Create app.py

app.py

@@ -0,0 +1,60 @@
+
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline 
+
+torch.random.manual_seed(0) 
+model = AutoModelForCausalLM.from_pretrained( 
+    "microsoft/Phi-3-mini-4k-instruct",  
+    device_map="cuda",  
+    torch_dtype="auto",  
+    trust_remote_code=True,  
+) 
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") 
+
+def generate_letter(date, time, purpose, place, sender, receiver):
+    prompt = (f"Write a formal letter with the following details:\n"
+              f"Date: {date}\nTime: {time}\nPurpose: {purpose}\nPlace: {place}\n"
+              f"Sender: {sender}\nReceiver: {receiver}\n\nLetter:")
+
+    messages = [ 
+        {"role": "system", "content": "You are a helpful AI assistant."}, 
+        {"role": "user", "content": f"{prompt}"}, 
+    ] 
+    
+    pipe = pipeline( 
+    "text-generation", 
+    model=model, 
+    tokenizer=tokenizer, 
+    ) 
+    
+    generation_args = { 
+        "max_new_tokens": 500, 
+        "return_full_text": False, 
+        "temperature": 0.0, 
+        "do_sample": False, 
+    } 
+    
+    output = pipe(messages, **generation_args) 
+    return output[0]['generated_text']
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_letter,
+    inputs=[
+        gr.Textbox(label="Date"),
+        gr.Textbox(label="Time"),
+        gr.Textbox(label="Purpose"),
+        gr.Textbox(label="Place"),
+        gr.Textbox(label="Sender"),
+        gr.Textbox(label="Receiver"),
+    ],
+    outputs=gr.Textbox(label="Generated Letter"),
+    title="Letter Generator",
+    description="Enter the details and generate a formal letter automatically."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()
+