try1 app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load a small language model for text generation (works on CPU)
+generator = pipeline("text-generation", model="EleutherAI/gpt-neo-125M")
+
+# Prompt engineering function
+def generate_caption(user_input):
+    prompt = f"""You are an expert Instagram caption writer.
+Create a stylish and catchy caption based on the following input:
+{user_input}
+Caption:"""
+    response = generator(prompt, max_length=40, do_sample=True, temperature=0.9)
+    return response[0]['generated_text'].split("Caption:")[-1].strip()
+
+# Gradio interface
+iface = gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Textbox(label="Describe the photo, vibe, and example captions you like", lines=5, placeholder="e.g., Vibe: chill, Photo: girl by the beach, Captions I like: 'based on a true story'"),
+    outputs=gr.Textbox(label="Generated Instagram Caption"),
+    title="📸 Caption Crafter",
+    description="Tell us your vibe and we'll craft a personalized caption for your Instagram post or story."
+)
+
+iface.launch()