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import os |
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from typing import Dict, List, Optional, Tuple |
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import gradio as gr |
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from huggingface_hub import InferenceClient |
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from tavily import TavilyClient |
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from config import ( |
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HTML_SYSTEM_PROMPT, GENERIC_SYSTEM_PROMPT, HTML_SYSTEM_PROMPT_WITH_SEARCH, |
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GENERIC_SYSTEM_PROMPT_WITH_SEARCH, FollowUpSystemPrompt |
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) |
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from chat_processing import ( |
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history_to_messages, messages_to_history, |
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remove_code_block, apply_search_replace_changes, send_to_sandbox, |
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history_to_chatbot_messages, get_gradio_language |
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) |
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from file_processing import ( |
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extract_text_from_file, create_multimodal_message, |
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) |
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from web_extraction import extract_website_content, enhance_query_with_search |
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HF_TOKEN = os.getenv('HF_TOKEN') |
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if not HF_TOKEN: |
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raise RuntimeError("HF_TOKEN environment variable is not set. Please set it to your Hugging Face API token.") |
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def get_inference_client(model_id, provider="auto"): |
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"""Return an InferenceClient with provider based on model_id and user selection.""" |
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return InferenceClient( |
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provider=provider, |
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api_key=HF_TOKEN, |
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bill_to="huggingface" |
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) |
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TAVILY_API_KEY = os.getenv('TAVILY_API_KEY') |
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tavily_client = None |
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if TAVILY_API_KEY: |
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try: |
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tavily_client = TavilyClient(api_key=TAVILY_API_KEY) |
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except Exception as e: |
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print(f"Failed to initialize Tavily client: {e}") |
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tavily_client = None |
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async def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[List[Tuple[str, str]]], _current_model: Dict, enable_search: bool = False, language: str = "html", progress=gr.Progress(track_tqdm=True)): |
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if query is None: |
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query = '' |
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if _history is None: |
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_history = [] |
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has_existing_html = False |
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if _history: |
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last_assistant_msg = _history[-1][1] if len(_history) > 0 else "" |
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if '<!DOCTYPE html>' in last_assistant_msg or '<html' in last_assistant_msg: |
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has_existing_html = True |
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progress(0, desc="Initializing...") |
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if has_existing_html: |
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system_prompt = FollowUpSystemPrompt |
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else: |
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if language == "html": |
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system_prompt = HTML_SYSTEM_PROMPT_WITH_SEARCH if enable_search else HTML_SYSTEM_PROMPT |
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else: |
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system_prompt = GENERIC_SYSTEM_PROMPT_WITH_SEARCH.format(language=language) if enable_search else GENERIC_SYSTEM_PROMPT.format(language=language) |
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messages = history_to_messages(_history, system_prompt) |
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file_text = "" |
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progress(0.1, desc="Processing file...") |
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if file: |
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file_text = extract_text_from_file(file) |
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if file_text: |
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file_text = file_text[:5000] |
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query = f"{query}\n\n[Reference file content below]\n{file_text}" |
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progress(0.2, desc="Extracting website content...") |
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website_text = "" |
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if website_url and website_url.strip(): |
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website_text = extract_website_content(website_url.strip()) |
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if website_text and not website_text.startswith("Error"): |
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website_text = website_text[:8000] |
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query = f"{query}\n\n[Website content to redesign below]\n{website_text}" |
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elif website_text.startswith("Error"): |
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fallback_guidance = """ |
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Since I couldn't extract the website content, please provide additional details about what you'd like to build: |
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1. What type of website is this? (e.g., e-commerce, blog, portfolio, dashboard) |
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2. What are the main features you want? |
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3. What's the target audience? |
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4. Any specific design preferences? (colors, style, layout) |
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This will help me create a better design for you.""" |
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query = f"{query}\n\n[Error extracting website: {website_text}]{fallback_guidance}" |
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progress(0.4, desc="Performing web search...") |
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enhanced_query = enhance_query_with_search(query, enable_search) |
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client = get_inference_client(_current_model["id"]) |
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if image is not None: |
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messages.append(create_multimodal_message(enhanced_query, image)) |
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else: |
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messages.append({'role': 'user', 'content': enhanced_query}) |
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progress(0.5, desc="Generating code with AI model...") |
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try: |
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completion = client.chat.completions.create( |
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model=_current_model["id"], |
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messages=messages, |
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stream=True, |
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max_tokens=5000 |
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) |
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progress(0.6, desc="Streaming response...") |
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content = "" |
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for chunk in completion: |
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if chunk.choices[0].delta.content: |
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content += chunk.choices[0].delta.content |
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clean_code = remove_code_block(content) |
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if has_existing_html: |
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if not (clean_code.strip().startswith("<!DOCTYPE html>") or clean_code.strip().startswith("<html")): |
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last_html = _history[-1][1] if _history else "" |
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modified_html = apply_search_replace_changes(last_html, clean_code) |
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clean_code = remove_code_block(modified_html) |
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yield ( |
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gr.update(value=clean_code, language=get_gradio_language(language)), |
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_history, |
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send_to_sandbox(clean_code) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML.</div>", |
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history_to_chatbot_messages(_history) |
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) |
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_history = messages_to_history(messages + [{'role': 'assistant', 'content': content}]) |
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final_code = remove_code_block(content) |
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yield ( |
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final_code, |
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_history, |
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send_to_sandbox(final_code), |
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history_to_chatbot_messages(_history), |
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) |
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except Exception as e: |
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error_message = f"Error: {str(e)}" |
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yield (error_message, _history, None, history_to_chatbot_messages(_history)) |
