import os import re from http import HTTPStatus from typing import Dict, List, Optional, Tuple import base64 import mimetypes import PyPDF2 import docx import cv2 import numpy as np from PIL import Image import pytesseract import requests from urllib.parse import urlparse, urljoin from bs4 import BeautifulSoup import html2text import json import time import webbrowser import urllib.parse import copy import html import gradio as gr from huggingface_hub import InferenceClient from tavily import TavilyClient from huggingface_hub import HfApi import tempfile from openai import OpenAI # Gradio supported languages for syntax highlighting GRADIO_SUPPORTED_LANGUAGES = [ "python", "c", "cpp", "markdown", "latex", "json", "html", "css", "javascript", "jinja2", "typescript", "yaml", "dockerfile", "shell", "r", "sql", "sql-msSQL", "sql-mySQL", "sql-mariaDB", "sql-sqlite", "sql-cassandra", "sql-plSQL", "sql-hive", "sql-pgSQL", "sql-gql", "sql-gpSQL", "sql-sparkSQL", "sql-esper", None ] def get_gradio_language(language): return language if language in GRADIO_SUPPORTED_LANGUAGES else None # Search/Replace Constants SEARCH_START = "<<<<<<< SEARCH" DIVIDER = "=======" REPLACE_END = ">>>>>>> REPLACE" # Configuration HTML_SYSTEM_PROMPT = """ONLY USE HTML, CSS AND JAVASCRIPT. If you want to use ICON make sure to import the library first. Try to create the best UI possible by using only HTML, CSS and JAVASCRIPT. MAKE IT RESPONSIVE USING MODERN CSS. Use as much as you can modern CSS for the styling, if you can't do something with modern CSS, then use custom CSS. Also, try to elaborate as much as you can, to create something unique. ALWAYS GIVE THE RESPONSE INTO A SINGLE HTML FILE For website redesign tasks: - Use the provided original HTML code as the starting point for redesign - Preserve all original content, structure, and functionality - Keep the same semantic HTML structure but enhance the styling - Reuse all original images and their URLs from the HTML code - Create a modern, responsive design with improved typography and spacing - Use modern CSS frameworks and design patterns - Ensure accessibility and mobile responsiveness - Maintain the same navigation and user flow - Enhance the visual design while keeping the original layout structure If an image is provided, analyze it and use the visual information to better understand the user's requirements. Always respond with code that can be executed or rendered directly. Always output only the HTML code inside a ```html ... ``` code block, and do not include any explanations or extra text. Do NOT add the language name at the top of the code output.""" TRANSFORMERS_JS_SYSTEM_PROMPT = """You are an expert web developer creating a transformers.js application. You will generate THREE separate files: index.html, index.js, and style.css. IMPORTANT: You MUST output ALL THREE files in the following format: ```html ``` ```javascript // index.js content here ``` ```css /* style.css content here */ ``` Requirements: 1. Create a modern, responsive web application using transformers.js 2. Use the transformers.js library for AI/ML functionality 3. Create a clean, professional UI with good user experience 4. Make the application fully responsive for mobile devices 5. Use modern CSS practices and JavaScript ES6+ features 6. Include proper error handling and loading states 7. Follow accessibility best practices The index.html should contain the basic HTML structure and link to the CSS and JS files. The index.js should contain all the JavaScript logic including transformers.js integration. The style.css should contain all the styling for the application. Always output only the three code blocks as shown above, and do not include any explanations or extra text.""" SVELTE_SYSTEM_PROMPT = """You are an expert Svelte developer creating a modern Svelte application. You will generate ONLY the custom files that need user-specific content for the user's requested application. IMPORTANT: You MUST output files in the following format. Generate ONLY the files needed for the user's specific request: ```svelte ``` ```css /* src/app.css content here */ ``` If you need additional components for the user's specific app, add them like: ```svelte ``` Requirements: 1. Create a modern, responsive Svelte application based on the user's specific request 2. Use TypeScript for better type safety 3. Create a clean, professional UI with good user experience 4. Make the application fully responsive for mobile devices 5. Use modern CSS practices and Svelte best practices 6. Include proper error handling and loading states 7. Follow accessibility best practices 8. Use Svelte's reactive features effectively 9. Include proper component structure and organization 10. Generate ONLY components that are actually needed for the user's requested application Files you should generate: - src/App.svelte: Main application component (ALWAYS required) - src/app.css: Global styles (ALWAYS required) - src/lib/[ComponentName].svelte: Additional components (ONLY if needed for the user's specific app) The other files (index.html, package.json, vite.config.ts, tsconfig files, svelte.config.js, src/main.ts, src/vite-env.d.ts) are provided by the Svelte template and don't need to be generated. Always output only the two code blocks as shown above, and do not include any explanations or extra text.""" SVELTE_SYSTEM_PROMPT_WITH_SEARCH = """You are an expert Svelte developer creating a modern Svelte application. You have access to real-time web search. When needed, use web search to find the latest information, best practices, or specific Svelte technologies. You will generate ONLY the custom files that need user-specific content. IMPORTANT: You MUST output ONLY the custom files in the following format: ```svelte ``` ```css /* src/app.css content here --> ``` Requirements: 1. Create a modern, responsive Svelte application 2. Use TypeScript for better type safety 3. Create a clean, professional UI with good user experience 4. Make the application fully responsive for mobile devices 5. Use modern CSS practices and Svelte best practices 6. Include proper error handling and loading states 7. Follow accessibility best practices 8. Use Svelte's reactive features effectively 9. Include proper component structure and organization 10. Use web search to find the latest Svelte patterns, libraries, and best practices The files you generate are: - src/App.svelte: Main application component (your custom app logic) - src/app.css: Global styles (your custom styling) The other files (index.html, package.json, vite.config.ts, tsconfig files, svelte.config.js, src/main.ts, src/vite-env.d.ts) are provided by the Svelte template and don't need to be generated. Always output only the two code blocks as shown above, and do not include any explanations or extra text.""" TRANSFORMERS_JS_SYSTEM_PROMPT_WITH_SEARCH = """You are an expert web developer creating a transformers.js application. You have access to real-time web search. When needed, use web search to find the latest information, best practices, or specific technologies for transformers.js. You will generate THREE separate files: index.html, index.js, and style.css. IMPORTANT: You MUST output ALL THREE files in the following format: ```html ``` ```javascript // index.js content here ``` ```css /* style.css content here */ ``` Requirements: 1. Create a modern, responsive web application using transformers.js 2. Use the transformers.js library for AI/ML functionality 3. Use web search to find current best practices and latest transformers.js features 4. Create a clean, professional UI with good user experience 5. Make the application fully responsive for mobile devices 6. Use modern CSS practices and JavaScript ES6+ features 7. Include proper error handling and loading states 8. Follow accessibility best practices The index.html should contain the basic HTML structure and link to the CSS and JS files. The index.js should contain all the JavaScript logic including transformers.js integration. The style.css should contain all the styling for the application. Always output only the three code blocks as shown above, and do not include any explanations or extra text.""" GENERIC_SYSTEM_PROMPT = """You are an expert {language} developer. Write clean, idiomatic, and runnable {language} code for the user's request. If possible, include comments and best practices. Output ONLY the code inside a ``` code block, and do not include any explanations or extra text. If the user provides a file or other context, use it as a reference. If the code is for a script or app, make it as self-contained as possible. Do NOT add the language name at the top of the code output.""" # System prompt with search capability HTML_SYSTEM_PROMPT_WITH_SEARCH = """ONLY USE HTML, CSS AND JAVASCRIPT. If you want to use ICON make sure to import the library first. Try to create the best UI possible by using only HTML, CSS and JAVASCRIPT. MAKE IT RESPONSIVE USING MODERN CSS. Use as much as you can modern CSS for the styling, if you can't do something with modern CSS, then use custom CSS. Also, try to elaborate as much as you can, to create something unique. ALWAYS GIVE THE RESPONSE INTO A SINGLE HTML FILE You have access to real-time web search. When needed, use web search to find the latest information, best practices, or specific technologies. For website redesign tasks: - Use the provided original HTML code as the starting point for redesign - Preserve all original content, structure, and functionality - Keep the same semantic HTML structure but enhance the styling - Reuse all original images and their URLs from the HTML code - Use web search to find current design trends and best practices for the specific type of website - Create a modern, responsive design with improved typography and spacing - Use modern CSS frameworks and design patterns - Ensure accessibility and mobile responsiveness - Maintain the same navigation and user flow - Enhance the visual design while keeping the original layout structure If an image is provided, analyze it and use the visual information to better understand the user's requirements. Always respond with code that can be executed or rendered directly. Always output only the HTML code inside a ```html ... ``` code block, and do not include any explanations or extra text. Do NOT add the language name at the top of the code output.""" GENERIC_SYSTEM_PROMPT_WITH_SEARCH = """You are an expert {language} developer. You have access to real-time web search. When needed, use web search to find the latest information, best practices, or specific technologies for {language}. Write clean, idiomatic, and runnable {language} code for the user's request. If possible, include comments and best practices. Output ONLY the code inside a ``` code block, and do not include any explanations or extra text. If the user provides a file or other context, use it as a reference. If the code is for a script or app, make it as self-contained as possible. Do NOT add the language name at the top of the code output.""" # Follow-up system prompt for modifying existing HTML files FollowUpSystemPrompt = f"""You are an expert web developer modifying an existing HTML file. The user wants to apply changes based on their request. You MUST output ONLY the changes required using the following SEARCH/REPLACE block format. Do NOT output the entire file. Explain the changes briefly *before* the blocks if necessary, but the code changes THEMSELVES MUST be within the blocks. Format Rules: 1. Start with {SEARCH_START} 2. Provide the exact lines from the current code that need to be replaced. 3. Use {DIVIDER} to separate the search block from the replacement. 4. Provide the new lines that should replace the original lines. 5. End with {REPLACE_END} 6. You can use multiple SEARCH/REPLACE blocks if changes are needed in different parts of the file. 7. To insert code, use an empty SEARCH block (only {SEARCH_START} and {DIVIDER} on their lines) if inserting at the very beginning, otherwise provide the line *before* the insertion point in the SEARCH block and include that line plus the new lines in the REPLACE block. 8. To delete code, provide the lines to delete in the SEARCH block and leave the REPLACE block empty (only {DIVIDER} and {REPLACE_END} on their lines). 9. IMPORTANT: The SEARCH block must *exactly* match the current code, including indentation and whitespace. Example Modifying Code: ``` Some explanation... {SEARCH_START}

Old Title

{DIVIDER}

New Title

{REPLACE_END} {SEARCH_START} {DIVIDER} {REPLACE_END} ``` Example Deleting Code: ``` Removing the paragraph... {SEARCH_START}

This paragraph will be deleted.

{DIVIDER} {REPLACE_END} ```""" # Follow-up system prompt for modifying existing transformers.js applications TransformersJSFollowUpSystemPrompt = f"""You are an expert web developer modifying an existing transformers.js application. The user wants to apply changes based on their request. You MUST output ONLY the changes required using the following SEARCH/REPLACE block format. Do NOT output the entire file. Explain the changes briefly *before* the blocks if necessary, but the code changes THEMSELVES MUST be within the blocks. The transformers.js application consists of three files: index.html, index.js, and style.css. When making changes, specify which file you're modifying by starting your search/replace blocks with the file name. Format Rules: 1. Start with {SEARCH_START} 2. Provide the exact lines from the current code that need to be replaced. 3. Use {DIVIDER} to separate the search block from the replacement. 4. Provide the new lines that should replace the original lines. 5. End with {REPLACE_END} 6. You can use multiple SEARCH/REPLACE blocks if changes are needed in different parts of the file. 7. To insert code, use an empty SEARCH block (only {SEARCH_START} and {DIVIDER} on their lines) if inserting at the very beginning, otherwise provide the line *before* the insertion point in the SEARCH block and include that line plus the new lines in the REPLACE block. 8. To delete code, provide the lines to delete in the SEARCH block and leave the REPLACE block empty (only {DIVIDER} and {REPLACE_END} on their lines). 9. IMPORTANT: The SEARCH block must *exactly* match the current code, including indentation and whitespace. Example Modifying HTML: ``` Changing the title in index.html... {SEARCH_START} Old Title {DIVIDER} New Title {REPLACE_END} ``` Example Modifying JavaScript: ``` Adding a new function to index.js... {SEARCH_START} // Existing code {DIVIDER} // Existing code function newFunction() {{ console.log("New function added"); }} {REPLACE_END} ``` Example Modifying CSS: ``` Changing background color in style.css... {SEARCH_START} body {{ background-color: white; }} {DIVIDER} body {{ background-color: #f0f0f0; }} {REPLACE_END} ```""" # Available models AVAILABLE_MODELS = [ { "name": "Moonshot Kimi-K2", "id": "moonshotai/Kimi-K2-Instruct", "description": "Moonshot AI Kimi-K2-Instruct model for code generation and general tasks" }, { "name": "DeepSeek V3", "id": "deepseek-ai/DeepSeek-V3-0324", "description": "DeepSeek V3 model for code generation" }, { "name": "DeepSeek R1", "id": "deepseek-ai/DeepSeek-R1-0528", "description": "DeepSeek R1 model for code generation" }, { "name": "ERNIE-4.5-VL", "id": "baidu/ERNIE-4.5-VL-424B-A47B-Base-PT", "description": "ERNIE-4.5-VL model for multimodal code generation with image support" }, { "name": "MiniMax M1", "id": "MiniMaxAI/MiniMax-M1-80k", "description": "MiniMax M1 model for code generation and general tasks" }, { "name": "Qwen3-235B-A22B", "id": "Qwen/Qwen3-235B-A22B", "description": "Qwen3-235B-A22B model for code generation and general tasks" }, { "name": "SmolLM3-3B", "id": "HuggingFaceTB/SmolLM3-3B", "description": "SmolLM3-3B model for code generation and general tasks" }, { "name": "GLM-4.5", "id": "GLM-4.5", "description": "GLM-4.5 model with thinking capabilities for advanced code generation" }, { "name": "GLM-4.1V-9B-Thinking", "id": "THUDM/GLM-4.1V-9B-Thinking", "description": "GLM-4.1V-9B-Thinking model for multimodal code generation with image support" }, { "name": "Qwen3-235B-A22B-Instruct-2507", "id": "Qwen/Qwen3-235B-A22B-Instruct-2507", "description": "Qwen3-235B-A22B-Instruct-2507 model for code generation and general tasks" }, { "name": "Qwen3-Coder-480B-A35B", "id": "Qwen/Qwen3-Coder-480B-A35B-Instruct", "description": "Qwen3-Coder-480B-A35B-Instruct model for advanced code generation and programming tasks" }, { "name": "Qwen3-32B", "id": "Qwen/Qwen3-32B", "description": "Qwen3-32B model for code generation and general tasks" }, { "name": "Qwen3-235B-A22B-Thinking", "id": "Qwen/Qwen3-235B-A22B-Thinking-2507", "description": "Qwen3-235B-A22B-Thinking model with advanced reasoning capabilities" } ] DEMO_LIST = [ { "title": "Todo App", "description": "Create a simple todo application with add, delete, and mark as complete functionality" }, { "title": "Calculator", "description": "Build a basic calculator with addition, subtraction, multiplication, and division" }, { "title": "Chat Interface", "description": "Build a chat interface with message history and user input" }, { "title": "E-commerce Product Card", "description": "Create a product card component for an e-commerce website" }, { "title": "Login Form", "description": "Build a responsive login form with validation" }, { "title": "Dashboard Layout", "description": "Create a dashboard layout with sidebar navigation and main content area" }, { "title": "Data Table", "description": "Build a data table with sorting and filtering capabilities" }, { "title": "Image Gallery", "description": "Create an image gallery with lightbox functionality and responsive grid layout" }, { "title": "UI from Image", "description": "Upload an image of a UI design and I'll generate the HTML/CSS code for it" }, { "title": "Extract Text from Image", "description": "Upload an image containing text and I'll extract and process the text content" }, { "title": "Website Redesign", "description": "Enter a website URL to extract its content and redesign it with a modern, responsive layout" }, { "title": "Modify HTML", "description": "After generating HTML, ask me to modify it with specific changes using search/replace format" }, { "title": "Search/Replace Example", "description": "Generate HTML first, then ask: 'Change the title to My New Title' or 'Add a blue background to the body'" }, { "title": "Transformers.js App", "description": "Create a transformers.js application with AI/ML functionality using the transformers.js library" }, { "title": "Svelte App", "description": "Create a modern Svelte application with TypeScript, Vite, and responsive design" } ] # HF Inference Client HF_TOKEN = os.getenv('HF_TOKEN') if not HF_TOKEN: raise RuntimeError("HF_TOKEN environment variable is not set. Please set it to your Hugging Face API token.") def get_inference_client(model_id, provider="auto"): """Return an InferenceClient with provider based on model_id and user selection.""" if model_id == "moonshotai/Kimi-K2-Instruct": provider = "groq" elif model_id == "Qwen/Qwen3-235B-A22B": provider = "cerebras" elif model_id == "Qwen/Qwen3-32B": provider = "cerebras" elif model_id == "Qwen/Qwen3-235B-A22B-Thinking-2507": provider = "auto" # Let HuggingFace handle provider selection return InferenceClient( provider=provider, api_key=HF_TOKEN, bill_to="huggingface" ) # Type definitions History = List[Tuple[str, str]] Messages = List[Dict[str, str]] # Tavily Search Client TAVILY_API_KEY = os.getenv('TAVILY_API_KEY') tavily_client = None if TAVILY_API_KEY: try: tavily_client = TavilyClient(api_key=TAVILY_API_KEY) except Exception as e: print(f"Failed to initialize Tavily client: {e}") tavily_client = None def history_to_messages(history: History, system: str) -> Messages: messages = [{'role': 'system', 'content': system}] for h in history: # Handle multimodal content in history user_content = h[0] if isinstance(user_content, list): # Extract text from multimodal content text_content = "" for item in user_content: if isinstance(item, dict) and item.get("type") == "text": text_content += item.get("text", "") user_content = text_content if text_content else str(user_content) messages.append({'role': 'user', 'content': user_content}) messages.append({'role': 'assistant', 'content': h[1]}) return messages def messages_to_history(messages: Messages) -> Tuple[str, History]: assert messages[0]['role'] == 'system' history = [] for q, r in zip(messages[1::2], messages[2::2]): # Extract text content from multimodal messages for history user_content = q['content'] if isinstance(user_content, list): text_content = "" for item in user_content: if isinstance(item, dict) and item.get("type") == "text": text_content += item.get("text", "") user_content = text_content if text_content else str(user_content) history.append([user_content, r['content']]) return history def history_to_chatbot_messages(history: History) -> List[Dict[str, str]]: """Convert history tuples to chatbot message format""" messages = [] for user_msg, assistant_msg in history: # Handle multimodal content if isinstance(user_msg, list): text_content = "" for item in user_msg: if isinstance(item, dict) and item.get("type") == "text": text_content += item.get("text", "") user_msg = text_content if text_content else str(user_msg) messages.append({"role": "user", "content": user_msg}) messages.append({"role": "assistant", "content": assistant_msg}) return messages def remove_code_block(text): # Try to match code blocks with language markers patterns = [ r'```(?:html|HTML)\n([\s\S]+?)\n```', # Match ```html or ```HTML r'```\n([\s\S]+?)\n```', # Match code blocks without language markers r'```([\s\S]+?)```' # Match code blocks without line breaks ] for pattern in patterns: match = re.search(pattern, text, re.DOTALL) if match: extracted = match.group(1).strip() # Remove a leading language marker line (e.g., 'python') if present if extracted.split('\n', 1)[0].strip().lower() in ['python', 'html', 'css', 'javascript', 'json', 'c', 'cpp', 'markdown', 'latex', 'jinja2', 'typescript', 'yaml', 'dockerfile', 'shell', 'r', 'sql', 'sql-mssql', 'sql-mysql', 'sql-mariadb', 'sql-sqlite', 'sql-cassandra', 'sql-plSQL', 'sql-hive', 'sql-pgsql', 'sql-gql', 'sql-gpsql', 'sql-sparksql', 'sql-esper']: return extracted.split('\n', 1)[1] if '\n' in extracted else '' return extracted # If no code block is found, check if the entire text is HTML if text.strip().startswith('') or text.strip().startswith(' 1 else '' return text.strip() def parse_transformers_js_output(text): """Parse transformers.js output and extract the three files (index.html, index.js, style.css)""" files = { 'index.html': '', 'index.js': '', 'style.css': '' } # Patterns to match the three code blocks html_pattern = r'```html\s*\n([\s\S]+?)\n```' js_pattern = r'```javascript\s*\n([\s\S]+?)\n```' css_pattern = r'```css\s*\n([\s\S]+?)\n```' # Extract HTML content html_match = re.search(html_pattern, text, re.IGNORECASE) if html_match: files['index.html'] = html_match.group(1).strip() # Extract JavaScript content js_match = re.search(js_pattern, text, re.IGNORECASE) if js_match: files['index.js'] = js_match.group(1).strip() # Extract CSS content css_match = re.search(css_pattern, text, re.IGNORECASE) if css_match: files['style.css'] = css_match.group(1).strip() # Fallback: support === index.html === format if any file is missing if not (files['index.html'] and files['index.js'] and files['style.css']): # Use regex to extract sections html_fallback = re.search(r'===\s*index\.html\s*===\n([\s\S]+?)(?=\n===|$)', text, re.IGNORECASE) js_fallback = re.search(r'===\s*index\.js\s*===\n([\s\S]+?)(?=\n===|$)', text, re.IGNORECASE) css_fallback = re.search(r'===\s*style\.css\s*===\n([\s\S]+?)(?=\n===|$)', text, re.IGNORECASE) if html_fallback: files['index.html'] = html_fallback.group(1).strip() if js_fallback: files['index.js'] = js_fallback.group(1).strip() if css_fallback: files['style.css'] = css_fallback.group(1).strip() return files def format_transformers_js_output(files): """Format the three files into a single display string""" output = [] output.append("=== index.html ===") output.append(files['index.html']) output.append("\n=== index.js ===") output.append(files['index.js']) output.append("\n=== style.css ===") output.append(files['style.css']) return '\n'.join(output) def parse_svelte_output(text): """Parse Svelte output to extract individual files""" files = { 'src/App.svelte': '', 'src/app.css': '' } import re # First try to extract using code block patterns svelte_pattern = r'```svelte\s*\n([\s\S]+?)\n```' css_pattern = r'```css\s*\n([\s\S]+?)\n```' # Extract svelte block for App.svelte svelte_match = re.search(svelte_pattern, text, re.IGNORECASE) css_match = re.search(css_pattern, text, re.IGNORECASE) if svelte_match: files['src/App.svelte'] = svelte_match.group(1).strip() if css_match: files['src/app.css'] = css_match.group(1).strip() # Fallback: support === filename === format if any file is missing if not (files['src/App.svelte'] and files['src/app.css']): # Use regex to extract sections app_svelte_fallback = re.search(r'===\s*src/App\.svelte\s*===\n([\s\S]+?)(?=\n===|$)', text, re.IGNORECASE) app_css_fallback = re.search(r'===\s*src/app\.css\s*===\n([\s\S]+?)(?=\n===|$)', text, re.IGNORECASE) if app_svelte_fallback: files['src/App.svelte'] = app_svelte_fallback.group(1).strip() if app_css_fallback: files['src/app.css'] = app_css_fallback.group(1).strip() return files def format_svelte_output(files): """Format Svelte files into a single display string""" output = [] output.append("=== src/App.svelte ===") output.append(files['src/App.svelte']) output.append("\n=== src/app.css ===") output.append(files['src/app.css']) return '\n'.join(output) def history_render(history: History): return gr.update(visible=True), history def clear_history(): return [], [], None, "" # Empty lists for both tuple format and chatbot messages, None for file, empty string for website URL def update_image_input_visibility(model): """Update image input visibility based on selected model""" is_ernie_vl = model.get("id") == "baidu/ERNIE-4.5-VL-424B-A47B-Base-PT" is_glm_vl = model.get("id") == "THUDM/GLM-4.1V-9B-Thinking" return gr.update(visible=is_ernie_vl or is_glm_vl) def process_image_for_model(image): """Convert image to base64 for model input""" if image is None: return None # Convert numpy array to PIL Image if needed import io import base64 import numpy as np from PIL import Image # Handle numpy array from Gradio if isinstance(image, np.ndarray): image = Image.fromarray(image) buffer = io.BytesIO() image.save(buffer, format='PNG') img_str = base64.b64encode(buffer.getvalue()).decode() return f"data:image/png;base64,{img_str}" def create_multimodal_message(text, image=None): """Create a multimodal message with text and optional image""" if image is None: return {"role": "user", "content": text} content = [ { "type": "text", "text": text }, { "type": "image_url", "image_url": { "url": process_image_for_model(image) } } ] return {"role": "user", "content": content} def apply_search_replace_changes(original_content: str, changes_text: str) -> str: """Apply search/replace changes to content (HTML, Python, etc.)""" if not changes_text.strip(): return original_content # Split the changes text into individual search/replace blocks blocks = [] current_block = "" lines = changes_text.split('\n') for line in lines: if line.strip() == SEARCH_START: if current_block.strip(): blocks.append(current_block.strip()) current_block = line + '\n' elif line.strip() == REPLACE_END: current_block += line + '\n' blocks.append(current_block.strip()) current_block = "" else: current_block += line + '\n' if current_block.strip(): blocks.append(current_block.strip()) modified_content = original_content for block in blocks: if not block.strip(): continue # Parse the search/replace block lines = block.split('\n') search_lines = [] replace_lines = [] in_search = False in_replace = False for line in lines: if line.strip() == SEARCH_START: in_search = True in_replace = False elif line.strip() == DIVIDER: in_search = False in_replace = True elif line.strip() == REPLACE_END: in_replace = False elif in_search: search_lines.append(line) elif in_replace: replace_lines.append(line) # Apply the search/replace if search_lines: search_text = '\n'.join(search_lines).strip() replace_text = '\n'.join(replace_lines).strip() if search_text in modified_content: modified_content = modified_content.replace(search_text, replace_text) else: print(f"Warning: Search text not found in content: {search_text[:100]}...") return modified_content def apply_transformers_js_search_replace_changes(original_formatted_content: str, changes_text: str) -> str: """Apply search/replace changes to transformers.js formatted content (three files)""" if not changes_text.strip(): return original_formatted_content # Parse the original formatted content to get the three files files = parse_transformers_js_output(original_formatted_content) # Split the changes text into individual search/replace blocks blocks = [] current_block = "" lines = changes_text.split('\n') for line in lines: if line.strip() == SEARCH_START: if current_block.strip(): blocks.append(current_block.strip()) current_block = line + '\n' elif line.strip() == REPLACE_END: current_block += line + '\n' blocks.append(current_block.strip()) current_block = "" else: current_block += line + '\n' if current_block.strip(): blocks.append(current_block.strip()) # Process each block and apply changes to the appropriate file for block in blocks: if not block.strip(): continue # Parse the search/replace block lines = block.split('\n') search_lines = [] replace_lines = [] in_search = False in_replace = False target_file = None for line in lines: if line.strip() == SEARCH_START: in_search = True in_replace = False elif line.strip() == DIVIDER: in_search = False in_replace = True elif line.strip() == REPLACE_END: in_replace = False elif in_search: search_lines.append(line) elif in_replace: replace_lines.append(line) # Determine which file this change targets based on the search content if search_lines: search_text = '\n'.join(search_lines).strip() replace_text = '\n'.join(replace_lines).strip() # Check which file contains the search text if search_text in files['index.html']: target_file = 'index.html' elif search_text in files['index.js']: target_file = 'index.js' elif search_text in files['style.css']: target_file = 'style.css' # Apply the change to the target file if target_file and search_text in files[target_file]: files[target_file] = files[target_file].replace(search_text, replace_text) else: print(f"Warning: Search text not found in any transformers.js file: {search_text[:100]}...") # Reformat the modified files return format_transformers_js_output(files) # Updated for faster Tavily search and closer prompt usage # Uses 'advanced' search_depth and auto_parameters=True for speed and relevance def perform_web_search(query: str, max_results: int = 5, include_domains=None, exclude_domains=None) -> str: """Perform web search using Tavily with default parameters""" if not tavily_client: return "Web search is not available. Please set the TAVILY_API_KEY environment variable." try: # Use Tavily defaults with advanced search depth for better results search_params = { "search_depth": "advanced", "max_results": min(max(1, max_results), 20) } if include_domains is not None: search_params["include_domains"] = include_domains if exclude_domains is not None: search_params["exclude_domains"] = exclude_domains response = tavily_client.search(query, **search_params) search_results = [] for result in response.get('results', []): title = result.get('title', 'No title') url = result.get('url', 'No URL') content = result.get('content', 'No content') search_results.append(f"Title: {title}\nURL: {url}\nContent: {content}\n") if search_results: return "Web Search Results:\n\n" + "\n---\n".join(search_results) else: return "No search results found." except Exception as e: return f"Search error: {str(e)}" def enhance_query_with_search(query: str, enable_search: bool) -> str: """Enhance the query with web search results if search is enabled""" if not enable_search or not tavily_client: return query # Perform search to get relevant information search_results = perform_web_search(query) # Combine original query with search results enhanced_query = f"""Original Query: {query} {search_results} Please use the search results above to help create the requested application with the most up-to-date information and best practices.""" return enhanced_query def send_to_sandbox(code): # Add a wrapper to inject necessary permissions and ensure full HTML wrapped_code = f""" {code} """ encoded_html = base64.b64encode(wrapped_code.encode('utf-8')).decode('utf-8') data_uri = f"data:text/html;charset=utf-8;base64,{encoded_html}" iframe = f'' return iframe def demo_card_click(e: gr.EventData): try: # Get the index from the event data if hasattr(e, '_data') and e._data: # Try different ways to get the index if 'index' in e._data: index = e._data['index'] elif 'component' in e._data and 'index' in e._data['component']: index = e._data['component']['index'] elif 'target' in e._data and 'index' in e._data['target']: index = e._data['target']['index'] else: # If we can't get the index, try to extract it from the card data index = 0 else: index = 0 # Ensure index is within bounds if index >= len(DEMO_LIST): index = 0 return DEMO_LIST[index]['description'] except (KeyError, IndexError, AttributeError) as e: # Return the first demo description as fallback return DEMO_LIST[0]['description'] def extract_text_from_image(image_path): """Extract text from image using OCR""" try: # Check if tesseract is available try: pytesseract.get_tesseract_version() except Exception: return "Error: Tesseract OCR is not installed. Please install Tesseract to extract text from images. See install_tesseract.md for instructions." # Read image using OpenCV image = cv2.imread(image_path) if image is None: return "Error: Could not read image file" # Convert to RGB (OpenCV uses BGR) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Preprocess image for better OCR results # Convert to grayscale gray = cv2.cvtColor(image_rgb, cv2.COLOR_RGB2GRAY) # Apply thresholding to get binary image _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) # Extract text using pytesseract text = pytesseract.image_to_string(binary, config='--psm 6') return text.strip() if text.strip() else "No text found in image" except Exception as e: return f"Error extracting text from image: {e}" def extract_text_from_file(file_path): if not file_path: return "" mime, _ = mimetypes.guess_type(file_path) ext = os.path.splitext(file_path)[1].lower() try: if ext == ".pdf": with open(file_path, "rb") as f: reader = PyPDF2.PdfReader(f) return "\n".join(page.extract_text() or "" for page in reader.pages) elif ext in [".txt", ".md"]: with open(file_path, "r", encoding="utf-8") as f: return f.read() elif ext == ".csv": with open(file_path, "r", encoding="utf-8") as f: return f.read() elif ext == ".docx": doc = docx.Document(file_path) return "\n".join([para.text for para in doc.paragraphs]) elif ext.lower() in [".jpg", ".jpeg", ".png", ".bmp", ".tiff", ".tif", ".gif", ".webp"]: return extract_text_from_image(file_path) else: return "" except Exception as e: return f"Error extracting text: {e}" def extract_website_content(url: str) -> str: """Extract HTML code and content from a website URL""" try: # Validate URL parsed_url = urlparse(url) if not parsed_url.scheme: url = "https://" + url parsed_url = urlparse(url) if not parsed_url.netloc: return "Error: Invalid URL provided" # Set comprehensive headers to mimic a real browser request headers = { 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8', 'Accept-Language': 'en-US,en;q=0.9', 'Accept-Encoding': 'gzip, deflate, br', 'DNT': '1', 'Connection': 'keep-alive', 'Upgrade-Insecure-Requests': '1', 'Sec-Fetch-Dest': 'document', 'Sec-Fetch-Mode': 'navigate', 'Sec-Fetch-Site': 'none', 'Sec-Fetch-User': '?1', 'Cache-Control': 'max-age=0' } # Create a session to maintain cookies and handle redirects session = requests.Session() session.headers.update(headers) # Make the request with retry logic max_retries = 3 for attempt in range(max_retries): try: response = session.get(url, timeout=15, allow_redirects=True) response.raise_for_status() break except requests.exceptions.HTTPError as e: if e.response.status_code == 403 and attempt < max_retries - 1: # Try with different User-Agent on 403 session.headers['User-Agent'] = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36' continue else: raise # Get the raw HTML content with proper encoding try: # Try to get the content with automatic encoding detection response.encoding = response.apparent_encoding raw_html = response.text except: # Fallback to UTF-8 if encoding detection fails raw_html = response.content.decode('utf-8', errors='ignore') # Debug: Check if we got valid HTML if not raw_html.strip().startswith(' 10: print(f"Warning: This site has {len(script_tags)} script tags - it may be a JavaScript-heavy site") print("The content might be loaded dynamically and not available in the initial HTML") # Extract title title = soup.find('title') title_text = title.get_text().strip() if title else "No title found" # Extract meta description meta_desc = soup.find('meta', attrs={'name': 'description'}) description = meta_desc.get('content', '') if meta_desc else "" # Extract main content areas for analysis content_sections = [] main_selectors = [ 'main', 'article', '.content', '.main-content', '.post-content', '#content', '#main', '.entry-content', '.post-body' ] for selector in main_selectors: elements = soup.select(selector) for element in elements: text = element.get_text().strip() if len(text) > 100: # Only include substantial content content_sections.append(text) # Extract navigation links for analysis nav_links = [] nav_elements = soup.find_all(['nav', 'header']) for nav in nav_elements: links = nav.find_all('a') for link in links: link_text = link.get_text().strip() link_href = link.get('href', '') if link_text and link_href: nav_links.append(f"{link_text}: {link_href}") # Extract and fix image URLs in the HTML img_elements = soup.find_all('img') for img in img_elements: src = img.get('src', '') if src: # Handle different URL formats if src.startswith('//'): # Protocol-relative URL absolute_src = 'https:' + src img['src'] = absolute_src elif src.startswith('/'): # Root-relative URL absolute_src = urljoin(url, src) img['src'] = absolute_src elif not src.startswith(('http://', 'https://')): # Relative URL absolute_src = urljoin(url, src) img['src'] = absolute_src # If it's already absolute, keep it as is # Also check for data-src (lazy loading) and other common attributes data_src = img.get('data-src', '') if data_src and not src: # Use data-src if src is empty if data_src.startswith('//'): absolute_data_src = 'https:' + data_src img['src'] = absolute_data_src elif data_src.startswith('/'): absolute_data_src = urljoin(url, data_src) img['src'] = absolute_data_src elif not data_src.startswith(('http://', 'https://')): absolute_data_src = urljoin(url, data_src) img['src'] = absolute_data_src else: img['src'] = data_src # Also fix background image URLs in style attributes elements_with_style = soup.find_all(attrs={'style': True}) for element in elements_with_style: style_attr = element.get('style', '') # Find and replace relative URLs in background-image import re bg_pattern = r'background-image:\s*url\(["\']?([^"\']+)["\']?\)' matches = re.findall(bg_pattern, style_attr, re.IGNORECASE) for match in matches: if match: if match.startswith('//'): absolute_bg = 'https:' + match style_attr = style_attr.replace(match, absolute_bg) elif match.startswith('/'): absolute_bg = urljoin(url, match) style_attr = style_attr.replace(match, absolute_bg) elif not match.startswith(('http://', 'https://')): absolute_bg = urljoin(url, match) style_attr = style_attr.replace(match, absolute_bg) element['style'] = style_attr # Fix background images in

GLM-4.5 Configuration Required

Please configure your GLM-4.5 API key to use this model.

``` """ yield type('Delta', (), {'content': error_msg, 'reasoning_content': None})() return # Configure OpenAI client for GLM-4.5 try: client = OpenAI( base_url=glm_base_url, api_key=glm_api_key, ) response = client.chat.completions.create( model="GLM-4.5", messages=messages, temperature=temperature, stream=True, max_tokens=65536, extra_body={ "thinking": { "type": "enabled" if thinking_enabled else "disabled", } } ) for chunk in response: if stop_generation: break if chunk.choices and chunk.choices[0].delta: yield chunk.choices[0].delta except Exception as e: # Fallback: if GLM-4.5 API fails, yield error with sample code error_msg = f"""Error connecting to GLM-4.5: {str(e)} Please check: 1. OPENAI_API_KEY environment variable is set correctly 2. API key is valid and has credits 3. Network connection is working 4. GLM_BASE_URL is correct (current: {glm_base_url}) Here's a sample HTML code to test the UI: ```html GLM-4.5 Error - Sample Output

🤖 GLM-4.5 Configuration Error

Error: {str(e)}

This is a sample HTML output to demonstrate the UI while you configure GLM-4.5.

```""" print(f"GLM-4.5 API Error: {e}") yield type('Delta', (), {'content': error_msg, 'reasoning_content': None})() class GLM45Model: def __init__(self): self.accumulated_content = "" self.accumulated_reasoning = "" def reset_state(self): self.accumulated_content = "" self.accumulated_reasoning = "" def _render_response(self, reasoning_content, regular_content, skip_think=False): html_parts = [] if reasoning_content and not skip_think: reasoning_escaped = html.escape(reasoning_content).replace("\n", "
") think_html = ( "
Thinking" "
" + reasoning_escaped + "
" ) html_parts.append(think_html) if regular_content: content_escaped = html.escape(regular_content).replace("\n", "
") content_html = f"
{content_escaped}
" html_parts.append(content_html) return "".join(html_parts) def _build_messages(self, raw_hist, sys_prompt): msgs = [] if sys_prompt.strip(): msgs.append({"role": "system", "content": sys_prompt.strip()}) for h in raw_hist: if h["role"] == "user": msgs.append({"role": "user", "content": h["content"]}) else: msg = {"role": "assistant", "content": h.get("content", "")} if h.get("reasoning_content"): msg["reasoning_content"] = h.get("reasoning_content") msgs.append(msg) return msgs def stream_generate(self, raw_hist, sys_prompt, thinking_enabled=True, temperature=1.0): global stop_generation stop_generation = False msgs = self._build_messages(raw_hist, sys_prompt) self.reset_state() try: for delta in stream_from_vllm(msgs, thinking_enabled, temperature): if stop_generation: break if hasattr(delta, 'content') and delta.content: self.accumulated_content += delta.content if hasattr(delta, 'reasoning_content') and delta.reasoning_content: self.accumulated_reasoning += delta.reasoning_content yield self._render_response(self.accumulated_reasoning, self.accumulated_content, not thinking_enabled) except Exception as e: yield self._render_response("", f"Error: {str(e)}") # Global GLM-4.5 instance glm45 = GLM45Model() def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[History], _current_model: Dict, enable_search: bool = False, language: str = "html", provider: str = "auto"): if query is None: query = '' if _history is None: _history = [] # Ensure _history is always a list of lists with at least 2 elements per item if not isinstance(_history, list): _history = [] _history = [h for h in _history if isinstance(h, list) and len(h) == 2] # Check if there's existing content in history to determine if this is a modification request has_existing_content = False last_assistant_msg = "" if _history and len(_history[-1]) > 1: last_assistant_msg = _history[-1][1] # Check for various content types that indicate an existing project if ('' in last_assistant_msg or 'Preview is only available for HTML. Please download your code using the download button above.", } else: yield { code_output: gr.update(value=clean_code, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: "
Generating transformers.js app...
", } elif language == "svelte": yield { code_output: gr.update(value=clean_code, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: "
Generating Svelte app...
", } else: if has_existing_content: if clean_code.strip().startswith("") or clean_code.strip().startswith("Preview is only available for HTML. Please download your code using the download button above.", } else: last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else "" modified_content = apply_search_replace_changes(last_content, clean_code) clean_content = remove_code_block(modified_content) yield { code_output: gr.update(value=clean_content, language=get_gradio_language(language)), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(clean_content) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", } else: yield { code_output: gr.update(value=clean_code, language=get_gradio_language(language)), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(clean_code) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", } except Exception as e: content = f"Error: {str(e)}" print(f"GLM-4.5 Error: {e}") # Final processing for GLM-4.5 clean_code = remove_code_block(content) # Store content with thinking information if available if reasoning_content: full_response = f"**Thinking:**\n{reasoning_content}\n\n**Code:**\n{content}" else: full_response = content if language == "transformers.js": files = parse_transformers_js_output(clean_code) if files['index.html'] and files['index.js'] and files['style.css']: formatted_output = format_transformers_js_output(files) _history.append([query, full_response]) yield { code_output: formatted_output, history: _history, sandbox: send_to_sandbox(files['index.html']), history_output: history_to_chatbot_messages(_history), } else: _history.append([query, full_response]) yield { code_output: clean_code, history: _history, sandbox: "
Error parsing transformers.js output. Please try again.
", history_output: history_to_chatbot_messages(_history), } elif language == "svelte": files = parse_svelte_output(clean_code) if files['src/App.svelte'] and files['src/app.css']: formatted_output = format_svelte_output(files) _history.append([query, full_response]) yield { code_output: formatted_output, history: _history, sandbox: "
Preview is only available for HTML. Please download your Svelte code using the download button above.
", history_output: history_to_chatbot_messages(_history), } else: _history.append([query, full_response]) yield { code_output: clean_code, history: _history, sandbox: "
Preview is only available for HTML. Please download your Svelte code using the download button above.
", history_output: history_to_chatbot_messages(_history), } else: if has_existing_content and not (clean_code.strip().startswith("") or clean_code.strip().startswith(" 1 else "" modified_content = apply_search_replace_changes(last_content, clean_code) clean_content = remove_code_block(modified_content) _history.append([query, full_response]) yield { code_output: clean_content, history: _history, sandbox: send_to_sandbox(clean_content) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", history_output: history_to_chatbot_messages(_history), } else: _history.append([query, full_response]) yield { code_output: clean_code, history: _history, sandbox: send_to_sandbox(clean_code) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", history_output: history_to_chatbot_messages(_history), } return # Use dynamic client based on selected model (for non-GLM-4.5 models) client = get_inference_client(_current_model["id"], provider) if image is not None: messages.append(create_multimodal_message(enhanced_query, image)) else: messages.append({'role': 'user', 'content': enhanced_query}) try: completion = client.chat.completions.create( model=_current_model["id"], messages=messages, stream=True, max_tokens=16384 ) content = "" for chunk in completion: # Only process if chunk.choices is non-empty if ( hasattr(chunk, "choices") and chunk.choices and hasattr(chunk.choices[0], "delta") and hasattr(chunk.choices[0].delta, "content") and chunk.choices[0].delta.content is not None ): content += chunk.choices[0].delta.content search_status = " (with web search)" if enable_search and tavily_client else "" # Handle transformers.js output differently if language == "transformers.js": files = parse_transformers_js_output(content) if files['index.html'] and files['index.js'] and files['style.css']: # Model returned complete transformers.js output formatted_output = format_transformers_js_output(files) yield { code_output: gr.update(value=formatted_output, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(files['index.html']) if files['index.html'] else "
Preview is only available for HTML. Please download your code using the download button above.
", } elif has_existing_content: # Model is returning search/replace changes for transformers.js - apply them last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else "" modified_content = apply_transformers_js_search_replace_changes(last_content, content) yield { code_output: gr.update(value=modified_content, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(parse_transformers_js_output(modified_content)['index.html']) if parse_transformers_js_output(modified_content)['index.html'] else "
Preview is only available for HTML. Please download your code using the download button above.
", } else: # Still streaming, show partial content yield { code_output: gr.update(value=content, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: "
Generating transformers.js app...
", } elif language == "svelte": # For Svelte, just show the content as it streams # We'll parse it properly in the final response yield { code_output: gr.update(value=content, language="html"), history_output: history_to_chatbot_messages(_history), sandbox: "
Generating Svelte app...
", } else: clean_code = remove_code_block(content) if has_existing_content: # Handle modification of existing content if clean_code.strip().startswith("") or clean_code.strip().startswith("Preview is only available for HTML. Please download your code using the download button above.", } else: # Model returned search/replace changes - apply them last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else "" modified_content = apply_search_replace_changes(last_content, clean_code) clean_content = remove_code_block(modified_content) yield { code_output: gr.update(value=clean_content, language=get_gradio_language(language)), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(clean_content) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", } else: yield { code_output: gr.update(value=clean_code, language=get_gradio_language(language)), history_output: history_to_chatbot_messages(_history), sandbox: send_to_sandbox(clean_code) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", } # Skip chunks with empty choices (end of stream) # Do not treat as error # Handle response based on whether this is a modification or new generation if language == "transformers.js": # Handle transformers.js output files = parse_transformers_js_output(content) if files['index.html'] and files['index.js'] and files['style.css']: # Model returned complete transformers.js output formatted_output = format_transformers_js_output(files) _history.append([query, formatted_output]) yield { code_output: formatted_output, history: _history, sandbox: send_to_sandbox(files['index.html']), history_output: history_to_chatbot_messages(_history), } elif has_existing_content: # Model returned search/replace changes for transformers.js - apply them last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else "" modified_content = apply_transformers_js_search_replace_changes(last_content, content) _history.append([query, modified_content]) yield { code_output: modified_content, history: _history, sandbox: send_to_sandbox(parse_transformers_js_output(modified_content)['index.html']), history_output: history_to_chatbot_messages(_history), } else: # Fallback if parsing failed _history.append([query, content]) yield { code_output: content, history: _history, sandbox: "
Error parsing transformers.js output. Please try again.
", history_output: history_to_chatbot_messages(_history), } elif language == "svelte": # Handle Svelte output files = parse_svelte_output(content) if files['src/App.svelte'] and files['src/app.css']: # Model returned complete Svelte output formatted_output = format_svelte_output(files) _history.append([query, formatted_output]) yield { code_output: formatted_output, history: _history, sandbox: "
Preview is only available for HTML. Please download your Svelte code using the download button above.
", history_output: history_to_chatbot_messages(_history), } elif has_existing_content: # Model returned search/replace changes for Svelte - apply them last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else "" modified_content = apply_search_replace_changes(last_content, content) _history.append([query, modified_content]) yield { code_output: modified_content, history: _history, sandbox: "
Preview is only available for HTML. Please download your Svelte code using the download button above.
", history_output: history_to_chatbot_messages(_history), } else: # Fallback if parsing failed - just use the raw content _history.append([query, content]) yield { code_output: content, history: _history, sandbox: "
Preview is only available for HTML. Please download your Svelte code using the download button above.
", history_output: history_to_chatbot_messages(_history), } elif has_existing_content: # Handle modification of existing content final_code = remove_code_block(content) if final_code.strip().startswith("") or final_code.strip().startswith(" 1 else "" modified_content = apply_search_replace_changes(last_content, final_code) clean_content = remove_code_block(modified_content) # Update history with the cleaned content _history.append([query, clean_content]) yield { code_output: clean_content, history: _history, sandbox: send_to_sandbox(clean_content) if language == "html" else "
Preview is only available for HTML. Please download your code using the download button above.
", history_output: history_to_chatbot_messages(_history), } else: # Regular generation - use the content as is _history.append([query, content]) yield { code_output: remove_code_block(content), history: _history, sandbox: send_to_sandbox(remove_code_block(content)), history_output: history_to_chatbot_messages(_history), } except Exception as e: error_message = f"Error: {str(e)}" yield { code_output: error_message, history_output: history_to_chatbot_messages(_history), } # Deploy to Spaces logic def wrap_html_in_gradio_app(html_code): # Escape triple quotes for safe embedding safe_html = html_code.replace('"""', r'\"\"\"') return ( 'import gradio as gr\n\n' 'def show_html():\n' f' return """{safe_html}"""\n\n' 'demo = gr.Interface(fn=show_html, inputs=None, outputs=gr.HTML())\n\n' 'if __name__ == "__main__":\n' ' demo.launch()\n' ) def deploy_to_spaces(code): if not code or not code.strip(): return # Do nothing if code is empty # Wrap the HTML code in a Gradio app app_py = wrap_html_in_gradio_app(code.strip()) base_url = "https://huggingface.co/new-space" params = urllib.parse.urlencode({ "name": "new-space", "sdk": "gradio" }) # Use urlencode for file params files_params = urllib.parse.urlencode({ "files[0][path]": "app.py", "files[0][content]": app_py }) full_url = f"{base_url}?{params}&{files_params}" webbrowser.open_new_tab(full_url) def wrap_html_in_static_app(html_code): # For static Spaces, just use the HTML code as-is return html_code def deploy_to_spaces_static(code): if not code or not code.strip(): return # Do nothing if code is empty # Use the HTML code directly for static Spaces app_html = wrap_html_in_static_app(code.strip()) base_url = "https://huggingface.co/new-space" params = urllib.parse.urlencode({ "name": "new-space", "sdk": "static" }) files_params = urllib.parse.urlencode({ "files[0][path]": "index.html", "files[0][content]": app_html }) full_url = f"{base_url}?{params}&{files_params}" webbrowser.open_new_tab(full_url) def check_hf_space_url(url: str) -> Tuple[bool, Optional[str], Optional[str]]: """Check if URL is a valid Hugging Face Spaces URL and extract username/project""" import re # Pattern to match HF Spaces URLs url_pattern = re.compile( r'^(https?://)?(huggingface\.co|hf\.co)/spaces/([\w-]+)/([\w-]+)$', re.IGNORECASE ) match = url_pattern.match(url.strip()) if match: username = match.group(3) project_name = match.group(4) return True, username, project_name return False, None, None def fetch_hf_space_content(username: str, project_name: str) -> str: """Fetch content from a Hugging Face Space""" try: import requests from huggingface_hub import HfApi # Try to get space info first api = HfApi() space_info = api.space_info(f"{username}/{project_name}") # Try to fetch the main file based on SDK sdk = space_info.sdk main_file = None # Define file patterns to try based on SDK if sdk == "static": file_patterns = ["index.html"] elif sdk == "gradio": file_patterns = ["app.py", "main.py", "gradio_app.py"] elif sdk == "streamlit": file_patterns = ["streamlit_app.py", "src/streamlit_app.py", "app.py", "src/app.py", "main.py", "src/main.py", "Home.py", "src/Home.py", "🏠_Home.py", "src/🏠_Home.py", "1_🏠_Home.py", "src/1_🏠_Home.py"] else: # Try common files for unknown SDKs file_patterns = ["app.py", "src/app.py", "index.html", "streamlit_app.py", "src/streamlit_app.py", "main.py", "src/main.py", "Home.py", "src/Home.py"] # Try to find and download the main file for file in file_patterns: try: content = api.hf_hub_download( repo_id=f"{username}/{project_name}", filename=file, repo_type="space" ) main_file = file break except: continue # If still no main file found, try to list repository files and find Python files if not main_file and sdk in ["streamlit", "gradio"]: try: from huggingface_hub import list_repo_files files = list_repo_files(repo_id=f"{username}/{project_name}", repo_type="space") # Look for Python files that might be the main file (root and src/ directory) python_files = [f for f in files if f.endswith('.py') and not f.startswith('.') and (('/' not in f) or f.startswith('src/'))] for py_file in python_files: try: content = api.hf_hub_download( repo_id=f"{username}/{project_name}", filename=py_file, repo_type="space" ) main_file = py_file break except: continue except: pass if main_file: content = api.hf_hub_download( repo_id=f"{username}/{project_name}", filename=main_file, repo_type="space" ) # Read the file content with open(content, 'r', encoding='utf-8') as f: file_content = f.read() return f"""IMPORTED PROJECT FROM HUGGING FACE SPACE ============================================== Space: {username}/{project_name} SDK: {sdk} Main File: {main_file} {file_content}""" else: # Try to get more information about available files for debugging try: from huggingface_hub import list_repo_files files = list_repo_files(repo_id=f"{username}/{project_name}", repo_type="space") available_files = [f for f in files if not f.startswith('.') and not f.endswith('.md')] return f"Error: Could not find main file in space {username}/{project_name}.\n\nSDK: {sdk}\nAvailable files: {', '.join(available_files[:10])}{'...' if len(available_files) > 10 else ''}\n\nTried looking for: {', '.join(file_patterns)}" except: return f"Error: Could not find main file in space {username}/{project_name}. Expected files for {sdk} SDK: {', '.join(file_patterns) if 'file_patterns' in locals() else 'standard files'}" except Exception as e: return f"Error fetching space content: {str(e)}" def load_project_from_url(url: str) -> Tuple[str, str]: """Load project from Hugging Face Space URL""" # Validate URL is_valid, username, project_name = check_hf_space_url(url) if not is_valid: return "Error: Please enter a valid Hugging Face Spaces URL.\n\nExpected format: https://huggingface.co/spaces/username/project", "" # Fetch content content = fetch_hf_space_content(username, project_name) if content.startswith("Error:"): return content, "" # Extract the actual code content by removing metadata lines = content.split('\n') code_start = 0 for i, line in enumerate(lines): # Skip metadata lines and find the start of actual code if (line.strip() and not line.startswith('=') and not line.startswith('IMPORTED PROJECT') and not line.startswith('Space:') and not line.startswith('SDK:') and not line.startswith('Main File:')): code_start = i break code_content = '\n'.join(lines[code_start:]) return f"✅ Successfully imported project from {username}/{project_name}", code_content # Main application with gr.Blocks( theme=gr.themes.Base( primary_hue="blue", secondary_hue="gray", neutral_hue="gray", font=gr.themes.GoogleFont("Inter"), font_mono=gr.themes.GoogleFont("JetBrains Mono"), text_size=gr.themes.sizes.text_md, spacing_size=gr.themes.sizes.spacing_md, radius_size=gr.themes.sizes.radius_md ), title="AnyCoder - AI Code Generator" ) as demo: history = gr.State([]) setting = gr.State({ "system": HTML_SYSTEM_PROMPT, }) current_model = gr.State(AVAILABLE_MODELS[0]) # Moonshot Kimi-K2 open_panel = gr.State(None) last_login_state = gr.State(None) with gr.Sidebar(): login_button = gr.LoginButton() # Add Load Project section gr.Markdown("📥 Load Existing Project") load_project_url = gr.Textbox( label="Hugging Face Space URL", placeholder="https://huggingface.co/spaces/username/project", lines=1 ) load_project_btn = gr.Button("Import Project", variant="secondary", size="sm") load_project_status = gr.Markdown(visible=False) gr.Markdown("---") input = gr.Textbox( label="What would you like to build?", placeholder="Describe your application...", lines=3, visible=True ) # Language dropdown for code generation language_choices = [ "html", "python", "transformers.js", "svelte", "c", "cpp", "markdown", "latex", "json", "css", "javascript", "jinja2", "typescript", "yaml", "dockerfile", "shell", "r", "sql", "sql-msSQL", "sql-mySQL", "sql-mariaDB", "sql-sqlite", "sql-cassandra", "sql-plSQL", "sql-hive", "sql-pgSQL", "sql-gql", "sql-gpSQL", "sql-sparkSQL", "sql-esper" ] language_dropdown = gr.Dropdown( choices=language_choices, value="html", label="Code Language", visible=True ) website_url_input = gr.Textbox( label="website for redesign", placeholder="https://example.com", lines=1, visible=True ) file_input = gr.File( label="Reference file", file_types=[".pdf", ".txt", ".md", ".csv", ".docx", ".jpg", ".jpeg", ".png", ".bmp", ".tiff", ".tif", ".gif", ".webp"], visible=True ) image_input = gr.Image( label="UI design image", visible=False ) with gr.Row(): btn = gr.Button("Generate", variant="primary", size="lg", scale=2, visible=True) clear_btn = gr.Button("Clear", variant="secondary", size="sm", scale=1, visible=True) # --- Move deploy/app name/sdk here, right before web search --- space_name_input = gr.Textbox( label="app name (e.g. my-cool-app)", placeholder="Enter your app name", lines=1, visible=False ) sdk_choices = [ ("Gradio (Python)", "gradio"), ("Streamlit (Python)", "streamlit"), ("Static (HTML)", "static"), ("Transformers.js", "transformers.js"), ("Svelte", "svelte") ] sdk_dropdown = gr.Dropdown( choices=[x[0] for x in sdk_choices], value="Static (HTML)", label="App SDK", visible=False ) deploy_btn = gr.Button("🚀 Deploy App", variant="primary", visible=False) deploy_status = gr.Markdown(visible=False, label="Deploy status") # --- End move --- search_toggle = gr.Checkbox( label="🔍 Web search", value=False, visible=True ) model_dropdown = gr.Dropdown( choices=[model['name'] for model in AVAILABLE_MODELS], value="Qwen3-Coder-480B-A35B", label="Model", visible=True ) provider_state = gr.State("auto") gr.Markdown("**Quick start**", visible=True) with gr.Column(visible=True) as quick_examples_col: for i, demo_item in enumerate(DEMO_LIST[:3]): demo_card = gr.Button( value=demo_item['title'], variant="secondary", size="sm" ) demo_card.click( fn=lambda idx=i: gr.update(value=DEMO_LIST[idx]['description']), outputs=input ) if not tavily_client: gr.Markdown("⚠️ Web search unavailable", visible=True) # Remove model display and web search available line def on_model_change(model_name): for m in AVAILABLE_MODELS: if m['name'] == model_name: return m, update_image_input_visibility(m) return AVAILABLE_MODELS[0], update_image_input_visibility(AVAILABLE_MODELS[0]) def save_prompt(input): return {setting: {"system": input}} model_dropdown.change( lambda model_name: on_model_change(model_name), inputs=model_dropdown, outputs=[current_model, image_input] ) # --- Remove deploy/app name/sdk from bottom column --- # (delete the gr.Column() block containing space_name_input, sdk_dropdown, deploy_btn, deploy_status) with gr.Column(): with gr.Tabs(): with gr.Tab("Code"): code_output = gr.Code( language="html", lines=25, interactive=True, label="Generated code" ) with gr.Tab("Preview"): sandbox = gr.HTML(label="Live preview") with gr.Tab("History"): history_output = gr.Chatbot(show_label=False, height=400, type="messages") # Load project function def handle_load_project(url): if not url.strip(): return gr.update(value="Please enter a URL.", visible=True) status, code = load_project_from_url(url) if code: # Extract space info for deployment is_valid, username, project_name = check_hf_space_url(url) space_info = f"{username}/{project_name}" if is_valid else "" # Success - update the code output and show success message # Also update history to include the loaded project loaded_history = [[f"Loaded project from {url}", code]] return [ gr.update(value=status, visible=True), gr.update(value=code, language="html"), gr.update(value=send_to_sandbox(code) if code.strip().startswith('') or code.strip().startswith('Preview not available for this file type."), gr.update(value=""), loaded_history, history_to_chatbot_messages(loaded_history), gr.update(value=space_info, visible=True), # Update space name with loaded project gr.update(value="Update Existing Space", visible=True) # Change button text ] else: # Error - just show error message return [ gr.update(value=status, visible=True), gr.update(), gr.update(), gr.update(), [], [], gr.update(value="", visible=False), gr.update(value="🚀 Deploy App", visible=False) ] # Event handlers def update_code_language(language): return gr.update(language=get_gradio_language(language)) def update_sdk_based_on_language(language): if language == "transformers.js": return gr.update(value="Transformers.js") elif language == "svelte": return gr.update(value="Svelte") elif language == "html": return gr.update(value="Static (HTML)") else: return gr.update(value="Gradio (Python)") language_dropdown.change(update_code_language, inputs=language_dropdown, outputs=code_output) language_dropdown.change(update_sdk_based_on_language, inputs=language_dropdown, outputs=sdk_dropdown) def preview_logic(code, language): if language == "html": return send_to_sandbox(code) elif language == "transformers.js": # For transformers.js, extract the HTML part for preview files = parse_transformers_js_output(code) if files['index.html']: return send_to_sandbox(files['index.html']) else: return "
Preview is only available for HTML. Please download your code using the download button above.
" elif language == "svelte": # For Svelte, we can't preview the compiled app, so show a message return "
Preview is only available for HTML. Please download your Svelte code and deploy it to see the result.
" else: return "
Preview is only available for HTML. Please download your code using the download button above.
" def show_deploy_components(*args): return [gr.Textbox(visible=True), gr.Dropdown(visible=True), gr.Button(visible=True)] def hide_deploy_components(*args): return [gr.Textbox(visible=False), gr.Dropdown(visible=False), gr.Button(visible=False)] # Load project button event load_project_btn.click( handle_load_project, inputs=[load_project_url], outputs=[load_project_status, code_output, sandbox, load_project_url, history, history_output, space_name_input, deploy_btn] ) btn.click( generation_code, inputs=[input, image_input, file_input, website_url_input, setting, history, current_model, search_toggle, language_dropdown, provider_state], outputs=[code_output, history, sandbox, history_output] ).then( show_deploy_components, None, [space_name_input, sdk_dropdown, deploy_btn] ) # Update preview when code or language changes code_output.change(preview_logic, inputs=[code_output, language_dropdown], outputs=sandbox) language_dropdown.change(preview_logic, inputs=[code_output, language_dropdown], outputs=sandbox) clear_btn.click(clear_history, outputs=[history, history_output, file_input, website_url_input]) clear_btn.click(hide_deploy_components, None, [space_name_input, sdk_dropdown, deploy_btn]) # Reset space name and button text when clearing clear_btn.click( lambda: [gr.update(value=""), gr.update(value="🚀 Deploy App")], outputs=[space_name_input, deploy_btn] ) # Deploy to Spaces logic def deploy_to_user_space( code, space_name, sdk_name, # new argument profile: gr.OAuthProfile | None = None, token: gr.OAuthToken | None = None ): import shutil if not code or not code.strip(): return gr.update(value="No code to deploy.", visible=True) if profile is None or token is None: return gr.update(value="Please log in with your Hugging Face account to deploy to your own Space. Otherwise, use the default deploy (opens in new tab).", visible=True) # Check if token has write permissions if not token.token or token.token == "hf_": return gr.update(value="Error: Invalid token. Please log in again with your Hugging Face account to get a valid write token.", visible=True) # Check if this is an update to an existing space (contains /) is_update = "/" in space_name.strip() if is_update: # This is an existing space, use the provided space_name as repo_id repo_id = space_name.strip() # Extract username from repo_id for permission check space_username = repo_id.split('/')[0] if space_username != profile.username: return gr.update(value=f"Error: You can only update your own spaces. This space belongs to {space_username}.", visible=True) # Verify the user has write access to this space try: api = HfApi(token=token.token) # Try to get space info to verify access space_info = api.space_info(repo_id) if not space_info: return gr.update(value=f"Error: Could not access space {repo_id}. Please check your permissions.", visible=True) except Exception as e: return gr.update(value=f"Error: No write access to space {repo_id}. Please ensure you have the correct permissions. Error: {str(e)}", visible=True) else: # This is a new space, create repo_id with current user username = profile.username repo_id = f"{username}/{space_name.strip()}" # Map SDK name to HF SDK slug sdk_map = { "Gradio (Python)": "gradio", "Streamlit (Python)": "docker", # Use 'docker' for Streamlit Spaces "Static (HTML)": "static", "Transformers.js": "static", # Transformers.js uses static SDK "Svelte": "static" # Svelte uses static SDK } sdk = sdk_map.get(sdk_name, "gradio") # Create API client with user's token for proper authentication api = HfApi(token=token.token) # Only create the repo for new spaces (not updates) and non-Transformers.js, non-Streamlit, and non-Svelte SDKs if not is_update and sdk != "docker" and sdk_name not in ["Transformers.js", "Svelte"]: try: api.create_repo( repo_id=repo_id, # e.g. username/space_name repo_type="space", space_sdk=sdk, # Use selected SDK exist_ok=True # Don't error if it already exists ) except Exception as e: return gr.update(value=f"Error creating Space: {e}", visible=True) # Streamlit/docker logic if sdk == "docker": try: # For new spaces, duplicate the template first if not is_update: # Use duplicate_space to create a Streamlit template space from huggingface_hub import duplicate_space # Duplicate the streamlit template space duplicated_repo = duplicate_space( from_id="streamlit/streamlit-template-space", to_id=space_name.strip(), token=token.token, exist_ok=True ) # Upload the user's code to src/streamlit_app.py (for both new and existing spaces) import tempfile with tempfile.NamedTemporaryFile("w", suffix=".py", delete=False) as f: f.write(code) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="src/streamlit_app.py", repo_id=repo_id, repo_type="space" ) space_url = f"https://huggingface.co/spaces/{repo_id}" action_text = "Updated" if is_update else "Deployed" return gr.update(value=f"✅ {action_text}! [Open your Space here]({space_url})", visible=True) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading Streamlit app: {e}", visible=True) finally: import os os.unlink(temp_path) except Exception as e: error_prefix = "Error duplicating Streamlit space" if not is_update else "Error updating Streamlit space" return gr.update(value=f"{error_prefix}: {e}", visible=True) # Transformers.js logic elif sdk_name == "Transformers.js" and not is_update: try: # Use duplicate_space to create a transformers.js template space from huggingface_hub import duplicate_space # Duplicate the transformers.js template space duplicated_repo = duplicate_space( from_id="static-templates/transformers.js", to_id=space_name.strip(), token=token.token, exist_ok=True ) print("Duplicated repo result:", duplicated_repo, type(duplicated_repo)) # Parse the transformers.js output to get the three files files = parse_transformers_js_output(code) if not files['index.html'] or not files['index.js'] or not files['style.css']: return gr.update(value="Error: Could not parse transformers.js output. Please regenerate the code.", visible=True) # Upload the three files to the duplicated space import tempfile # Upload index.html with tempfile.NamedTemporaryFile("w", suffix=".html", delete=False) as f: f.write(files['index.html']) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="index.html", repo_id=repo_id, repo_type="space" ) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading index.html: {e}", visible=True) finally: import os os.unlink(temp_path) # Upload index.js with tempfile.NamedTemporaryFile("w", suffix=".js", delete=False) as f: f.write(files['index.js']) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="index.js", repo_id=repo_id, repo_type="space" ) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading index.js: {e}", visible=True) finally: import os os.unlink(temp_path) # Upload style.css with tempfile.NamedTemporaryFile("w", suffix=".css", delete=False) as f: f.write(files['style.css']) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="style.css", repo_id=repo_id, repo_type="space" ) space_url = f"https://huggingface.co/spaces/{repo_id}" action_text = "Updated" if is_update else "Deployed" return gr.update(value=f"✅ {action_text}! [Open your Transformers.js Space here]({space_url})", visible=True) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading style.css: {e}", visible=True) finally: import os os.unlink(temp_path) except Exception as e: # Handle potential RepoUrl object errors error_msg = str(e) if "'url'" in error_msg or "RepoUrl" in error_msg: return gr.update(value=f"Error duplicating Transformers.js space: RepoUrl handling error. Please try again. Details: {error_msg}", visible=True) return gr.update(value=f"Error duplicating Transformers.js space: {error_msg}", visible=True) # Svelte logic elif sdk_name == "Svelte" and not is_update: try: # Use duplicate_space to create a Svelte template space from huggingface_hub import duplicate_space # Duplicate the Svelte template space duplicated_repo = duplicate_space( from_id="static-templates/svelte", to_id=repo_id, # Use the full repo_id (username/space_name) token=token.token, exist_ok=True ) print("Duplicated Svelte repo result:", duplicated_repo, type(duplicated_repo)) # Extract the actual repo ID from the duplicated space # The duplicated_repo is a RepoUrl object, convert to string and extract the repo ID try: duplicated_repo_str = str(duplicated_repo) # Extract username and repo name from the URL if "/spaces/" in duplicated_repo_str: parts = duplicated_repo_str.split("/spaces/")[-1].split("/") if len(parts) >= 2: actual_repo_id = f"{parts[0]}/{parts[1]}" else: actual_repo_id = repo_id # Fallback to original else: actual_repo_id = repo_id # Fallback to original except Exception as e: print(f"Error extracting repo ID from duplicated_repo: {e}") actual_repo_id = repo_id # Fallback to original print("Actual repo ID for Svelte uploads:", actual_repo_id) # Parse the Svelte output to get the custom files files = parse_svelte_output(code) if not files['src/App.svelte']: return gr.update(value="Error: Could not parse Svelte output. Please regenerate the code.", visible=True) # Upload only the custom Svelte files to the duplicated space import tempfile # Upload src/App.svelte (required) with tempfile.NamedTemporaryFile("w", suffix=".svelte", delete=False) as f: f.write(files['src/App.svelte']) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="src/App.svelte", repo_id=actual_repo_id, repo_type="space" ) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {actual_repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading src/App.svelte: {e}", visible=True) finally: import os os.unlink(temp_path) # Upload src/app.css (optional) if files['src/app.css']: with tempfile.NamedTemporaryFile("w", suffix=".css", delete=False) as f: f.write(files['src/app.css']) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo="src/app.css", repo_id=actual_repo_id, repo_type="space" ) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {actual_repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading src/app.css: {e}", visible=True) finally: import os os.unlink(temp_path) # Success - all files uploaded space_url = f"https://huggingface.co/spaces/{actual_repo_id}" action_text = "Updated" if is_update else "Deployed" return gr.update(value=f"✅ {action_text}! [Open your Svelte Space here]({space_url})", visible=True) except Exception as e: # Handle potential RepoUrl object errors error_msg = str(e) if "'url'" in error_msg or "RepoUrl" in error_msg: return gr.update(value=f"Error duplicating Svelte space: RepoUrl handling error. Please try again. Details: {error_msg}", visible=True) return gr.update(value=f"Error duplicating Svelte space: {error_msg}", visible=True) # Other SDKs (existing logic) if sdk == "static": import time file_name = "index.html" # Wait and retry logic after repo creation max_attempts = 3 for attempt in range(max_attempts): import tempfile with tempfile.NamedTemporaryFile("w", suffix=".html", delete=False) as f: f.write(code) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo=file_name, repo_id=repo_id, repo_type="space" ) space_url = f"https://huggingface.co/spaces/{repo_id}" action_text = "Updated" if is_update else "Deployed" return gr.update(value=f"✅ {action_text}! [Open your Space here]({space_url})", visible=True) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) elif attempt < max_attempts - 1: time.sleep(2) # Wait before retrying else: return gr.update(value=f"Error uploading file after {max_attempts} attempts: {e}. Please check your permissions and try again.", visible=True) finally: import os os.unlink(temp_path) else: file_name = "app.py" import tempfile with tempfile.NamedTemporaryFile("w", suffix=f".{file_name.split('.')[-1]}", delete=False) as f: f.write(code) temp_path = f.name try: api.upload_file( path_or_fileobj=temp_path, path_in_repo=file_name, repo_id=repo_id, repo_type="space" ) space_url = f"https://huggingface.co/spaces/{repo_id}" action_text = "Updated" if is_update else "Deployed" return gr.update(value=f"✅ {action_text}! [Open your Space here]({space_url})", visible=True) except Exception as e: error_msg = str(e) if "403 Forbidden" in error_msg and "write token" in error_msg: return gr.update(value=f"Error: Permission denied. Please ensure you have write access to {repo_id} and your token has the correct permissions.", visible=True) else: return gr.update(value=f"Error uploading file: {e}", visible=True) finally: import os os.unlink(temp_path) # Connect the deploy button to the new function deploy_btn.click( deploy_to_user_space, inputs=[code_output, space_name_input, sdk_dropdown], outputs=deploy_status ) # Keep the old deploy method as fallback (if not logged in, user can still use the old method) # Optionally, you can keep the old deploy_btn.click for the default method as a secondary button. if __name__ == "__main__": demo.queue(api_open=False, default_concurrency_limit=20).launch(show_api=False, ssr_mode=True, mcp_server=False)