try3 app.py

app.py

@@ -1,10 +1,9 @@
 import gradio as gr
 from transformers import pipeline
 
-# Use an instruction-following model for better results
-generator = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
+# Use a public model (works without login)
+generator = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
 
-# Caption generation function
 def generate_caption(user_input):
     prompt = f"""You are an expert Instagram caption writer.
 Given this input, craft one stylish, short, and emotionally resonant caption (max 20 words).
@@ -16,12 +15,11 @@ Caption:"""
     response = generator(prompt, max_new_tokens=50, do_sample=True, temperature=0.8)
     return response[0]['generated_text'].split("Caption:")[-1].strip()
 
-# Example input to display inside the textbox
-example_prompt = """Vibe: chill  
-Photo: me and my dog sitting on a picnic blanket in a sunny park  
-Captions I like: 'sunny side up', 'pure bliss'"""
+# Example to show in UI
+example_prompt = """Vibe: confident and stylish  
+Photo: me stepping out of a cab in heels at night in NYC  
+Captions I like: 'main character energy', 'own the moment'"""
 
-# Gradio interface
 iface = gr.Interface(
     fn=generate_caption,
     inputs=gr.Textbox(
@@ -35,4 +33,4 @@ iface = gr.Interface(
     description="Tell us your vibe and we’ll craft a personalized caption for your Instagram post or story."
 )
 
-iface.launch()
+iface.launch()