diff --git a/python/packages/autogen-studio/autogenstudio/datamodel/__init__.py b/python/packages/autogen-studio/autogenstudio/datamodel/__init__.py index b7f6f8da56e0..435031aab9d9 100644 --- a/python/packages/autogen-studio/autogenstudio/datamodel/__init__.py +++ b/python/packages/autogen-studio/autogenstudio/datamodel/__init__.py @@ -2,7 +2,6 @@ from .types import ( Gallery, GalleryComponents, - GalleryItems, GalleryMetadata, LLMCallEventMessage, MessageConfig, @@ -24,4 +23,7 @@ "Response", "SocketMessage", "LLMCallEventMessage", + "Gallery", + "GalleryComponents", + "GalleryMetadata", ] diff --git a/python/packages/autogen-studio/autogenstudio/datamodel/types.py b/python/packages/autogen-studio/autogenstudio/datamodel/types.py index 3e3bdbbe43ad..8475a891e329 100644 --- a/python/packages/autogen-studio/autogenstudio/datamodel/types.py +++ b/python/packages/autogen-studio/autogenstudio/datamodel/types.py @@ -52,11 +52,7 @@ class GalleryComponents(BaseModel): models: List[ComponentModel] tools: List[ComponentModel] terminations: List[ComponentModel] - - -class GalleryItems(BaseModel): teams: List[ComponentModel] - components: GalleryComponents class Gallery(BaseModel): @@ -64,7 +60,7 @@ class Gallery(BaseModel): name: str url: Optional[str] = None metadata: GalleryMetadata - items: GalleryItems + components: GalleryComponents # web request/response data models diff --git a/python/packages/autogen-studio/autogenstudio/gallery/builder.py b/python/packages/autogen-studio/autogenstudio/gallery/builder.py index 9c2b8c9d0bd9..78ba42ca3b24 100644 --- a/python/packages/autogen-studio/autogenstudio/gallery/builder.py +++ b/python/packages/autogen-studio/autogenstudio/gallery/builder.py @@ -10,7 +10,7 @@ from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.models.openai._openai_client import AzureOpenAIChatCompletionClient -from autogenstudio.datamodel import Gallery, GalleryComponents, GalleryItems, GalleryMetadata +from autogenstudio.datamodel import Gallery, GalleryComponents, GalleryMetadata from . import tools as tools @@ -119,11 +119,12 @@ def build(self) -> Gallery: name=self.name, url=self.url, metadata=self.metadata, - items=GalleryItems( + components=GalleryComponents( teams=self.teams, - components=GalleryComponents( - agents=self.agents, models=self.models, tools=self.tools, terminations=self.terminations - ), + agents=self.agents, + models=self.models, + tools=self.tools, + terminations=self.terminations, ), ) @@ -195,7 +196,11 @@ def create_default_gallery() -> Gallery: builder.add_termination(calc_text_term.dump_component()) builder.add_termination(calc_max_term.dump_component()) - builder.add_termination(calc_or_term.dump_component()) + builder.add_termination( + calc_or_term.dump_component(), + label="OR Termination", + description="Termination condition that ends the conversation when either a message contains 'TERMINATE' or the maximum number of messages is reached.", + ) # Create calculator team calc_team = RoundRobinGroupChat(participants=[calc_assistant], termination_condition=calc_or_term) @@ -227,7 +232,11 @@ def create_default_gallery() -> Gallery: model_client=base_model, headless=True, ) - builder.add_agent(websurfer_agent.dump_component()) + builder.add_agent( + websurfer_agent.dump_component(), + label="Web Surfer Agent", + description="An agent that solves tasks by browsing the web using a headless browser.", + ) # Create verification assistant verification_assistant = AssistantAgent( @@ -236,7 +245,11 @@ def create_default_gallery() -> Gallery: system_message="You are a task verification assistant who is working with a web surfer agent to solve tasks. At each point, check if the task has been completed as requested by the user. If the websurfer_agent responds and the task has not yet been completed, respond with what is left to do and then say 'keep going'. If and only when the task has been completed, summarize and present a final answer that directly addresses the user task in detail and then respond with TERMINATE.", model_client=base_model, ) - builder.add_agent(verification_assistant.dump_component()) + builder.add_agent( + verification_assistant.dump_component(), + label="Verification Assistant", + description="an agent that verifies and summarizes information", + ) # Create user proxy web_user_proxy = UserProxyAgent( diff --git a/python/packages/autogen-studio/frontend/src/components/sidebar.tsx b/python/packages/autogen-studio/frontend/src/components/sidebar.tsx index 0b4bd3c38c9c..8b060771e57b 100644 --- a/python/packages/autogen-studio/frontend/src/components/sidebar.tsx +++ b/python/packages/autogen-studio/frontend/src/components/sidebar.tsx @@ -105,7 +105,7 @@ const Sidebar = ({ link, meta, isMobile }: SidebarProps) => { return (
{ // import { Minimize2, Maximize2, ArrowsMaximize, X } from 'lucide-react'; // import { Tooltip } from 'antd'; +function safeJsonStringify(input: any): string { + if (typeof input === "object" && input !== null) { + return JSON.stringify(input); + } + return input; +} + export const TruncatableText = memo( ({ content = "", @@ -76,10 +83,12 @@ export const TruncatableText = memo( const [isExpanded, setIsExpanded] = useState(false); const [isFullscreen, setIsFullscreen] = useState(false); const threshold = isJson ? jsonThreshold : textThreshold; + content = safeJsonStringify(content) + ""; const shouldTruncate = content.length > threshold; - const toggleExpand = () => { + const toggleExpand = (e: React.MouseEvent) => { setIsExpanded(!isExpanded); + e.stopPropagation(); }; const displayContent = diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/default_gallery.json b/python/packages/autogen-studio/frontend/src/components/views/gallery/default_gallery.json index ac2a1dbbe749..8494cc0a9518 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/default_gallery.json +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/default_gallery.json @@ -4,8 +4,8 @@ "url": null, "metadata": { "author": "AutoGen Team", - "created_at": "2025-02-11T18:37:53.922275", - "updated_at": "2025-02-11T18:37:54.268540", + "created_at": "2025-02-18T16:52:37.999327", + "updated_at": "2025-02-18T16:52:38.055078", "version": "1.0.0", "description": "A default gallery containing basic components for human-in-loop conversations", "tags": ["human-in-loop", "assistant", "web agents"], @@ -14,7 +14,437 @@ "category": "conversation", "last_synced": null }, - "items": { + "components": { + "agents": [ + { + "provider": "autogen_agentchat.agents.AssistantAgent", + "component_type": "agent", + "version": 1, + "component_version": 1, + "description": "An agent that provides assistance with ability to use tools.", + "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": "gpt-4o-mini" + } + }, + "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": "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 + } + } + ], + "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": "An agent that provides assistance with ability to use tools.", + "system_message": "You are a helpful assistant. Solve tasks carefully. When done, say TERMINATE.", + "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_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": "gpt-4o-mini" + } + }, + "description": "an agent that solves tasks by browsing the web", + "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": "gpt-4o-mini" + } + }, + "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": "an agent that verifies and summarizes information", + "system_message": "You are a task verification assistant who is working with a web surfer agent to solve tasks. At each point, check if the task has been completed as requested by the user. If the websurfer_agent responds and the task has not yet been completed, respond with what is left to do and then say 'keep going'. If and only when the task has been completed, summarize and present a final answer that directly addresses the user task in detail and then respond with TERMINATE.", + "model_client_stream": false, + "reflect_on_tool_use": false, + "tool_call_summary_format": "{result}" + } + }, + { + "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" + } + } + ], + "models": [ + { + "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient", + "component_type": "model", + "version": 1, + "component_version": 1, + "description": "OpenAI GPT-4o-mini", + "label": "OpenAI GPT-4o Mini", + "config": { + "model": "gpt-4o-mini" + } + }, + { + "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient", + "component_type": "model", + "version": 1, + "component_version": 1, + "description": "Local Mistral-7B model client for instruction-based generation (Ollama, LMStudio).", + "label": "Mistral-7B Local", + "config": { + "model": "TheBloke/Mistral-7B-Instruct-v0.2-GGUF", + "model_info": { + "vision": false, + "function_calling": true, + "json_output": false, + "family": "unknown" + }, + "base_url": "http://localhost:1234/v1" + } + }, + { + "provider": "autogen_ext.models.openai.AzureOpenAIChatCompletionClient", + "component_type": "model", + "version": 1, + "component_version": 1, + "description": "GPT-4o Mini Azure OpenAI model client.", + "label": "AzureOpenAI GPT-4o-mini", + "config": { + "model": "gpt-4o-mini", + "api_key": "sk-...", + "azure_endpoint": "https://{your-custom-endpoint}.openai.azure.com/", + "azure_deployment": "{your-azure-deployment}", + "api_version": "2024-06-01" + } + } + ], + "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 + } + }, + { + "provider": "autogen_core.tools.FunctionTool", + "component_type": "tool", + "version": 1, + "component_version": 1, + "description": "A tool that performs Bing searches using the Bing Web Search API. Requires the requests library, BING_SEARCH_KEY env variable to function.", + "label": "Bing Search Tool", + "config": { + "source_code": "async def bing_search(\n query: str,\n num_results: int = 3,\n include_snippets: bool = True,\n include_content: bool = True,\n content_max_length: Optional[int] = 10000,\n language: str = \"en\",\n country: Optional[str] = None,\n safe_search: str = \"moderate\",\n response_filter: str = \"webpages\",\n) -> List[Dict[str, str]]:\n \"\"\"\n Perform a Bing search using the Bing Web Search API.\n\n Args:\n query: Search query string\n num_results: Number of results to return (max 50)\n include_snippets: Include result snippets in output\n include_content: Include full webpage content in markdown format\n content_max_length: Maximum length of webpage content (if included)\n language: Language code for search results (e.g., 'en', 'es', 'fr')\n country: Optional market code for search results (e.g., 'us', 'uk')\n safe_search: SafeSearch setting ('off', 'moderate', or 'strict')\n response_filter: Type of results ('webpages', 'news', 'images', or 'videos')\n\n Returns:\n List[Dict[str, str]]: List of search results\n\n Raises:\n ValueError: If API credentials are invalid or request fails\n \"\"\"\n # Get and validate API key\n api_key = os.getenv(\"BING_SEARCH_KEY\", \"\").strip()\n\n if not api_key:\n raise ValueError(\n \"BING_SEARCH_KEY environment variable is not set. \" \"Please obtain an API key from Azure Portal.\"\n )\n\n # Validate safe_search parameter\n valid_safe_search = [\"off\", \"moderate\", \"strict\"]\n if safe_search.lower() not in valid_safe_search:\n raise ValueError(f\"Invalid safe_search value. Must be one of: {', '.join(valid_safe_search)}\")\n\n # Validate response_filter parameter\n valid_filters = [\"webpages\", \"news\", \"images\", \"videos\"]\n if response_filter.lower() not in valid_filters:\n raise ValueError(f\"Invalid response_filter value. Must be one of: {', '.join(valid_filters)}\")\n\n async def fetch_page_content(url: str, max_length: Optional[int] = 50000) -> str:\n \"\"\"Helper function to fetch and convert webpage content to markdown\"\"\"\n headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(url, headers=headers, timeout=10)\n response.raise_for_status()\n\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 h2t = html2text.HTML2Text()\n h2t.body_width = 0\n h2t.ignore_images = False\n h2t.ignore_emphasis = False\n h2t.ignore_links = False\n h2t.ignore_tables = False\n\n markdown = h2t.handle(str(soup))\n\n if max_length and len(markdown) > max_length:\n markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n return markdown.strip()\n\n except Exception as e:\n return f\"Error fetching content: {str(e)}\"\n\n # Build request headers and parameters\n headers = {\"Ocp-Apim-Subscription-Key\": api_key, \"Accept\": \"application/json\"}\n\n params = {\n \"q\": query,\n \"count\": min(max(1, num_results), 50),\n \"mkt\": f\"{language}-{country.upper()}\" if country else language,\n \"safeSearch\": safe_search.capitalize(),\n \"responseFilter\": response_filter,\n \"textFormat\": \"raw\",\n }\n\n # Make the request\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(\n \"https://api.bing.microsoft.com/v7.0/search\", headers=headers, params=params, timeout=10\n )\n\n # Handle common error cases\n if response.status_code == 401:\n raise ValueError(\"Authentication failed. Please verify your Bing Search API key.\")\n elif response.status_code == 403:\n raise ValueError(\n \"Access forbidden. This could mean:\\n\"\n \"1. The API key is invalid\\n\"\n \"2. The API key has expired\\n\"\n \"3. You've exceeded your API quota\"\n )\n elif response.status_code == 429:\n raise ValueError(\"API quota exceeded. Please try again later.\")\n\n response.raise_for_status()\n data = response.json()\n\n # Process results based on response_filter\n results = []\n if response_filter == \"webpages\" and \"webPages\" in data:\n items = data[\"webPages\"][\"value\"]\n elif response_filter == \"news\" and \"news\" in data:\n items = data[\"news\"][\"value\"]\n elif response_filter == \"images\" and \"images\" in data:\n items = data[\"images\"][\"value\"]\n elif response_filter == \"videos\" and \"videos\" in data:\n items = data[\"videos\"][\"value\"]\n else:\n if not any(key in data for key in [\"webPages\", \"news\", \"images\", \"videos\"]):\n return [] # No results found\n raise ValueError(f\"No {response_filter} results found in API response\")\n\n # Extract relevant information based on result type\n for item in items:\n result = {\"title\": item.get(\"name\", \"\")}\n\n if response_filter == \"webpages\":\n result[\"link\"] = item.get(\"url\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"snippet\", \"\")\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n elif response_filter == \"news\":\n result[\"link\"] = item.get(\"url\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n result[\"date\"] = item.get(\"datePublished\", \"\")\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n elif response_filter == \"images\":\n result[\"link\"] = item.get(\"contentUrl\", \"\")\n result[\"thumbnail\"] = item.get(\"thumbnailUrl\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n\n elif response_filter == \"videos\":\n result[\"link\"] = item.get(\"contentUrl\", \"\")\n result[\"thumbnail\"] = item.get(\"thumbnailUrl\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n result[\"duration\"] = item.get(\"duration\", \"\")\n\n results.append(result)\n\n return results[:num_results]\n\n except httpx.RequestException as e:\n error_msg = str(e)\n if \"InvalidApiKey\" in error_msg:\n raise ValueError(\"Invalid API key. Please check your BING_SEARCH_KEY environment variable.\") from e\n elif \"KeyExpired\" in error_msg:\n raise ValueError(\"API key has expired. Please generate a new key.\") from e\n else:\n raise ValueError(f\"Search request failed: {error_msg}\") from e\n except json.JSONDecodeError:\n raise ValueError(\"Failed to parse API response. \" \"Please verify your API credentials and try again.\") from None\n except Exception as e:\n raise ValueError(f\"Unexpected error during search: {str(e)}\") from e\n", + "name": "bing_search", + "description": "\n Perform Bing searches using the Bing Web Search API. Requires BING_SEARCH_KEY environment variable.\n Supports web, news, image, and video searches.\n See function documentation for detailed setup instructions.\n ", + "global_imports": [ + { + "module": "typing", + "imports": ["List", "Dict", "Optional"] + }, + "os", + "httpx", + "json", + "html2text", + { + "module": "bs4", + "imports": ["BeautifulSoup"] + }, + { + "module": "urllib.parse", + "imports": ["urljoin"] + } + ], + "has_cancellation_support": false + } + }, + { + "provider": "autogen_core.tools.FunctionTool", + "component_type": "tool", + "version": 1, + "component_version": 1, + "description": "A tool that performs Google searches using the Google Custom Search API. Requires the requests library, [GOOGLE_API_KEY, GOOGLE_CSE_ID] to be set, env variable to function.", + "label": "Google Search Tool", + "config": { + "source_code": "async def google_search(\n query: str,\n num_results: int = 3,\n include_snippets: bool = True,\n include_content: bool = True,\n content_max_length: Optional[int] = 10000,\n language: str = \"en\",\n country: Optional[str] = None,\n safe_search: bool = True,\n) -> List[Dict[str, str]]:\n \"\"\"\n Perform a Google search using the Custom Search API and optionally fetch webpage content.\n\n Args:\n query: Search query string\n num_results: Number of results to return (max 10)\n include_snippets: Include result snippets in output\n include_content: Include full webpage content in markdown format\n content_max_length: Maximum length of webpage content (if included)\n language: Language code for search results (e.g., en, es, fr)\n country: Optional country code for search results (e.g., us, uk)\n safe_search: Enable safe search filtering\n\n Returns:\n List[Dict[str, str]]: List of search results, each containing:\n - title: Result title\n - link: Result URL\n - snippet: Result description (if include_snippets=True)\n - content: Webpage content in markdown (if include_content=True)\n \"\"\"\n api_key = os.getenv(\"GOOGLE_API_KEY\")\n cse_id = os.getenv(\"GOOGLE_CSE_ID\")\n\n if not api_key or not cse_id:\n raise ValueError(\"Missing required environment variables. Please set GOOGLE_API_KEY and GOOGLE_CSE_ID.\")\n\n num_results = min(max(1, num_results), 10)\n\n async def fetch_page_content(url: str, max_length: Optional[int] = 50000) -> str:\n \"\"\"Helper function to fetch and convert webpage content to markdown\"\"\"\n headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(url, headers=headers, timeout=10)\n response.raise_for_status()\n\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 h2t = html2text.HTML2Text()\n h2t.body_width = 0\n h2t.ignore_images = False\n h2t.ignore_emphasis = False\n h2t.ignore_links = False\n h2t.ignore_tables = False\n\n markdown = h2t.handle(str(soup))\n\n if max_length and len(markdown) > max_length:\n markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n return markdown.strip()\n\n except Exception as e:\n return f\"Error fetching content: {str(e)}\"\n\n params = {\n \"key\": api_key,\n \"cx\": cse_id,\n \"q\": query,\n \"num\": num_results,\n \"hl\": language,\n \"safe\": \"active\" if safe_search else \"off\",\n }\n\n if country:\n params[\"gl\"] = country\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(\"https://www.googleapis.com/customsearch/v1\", params=params, timeout=10)\n response.raise_for_status()\n data = response.json()\n\n results = []\n if \"items\" in data:\n for item in data[\"items\"]:\n result = {\"title\": item.get(\"title\", \"\"), \"link\": item.get(\"link\", \"\")}\n if include_snippets:\n result[\"snippet\"] = item.get(\"snippet\", \"\")\n\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n results.append(result)\n\n return results\n\n except httpx.RequestError as e:\n raise ValueError(f\"Failed to perform search: {str(e)}\") from e\n except KeyError as e:\n raise ValueError(f\"Invalid API response format: {str(e)}\") from e\n except Exception as e:\n raise ValueError(f\"Error during search: {str(e)}\") from e\n", + "name": "google_search", + "description": "\n Perform Google searches using the Custom Search API with optional webpage content fetching.\n Requires GOOGLE_API_KEY and GOOGLE_CSE_ID environment variables to be set.\n ", + "global_imports": [ + { + "module": "typing", + "imports": ["List", "Dict", "Optional"] + }, + "os", + "httpx", + "html2text", + { + "module": "bs4", + "imports": ["BeautifulSoup"] + }, + { + "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": null, + "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 + } + } + ] + } + } + ], "teams": [ { "provider": "autogen_agentchat.teams.RoundRobinGroupChat", @@ -652,438 +1082,6 @@ "max_selector_attempts": 3 } } - ], - "components": { - "agents": [ - { - "provider": "autogen_agentchat.agents.AssistantAgent", - "component_type": "agent", - "version": 1, - "component_version": 1, - "description": "An agent that provides assistance with ability to use tools.", - "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": "gpt-4o-mini" - } - }, - "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": "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 - } - } - ], - "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": "An agent that provides assistance with ability to use tools.", - "system_message": "You are a helpful assistant. Solve tasks carefully. When done, say TERMINATE.", - "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_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": "gpt-4o-mini" - } - }, - "description": "an agent that solves tasks by browsing the web", - "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": "gpt-4o-mini" - } - }, - "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": "an agent that verifies and summarizes information", - "system_message": "You are a task verification assistant who is working with a web surfer agent to solve tasks. At each point, check if the task has been completed as requested by the user. If the websurfer_agent responds and the task has not yet been completed, respond with what is left to do and then say 'keep going'. If and only when the task has been completed, summarize and present a final answer that directly addresses the user task in detail and then respond with TERMINATE.", - "model_client_stream": false, - "reflect_on_tool_use": false, - "tool_call_summary_format": "{result}" - } - }, - { - "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" - } - } - ], - "models": [ - { - "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient", - "component_type": "model", - "version": 1, - "component_version": 1, - "description": "OpenAI GPT-4o-mini", - "label": "OpenAI GPT-4o Mini", - "config": { - "model": "gpt-4o-mini" - } - }, - { - "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient", - "component_type": "model", - "version": 1, - "component_version": 1, - "description": "Local Mistral-7B model client for instruction-based generation (Ollama, LMStudio).", - "label": "Mistral-7B Local", - "config": { - "model": "TheBloke/Mistral-7B-Instruct-v0.2-GGUF", - "model_info": { - "vision": false, - "function_calling": true, - "json_output": false, - "family": "unknown" - }, - "base_url": "http://localhost:1234/v1" - } - }, - { - "provider": "autogen_ext.models.openai.AzureOpenAIChatCompletionClient", - "component_type": "model", - "version": 1, - "component_version": 1, - "description": "GPT-4o Mini Azure OpenAI model client.", - "label": "AzureOpenAI GPT-4o-mini", - "config": { - "model": "gpt-4o-mini", - "api_key": "sk-...", - "azure_endpoint": "https://{your-custom-endpoint}.openai.azure.com/", - "azure_deployment": "{your-azure-deployment}", - "api_version": "2024-06-01" - } - } - ], - "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 - } - }, - { - "provider": "autogen_core.tools.FunctionTool", - "component_type": "tool", - "version": 1, - "component_version": 1, - "description": "A tool that performs Bing searches using the Bing Web Search API. Requires the requests library, BING_SEARCH_KEY env variable to function.", - "label": "Bing Search Tool", - "config": { - "source_code": "async def bing_search(\n query: str,\n num_results: int = 3,\n include_snippets: bool = True,\n include_content: bool = True,\n content_max_length: Optional[int] = 10000,\n language: str = \"en\",\n country: Optional[str] = None,\n safe_search: str = \"moderate\",\n response_filter: str = \"webpages\",\n) -> List[Dict[str, str]]:\n \"\"\"\n Perform a Bing search using the Bing Web Search API.\n\n Args:\n query: Search query string\n num_results: Number of results to return (max 50)\n include_snippets: Include result snippets in output\n include_content: Include full webpage content in markdown format\n content_max_length: Maximum length of webpage content (if included)\n language: Language code for search results (e.g., 'en', 'es', 'fr')\n country: Optional market code for search results (e.g., 'us', 'uk')\n safe_search: SafeSearch setting ('off', 'moderate', or 'strict')\n response_filter: Type of results ('webpages', 'news', 'images', or 'videos')\n\n Returns:\n List[Dict[str, str]]: List of search results\n\n Raises:\n ValueError: If API credentials are invalid or request fails\n \"\"\"\n # Get and validate API key\n api_key = os.getenv(\"BING_SEARCH_KEY\", \"\").strip()\n\n if not api_key:\n raise ValueError(\n \"BING_SEARCH_KEY environment variable is not set. \" \"Please obtain an API key from Azure Portal.\"\n )\n\n # Validate safe_search parameter\n valid_safe_search = [\"off\", \"moderate\", \"strict\"]\n if safe_search.lower() not in valid_safe_search:\n raise ValueError(f\"Invalid safe_search value. Must be one of: {', '.join(valid_safe_search)}\")\n\n # Validate response_filter parameter\n valid_filters = [\"webpages\", \"news\", \"images\", \"videos\"]\n if response_filter.lower() not in valid_filters:\n raise ValueError(f\"Invalid response_filter value. Must be one of: {', '.join(valid_filters)}\")\n\n async def fetch_page_content(url: str, max_length: Optional[int] = 50000) -> str:\n \"\"\"Helper function to fetch and convert webpage content to markdown\"\"\"\n headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(url, headers=headers, timeout=10)\n response.raise_for_status()\n\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 h2t = html2text.HTML2Text()\n h2t.body_width = 0\n h2t.ignore_images = False\n h2t.ignore_emphasis = False\n h2t.ignore_links = False\n h2t.ignore_tables = False\n\n markdown = h2t.handle(str(soup))\n\n if max_length and len(markdown) > max_length:\n markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n return markdown.strip()\n\n except Exception as e:\n return f\"Error fetching content: {str(e)}\"\n\n # Build request headers and parameters\n headers = {\"Ocp-Apim-Subscription-Key\": api_key, \"Accept\": \"application/json\"}\n\n params = {\n \"q\": query,\n \"count\": min(max(1, num_results), 50),\n \"mkt\": f\"{language}-{country.upper()}\" if country else language,\n \"safeSearch\": safe_search.capitalize(),\n \"responseFilter\": response_filter,\n \"textFormat\": \"raw\",\n }\n\n # Make the request\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(\n \"https://api.bing.microsoft.com/v7.0/search\", headers=headers, params=params, timeout=10\n )\n\n # Handle common error cases\n if response.status_code == 401:\n raise ValueError(\"Authentication failed. Please verify your Bing Search API key.\")\n elif response.status_code == 403:\n raise ValueError(\n \"Access forbidden. This could mean:\\n\"\n \"1. The API key is invalid\\n\"\n \"2. The API key has expired\\n\"\n \"3. You've exceeded your API quota\"\n )\n elif response.status_code == 429:\n raise ValueError(\"API quota exceeded. Please try again later.\")\n\n response.raise_for_status()\n data = response.json()\n\n # Process results based on response_filter\n results = []\n if response_filter == \"webpages\" and \"webPages\" in data:\n items = data[\"webPages\"][\"value\"]\n elif response_filter == \"news\" and \"news\" in data:\n items = data[\"news\"][\"value\"]\n elif response_filter == \"images\" and \"images\" in data:\n items = data[\"images\"][\"value\"]\n elif response_filter == \"videos\" and \"videos\" in data:\n items = data[\"videos\"][\"value\"]\n else:\n if not any(key in data for key in [\"webPages\", \"news\", \"images\", \"videos\"]):\n return [] # No results found\n raise ValueError(f\"No {response_filter} results found in API response\")\n\n # Extract relevant information based on result type\n for item in items:\n result = {\"title\": item.get(\"name\", \"\")}\n\n if response_filter == \"webpages\":\n result[\"link\"] = item.get(\"url\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"snippet\", \"\")\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n elif response_filter == \"news\":\n result[\"link\"] = item.get(\"url\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n result[\"date\"] = item.get(\"datePublished\", \"\")\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n elif response_filter == \"images\":\n result[\"link\"] = item.get(\"contentUrl\", \"\")\n result[\"thumbnail\"] = item.get(\"thumbnailUrl\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n\n elif response_filter == \"videos\":\n result[\"link\"] = item.get(\"contentUrl\", \"\")\n result[\"thumbnail\"] = item.get(\"thumbnailUrl\", \"\")\n if include_snippets:\n result[\"snippet\"] = item.get(\"description\", \"\")\n result[\"duration\"] = item.get(\"duration\", \"\")\n\n results.append(result)\n\n return results[:num_results]\n\n except httpx.RequestException as e:\n error_msg = str(e)\n if \"InvalidApiKey\" in error_msg:\n raise ValueError(\"Invalid API key. Please check your BING_SEARCH_KEY environment variable.\") from e\n elif \"KeyExpired\" in error_msg:\n raise ValueError(\"API key has expired. Please generate a new key.\") from e\n else:\n raise ValueError(f\"Search request failed: {error_msg}\") from e\n except json.JSONDecodeError:\n raise ValueError(\"Failed to parse API response. \" \"Please verify your API credentials and try again.\") from None\n except Exception as e:\n raise ValueError(f\"Unexpected error during search: {str(e)}\") from e\n", - "name": "bing_search", - "description": "\n Perform Bing searches using the Bing Web Search API. Requires BING_SEARCH_KEY environment variable.\n Supports web, news, image, and video searches.\n See function documentation for detailed setup instructions.\n ", - "global_imports": [ - { - "module": "typing", - "imports": ["List", "Dict", "Optional"] - }, - "os", - "httpx", - "json", - "html2text", - { - "module": "bs4", - "imports": ["BeautifulSoup"] - }, - { - "module": "urllib.parse", - "imports": ["urljoin"] - } - ], - "has_cancellation_support": false - } - }, - { - "provider": "autogen_core.tools.FunctionTool", - "component_type": "tool", - "version": 1, - "component_version": 1, - "description": "A tool that performs Google searches using the Google Custom Search API. Requires the requests library, [GOOGLE_API_KEY, GOOGLE_CSE_ID] to be set, env variable to function.", - "label": "Google Search Tool", - "config": { - "source_code": "async def google_search(\n query: str,\n num_results: int = 3,\n include_snippets: bool = True,\n include_content: bool = True,\n content_max_length: Optional[int] = 10000,\n language: str = \"en\",\n country: Optional[str] = None,\n safe_search: bool = True,\n) -> List[Dict[str, str]]:\n \"\"\"\n Perform a Google search using the Custom Search API and optionally fetch webpage content.\n\n Args:\n query: Search query string\n num_results: Number of results to return (max 10)\n include_snippets: Include result snippets in output\n include_content: Include full webpage content in markdown format\n content_max_length: Maximum length of webpage content (if included)\n language: Language code for search results (e.g., en, es, fr)\n country: Optional country code for search results (e.g., us, uk)\n safe_search: Enable safe search filtering\n\n Returns:\n List[Dict[str, str]]: List of search results, each containing:\n - title: Result title\n - link: Result URL\n - snippet: Result description (if include_snippets=True)\n - content: Webpage content in markdown (if include_content=True)\n \"\"\"\n api_key = os.getenv(\"GOOGLE_API_KEY\")\n cse_id = os.getenv(\"GOOGLE_CSE_ID\")\n\n if not api_key or not cse_id:\n raise ValueError(\"Missing required environment variables. Please set GOOGLE_API_KEY and GOOGLE_CSE_ID.\")\n\n num_results = min(max(1, num_results), 10)\n\n async def fetch_page_content(url: str, max_length: Optional[int] = 50000) -> str:\n \"\"\"Helper function to fetch and convert webpage content to markdown\"\"\"\n headers = {\"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36\"}\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(url, headers=headers, timeout=10)\n response.raise_for_status()\n\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 h2t = html2text.HTML2Text()\n h2t.body_width = 0\n h2t.ignore_images = False\n h2t.ignore_emphasis = False\n h2t.ignore_links = False\n h2t.ignore_tables = False\n\n markdown = h2t.handle(str(soup))\n\n if max_length and len(markdown) > max_length:\n markdown = markdown[:max_length] + \"\\n...(truncated)\"\n\n return markdown.strip()\n\n except Exception as e:\n return f\"Error fetching content: {str(e)}\"\n\n params = {\n \"key\": api_key,\n \"cx\": cse_id,\n \"q\": query,\n \"num\": num_results,\n \"hl\": language,\n \"safe\": \"active\" if safe_search else \"off\",\n }\n\n if country:\n params[\"gl\"] = country\n\n try:\n async with httpx.AsyncClient() as client:\n response = await client.get(\"https://www.googleapis.com/customsearch/v1\", params=params, timeout=10)\n response.raise_for_status()\n data = response.json()\n\n results = []\n if \"items\" in data:\n for item in data[\"items\"]:\n result = {\"title\": item.get(\"title\", \"\"), \"link\": item.get(\"link\", \"\")}\n if include_snippets:\n result[\"snippet\"] = item.get(\"snippet\", \"\")\n\n if include_content:\n result[\"content\"] = await fetch_page_content(result[\"link\"], max_length=content_max_length)\n\n results.append(result)\n\n return results\n\n except httpx.RequestError as e:\n raise ValueError(f\"Failed to perform search: {str(e)}\") from e\n except KeyError as e:\n raise ValueError(f\"Invalid API response format: {str(e)}\") from e\n except Exception as e:\n raise ValueError(f\"Error during search: {str(e)}\") from e\n", - "name": "google_search", - "description": "\n Perform Google searches using the Custom Search API with optional webpage content fetching.\n Requires GOOGLE_API_KEY and GOOGLE_CSE_ID environment variables to be set.\n ", - "global_imports": [ - { - "module": "typing", - "imports": ["List", "Dict", "Optional"] - }, - "os", - "httpx", - "html2text", - { - "module": "bs4", - "imports": ["BeautifulSoup"] - }, - { - "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": null, - "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 - } - } - ] - } - } - ] - } + ] } } diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/detail.tsx b/python/packages/autogen-studio/frontend/src/components/views/gallery/detail.tsx index 0eb23391fed2..88942fd4476b 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/detail.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/detail.tsx @@ -1,170 +1,228 @@ -import React, { useState, useRef } from "react"; -import { Button, message, Tooltip } from "antd"; +import React, { useState } from "react"; +import { Tabs, Button, Tooltip, Drawer } from "antd"; import { Package, Users, Bot, Globe, - RefreshCw, - Edit2, - X, Wrench, Brain, Timer, - Save, - ChevronUp, - ChevronDown, Edit, + Copy, + Trash, } from "lucide-react"; +import { ComponentEditor } from "../team/builder/component-editor/component-editor"; +import { TruncatableText } from "../atoms"; import type { Gallery } from "./types"; -import { useGalleryStore } from "./store"; -import { MonacoEditor } from "../monaco"; -import { getRelativeTimeString, TruncatableText } from "../atoms"; -import { Component, ComponentConfig } from "../../types/datamodel"; +import { + Component, + ComponentConfig, + ComponentTypes, +} from "../../types/datamodel"; -const ComponentGrid: React.FC<{ - title: string; - icon: React.ReactNode; - items: Component[]; -}> = ({ title, icon, items }) => { - const [isExpanded, setIsExpanded] = useState(true); +type CategoryKey = `${ComponentTypes}s`; - return ( -
-
setIsExpanded(!isExpanded)} - > -
- {icon} - - {items.length} {items.length === 1 ? title : `${title}s`} - -
- {isExpanded ? ( - - ) : ( - - )} -
+interface CardActions { + onEdit: (component: Component, index: number) => void; + onDuplicate: (component: Component, index: number) => void; + onDelete: (component: Component, index: number) => void; +} -
- {items.map((item, idx) => ( -
-
- {item.provider} -
-
{item.label}
- {item.description && ( -
- -
- )} -
- ))} +// Component Card +const ComponentCard: React.FC< + CardActions & { + item: Component; + index: number; + } +> = ({ item, onEdit, onDuplicate, onDelete, index }) => ( +
onEdit(item, index)} + > +
+
+ {item.provider} +
+
+
- ); -}; +
+
{item.label}
+
+ +
+
+
+); -interface GalleryDetailProps { +// Component Grid +const ComponentGrid: React.FC< + { + items: Component[]; + title: string; + } & CardActions +> = ({ items, title, ...actions }) => ( +
+

+ {items.length} {items.length === 1 ? title : `${title}s`} +

+
+ {items.map((item, idx) => ( + + ))} +
+
+); + +const iconMap = { + team: Users, + agent: Bot, + tool: Wrench, + model: Brain, + termination: Timer, +} as const; + +export const GalleryDetail: React.FC<{ gallery: Gallery; onSave: (updates: Partial) => void; onDirtyStateChange: (isDirty: boolean) => void; -} +}> = ({ gallery, onSave, onDirtyStateChange }) => { + const [editingComponent, setEditingComponent] = useState<{ + component: Component; + category: CategoryKey; + index: number; + } | null>(null); + const [activeTab, setActiveTab] = useState("team"); + + const updateGallery = ( + category: CategoryKey, + updater: ( + components: Component[] + ) => Component[] + ) => { + const updatedGallery = { + ...gallery, + components: { + ...gallery.components, + [category]: updater(gallery.components[category]), + }, + }; + onSave(updatedGallery); + onDirtyStateChange(true); + }; -export const GalleryDetail: React.FC = ({ - gallery, - onSave, - onDirtyStateChange, -}) => { - const [isEditing, setIsEditing] = useState(false); - const [isSyncing, setIsSyncing] = useState(false); - const [jsonValue, setJsonValue] = useState(JSON.stringify(gallery, null, 2)); - const editorRef = useRef(null); - const { syncGallery, getLastSyncTime } = useGalleryStore(); + const handlers = { + onEdit: (component: Component, index: number) => { + setEditingComponent({ + component, + category: `${activeTab}s` as CategoryKey, + index, + }); + }, - const handleSync = async () => { - if (!gallery.url) return; + onDuplicate: (component: Component, index: number) => { + const category = `${activeTab}s` as CategoryKey; + const baseLabel = component.label?.replace(/_\d+$/, ""); + const components = gallery.components[category]; - setIsSyncing(true); - try { - await syncGallery(gallery.id); - message.success("Gallery synced successfully"); - } catch (error) { - message.error("Failed to sync gallery"); - } finally { - setIsSyncing(false); - } - }; + const nextNumber = + Math.max( + ...components + .map((c) => { + const match = c.label?.match( + new RegExp(`^${baseLabel}_?(\\d+)?$`) + ); + return match ? parseInt(match[1] || "0") : 0; + }) + .filter((n) => !isNaN(n)), + 0 + ) + 1; - const handleJsonChange = (value: string) => { - setJsonValue(value); - onDirtyStateChange(true); + updateGallery(category, (components) => [ + ...components, + { ...component, label: `${baseLabel}_${nextNumber}` }, + ]); + }, + + onDelete: (component: Component, index: number) => { + const category = `${activeTab}s` as CategoryKey; + updateGallery(category, (components) => + components.filter((_, i) => i !== index) + ); + }, }; - const handleSave = async () => { - try { - const parsedGallery = JSON.parse(jsonValue); - const updatedGallery = { - ...parsedGallery, - id: gallery.id, - metadata: { - ...parsedGallery.metadata, - updated_at: new Date().toISOString(), - }, - }; - await onSave(updatedGallery); - onDirtyStateChange(false); - setIsEditing(false); - message.success("Gallery updated successfully"); - } catch (error) { - message.error("Invalid JSON format"); - } + const handleComponentUpdate = ( + updatedComponent: Component + ) => { + if (!editingComponent) return; + + updateGallery(editingComponent.category, (components) => + components.map((c, i) => + i === editingComponent.index ? updatedComponent : c + ) + ); + setEditingComponent(null); }; - const gridItems = [ - { - icon: , - title: "team", - items: gallery.items.teams, - }, - { - icon: , - title: "agent", - items: gallery.items.components.agents, - }, - { - icon: , - title: "tool", - items: gallery.items.components.tools, - }, - { - icon: , - title: "model", - items: gallery.items.components.models, - }, - { - icon: , - title: "termination", - items: gallery.items.components.terminations, - }, - ]; + const tabItems = Object.entries(iconMap).map(([key, Icon]) => ({ + key, + label: ( + + + {key.charAt(0).toUpperCase() + key.slice(1)}s + + ({gallery.components[`${key}s` as CategoryKey].length}) + + + ), + children: ( + + ), + })); return ( -
- {/* Banner Section - Kept unchanged */} -
+
+
Gallery Banner = ({ )}
-

+

{gallery.metadata.description}

-

- {gallery.metadata.author} -

-
- {Object.values(gallery.items.components).reduce( + {Object.values(gallery.components).reduce( (sum, arr) => sum + arr.length, 0 )}{" "} @@ -204,113 +258,36 @@ export const GalleryDetail: React.FC = ({
v{gallery.metadata.version}
- {gallery.metadata.tags?.map((tag) => ( -
- {tag} -
- ))}
- {/* Action Buttons */} -
- {gallery.url && ( - - - - )} - {!isEditing ? ( - - ) : ( - <> - - - - )} -
+ setActiveTab(key as ComponentTypes)} + /> - {/* Grid Layout */} -
- {gridItems.map((item) => ( - setEditingComponent(null)} + open={!!editingComponent} + className="component-editor-drawer" + > + {editingComponent && ( + setEditingComponent(null)} + navigationDepth={true} /> - ))} -
- - {/* Editor Section */} - {isEditing && ( -
-
-

- Edit Gallery Configuration -

-
- -
-
-
- -
-
- )} + )} +
); }; + +export default GalleryDetail; diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/manager.tsx b/python/packages/autogen-studio/frontend/src/components/views/gallery/manager.tsx index 7dd8e15cd640..dbbc40a14aaf 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/manager.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/manager.tsx @@ -85,14 +85,12 @@ export const GalleryManager: React.FC = () => { created_at: new Date().toISOString(), updated_at: new Date().toISOString(), }, - items: galleryData.items || { + components: galleryData.components || { teams: [], - components: { - agents: [], - models: [], - tools: [], - terminations: [], - }, + agents: [], + models: [], + tools: [], + terminations: [], }, }; diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/sidebar.tsx b/python/packages/autogen-studio/frontend/src/components/views/gallery/sidebar.tsx index d375677158df..a58908c0a245 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/sidebar.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/sidebar.tsx @@ -237,7 +237,7 @@ export const GallerySidebar: React.FC = ({
- {Object.values(gallery.items.components).reduce( + {Object.values(gallery.components).reduce( (sum, arr) => sum + arr.length, 0 )}{" "} diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/store.tsx b/python/packages/autogen-studio/frontend/src/components/views/gallery/store.tsx index 604d4e57e73c..951c5e225f02 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/store.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/store.tsx @@ -145,13 +145,18 @@ export const useGalleryStore = create()( getGalleryComponents: () => { const defaultGallery = get().getDefaultGallery(); return { - teams: defaultGallery.items.teams, - components: defaultGallery.items.components, + teams: defaultGallery.components.teams, + components: { + agents: defaultGallery.components.agents, + models: defaultGallery.components.models, + tools: defaultGallery.components.tools, + terminations: defaultGallery.components.terminations, + }, }; }, }), { - name: "gallery-storage-v7", + name: "gallery-storage-v8", } ) ); diff --git a/python/packages/autogen-studio/frontend/src/components/views/gallery/types.ts b/python/packages/autogen-studio/frontend/src/components/views/gallery/types.ts index 7db306b904d9..479d89af54f4 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/gallery/types.ts +++ b/python/packages/autogen-studio/frontend/src/components/views/gallery/types.ts @@ -25,14 +25,12 @@ export interface Gallery { name: string; url?: string; metadata: GalleryMetadata; - items: { + components: { teams: Component[]; - components: { - agents: Component[]; - models: Component[]; - tools: Component[]; - terminations: Component[]; - }; + agents: Component[]; + models: Component[]; + tools: Component[]; + terminations: Component[]; }; } diff --git a/python/packages/autogen-studio/frontend/src/components/views/playground/chat/logrenderer.tsx b/python/packages/autogen-studio/frontend/src/components/views/playground/chat/logrenderer.tsx index 6a34f8a8e249..9942c583b3b4 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/playground/chat/logrenderer.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/playground/chat/logrenderer.tsx @@ -57,7 +57,7 @@ const FullLogView = ({ @@ -79,14 +79,19 @@ const FullLogView = ({
- {msg.role} {msg.name && `(${msg.name})`} + {(msg.name && `${msg.name}`) || msg.role}{" "} + {Array.isArray(msg.content) + " array "}
- + {Array.isArray(msg.content) ? ( + msg.content.map((item, index) => ( +
+ +
+ )) + ) : ( + + )}
))}
@@ -142,6 +147,8 @@ const LLMLogRenderer: React.FC = ({ content }) => { } }, [content]); + console.log(parsedContent); + if (!parsedContent) { return (
diff --git a/python/packages/autogen-studio/frontend/src/components/views/playground/chat/rendermessage.tsx b/python/packages/autogen-studio/frontend/src/components/views/playground/chat/rendermessage.tsx index 2041a1a1a7a7..e9025e2f1f82 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/playground/chat/rendermessage.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/playground/chat/rendermessage.tsx @@ -1,12 +1,5 @@ -import React, { useState, memo } from "react"; -import { - User, - Bot, - Maximize2, - Minimize2, - DraftingCompass, - Brain, -} from "lucide-react"; +import React from "react"; +import { User, Bot, DraftingCompass, Bug } from "lucide-react"; import { AgentMessageConfig, FunctionCall, @@ -176,7 +169,7 @@ export const RenderMessage: React.FC = ({ {isUser ? ( ) : message.source == "llm_call_event" ? ( - + ) : ( )} diff --git a/python/packages/autogen-studio/frontend/src/components/views/playground/manager.tsx b/python/packages/autogen-studio/frontend/src/components/views/playground/manager.tsx index 97be1dd0d045..c0be689ee191 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/playground/manager.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/playground/manager.tsx @@ -196,7 +196,7 @@ export const SessionManager: React.FC = () => { if (teamsData.length > 0) { setTeams(teamsData); } else { - const sampleTeam = defaultGallery.items.teams[0]; + const sampleTeam = defaultGallery.components.teams[0]; // If no teams, create a default team const defaultTeam = await teamAPI.createTeam( { diff --git a/python/packages/autogen-studio/frontend/src/components/views/settings/manager.tsx b/python/packages/autogen-studio/frontend/src/components/views/settings/manager.tsx index fbae94e50960..0ab511e796e8 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/settings/manager.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/settings/manager.tsx @@ -26,7 +26,7 @@ const SettingToggle: React.FC = ({ label, description, }) => ( -
+
{description && ( @@ -85,7 +85,7 @@ export const SettingsManager: React.FC = () => { icon={MessagesSquare} onReset={resetPlaygroundSettings} /> -
+
diff --git a/python/packages/autogen-studio/frontend/src/components/views/team/api.ts b/python/packages/autogen-studio/frontend/src/components/views/team/api.ts index 65ff98b28ff3..c3059d8c98c9 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/team/api.ts +++ b/python/packages/autogen-studio/frontend/src/components/views/team/api.ts @@ -107,7 +107,7 @@ export class ValidationAPI { async validateComponent( component: Component ): Promise { - const response = await fetch(`${this.getBaseUrl()}/validate`, { + const response = await fetch(`${this.getBaseUrl()}/validate/`, { method: "POST", headers: this.getHeaders(), body: JSON.stringify({ diff --git a/python/packages/autogen-studio/frontend/src/components/views/team/builder/builder.tsx b/python/packages/autogen-studio/frontend/src/components/views/team/builder/builder.tsx index 335c4e9f1611..5a8159b4ca4d 100644 --- a/python/packages/autogen-studio/frontend/src/components/views/team/builder/builder.tsx +++ b/python/packages/autogen-studio/frontend/src/components/views/team/builder/builder.tsx @@ -20,7 +20,7 @@ import { MiniMap, } from "@xyflow/react"; import "@xyflow/react/dist/style.css"; -import { Button, Layout, message, Switch, Tooltip } from "antd"; +import { Button, Drawer, Layout, message, Switch, Tooltip } from "antd"; import { Cable, CheckCircle, @@ -41,11 +41,11 @@ import { edgeTypes, nodeTypes } from "./nodes"; import "./builder.css"; import TeamBuilderToolbar from "./toolbar"; import { MonacoEditor } from "../../monaco"; -import { NodeEditor } from "./node-editor/node-editor"; import debounce from "lodash.debounce"; import TestDrawer from "./testdrawer"; import { validationAPI, ValidationResponse } from "../api"; import { ValidationErrors } from "./validationerrors"; +import ComponentEditor from "./component-editor/component-editor"; const { Sider, Content } = Layout; interface DragItemData { @@ -529,17 +529,35 @@ export const TeamBuilder: React.FC = ({ - n.id === selectedNodeId) || null} - onUpdate={(updates) => { - if (selectedNodeId) { - console.log("updating node", selectedNodeId, updates); - updateNode(selectedNodeId, updates); - handleSave(); - } - }} - onClose={() => setSelectedNode(null)} - /> + {selectedNodeId && ( + setSelectedNode(null)} + open={!!selectedNodeId} + className="component-editor-drawer" + > + {nodes.find((n) => n.id === selectedNodeId)?.data.component && ( + n.id === selectedNodeId)!.data.component + } + onChange={(updatedComponent) => { + console.log("builder updating component", updatedComponent); + if (selectedNodeId) { + updateNode(selectedNodeId, { + component: updatedComponent, + }); + handleSave(); + } + }} + onClose={() => setSelectedNode(null)} + navigationDepth={true} + /> + )} + + )} ; + onChange: (updatedComponent: Component) => void; + onClose?: () => void; + navigationDepth?: boolean; +} + +export const ComponentEditor: React.FC = ({ + component, + onChange, + onClose, + navigationDepth = false, +}) => { + const [editPath, setEditPath] = useState([]); + const [workingCopy, setWorkingCopy] = useState>( + Object.assign({}, component) + ); + const [isJsonEditing, setIsJsonEditing] = useState(false); + + const editorRef = useRef(null); + + // Reset working copy when component changes + React.useEffect(() => { + setWorkingCopy(component); + setEditPath([]); + }, [component]); + + const getCurrentComponent = useCallback( + (root: Component) => { + return editPath.reduce | null>( + (current, path) => { + if (!current) return null; + + const field = current.config[ + path.parentField as keyof typeof current.config + ] as + | Component[] + | Component + | undefined; + + if (Array.isArray(field)) { + return ( + field.find( + (item) => + item.label === path.id || + (item.config && + "name" in item.config && + item.config.name === path.id) + ) || null + ); + } + + return field || null; + }, + root + ); + }, + [editPath] + ); + + const updateComponentAtPath = useCallback( + ( + root: Component, + path: EditPath[], + updates: Partial> + ): Component => { + if (path.length === 0) { + return { + ...root, + ...updates, + config: { + ...root.config, + ...(updates.config || {}), + }, + }; + } + + const [currentPath, ...remainingPath] = path; + const field = + root.config[currentPath.parentField as keyof typeof root.config]; + + const updateField = (fieldValue: any): any => { + if (Array.isArray(fieldValue)) { + return fieldValue.map((item) => { + if (!("component_type" in item)) return item; + if ( + item.label === currentPath.id || + ("name" in item.config && item.config.name === currentPath.id) + ) { + return updateComponentAtPath(item, remainingPath, updates); + } + return item; + }); + } + + if (fieldValue && "component_type" in fieldValue) { + return updateComponentAtPath( + fieldValue as Component, + remainingPath, + updates + ); + } + + return fieldValue; + }; + + return { + ...root, + config: { + ...root.config, + [currentPath.parentField]: updateField(field), + }, + }; + }, + [] + ); + + const handleComponentUpdate = useCallback( + (updates: Partial>) => { + const updatedComponent = updateComponentAtPath( + workingCopy, + editPath, + updates + ); + console.log("updatedComponent", updatedComponent); + setWorkingCopy(updatedComponent); + // onChange(updatedComponent); + }, + [workingCopy, editPath, updateComponentAtPath] + ); + + const handleNavigate = useCallback( + (componentType: string, id: string, parentField: string) => { + if (!navigationDepth) return; + setEditPath((prev) => [...prev, { componentType, id, parentField }]); + }, + [navigationDepth] + ); + + const handleNavigateBack = useCallback(() => { + setEditPath((prev) => prev.slice(0, -1)); + }, []); + + const debouncedJsonUpdate = useCallback( + debounce((value: string) => { + try { + const updatedComponent = JSON.parse(value); + setWorkingCopy(updatedComponent); + } catch (err) { + console.error("Invalid JSON", err); + } + }, 500), + [] + ); + + const currentComponent = getCurrentComponent(workingCopy) || workingCopy; + + const renderFields = useCallback(() => { + const commonProps = { + component: currentComponent, + onChange: handleComponentUpdate, + }; + + if (isTeamComponent(currentComponent)) { + return ( + + ); + } + if (isAgentComponent(currentComponent)) { + return ( + + ); + } + if (isModelComponent(currentComponent)) { + return ( + + ); + } + if (isToolComponent(currentComponent)) { + return ; + } + if (isTerminationComponent(currentComponent)) { + return ( + + ); + } + + return null; + }, [currentComponent, handleComponentUpdate, handleNavigate]); + + const breadcrumbItems = React.useMemo( + () => [ + { title: workingCopy.label || "Root" }, + ...editPath.map((path) => ({ + title: path.id, + })), + ], + [workingCopy.label, editPath] + ); + + const handleSave = useCallback(() => { + console.log("working copy", workingCopy.config); + onChange(workingCopy); + onClose?.(); + }, [workingCopy, onChange, onClose]); + + return ( +
+
+ {navigationDepth && editPath.length > 0 && ( + +
+ {isJsonEditing ? ( +
+ +
+ ) : ( +
{renderFields()}
+ )} + {onClose && ( +
+ + +
+ )} +
+ ); +}; + +export default ComponentEditor; diff --git a/python/packages/autogen-studio/frontend/src/components/views/team/builder/node-editor/detailgroup.tsx b/python/packages/autogen-studio/frontend/src/components/views/team/builder/component-editor/detailgroup.tsx similarity index 100% rename from python/packages/autogen-studio/frontend/src/components/views/team/builder/node-editor/detailgroup.tsx rename to python/packages/autogen-studio/frontend/src/components/views/team/builder/component-editor/detailgroup.tsx diff --git a/python/packages/autogen-studio/frontend/src/components/views/team/builder/component-editor/fields/agent-fields.tsx b/python/packages/autogen-studio/frontend/src/components/views/team/builder/component-editor/fields/agent-fields.tsx new file mode 100644 index 000000000000..4034a88ea895 --- /dev/null +++ b/python/packages/autogen-studio/frontend/src/components/views/team/builder/component-editor/fields/agent-fields.tsx @@ -0,0 +1,324 @@ +import React, { useCallback } from "react"; +import { Input, Switch, Button, Tooltip } from "antd"; +import { Edit, HelpCircle, Trash2 } from "lucide-react"; +import { + Component, + ComponentConfig, + AgentConfig, +} from "../../../../../types/datamodel"; +import { + isAssistantAgent, + isUserProxyAgent, + isWebSurferAgent, +} from "../../../../../types/guards"; +import DetailGroup from "../detailgroup"; + +const { TextArea } = Input; + +interface AgentFieldsProps { + component: Component; + onChange: (updates: Partial>) => void; + onNavigate?: (componentType: string, id: string, parentField: string) => void; +} + +const InputWithTooltip: React.FC<{ + label: string; + tooltip: string; + required?: boolean; + children: React.ReactNode; +}> = ({ label, tooltip, required, children }) => ( + +); + +export const AgentFields: React.FC = ({ + component, + onChange, + onNavigate, +}) => { + if (!component) return null; + + const handleComponentUpdate = useCallback( + (updates: Partial>) => { + onChange({ + ...component, + ...updates, + config: { + ...component.config, + ...(updates.config || {}), + }, + }); + }, + [component, onChange] + ); + + const handleConfigUpdate = useCallback( + (field: string, value: unknown) => { + handleComponentUpdate({ + config: { + ...component.config, + [field]: value, + }, + }); + }, + [component, handleComponentUpdate] + ); + + const handleRemoveTool = useCallback( + (toolIndex: number) => { + if (!isAssistantAgent(component)) return; + const newTools = [...(component.config.tools || [])]; + newTools.splice(toolIndex, 1); + handleConfigUpdate("tools", newTools); + }, + [component, handleConfigUpdate] + ); + + const renderNestedComponents = () => { + if (isAssistantAgent(component)) { + return ( +
+ {component.config.model_client && ( +
+

Model Client

+
+
+ + {component.config.model_client.config.model} + + {onNavigate && ( +
+
+
+ )} + + {component.config.tools && component.config.tools.length > 0 && ( +
+

Tools

+
+ {component.config.tools.map((tool, index) => ( +
+
+ + {tool.label || tool.config.name} + +
+ {onNavigate && ( +
+
+
+ ))} +
+
+ )} +
+ ); + } + + if (isWebSurferAgent(component)) { + return ( +
+ {component.config.model_client && ( +
+

Model Client

+
+
+ + {component.config.model_client.config.model} + + {onNavigate && ( +
+
+
+ )} +
+ ); + } + + return ( +
+ No nested components +
+ ); + }; + + return ( +
+ +
+ + +