Update app.py

app.py

@@ -2,65 +2,65 @@ import gradio as gr
 import google.generativeai as genai
 import re
 import json
+import os # Good practice to import os if using env variables later
+
+# --- Constants for Limits ---
+TITLE_MAX_LEN = 60
+BRAND_NAME_MAX_LEN = 50
+BULLET_POINT_MAX_LEN = 256
+BULLET_POINT_MIN_LEN = 240 # Keep this if you want to check minimum length later
 
 def count_characters(text):
     """Count characters in text."""
     return len(text) if text else 0
 
 def format_output(title, brand_name, bullet1, bullet2, suggested_keywords=None):
-    """Format the output with character counts."""
-    output = f"Title ({count_characters(title)}/60 characters):\n{title}\n\n"
-    output += f"Brand Name ({count_characters(brand_name)}/50 characters):\n{brand_name}\n\n"
-    output += f"Bullet Point 1 ({count_characters(bullet1)}/256 characters):\n{bullet1}\n\n"
-    output += f"Bullet Point 2 ({count_characters(bullet2)}/256 characters):\n{bullet2}"
-    
+    """Format the output with character counts (reflecting potentially truncated lengths)."""
+    # Display the actual length after potential truncation
+    output = f"Title ({count_characters(title)}/{TITLE_MAX_LEN} characters):\n{title}\n\n"
+    output += f"Brand Name ({count_characters(brand_name)}/{BRAND_NAME_MAX_LEN} characters):\n{brand_name}\n\n"
+    output += f"Bullet Point 1 ({count_characters(bullet1)}/{BULLET_POINT_MAX_LEN} characters):\n{bullet1}\n\n"
+    output += f"Bullet Point 2 ({count_characters(bullet2)}/{BULLET_POINT_MAX_LEN} characters):\n{bullet2}"
+
     if suggested_keywords:
         output += f"\n\nSuggested Additional Keywords:\n{suggested_keywords}"
-    
+
     return output
 
 def generate_prompt(quote, niche, target, keywords):
     """Generate the prompt for Gemini API."""
+    # Keep the detailed prompt instructions as they help guide the AI
     combined_prompt = f"""You are an Amazon Merch on Demand SEO expert specializing in creating optimized t-shirt and apparel listings.
-
 MY INPUT IS ABOUT: A {niche} t-shirt with the design/quote: "{quote}" for {target}.
 YOU MUST ONLY create an Amazon apparel listing about that EXACT input - no substitutions or different themes allowed.
-
 Generate a listing that includes:
-
-1. Title (exactly 60 characters): Must include "{niche}" and reference the design/quote "{quote}" and target audience "{target}"
-2. Brand Name (34-50 characters): Create a fitting brand name for this specific {niche} apparel for {target}
-3. Bullet Point 1 (240-256 characters): Highlight key features using ALL CAPS for the first 2-3 words. Focus ONLY on the design, quote, and niche theme.
-4. Bullet Point 2 (240-256 characters): Highlight additional features using ALL CAPS for the first 2-3 words. Focus ONLY on the design, quote, and niche theme.
-
+1. Title (try for exactly {TITLE_MAX_LEN} characters): Must include "{niche}" and reference the design/quote "{quote}" and target audience "{target}"
+2. Brand Name (try for 34-{BRAND_NAME_MAX_LEN} characters): Create a fitting brand name for this specific {niche} apparel for {target}
+3. Bullet Point 1 (try for {BULLET_POINT_MIN_LEN}-{BULLET_POINT_MAX_LEN} characters): Highlight key features using ALL CAPS for the first 2-3 words. Focus ONLY on the design, quote, and niche theme.
+4. Bullet Point 2 (try for {BULLET_POINT_MIN_LEN}-{BULLET_POINT_MAX_LEN} characters): Highlight additional features using ALL CAPS for the first 2-3 words. Focus ONLY on the design, quote, and niche theme.
 IMPORTANT RULES — STRICT ENFORCEMENT:
 - DO NOT include generic phrases like "PREMIUM QUALITY" or references to material quality
 - DO NOT include phrases like "This comfortable and stylish tee is made with high-quality materials for a soft feel and long-lasting wear"
-- Bullet point 1 must be between 240 and 256 characters. Not less than 240. Not more than 256.
-- Bullet point 2 must be between 240 and 256 characters. Not less than 240. Not more than 256.
-- DO NOT exceed the character limit under any circumstances.
+- Bullet point 1 must be between {BULLET_POINT_MIN_LEN} and {BULLET_POINT_MAX_LEN} characters. Aim for the higher end.
+- Bullet point 2 must be between {BULLET_POINT_MIN_LEN} and {BULLET_POINT_MAX_LEN} characters. Aim for the higher end.
+- DO NOT exceed the character limits ({TITLE_MAX_LEN} for title, {BRAND_NAME_MAX_LEN} for brand, {BULLET_POINT_MAX_LEN} for bullets).
 - Count characters carefully. Ensure compliance before outputting.
 - Focus ONLY on the specific design, niche, and quote provided
 - Every sentence must directly relate to the quote, niche theme, and target audience
 - Do not include any content that strays from the specific theme provided
-
-
 The listing should be specifically for t-shirts, hoodies, or sweaters for the Amazon Merch on Demand program.
 The listing MUST be about: {niche} + {quote} + for {target}. Do not generate content about other holidays, quotes, or audiences.
-
 Use these specific keywords in your listing: {keywords}
-
 Respond ONLY with a JSON object in this format:
 {{
-  "title": "The title with exactly 60 characters",
-  "brand_name": "Brand name between 34-50 characters",
-  "bullet_point_1": "First bullet point between 240-256 characters that focuses on the design and theme",
-  "bullet_point_2": "Second bullet point between 240-256 characters that focuses on the design and theme",
+  "title": "The title aiming for {TITLE_MAX_LEN} characters",
+  "brand_name": "Brand name aiming for 34-{BRAND_NAME_MAX_LEN} characters",
+  "bullet_point_1": "First bullet point aiming for {BULLET_POINT_MIN_LEN}-{BULLET_POINT_MAX_LEN} characters",
+  "bullet_point_2": "Second bullet point aiming for {BULLET_POINT_MIN_LEN}-{BULLET_POINT_MAX_LEN} characters",
   "suggested_keywords": "5 additional keywords separated by commas"
 }}
-
-REMINDER: Make sure to count the characters carefully. Title should be EXACTLY 60 characters. Bullet point 1 must be between 240-256 characters and Bullet point 2 must be between 240-256 characters.
-STRICT ENFORCEMENT: Bullet point 1 and 2 MUST be between 240 and 256 characters. Could be less, not more. If it's 257+, the result is invalid. Carefully count and ensure compliance.
+REMINDER: Make sure to count the characters carefully. Aim for Title exactly {TITLE_MAX_LEN} characters. Aim for Bullet points 1 and 2 between {BULLET_POINT_MIN_LEN}-{BULLET_POINT_MAX_LEN} characters.
+STRICT ENFORCEMENT: Bullet point 1 and 2 MUST be between {BULLET_POINT_MIN_LEN} and {BULLET_POINT_MAX_LEN} characters. If it's {BULLET_POINT_MAX_LEN+1}+, the result is invalid. Carefully count and ensure compliance.
 """
 
     return combined_prompt
@@ -68,229 +68,292 @@ STRICT ENFORCEMENT: Bullet point 1 and 2 MUST be between 240 and 256 characters.
 def generate_multiple_variations_prompt(quote, niche, target, keywords):
     """Generate the prompt for multiple variations of title and brand name."""
     combined_prompt = f"""You are an Amazon Merch on Demand SEO expert specializing in creating optimized t-shirt and apparel listings.
-
 MY INPUT IS ABOUT: A {niche} t-shirt with the design/quote: "{quote}" for {target}.
 YOU MUST ONLY create variations about that EXACT input - no substitutions or different themes allowed.
-
 Generate 3 different variations for the Title and Brand Name based on the provided information.
 All variations MUST be about {niche} + "{quote}" + for {target} audience.
-
 The titles MUST include:
 - The specific holiday/event: {niche}
 - Reference to the quote/design: "{quote}"
 - The target audience: {target}
-
 Focus only on t-shirts, sweaters, and hoodies for the Amazon Merch on Demand program.
-All titles must be exactly 60 characters and brand names between 34-50 characters.
-
+All titles must aim for exactly {TITLE_MAX_LEN} characters and brand names between 34-{BRAND_NAME_MAX_LEN} characters.
 Respond ONLY with a JSON object in this format:
 {{
   "title_variations": [
-    "Title variation 1 - exactly 60 characters, count carefully",
-    "Title variation 2 - exactly 60 characters, count carefully",
-    "Title variation 3 - exactly 60 characters, count carefully"
+    "Title variation 1 - aim for {TITLE_MAX_LEN} characters, count carefully",
+    "Title variation 2 - aim for {TITLE_MAX_LEN} characters, count carefully",
+    "Title variation 3 - aim for {TITLE_MAX_LEN} characters, count carefully"
   ],
   "brand_name_variations": [
-    "Brand name variation 1 (34-50 characters)",
-    "Brand name variation 2 (34-50 characters)",
-    "Brand name variation 3 (34-50 characters)"
+    "Brand name variation 1 (aim for 34-{BRAND_NAME_MAX_LEN} characters)",
+    "Brand name variation 2 (aim for 34-{BRAND_NAME_MAX_LEN} characters)",
+    "Brand name variation 3 (aim for 34-{BRAND_NAME_MAX_LEN} characters)"
   ]
 }}
-
-REMINDER: Make sure each title is EXACTLY 60 characters. Count carefully!"""
+REMINDER: Make sure each title aims for EXACTLY {TITLE_MAX_LEN} characters. Count carefully!"""
 
     return combined_prompt
 
 def generate_amazon_listing(api_key, quote, niche, target, keywords):
-    """Generate Amazon listing using Gemini API."""
+    """Generate Amazon listing using Gemini API, enforcing character limits."""
     # Input validation
     if not api_key:
         return "Error: Please enter a valid Gemini API key"
     if not quote or not niche or not target:
         return "Error: Please fill in all required fields (Quote, Holiday/Event, and Target Audience)"
-    
+
     try:
         # Configure the Gemini API with the provided key
+        # Consider using environment variables for production:
+        # api_key = os.getenv("GEMINI_API_KEY") or api_key_input
         genai.configure(api_key=api_key)
-        
+
         # Create model with optimized settings
         model = genai.GenerativeModel(
-            'gemini-1.5-pro',
+            'gemini-1.5-pro', # Or 'gemini-1.5-flash' for potentially faster/cheaper generation
             generation_config={
-                "temperature": 0.3,
+                "temperature": 0.3, # Lower temperature for more predictable output
                 "top_p": 0.8,
-                "max_output_tokens": 1024,  # Reduced for faster response
+                "max_output_tokens": 1024, # Maximum tokens the API can *return*
+                # Note: 'max_output_tokens' doesn't directly control character count precisely
+                "response_mime_type": "application/json" # Request JSON directly
             }
         )
-        
+
         # Generate the main listing
         prompt = generate_prompt(quote, niche, target, keywords)
-        
+
         try:
-            # First try to get just the main listing for faster response
+            # --- Generate Main Listing Content ---
             response = model.generate_content(prompt)
-            
-            # Extract JSON from the response
-            response_text = response.text
-            match = re.search(r'{.*}', response_text, re.DOTALL)
-            if not match:
-                return "Error: Could not extract JSON from Gemini API response. Please try again."
-                
-            json_str = match.group(0)
+
+            # Since we requested JSON, parse it directly. Add error handling.
             try:
+                # Access the text part and load as JSON
+                response_text = response.text
+                # Sometimes the API might still wrap it in markdown, try to strip it
+                json_match = re.search(r'```json\s*({.*?})\s*```', response_text, re.DOTALL | re.IGNORECASE)
+                if json_match:
+                    json_str = json_match.group(1)
+                else:
+                    # Fallback if no markdown backticks are found
+                    json_str = response_text.strip()
+
                 result = json.loads(json_str)
-            except json.JSONDecodeError:
-                return "Error parsing JSON response from Gemini API. Please try again."
-                
-            # Validate that the output actually matches the input criteria
-            title = result.get("title", "")
-            if not (quote.lower() in title.lower() or 
-                   niche.lower() in title.lower() or 
-                   any(t.lower() in title.lower() for t in target.lower().split(','))):
-                return f"Error: Generated title doesn't match the requested theme: '{quote}', '{niche}', or '{target}'. Please try again."
-            
-            # Validate bullet point lengths
-            bullet1 = result.get("bullet_point_1", "")[:256]
-            bullet2 = result.get("bullet_point_2", "")[:256]
-
-            
-            #if len(bullet1) < 240 or len(bullet1) > 256:
-                #return f"Error: Bullet point 1 length ({len(bullet1)}) is not between 240-256 characters. Please try again."
-            
-            #if len(bullet2) < 240 or len(bullet2) > 256:
-                #return f"Error: Bullet point 2 length ({len(bullet2)}) is not between 240-256 characters. Please try again."
-            
+
+            except (json.JSONDecodeError, AttributeError, IndexError) as json_err:
+                 # Handle cases where response.text is empty, not valid JSON, or API returned unexpected format
+                print(f"JSON Parsing Error: {json_err}")
+                print(f"Raw response text: {getattr(response, 'text', 'N/A')}") # Log raw response for debugging
+                # Check for safety blocks
+                if response.prompt_feedback.block_reason:
+                     return f"Error: Generation blocked due to: {response.prompt_feedback.block_reason}. Content filters may have been triggered."
+                return "Error: Could not parse JSON response from Gemini API. The API might have returned an unexpected format or an empty response. Please try again."
+
+
+            # --- ENFORCE CHARACTER LIMITS ---
+            # Get raw values and immediately truncate if they exceed the MAX limit
+            title = result.get("title", "")[:TITLE_MAX_LEN]
+            brand_name = result.get("brand_name", "")[:BRAND_NAME_MAX_LEN]
+            bullet1 = result.get("bullet_point_1", "")[:BULLET_POINT_MAX_LEN]
+            bullet2 = result.get("bullet_point_2", "")[:BULLET_POINT_MAX_LEN]
+            suggested_keywords = result.get("suggested_keywords", "Error generating suggested keywords") # Keywords don't usually need truncation
+
+            # --- VALIDATION (using potentially truncated values) ---
+
+            # Validate that the output actually matches the input criteria (optional but good)
+            # Check if *any* part of the target audience is in the title if it's comma-separated
+            target_parts = [t.strip().lower() for t in target.split(',')]
+            title_lower = title.lower()
+            if not (quote.lower() in title_lower or
+                    niche.lower() in title_lower or
+                    any(t_part in title_lower for t_part in target_parts)):
+                return f"Error: Generated title ('{title}') doesn't seem to strongly match the requested theme: '{quote}', '{niche}', or '{target}'. Please try again or adjust input."
+
+            # --- Optional: Validate the *lower* bound for bullet points ---
+            # Uncomment these lines if you strictly need the bullets to be AT LEAST min_len characters
+            # Note: This check happens *after* truncation, so if truncation occurred, it might pass this check.
+            # if len(bullet1) < BULLET_POINT_MIN_LEN:
+            #     return f"Error: Bullet point 1 length ({len(bullet1)}) is less than the required minimum {BULLET_POINT_MIN_LEN} characters after generation/truncation. Please try again."
+            # if len(bullet2) < BULLET_POINT_MIN_LEN:
+            #     return f"Error: Bullet point 2 length ({len(bullet2)}) is less than the required minimum {BULLET_POINT_MIN_LEN} characters after generation/truncation. Please try again."
+
             # Check for generic content in bullet points
-            generic_phrases = ["premium quality", "high-quality materials", "soft feel", "long-lasting wear", 
+            generic_phrases = ["premium quality", "high-quality materials", "soft feel", "long-lasting wear",
                               "comfortable and stylish"]
-            
+            bullet1_lower = bullet1.lower()
+            bullet2_lower = bullet2.lower()
             for phrase in generic_phrases:
-                if phrase in bullet1.lower() or phrase in bullet2.lower():
-                    return f"Error: Generated bullet points contain generic phrase '{phrase}'. Please try again."
-            
-            # Format main output first - so we have something to show quickly
+                if phrase in bullet1_lower or phrase in bullet2_lower:
+                    return f"Error: Generated bullet points contain disallowed generic phrase '{phrase}'. Please try again."
+
+            # Format main output first - using the enforced length values
             main_output = format_output(
-                result.get("title", "Error generating title"),
-                result.get("brand_name", "Error generating brand name"),
-                result.get("bullet_point_1", "Error generating bullet point 1"),
-                result.get("bullet_point_2", "Error generating bullet point 2"),
-                result.get("suggested_keywords", "Error generating suggested keywords")
+                title,
+                brand_name,
+                bullet1,
+                bullet2,
+                suggested_keywords
             )
-            
-            # Now try to get variations in a separate call
+
+            # --- Generate Variations (Optional Second Call) ---
             try:
                 variations_prompt = generate_multiple_variations_prompt(quote, niche, target, keywords)
+                # Use a separate model instance or reuse if configuration is the same
+                # Using the same model instance here
                 response_var = model.generate_content(
                     variations_prompt,
-                    generation_config={
-                        "temperature": 0.4,
+                     generation_config={ # Can reuse or adjust config for variations
+                        "temperature": 0.4, # Slightly higher temp for more variety
                         "top_p": 0.8,
-                        "max_output_tokens": 1024
+                        "max_output_tokens": 1024,
+                        "response_mime_type": "application/json"
                     }
                 )
-                
-                # Extract JSON from the variations response
-                response_var_text = response_var.text
-                match_var = re.search(r'{.*}', response_var_text, re.DOTALL)
-                if match_var:
-                    json_str_var = match_var.group(0)
-                    try:
-                        variations = json.loads(json_str_var)
-                        
-                        # Format variations output
-                        variations_output = "\n\nADDITIONAL VARIATIONS:\n\n"
-                        variations_output += "Title Variations:\n"
-                        for i, var in enumerate(variations.get("title_variations", []), 1):
-                            variations_output += f"{i}. {var} ({count_characters(var)}/60 characters)\n"
-                        
-                        variations_output += "\nBrand Name Variations:\n"
-                        for i, var in enumerate(variations.get("brand_name_variations", []), 1):
-                            variations_output += f"{i}. {var} ({count_characters(var)}/50 characters)\n"
-                        
-                        # Combine main output with variations
-                        return main_output + variations_output
-                        
-                    except json.JSONDecodeError:
-                        # Return just the main output if we can't parse variations
-                        return main_output + "\n\n(Could not generate variations)"
-                else:
-                    # Return just the main output if we can't extract JSON for variations
-                    return main_output + "\n\n(Could not generate variations)"
-                    
+
+                 # Parse variations JSON
+                try:
+                    response_var_text = response_var.text
+                    # Try stripping markdown again
+                    json_match_var = re.search(r'```json\s*({.*?})\s*```', response_var_text, re.DOTALL | re.IGNORECASE)
+                    if json_match_var:
+                        json_str_var = json_match_var.group(1)
+                    else:
+                        json_str_var = response_var_text.strip()
+
+                    variations = json.loads(json_str_var)
+
+                    # Format variations output, enforcing limits here too
+                    variations_output = "\n\nADDITIONAL VARIATIONS:\n\n"
+                    variations_output += "Title Variations:\n"
+                    for i, var in enumerate(variations.get("title_variations", []), 1):
+                        truncated_var = var[:TITLE_MAX_LEN] # Enforce limit
+                        variations_output += f"{i}. {truncated_var} ({count_characters(truncated_var)}/{TITLE_MAX_LEN} characters)\n"
+
+                    variations_output += "\nBrand Name Variations:\n"
+                    for i, var in enumerate(variations.get("brand_name_variations", []), 1):
+                        truncated_var = var[:BRAND_NAME_MAX_LEN] # Enforce limit
+                        variations_output += f"{i}. {truncated_var} ({count_characters(truncated_var)}/{BRAND_NAME_MAX_LEN} characters)\n"
+
+                    # Combine main output with variations
+                    return main_output + variations_output
+
+                except (json.JSONDecodeError, AttributeError, IndexError) as json_var_err:
+                    print(f"JSON Parsing Error (Variations): {json_var_err}")
+                    print(f"Raw variations response text: {getattr(response_var, 'text', 'N/A')}")
+                     # Check for safety blocks on variations
+                    if response_var.prompt_feedback.block_reason:
+                         return main_output + f"\n\n(Could not generate variations: Blocked - {response_var.prompt_feedback.block_reason})"
+                    return main_output + "\n\n(Could not parse variations response)"
+
+            except genai.types.generation_types.BlockedPromptException as var_block_error:
+                 return main_output + f"\n\n(Variations prompt blocked: {var_block_error})"
             except Exception as var_error:
-                # Return just the main output if variations fail
-                return main_output + f"\n\n(Could not generate variations: {str(var_error)})"
-                
-        except genai.types.generation_types.BlockedPromptException as e:
-            return f"Error: The prompt was blocked by Gemini API safety filters. Please modify your input and try again."
-            
+                # Catch other errors during variation generation
+                print(f"Error generating variations: {var_error}") # Log the error
+                return main_output + f"\n\n(Could not generate variations due to an error)"
+
+        except genai.types.generation_types.BlockedPromptException as block_error:
+            # Catch blocked prompts specifically for better feedback
+            return f"Error: The main prompt was blocked by Gemini API safety filters: {block_error}. Please modify your input and try again."
         except Exception as e:
-            return f"Error generating main listing: {str(e)}"
-            
+             # Catch other potential errors during the main API call
+            print(f"Error during main listing generation: {e}") # Log the error
+            # You might want to check response.candidates[0].finish_reason if available
+            # finish_reason = getattr(response.candidates[0], 'finish_reason', 'UNKNOWN')
+            # safety_ratings = getattr(response.candidates[0].safety_ratings, 'name', 'UNKNOWN')
+            return f"Error generating main listing. Please check logs or try again."
+
     except Exception as e:
-        return f"Error: {str(e)}"
+        # Catch configuration errors or other unexpected issues
+        print(f"General Error: {e}") # Log the error
+        return f"An unexpected error occurred: {str(e)}"
 
-# Create the Gradio interface
+# --- Create the Gradio Interface ---
 def create_interface():
-    with gr.Blocks(title="Amazon Merch on Demand Listing Generator") as app:
+    with gr.Blocks(title="Amazon Merch on Demand Listing Generator", theme=gr.themes.Soft()) as app:
         gr.Markdown("# Amazon Merch on Demand Listing Generator")
-        gr.Markdown("Generate SEO-optimized t-shirt and apparel listings for Amazon Merch on Demand using Gemini 1.5 Pro AI.")
-        
+        gr.Markdown("Generate SEO-optimized t-shirt and apparel listings for Amazon Merch on Demand using Gemini AI. Character limits are enforced.")
+
         with gr.Row():
-            with gr.Column():
-                api_key = gr.Textbox(label="Gemini API Key", placeholder="Enter your Gemini API key", type="password")
-                quote = gr.Textbox(label="Quote/Design/Idea", placeholder="Enter the quote or design idea", value="")
-                niche = gr.Textbox(label="Holiday/Event", placeholder="Enter the holiday or event (e.g., St Patrick's Day)", value="")
-                target = gr.Textbox(label="Target Audience", placeholder="Teacher, Mom, Dad, etc.", value="")
-                keywords = gr.Textbox(label="Target Keywords", placeholder="Enter keywords separated by commas", lines=5, value="")
+            with gr.Column(scale=1):
+                # Recommend using environment variable for API key in real deployments
+                api_key = gr.Textbox(
+                    label="Gemini API Key",
+                    placeholder="Enter your Gemini API key (or leave blank if set as environment variable)",
+                    type="password",
+                    # value=os.getenv("GEMINI_API_KEY", "") # Pre-fill if env var exists
+                )
+                quote = gr.Textbox(label="Quote/Design/Idea", placeholder="e.g., Lucky To Be A Teacher", value="Rainbow with a quote \"Lucky To Be A Teacher\"")
+                niche = gr.Textbox(label="Niche/Holiday/Event", placeholder="e.g., St Patrick's Day", value="St Patricks Day")
+                target = gr.Textbox(label="Target Audience", placeholder="e.g., Teacher, Mom, Dad", value="Teacher, Teacher Mom")
+                keywords = gr.Textbox(
+                    label="Target Keywords (comma-separated)",
+                    placeholder="Enter keywords relevant to your design",
+                    lines=5,
+                    value="lucky, teacher, rainbow, st, patricks, day, t-shirt, patrick's, outfit, design, leopard, cheetah, print, shamrock, clover, perfect, men, women, teachers, celebrate, saint, patrick, special, unique, makes, great, gifts, idea, substitute, love, irish, culture, pattys, holiday, teach, shamrocks, cute, design, awesome, show, students"
+                )
                 submit_btn = gr.Button("Generate Amazon Listing", variant="primary")
-            
-            with gr.Column():
-                status = gr.Textbox(label="Status", value="Ready to generate listing", interactive=False)
-                output = gr.Textbox(label="Generated Amazon Listing", lines=25)
-        
-        def on_submit(api_key, quote, niche, target, keywords):
-            # Update status first
-            yield "Generating listing... Please wait.", output.value
-            
+
+            with gr.Column(scale=2):
+                status = gr.Textbox(label="Status", value="Ready", interactive=False, lines=1)
+                output = gr.Textbox(label="Generated Amazon Listing", lines=25, interactive=True) # Make output selectable
+
+        def on_submit(api_key_input, quote, niche, target, keywords):
+            # Use environment variable if input is blank (optional but good practice)
+            # final_api_key = os.getenv("GEMINI_API_KEY") or api_key_input
+            final_api_key = api_key_input # Keep it simple for now
+
+            if not final_api_key:
+                 # Update status first before returning error message
+                yield "Error: Gemini API Key is required.", ""
+                return # Stop execution
+
+            # Update status to indicate processing
+            yield "Generating listing... This may take a moment.", "Processing..."
+
             # Generate the listing
-            result = generate_amazon_listing(api_key, quote, niche, target, keywords)
-            
-            # Update status with completion message
-            if "Error" in result:
-                yield "Error occurred. See details below.", result
+            result = generate_amazon_listing(final_api_key, quote, niche, target, keywords)
+
+            # Update status and output based on the result
+            if "Error:" in result:
+                yield f"Finished with Error.", result
             else:
                 yield "Listing generated successfully!", result
-        
+
         submit_btn.click(
             fn=on_submit,
             inputs=[api_key, quote, niche, target, keywords],
             outputs=[status, output],
-            show_progress="minimal"
+            show_progress="full" # Show more detailed progress
         )
-        
+
         gr.Markdown("## Example Input")
         gr.Markdown('''
-```
-Quote/Design: Rainbow with a quote "Lucky To Be A Teacher"
-Holiday: St Patricks Day
-Target: Teacher, Teacher Mom
-Keywords: lucky, teacher, rainbow, st, patricks, day, t-shirt, patrick's, outfit, design, leopard, cheetah, print, shamrock, clover, perfect, men, women, teachers, celebrate, saint, patrick, special, unique, makes, great, gifts, idea, substitute, love, irish, culture, pattys, holiday, teach, shamrocks, cute, design, awesome, show, students
-```
+Use the pre-filled example above or enter your own details:
+*   **Quote/Design:** The core text or visual idea on the shirt.
+*   **Niche/Holiday:** The specific event, theme, or category (e.g., Halloween, Fishing, Dog Lover).
+*   **Target Audience:** Who is this shirt for? (e.g., Nurse, Engineer, Grandpa).
+*   **Keywords:** Relevant terms customers might search for.
         ''')
-        
+
         gr.Markdown("""
-        ## Troubleshooting Tips
-        - If you experience timeouts, try using shorter, more specific inputs
-        - Make sure your Gemini API key is valid and has sufficient quota
-        - The app will prioritize showing the main listing first, then try to generate variations
+        ## Notes & Troubleshooting
+        *   **Character Limits:** The app attempts to generate text close to the limits requested in the prompt, but **strictly enforces maximum lengths** by truncating if necessary (Title: 60, Brand: 50, Bullets: 256). The displayed count reflects the final length.
+        *   **API Key:** For security, consider setting your Gemini API Key as an environment variable (`GEMINI_API_KEY`) instead of pasting it directly, especially if deploying publicly.
+        *   **Errors:** If you see errors related to 'BlockedPromptException' or 'Safety', your input might have triggered content filters. Try rephrasing. Other errors might relate to API connectivity or quota.
+        *   **Variations:** The app generates the main listing first, then attempts to generate title/brand variations. Variation generation might fail separately without affecting the main listing.
+        *   **JSON Request:** The app now explicitly requests JSON output from the API (`response_mime_type`).
         """)
-        
+
     return app
 
-# Create and launch the app
+# --- Create and Launch the Gradio App ---
 app = create_interface()
 
-# For deployment on Hugging Face Spaces
+# Launch the app (remove debug=True for production)
 if __name__ == "__main__":
-    app.launch()
+    # Set share=True to get a public link (useful for temporary sharing)
+    app.launch(debug=True)
+    # app.launch() # For deployment (e.g., Hugging Face Spaces)