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 gradio as gr from huggingface_hub import InferenceClient, HfApi, create_repo, whoami from tavily import TavilyClient # Configuration SystemPrompt = """You are a helpful coding assistant. You help users create applications by generating code based on their requirements. When asked to create an application, you should: 1. Understand the user's requirements 2. Generate clean, working code 3. Provide HTML output when appropriate for web applications 4. Include necessary comments and documentation 5. Ensure the code is functional and follows best practices 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.""" # System prompt with search capability SystemPromptWithSearch = """You are a helpful coding assistant with access to real-time web search. You help users create applications by generating code based on their requirements. When asked to create an application, you should: 1. Understand the user's requirements 2. Use web search when needed to find the latest information, best practices, or specific technologies 3. Generate clean, working code 4. Provide HTML output when appropriate for web applications 5. Include necessary comments and documentation 6. Ensure the code is functional and follows best practices 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.""" # Available models AVAILABLE_MODELS = [ { "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" } ] 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": "Weather Dashboard", "description": "Create a weather dashboard that displays current weather information" }, { "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" } ] # HF Inference Client HF_TOKEN = os.getenv('HF_TOKEN') client = InferenceClient( provider="auto", 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() return extracted # If no code block is found, check if the entire text is HTML if text.strip().startswith('') or text.strip().startswith(' 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 get_user_info(profile: gr.OAuthProfile | None) -> str: """Get user information from OAuth profile""" if profile is None: return "👤 **Guest User**\n*Sign in to personalize your experience*" return f"👤 **{profile.name}**\n*Welcome back!*" def create_space_from_code(html_code: str, title: str, oauth_token: gr.OAuthToken | None) -> str: """Create a new Hugging Face Space with the generated HTML code""" if not oauth_token: return "❌ **Error:** Please sign in with your Hugging Face account to deploy spaces." if not html_code or not html_code.strip(): return "❌ **Error:** No code to deploy. Please generate some code first." if not title or not title.strip(): return "❌ **Error:** Please provide a title for your space." try: # Clean up the title for use as repo name import re clean_title = re.sub(r'[^a-zA-Z0-9\s-]', '', title) clean_title = re.sub(r'\s+', '-', clean_title).lower() clean_title = clean_title[:50] # Limit length # Get user info to create repo under their account user_info = whoami(oauth_token.token) username = user_info.get('name', 'unknown') # Create unique repo ID import time timestamp = int(time.time()) repo_id = f"{username}/{clean_title}-{timestamp}" # Create the space api = HfApi(token=oauth_token.token) api.create_repo( repo_id=repo_id, repo_type="space", space_sdk="static", space_hardware="cpu-basic" ) # Create the HTML file content html_content = f"""Generated with AnyCoder - AI-Powered Code Generator