Update app.py

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import os
 import re
-# import traceback # Optional for debugging
 
 API_TOKEN = os.getenv("HF_TOKEN", None)
 MODEL = "Qwen/Qwen3-32B"
@@ -13,79 +12,41 @@ try:
 except Exception as e:
     raise gr.Error(f"Failed to initialize model client for {MODEL}. Error: {e}. Check HF_TOKEN and model availability.")
 
-# --- Helper Function to Parse Code during Streaming ---
-def parse_streaming_code(current_response: str) -> dict:
-    """
-    Parses potentially incomplete AI output stream.
-    Identifies if .TAB separator is present and splits code accordingly.
-    Returns dict with html_code, backend_code, filename, language, and visibility flag.
-    """
-    files = {
-        'html_code': '',
-        'backend_code': '',
-        'backend_filename': 'Backend', # Default label
-        'backend_language': None,
-        'backend_visible': False       # Default visibility
-    }
-    separator_pattern = r'\.TAB\[NAME=([^\]]+)\]\n?'
-    match = re.search(separator_pattern, current_response)
-
-    if match:
-        # Separator found in the stream so far
-        html_part = current_response[:match.start()].strip()
-        backend_part = current_response[match.end():].strip() # Code after separator
-        backend_filename = match.group(1).strip()
-
-        files['html_code'] = html_part
-        files['backend_code'] = backend_part
-        files['backend_filename'] = backend_filename
-        files['backend_visible'] = True # Make backend visible
-
-        # Determine language
-        if backend_filename.endswith(".py"): files['backend_language'] = 'python'
-        elif backend_filename.endswith(".js"): files['backend_language'] = 'javascript'
-        elif backend_filename.endswith(".css"): files['backend_language'] = 'css'
-        else: files['backend_language'] = None
-    else:
-        # No separator found yet, assume all content is HTML
-        files['html_code'] = current_response.strip()
-        # Keep backend_visible as False
-
+# Parse all ```filename.ext\n<code>``` blocks
+def parse_code_blocks(response: str) -> list:
+    pattern = r"```([^\n]+)\n(.*?)```"
+    blocks = re.findall(pattern, response, re.DOTALL)
+    files = []
+    for filename, code in blocks:
+        lang = None
+        if filename.endswith(".py"):
+            lang = "python"
+        elif filename.endswith(".js"):
+            lang = "javascript"
+        elif filename.endswith(".html"):
+            lang = "html"
+        elif filename.endswith(".css"):
+            lang = "css"
+        files.append({
+            "filename": filename.strip(),
+            "language": lang,
+            "code": code.strip()
+        })
     return files
 
-# --- Minimal Cleaning for Intermediate Stream Chunks ---
-def clean_intermediate_stream(text: str) -> str:
-    """ Basic cleaning for streaming chunks (e.g., remove chat markers). """
-    cleaned = re.sub(r"<\s*\|?\s*(user|system|assistant)\s*\|?\s*>", "", text, flags=re.IGNORECASE)
-    # Avoid stripping aggressively during stream as it might remove partial code
-    return cleaned
+def strip_think_tags(text: str) -> str:
+    return re.sub(r"<think>.*?</think>", "", text, flags=re.DOTALL)
 
-# --- Core Code Generation Function - Modified for Streaming UI Updates ---
-def generate_code(
-    prompt: str,
-    backend_choice: str,
-    max_tokens: int,
-    temperature: float,
-    top_p: float,
-):
-    print(f"Streaming code generation for: {prompt[:100]}... | Backend: {backend_choice}")
+def extract_thoughts(text: str) -> str:
+    matches = re.findall(r"<think>(.*?)</think>", text, flags=re.DOTALL)
+    return "\n".join(matches).strip()
 
-    system_message = ( # System message remains the same
-         "You are an AI that generates website code. You MUST ONLY output the raw code, without any conversational text like 'Here is the code' or explanations before or after the code blocks. "
-         "You MUST NOT wrap the code in markdown fences like ```html, ```python, or ```js. "
-         "If the user requests 'Static' or the prompt clearly implies only frontend code, generate ONLY the content for the `index.html` file. "
-         "If the user requests 'Flask' or 'Node.js' and the prompt requires backend logic, you MUST generate both the `index.html` content AND the corresponding main backend file content (e.g., `app.py` for Flask, `server.js` or `app.js` for Node.js). "
-         "When generating multiple files, you MUST separate them EXACTLY as follows: "
-         "1. Output the complete code for the first file (e.g., `index.html`). "
-         "2. On a new line immediately after the first file's code, add the separator '.TAB[NAME=filename.ext]' (e.g., '.TAB[NAME=app.py]' or '.TAB[NAME=server.js]'). "
-         "3. On the next line, immediately start the code for the second file. "
-         "Generate only the necessary files (usually index.html and potentially one backend file). "
-         "The generated website code must be SFW and have minimal errors. "
-         "Only include comments where user modification is strictly required. Avoid explanatory comments. "
-         "If the user asks you to create code that is NOT for a website, you MUST respond ONLY with the exact phrase: "
-         "'hey there! am here to create websites for you unfortunately am programmed to not create codes! otherwise I would go on the naughty list :-('"
-    )
+system_message = (
+    "You are an AI that generates website code using markdown-style code blocks. "
+    "Each file should be output as: ```filename.ext\\n<code>\\n``` with no explanation."
+)
 
+def generate_code(prompt, backend_choice, max_tokens, temperature, top_p):
     user_prompt = f"USER_PROMPT = {prompt}\nUSER_BACKEND = {backend_choice}"
 
     messages = [
@@ -94,15 +55,10 @@ def generate_code(
     ]
 
     full_response = ""
-    # Initialize state for UI updates
-    current_html = ""
-    current_backend = ""
-    current_backend_label = "Backend"
-    current_backend_lang = None
-    is_backend_visible = False
+    current_thoughts = ""
 
-    # Initial clear of outputs
-    yield gr.update(value="", visible=True), gr.update(visible=False), gr.update(value="", visible=False)
+    # Reset outputs: code file tabs and thinking box
+    yield [], gr.update(visible=True, value="")
 
     try:
         stream = client.chat_completion(
@@ -117,142 +73,56 @@ def generate_code(
             token = message.choices[0].delta.content
             if isinstance(token, str):
                 full_response += token
-                # Clean intermediate response minimally
-                cleaned_response_chunk = clean_intermediate_stream(full_response)
-
-                # Parse the *entire accumulated* cleaned response on each iteration
-                parsed_state = parse_streaming_code(cleaned_response_chunk)
-
-                # Update state variables
-                current_html = parsed_state['html_code']
-                current_backend = parsed_state['backend_code']
-                current_backend_label = parsed_state['backend_filename']
-                current_backend_lang = parsed_state['backend_language']
-                is_backend_visible = parsed_state['backend_visible'] # This determines visibility
-
-                # Prepare Gradio updates based on the *current* parsed state
-                html_update = gr.update(value=current_html)
-                # Update the backend tab's visibility
-                tab_update = gr.update(visible=is_backend_visible)
-                # Update the backend code block's content, label, language, and visibility
-                backend_code_update = gr.update(
-                    value=current_backend,
-                    label=current_backend_label,
-                    language=current_backend_lang,
-                    visible=is_backend_visible # Make code block visible *if* tab is visible
-                )
-
-                # Yield updates for html_code, backend_tab, backend_code
-                yield html_update, tab_update, backend_code_update
-
-        # --- Final Clean and Update after Stream ---
-        # Ensure the final state is clean and fully parsed
-        final_cleaned_response = full_response.strip()
-        # Remove fences/phrases missed during stream (optional but good practice)
-        final_cleaned_response = re.sub(r"^\s*```[a-z]*\s*\n?", "", final_cleaned_response)
-        final_cleaned_response = re.sub(r"\n?\s*```\s*$", "", final_cleaned_response)
-        common_phrases = ["Here is the code:", "Okay, here is the code:", "Here's the code:", "Sure, here is the code you requested:"]
-        temp_lower = final_cleaned_response.lower()
-        for phrase in common_phrases:
-            if temp_lower.startswith(phrase.lower()):
-                final_cleaned_response = final_cleaned_response[len(phrase):].lstrip()
-                temp_lower = final_cleaned_response.lower()
-
-        # Check for refusal message in the final response
-        refusal_message = "hey there! am here to create websites for you unfortunately am programmed to not create codes! otherwise I would go on the naughty list :-("
-        if refusal_message in final_cleaned_response:
-             yield gr.update(value=refusal_message), gr.update(visible=False), gr.update(value="", visible=False)
-             return # Stop processing
-
-        # Final parse
-        final_parsed_state = parse_streaming_code(final_cleaned_response)
-
-        # Final updates to ensure everything is correct
-        final_html_update = gr.update(value=final_parsed_state['html_code'])
-        final_tab_update = gr.update(visible=final_parsed_state['backend_visible'])
-        final_backend_code_update = gr.update(
-            value=final_parsed_state['backend_code'],
-            label=final_parsed_state['backend_filename'],
-            language=final_parsed_state['backend_language'],
-            visible=final_parsed_state['backend_visible']
-        )
-        yield final_html_update, final_tab_update, final_backend_code_update
 
+                # Extract thinking chunks and show them
+                thoughts = extract_thoughts(full_response)
+                if thoughts != current_thoughts:
+                    current_thoughts = thoughts
+                    yield gr.update(visible=True, value=current_thoughts)
+
+                cleaned = strip_think_tags(full_response)
+                files = parse_code_blocks(cleaned)
+                updates = []
+                for f in files:
+                    updates.append(gr.Code(value=f["code"], label=f["filename"], language=f["language"]))
+                yield updates, gr.update(visible=True, value=current_thoughts)
+
+        # Final clean state
+        cleaned = strip_think_tags(full_response)
+        files = parse_code_blocks(cleaned)
+        final_updates = [gr.Code(value=f["code"], label=f["filename"], language=f["language"]) for f in files]
+        yield final_updates, gr.update(visible=False)
 
     except Exception as e:
         print(f"ERROR during code generation stream: {e}")
-        # traceback.print_exc() # Uncomment for detailed traceback
-        error_message = f"## Error\n\nFailed during streaming.\n**Reason:** {e}"
-        # Show error in HTML block, hide backend tab and code
-        yield gr.update(value=error_message), gr.update(visible=False), gr.update(value="", visible=False)
-
+        yield [gr.Markdown(f"**Error:** {e}")], gr.update(visible=False)
 
-# --- Build Gradio Interface ---
 with gr.Blocks(css=".gradio-container { max-width: 90% !important; }") as demo:
     gr.Markdown("# ✨ Website Code Generator ✨")
-    gr.Markdown(
-        "Describe the website you want. See code generated live.\n"
-        "If backend code is generated, a second tab will appear."
-    )
+    gr.Markdown("Describe the website you want. Multiple file tabs will be created automatically.")
 
     with gr.Row():
         with gr.Column(scale=2):
-            prompt_input = gr.Textbox(
-                label="Website Description",
-                placeholder="e.g., A Flask app with a simple chat using Socket.IO",
-                lines=6,
-            )
-            backend_radio = gr.Radio(
-                ["Static", "Flask", "Node.js"],
-                label="Backend Context",
-                value="Static",
-                info="Guides AI if backend code (like Python/JS) is needed alongside HTML."
-            )
+            prompt_input = gr.Textbox(label="Website Description", lines=6)
+            backend_radio = gr.Radio(["Static", "Flask", "Node.js"], label="Backend Context", value="Static")
             generate_button = gr.Button("✨ Generate Website Code", variant="primary")
 
         with gr.Column(scale=3):
-            # Define Tabs structure
-            with gr.Tabs(elem_id="code-tabs"):
-                # Tab 1: Always present for HTML
-                with gr.Tab("index.html", elem_id="html-tab") as html_tab:
-                     html_code_output = gr.Code(
-                         label="index.html",
-                         language="html",
-                         lines=25,
-                         interactive=False,
-                         elem_id="html_code",
-                     )
-                # Tab 2: Backend - defined but starts hidden
-                with gr.Tab("Backend", elem_id="backend-tab", visible=False) as backend_tab:
-                     backend_code_output = gr.Code(
-                         label="Backend", # Label updated dynamically if tab becomes visible
-                         language=None,   # Language updated dynamically
-                         lines=25,
-                         interactive=False,
-                         elem_id="backend_code",
-                         visible=False # Code block also starts hidden
-                     )
+            file_outputs = gr.Group(update=lambda: [])
+            thinking_box = gr.Textbox(label="Model is thinking...", visible=False, interactive=False)
 
     with gr.Accordion("Advanced Settings", open=False):
-        max_tokens_slider = gr.Slider(
-            minimum=512, maximum=4096, value=3072, step=256, label="Max New Tokens"
-        )
-        temperature_slider = gr.Slider(
-            minimum=0.1, maximum=1.2, value=0.7, step=0.1, label="Temperature"
-        )
-        top_p_slider = gr.Slider(
-            minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-P"
-        )
+        max_tokens_slider = gr.Slider(512, 4096, value=3072, step=256, label="Max New Tokens")
+        temperature_slider = gr.Slider(0.1, 1.2, value=0.7, step=0.1, label="Temperature")
+        top_p_slider = gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-P")
 
-    # Click function now targets html_code_output, backend_tab, and backend_code_output
     generate_button.click(
         fn=generate_code,
         inputs=[prompt_input, backend_radio, max_tokens_slider, temperature_slider, top_p_slider],
-        # Outputs MUST match the number and order of updates yielded by the function
-        outputs=[html_code_output, backend_tab, backend_code_output],
+        outputs=[file_outputs, thinking_box],
     )
 
 if __name__ == "__main__":
     if not API_TOKEN:
         print("Warning: HF_TOKEN environment variable not set. Using anonymous access.")
-    demo.queue(max_size=10).launch()
+    demo.queue().launch()