Update app.py

app.py

@@ -1,49 +1,58 @@
 import gradio as gr
 from transformers import pipeline
 
-# Initialize the text generation pipeline
-generator = pipeline('text-generation', model='gpt2')
+# Load the powerful open-source model
+generator = pipeline(
+    "text-generation",
+    model="mistralai/Mistral-7B-Instruct-v0.1",
+    device_map="auto"  # If running locally with GPU; otherwise remove
+)
+
+# Define max length recommendations
+max_lengths = {
+    "social media post": 280,
+    "email newsletter": 800,
+    "product description": 600,
+    "ad copy": 400
+}
 
-def generate_marketing_text(prompt, content_type, max_length=150, temperature=0.7):
+def generate_marketing_text(prompt, content_type, _, temperature=0.7):
     """
-    Generate marketing text based on the prompt and content type using GPT-2
+    Generate marketing text using Mistral 7B based on topic and content type.
     """
-    # Set a reasonable max_length to avoid timeouts
-    if max_length > 250:
-        max_length = 250
-    
-    # Enhance the prompt based on content type
-    enhanced_prompt = f"Write a {content_type} about {prompt}. "
-    
-    # Generate text
+    # Clean and enhance prompt
+    enhanced_prompt = f"Write a {content_type} for this product: {prompt}\nMake it engaging, professional, and persuasive."
+
+    # Determine proper max_length for the type
+    max_length = max_lengths.get(content_type, 400)
+
+    # Generate the text
     result = generator(
-        enhanced_prompt, 
-        max_length=max_length, 
-        temperature=temperature, 
+        enhanced_prompt,
+        max_length=max_length,
+        temperature=temperature,
         do_sample=True,
         pad_token_id=50256
     )
-    
-    # Return the generated text
+
     return result[0]['generated_text']
 
-# Create Gradio interface
+# Gradio UI
 demo = gr.Interface(
     fn=generate_marketing_text,
     inputs=[
-        gr.Textbox(lines=3, placeholder="Enter your topic here...", label="Topic"),
+        gr.Textbox(lines=3, placeholder="Enter your product or topic here...", label="Topic"),
         gr.Radio(
             ["social media post", "email newsletter", "product description", "ad copy"],
             label="Content Type",
             value="social media post"
         ),
-        gr.Slider(minimum=50, maximum=250, value=150, step=10, label="Maximum Length"),
+        gr.Slider(minimum=50, maximum=800, value=280, step=10, label="(Disabled) Max Length", interactive=False),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Creativity (Temperature)")
     ],
     outputs=gr.Textbox(lines=10, label="Generated Marketing Content"),
     title="AdGenAI - Marketing Content Generator",
-    description="Enter a topic and select content type to generate marketing content using AI."
+    description="Enter a topic and select a content type to generate persuasive, high-quality marketing content using Mistral 7B."
 )
 
-# Launch the app
-demo.launch()
+demo.launch()