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Update app.py
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app.py
CHANGED
@@ -2,6 +2,7 @@ import gradio as gr
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from huggingface_hub import InferenceClient
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import os
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import re
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API_TOKEN = os.getenv("HF_TOKEN", None)
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MODEL = "Qwen/Qwen2.5-Coder-32B-Instruct"
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except Exception as e:
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raise gr.Error(f"Failed to initialize model client for {MODEL}. Error: {e}. Check HF_TOKEN and model availability.")
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separator_pattern = r'\.TAB\[NAME=([^\]]+)\]\n?'
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backend_filename =
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files['backend_language'] = 'javascript'
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elif backend_filename.endswith(".css"):
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files['backend_language'] = 'css'
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else:
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files['backend_language'] = None
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return files
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def generate_code(
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prompt: str,
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backend_choice: str,
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max_tokens: int,
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temperature: float,
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top_p: float,
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progress=gr.Progress(track_tqdm=True)
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):
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print(f"
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progress(0, desc="Initializing Request...")
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system_message = (
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"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. "
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"You MUST NOT wrap the code in markdown fences like ```html, ```python, or ```js. "
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"If the user requests 'Static' or the prompt clearly implies only frontend code, generate ONLY the content for the `index.html` file. "
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@@ -81,11 +94,17 @@ def generate_code(
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]
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full_response = ""
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try:
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progress(0.1, desc="Sending Request to Model...")
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stream = client.chat_completion(
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messages=messages,
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max_tokens=max_tokens,
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@@ -94,65 +113,86 @@ def generate_code(
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top_p=top_p,
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)
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progress(0.2, desc="Receiving Stream...")
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for message in stream:
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token = message.choices[0].delta.content
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if isinstance(token, str):
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full_response += token
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for phrase in common_phrases:
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if
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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 :-("
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if refusal_message in
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return
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progress(1, desc="Done")
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return html_update, backend_update
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except Exception as e:
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print(f"ERROR during code generation: {e}")
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error_message = f"## Error\n\nFailed
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with gr.Blocks(css=".gradio-container { max-width: 90% !important; }") as demo:
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gr.Markdown("# ✨ Website Code Generator ✨")
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gr.Markdown(
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"Describe the website you want.
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"If
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)
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with gr.Row():
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@@ -171,7 +211,9 @@ with gr.Blocks(css=".gradio-container { max-width: 90% !important; }") as demo:
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generate_button = gr.Button("✨ Generate Website Code", variant="primary")
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with gr.Column(scale=3):
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with gr.Tab("index.html", elem_id="html-tab") as html_tab:
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html_code_output = gr.Code(
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label="index.html",
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interactive=False,
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elem_id="html_code",
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)
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with gr.Tab("Backend", elem_id="backend-tab", visible=False) as backend_tab:
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backend_code_output = gr.Code(
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label="Backend",
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language=None,
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lines=25,
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interactive=False,
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elem_id="backend_code",
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visible=False
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)
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with gr.Accordion("Advanced Settings", open=False):
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minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-P"
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)
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generate_button.click(
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fn=generate_code,
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inputs=[prompt_input, backend_radio, max_tokens_slider, temperature_slider, top_p_slider],
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)
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if __name__ == "__main__":
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from huggingface_hub import InferenceClient
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import os
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import re
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# import traceback # Optional for debugging
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API_TOKEN = os.getenv("HF_TOKEN", None)
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MODEL = "Qwen/Qwen2.5-Coder-32B-Instruct"
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except Exception as e:
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raise gr.Error(f"Failed to initialize model client for {MODEL}. Error: {e}. Check HF_TOKEN and model availability.")
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# --- Helper Function to Parse Code during Streaming ---
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def parse_streaming_code(current_response: str) -> dict:
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"""
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Parses potentially incomplete AI output stream.
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Identifies if .TAB separator is present and splits code accordingly.
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Returns dict with html_code, backend_code, filename, language, and visibility flag.
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"""
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files = {
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'html_code': '',
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'backend_code': '',
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'backend_filename': 'Backend', # Default label
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'backend_language': None,
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'backend_visible': False # Default visibility
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}
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separator_pattern = r'\.TAB\[NAME=([^\]]+)\]\n?'
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match = re.search(separator_pattern, current_response)
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if match:
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# Separator found in the stream so far
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html_part = current_response[:match.start()].strip()
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backend_part = current_response[match.end():].strip() # Code after separator
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backend_filename = match.group(1).strip()
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files['html_code'] = html_part
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files['backend_code'] = backend_part
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files['backend_filename'] = backend_filename
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files['backend_visible'] = True # Make backend visible
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# Determine language
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if backend_filename.endswith(".py"): files['backend_language'] = 'python'
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elif backend_filename.endswith(".js"): files['backend_language'] = 'javascript'
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elif backend_filename.endswith(".css"): files['backend_language'] = 'css'
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else: files['backend_language'] = None
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else:
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# No separator found yet, assume all content is HTML
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files['html_code'] = current_response.strip()
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# Keep backend_visible as False
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return files
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# --- Minimal Cleaning for Intermediate Stream Chunks ---
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def clean_intermediate_stream(text: str) -> str:
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""" Basic cleaning for streaming chunks (e.g., remove chat markers). """
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cleaned = re.sub(r"<\s*\|?\s*(user|system|assistant)\s*\|?\s*>", "", text, flags=re.IGNORECASE)
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# Avoid stripping aggressively during stream as it might remove partial code
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return cleaned
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# --- Core Code Generation Function - Modified for Streaming UI Updates ---
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def generate_code(
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prompt: str,
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backend_choice: str,
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max_tokens: int,
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temperature: float,
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top_p: float,
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):
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print(f"Streaming code generation for: {prompt[:100]}... | Backend: {backend_choice}")
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system_message = ( # System message remains the same
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"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. "
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"You MUST NOT wrap the code in markdown fences like ```html, ```python, or ```js. "
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"If the user requests 'Static' or the prompt clearly implies only frontend code, generate ONLY the content for the `index.html` file. "
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]
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full_response = ""
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# Initialize state for UI updates
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current_html = ""
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current_backend = ""
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current_backend_label = "Backend"
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current_backend_lang = None
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is_backend_visible = False
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# Initial clear of outputs
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yield gr.update(value="", visible=True), gr.update(visible=False), gr.update(value="", visible=False)
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try:
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stream = client.chat_completion(
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messages=messages,
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max_tokens=max_tokens,
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top_p=top_p,
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)
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for message in stream:
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token = message.choices[0].delta.content
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if isinstance(token, str):
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full_response += token
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# Clean intermediate response minimally
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cleaned_response_chunk = clean_intermediate_stream(full_response)
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# Parse the *entire accumulated* cleaned response on each iteration
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parsed_state = parse_streaming_code(cleaned_response_chunk)
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# Update state variables
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current_html = parsed_state['html_code']
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current_backend = parsed_state['backend_code']
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current_backend_label = parsed_state['backend_filename']
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current_backend_lang = parsed_state['backend_language']
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is_backend_visible = parsed_state['backend_visible'] # This determines visibility
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# Prepare Gradio updates based on the *current* parsed state
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html_update = gr.update(value=current_html)
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# Update the backend tab's visibility
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tab_update = gr.update(visible=is_backend_visible)
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# Update the backend code block's content, label, language, and visibility
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backend_code_update = gr.update(
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value=current_backend,
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label=current_backend_label,
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language=current_backend_lang,
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visible=is_backend_visible # Make code block visible *if* tab is visible
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)
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# Yield updates for html_code, backend_tab, backend_code
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yield html_update, tab_update, backend_code_update
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# --- Final Clean and Update after Stream ---
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# Ensure the final state is clean and fully parsed
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final_cleaned_response = full_response.strip()
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# Remove fences/phrases missed during stream (optional but good practice)
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final_cleaned_response = re.sub(r"^\s*```[a-z]*\s*\n?", "", final_cleaned_response)
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final_cleaned_response = re.sub(r"\n?\s*```\s*$", "", final_cleaned_response)
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common_phrases = ["Here is the code:", "Okay, here is the code:", "Here's the code:", "Sure, here is the code you requested:"]
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temp_lower = final_cleaned_response.lower()
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for phrase in common_phrases:
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if temp_lower.startswith(phrase.lower()):
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final_cleaned_response = final_cleaned_response[len(phrase):].lstrip()
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temp_lower = final_cleaned_response.lower()
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# Check for refusal message in the final response
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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 :-("
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if refusal_message in final_cleaned_response:
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yield gr.update(value=refusal_message), gr.update(visible=False), gr.update(value="", visible=False)
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return # Stop processing
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# Final parse
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final_parsed_state = parse_streaming_code(final_cleaned_response)
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# Final updates to ensure everything is correct
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final_html_update = gr.update(value=final_parsed_state['html_code'])
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final_tab_update = gr.update(visible=final_parsed_state['backend_visible'])
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final_backend_code_update = gr.update(
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value=final_parsed_state['backend_code'],
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label=final_parsed_state['backend_filename'],
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language=final_parsed_state['backend_language'],
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visible=final_parsed_state['backend_visible']
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)
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yield final_html_update, final_tab_update, final_backend_code_update
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except Exception as e:
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print(f"ERROR during code generation stream: {e}")
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# traceback.print_exc() # Uncomment for detailed traceback
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error_message = f"## Error\n\nFailed during streaming.\n**Reason:** {e}"
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# Show error in HTML block, hide backend tab and code
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yield gr.update(value=error_message), gr.update(visible=False), gr.update(value="", visible=False)
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# --- Build Gradio Interface ---
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with gr.Blocks(css=".gradio-container { max-width: 90% !important; }") as demo:
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gr.Markdown("# ✨ Website Code Generator ✨")
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gr.Markdown(
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"Describe the website you want. See code generated live.\n"
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"If backend code is generated, a second tab will appear."
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)
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with gr.Row():
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generate_button = gr.Button("✨ Generate Website Code", variant="primary")
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with gr.Column(scale=3):
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# Define Tabs structure
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with gr.Tabs(elem_id="code-tabs"):
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# Tab 1: Always present for HTML
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with gr.Tab("index.html", elem_id="html-tab") as html_tab:
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html_code_output = gr.Code(
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label="index.html",
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interactive=False,
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elem_id="html_code",
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# Tab 2: Backend - defined but starts hidden
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with gr.Tab("Backend", elem_id="backend-tab", visible=False) as backend_tab:
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backend_code_output = gr.Code(
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label="Backend", # Label updated dynamically if tab becomes visible
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language=None, # Language updated dynamically
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lines=25,
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interactive=False,
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elem_id="backend_code",
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visible=False # Code block also starts hidden
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)
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with gr.Accordion("Advanced Settings", open=False):
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minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-P"
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)
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# Click function now targets html_code_output, backend_tab, and backend_code_output
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generate_button.click(
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fn=generate_code,
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inputs=[prompt_input, backend_radio, max_tokens_slider, temperature_slider, top_p_slider],
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# Outputs MUST match the number and order of updates yielded by the function
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outputs=[html_code_output, backend_tab, backend_code_output],
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)
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if __name__ == "__main__":
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