Update app.py

app.py

@@ -4,21 +4,18 @@ from typing import Optional, Dict, List, Tuple
 import gradio as gr
 
 from constants import HTML_SYSTEM_PROMPT, AVAILABLE_MODELS, DEMO_LIST
-from hf_client import get_inference_client, tavily_client
+from hf_client import get_inference_client
 from tavily_search import enhance_query_with_search
 from utils import (
     extract_text_from_file,
     extract_website_content,
     apply_search_replace_changes,
-    apply_transformers_js_search_replace_changes,
     history_to_messages,
     history_to_chatbot_messages,
     remove_code_block,
     parse_transformers_js_output,
     format_transformers_js_output
 )
-from search_replace import SEARCH_START, DIVIDER, REPLACE_END
-from web_scraper import extract_text_from_image
 from deploy import send_to_sandbox, handle_load_project
 
 # Type aliases
@@ -37,33 +34,28 @@ def generation_code(
     language: str,
     provider: str
 ) -> Tuple[str, History, str, List[Dict[str, str]]]:
-    # Initialize inputs
+
     if query is None:
         query = ''
     if _history is None:
         _history = []
 
-    # Prepare system prompt and history
     system_prompt = _setting.get('system', HTML_SYSTEM_PROMPT)
     messages = history_to_messages(_history, system_prompt)
 
-    # Append file content if provided
     if file:
         file_text = extract_text_from_file(file)
         if file_text:
             query += f"\n\n[Reference file content below]\n{file_text[:5000]}"
 
-    # Append website content if provided
     if website_url:
         website_text = extract_website_content(website_url)
         if not website_text.startswith("Error"):
             query += f"\n\n[Website content below]\n{website_text[:8000]}"
 
-    # Enhance with web search if enabled
     final_query = enhance_query_with_search(query, enable_search)
     messages.append({'role': 'user', 'content': final_query})
 
-    # Call HF inference
     client = get_inference_client(_current_model['id'], provider)
     completion = client.chat.completions.create(
         model=_current_model['id'],
@@ -72,7 +64,6 @@ def generation_code(
     )
     content = completion.choices[0].message.content
 
-    # Process output based on language and existing content
     has_existing = bool(_history and _history[-1][1])
     if language == 'transformers.js':
         files = parse_transformers_js_output(content)
@@ -85,20 +76,17 @@ def generation_code(
         code_str = clean
         sandbox_html = send_to_sandbox(clean) if language == 'html' else ''
 
-    # Update history and prepare chatbot messages
     new_history = _history + [(query, code_str)]
     chat_msgs = history_to_chatbot_messages(new_history)
 
-    # Return exactly four outputs: code, history state, preview HTML, and chat history
     return code_str, new_history, sandbox_html, chat_msgs
 
-# Build Gradio UI
 with gr.Blocks(
     theme=gr.themes.Base(),
     title="AnyCoder - AI Code Generator"
 ) as demo:
     history_state = gr.State([])
-    setting_state = gr.State({ 'system': HTML_SYSTEM_PROMPT })
+    setting_state = gr.State({'system': HTML_SYSTEM_PROMPT})
     current_model = gr.State(AVAILABLE_MODELS[9])
 
     with gr.Sidebar():
@@ -108,7 +96,7 @@ with gr.Blocks(
         load_project_status = gr.Markdown(visible=False)
 
         input_box = gr.Textbox(label="What to build?", lines=3)
-        language_dropdown = gr.Dropdown(choices=["html","python","transformers.js"], value="html")
+        language_dropdown = gr.Dropdown(choices=["html", "python", "transformers.js"], value="html")
         website_input = gr.Textbox(label="Website URL")
         file_input = gr.File(label="Reference file")
         image_input = gr.Image(label="Design image")