AMZ-Listing-Pro / app.py
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import gradio as gr
import google.generativeai as genai
import re
import json
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}"
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."""
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.
IMPORTANT RULES FOR BULLET POINTS:
- Bullet points must be between 240-256 characters
- 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"
- 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",
"suggested_keywords": "5 additional keywords separated by commas"
}}
REMINDER: Make sure to count the characters carefully. Title should be EXACTLY 60 characters. Bullet points should be between 240-256 characters."""
return combined_prompt
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.
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"
],
"brand_name_variations": [
"Brand name variation 1 (34-50 characters)",
"Brand name variation 2 (34-50 characters)",
"Brand name variation 3 (34-50 characters)"
]
}}
REMINDER: Make sure each title is EXACTLY 60 characters. Count carefully!"""
return combined_prompt
def generate_amazon_listing(api_key, quote, niche, target, keywords):
"""Generate Amazon listing using Gemini API."""
# 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
genai.configure(api_key=api_key)
# Create model with optimized settings
model = genai.GenerativeModel(
'gemini-1.5-pro',
generation_config={
"temperature": 0.3,
"top_p": 0.8,
"max_output_tokens": 1024, # Reduced for faster response
}
)
# Generate the main listing
prompt = generate_prompt(quote, niche, target, keywords)
try:
# First try to get just the main listing for faster response
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)
try:
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", "")
bullet2 = result.get("bullet_point_2", "")
#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."
# Check for generic content in bullet points
generic_phrases = ["premium quality", "high-quality materials", "soft feel", "long-lasting wear",
"comfortable and stylish", "perfect gift", "great gift"]
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
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")
)
# Now try to get variations in a separate call
try:
variations_prompt = generate_multiple_variations_prompt(quote, niche, target, keywords)
response_var = model.generate_content(
variations_prompt,
generation_config={
"temperature": 0.4,
"top_p": 0.8,
"max_output_tokens": 1024
}
)
# 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)"
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."
except Exception as e:
return f"Error generating main listing: {str(e)}"
except Exception as e:
return f"Error: {str(e)}"
# Create the Gradio interface
def create_interface():
with gr.Blocks(title="Amazon Merch on Demand Listing Generator") 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.")
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="")
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
# 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
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"
)
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
```
''')
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
""")
return app
# Create and launch the app
app = create_interface()
# For deployment on Hugging Face Spaces
if __name__ == "__main__":
app.launch()