore drill downs where needed e.g, if the answer is likely in a link in the returned search results, suggest clicking on the link\n        3. Suggest additional angles or perspectives to explore. Be judicious in suggesting new paths to avoid scope creep or wasting resources, if the task appears to be addressed and we can provide a report, do this and respond with \"TERMINATE\".\n        4. Track progress toward answering the original question\n        5. When the research is complete, provide a detailed summary in markdown format. For incomplete research, end your message with \"CONTINUE RESEARCH\". For complete research, end your message with APPROVED.\n        Your responses should be structured as:\n        - Progress Assessment\n        - Gaps/Issues (if any)\n        - Suggestions (if needed)\n        - Next Steps or Final Summary",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            },
            {
              "provider": "autogen_agentchat.agents.AssistantAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that provides assistance with tool use.",
              "label": "AssistantAgent",
              "config": {
                "name": "summary_agent",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "deepseek/deepseek-r1:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "unknown"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [],
                "handoffs": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "A summary agent that provides a detailed markdown summary of the research as a report to the user.",
                "system_message": "You are a summary agent. Your role is to provide a detailed markdown summary of the research as a report to the user. Your report should have a reasonable title that matches the research question and should summarize the key details in the results found in natural an actionable manner. The main results/answer should be in the first paragraph. Where reasonable, your report should have clear comparison tables that drive critical insights. Most importantly, you should have a reference section and cite the key sources (where available) for facts obtained INSIDE THE MAIN REPORT. Also, where appropriate, you may add images if available that illustrate concepts needed for the summary.\n        Your report should end with the word \"TERMINATE\" to signal the end of the conversation.",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            }
          ],
          "model_client": {
            "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
            "component_type": "model",
            "version": 1,
            "component_version": 1,
            "description": "Chat completion client for OpenAI hosted models.",
            "label": "OpenAIChatCompletionClient",
            "config": {
              "model": "deepseek/deepseek-r1:free",
              "api_key": "**********",
              "model_info": {
                "vision": false,
                "function_calling": true,
                "json_output": true,
                "family": "unknown"
              },
              "base_url": "https://openrouter.ai/api/v1"
            }
          },
          "termination_condition": {
            "provider": "autogen_agentchat.base.OrTerminationCondition",
            "component_type": "termination",
            "version": 1,
            "component_version": 1,
            "label": "OrTerminationCondition",
            "config": {
              "conditions": [
                {
                  "provider": "autogen_agentchat.conditions.TextMentionTermination",
                  "component_type": "termination",
                  "version": 1,
                  "component_version": 1,
                  "description": "Terminate the conversation if a specific text is mentioned.",
                  "label": "TextMentionTermination",
                  "config": {
                    "text": "TERMINATE"
                  }
                },
                {
                  "provider": "autogen_agentchat.conditions.MaxMessageTermination",
                  "component_type": "termination",
                  "version": 1,
                  "component_version": 1,
                  "description": "Terminate the conversation after a maximum number of messages have been exchanged.",
                  "label": "MaxMessageTermination",
                  "config": {
                    "max_messages": 30,
                    "include_agent_event": false
                  }
                }
              ]
            }
          },
          "selector_prompt": "You are coordinating a research team by selecting the team member to speak/act next. The following team member roles are available:\n    {roles}.\n    The research_assistant performs searches and analyzes information.\n    The verifier evaluates progress and ensures completeness.\n    The summary_agent provides a detailed markdown summary of the research as a report to the user.\n\n    Given the current context, select the most appropriate next speaker.\n    The research_assistant should search and analyze.\n    The verifier should evaluate progress and guide the research (select this role is there is a need to verify/evaluate progress). You should ONLY select the summary_agent role if the research is complete and it is time to generate a report.\n\n    Base your selection on:\n    1. Current stage of research\n    2. Last speaker's findings or suggestions\n    3. Need for verification vs need for new information\n    Read the following conversation. Then select the next role from {participants} to play. Only return the role.\n\n    {history}\n\n    Read the above conversation. Then select the next role from {participants} to play. ONLY RETURN THE ROLE.",
          "allow_repeated_speaker": true,
          "max_selector_attempts": 3
        }
      },
      {
        "provider": "autogen_agentchat.teams.MagenticOneGroupChat",
        "component_type": "team",
        "version": 1,
        "component_version": 1,
        "description": "A team that runs a group chat with participants managed by the MagenticOneOrchestrator.",
        "label": "MagenticOneGroupChat",
        "config": {
          "participants": [
            {
              "provider": "autogen_ext.agents.file_surfer.FileSurfer",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent, used by MagenticOne, that acts as a local file previewer. FileSurfer can open and read a variety of common file types, and can navigate the local file hierarchy.",
              "label": "FileSurfer",
              "config": {
                "name": "FileSurfer",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "deepseek/deepseek-r1:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "r1"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "description": "An agent that can handle local files."
              }
            },
            {
              "provider": "autogen_agentchat.agents.AssistantAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that provides assistance with tool use.",
              "label": "AssistantAgent",
              "config": {
                "name": "assistant",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "deepseek/deepseek-r1:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "r1"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "An agent that provides assistance with ability to use tools.",
                "system_message": "You are a helpful AI assistant. Solve tasks using your tools. Reply with TERMINATE when the task has been completed.",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            },
            {
              "provider": "autogen_ext.agents.web_surfer.MultimodalWebSurfer",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "MultimodalWebSurfer is a multimodal agent that acts as a web surfer that can search the web and visit web pages.",
              "label": "MultimodalWebSurfer",
              "config": {
                "name": "WebSurfer",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "google/gemini-2.0-flash-exp:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "r1"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "description": "\n    A helpful assistant with access to a web browser.\n    Ask them to perform web searches, open pages, and interact with content (e.g., clicking links, scrolling the viewport, filling in form fields, etc.).\n    It can also summarize the entire page, or answer questions based on the content of the page.\n    It can also be asked to sleep and wait for pages to load, in cases where the page seems not yet fully loaded.\n    ",
                "headless": true,
                "start_page": "https://www.bing.com/",
                "animate_actions": false,
                "to_save_screenshots": false,
                "use_ocr": false,
                "to_resize_viewport": true
              }
            },
            {
              "provider": "autogen_ext.agents.magentic_one.MagenticOneCoderAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent, used by MagenticOne that provides coding assistance using an LLM model client.",
              "label": "MagenticOneCoderAgent",
              "config": {
                "name": "Coder",
                "model_client": {
                  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
                  "component_type": "model",
                  "version": 1,
                  "component_version": 1,
                  "description": "Chat completion client for OpenAI hosted models.",
                  "label": "OpenAIChatCompletionClient",
                  "config": {
                    "model": "deepseek/deepseek-r1:free",
                    "api_key": "**********",
                    "model_info": {
                      "vision": false,
                      "function_calling": true,
                      "json_output": true,
                      "family": "r1"
                    },
                    "base_url": "https://openrouter.ai/api/v1"
                  }
                },
                "tools": [],
                "model_context": {
                  "provider": "autogen_core.model_context.UnboundedChatCompletionContext",
                  "component_type": "chat_completion_context",
                  "version": 1,
                  "component_version": 1,
                  "description": "An unbounded chat completion context that keeps a view of the all the messages.",
                  "label": "UnboundedChatCompletionContext",
                  "config": {}
                },
                "description": "A helpful and general-purpose AI assistant that has strong language skills, Python skills, and Linux command line skills.",
                "system_message": "You are a helpful AI assistant.\nSolve tasks using your coding and language skills.\nIn the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.\n    1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time, check the operating system. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.\n    2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.\nSolve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.\nWhen using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.\nDon't include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use the 'print' function for the output when relevant. Check the execution result returned by the user.\nIf the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can't be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.\nWhen you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.",
                "model_client_stream": false,
                "reflect_on_tool_use": false,
                "tool_call_summary_format": "{result}"
              }
            },
            {
              "provider": "autogen_agentchat.agents.CodeExecutorAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that extracts and executes code snippets found in received messages and returns the output.",
              "label": "CodeExecutorAgent",
              "config": {
                "name": "Executor",
                "code_executor": {
                  "provider": "autogen_ext.code_executors.local.LocalCommandLineCodeExecutor",
                  "component_type": "code_executor",
                  "version": 1,
                  "component_version": 1,
                  "description": "A code executor class that executes code through a local command line\n    environment.",
                  "label": "LocalCommandLineCodeExecutor",
                  "config": {
                    "timeout": 60,
                    "work_dir": ".",
                    "functions_module": "functions"
                  }
                },
                "description": "A computer terminal that performs no other action than running Python scripts (provided to it quoted in ```python code blocks), or sh shell scripts (provided to it quoted in ```sh code blocks)."
              }
            },
            {
              "provider": "autogen_agentchat.agents.UserProxyAgent",
              "component_type": "agent",
              "version": 1,
              "component_version": 1,
              "description": "An agent that can represent a human user through an input function.",
              "label": "UserProxyAgent",
              "config": {
                "name": "User",
                "description": "A human user"
              }
            }
          ],
          "model_client": {
            "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
            "component_type": "model",
            "version": 1,
            "component_version": 1,
            "description": "Chat completion client for OpenAI hosted models.",
            "label": "OpenAIChatCompletionClient",
            "config": {
              "model": "google/gemini-2.0-flash-exp:free",
              "api_key": "**********",
              "model_info": {
                "vision": true,
                "function_calling": true,
                "json_output": true,
                "family": "r1"
              },
              "base_url": "https://openrouter.ai/api/v1"
            }
          },
          "termination_condition": {
            "provider": "autogen_agentchat.conditions.TextMentionTermination",
            "component_type": "termination",
            "version": 1,
            "component_version": 1,
            "description": "Terminate the conversation if a specific text is mentioned.",
            "label": "TextMentionTermination",
            "config": {
              "text": "TERMINATE"
            }
          },
          "max_turns": 60,
          "max_stalls": 3,
          "final_answer_prompt": "\nWe are working on the following task:\n{task}\n\nWe have completed the task.\n\nThe above messages contain the conversation that took place to complete the task.\n\nBased on the information gathered, provide the final answer to the original request.\nThe answer should be phrased as if you were speaking to the user.\n"
        }
      }
    ]
  }
}