used transformer instead of openai

app.py

@@ -6,21 +6,39 @@
 #     return generator(f"Write a blog on: {topic}", max_length=200)[0]["generated_text"]
 
 
+# from transformers import pipeline
+# import gradio as gr
+
+# # Load the model
+# generator = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
+
+# # Define your function
+# def generate_text(prompt):
+#     result = generator(prompt, max_length=100, num_return_sequences=1, do_sample=True, 
+#     temperature=0.7, 
+#     top_p=0.9,)
+#     return result[0]["generated_text"]
+
+# # Create Gradio interface
+# iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Text Generator with GPT-2")
+
+# # ✅ This line is required to actually launch the app on Hugging Face Spaces
+# iface.launch()
+
+
+
 from transformers import pipeline
 import gradio as gr
 
-# Load the model
 generator = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
 
-# Define your function
-def generate_text(prompt):
-    result = generator(prompt, max_length=100, num_return_sequences=1, do_sample=True, 
-    temperature=0.7, 
-    top_p=0.9,)
-    return result[0]["generated_text"]
-
-# Create Gradio interface
-iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Text Generator with GPT-2")
+def generate_blog(topic):
+    prompt = f"""
+    Write a detailed and engaging blog post about "{topic}".
+    Include an introduction, 2–3 subheadings with paragraphs, and a conclusion.
+    Make it informative and conversational.
+    """
+    result = generator(prompt, max_length=700, do_sample=True, temperature=0.7, top_p=0.9)
+    return result[0]['generated_text']
 
-# ✅ This line is required to actually launch the app on Hugging Face Spaces
-iface.launch()
+gr.Interface(fn=generate_blog, inputs="text", outputs="text", title="AI Blog Writer").launch()