Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load the model and tokenizer
+model_name = "microsoft/Phi-3-mini-4k-instruct-gguf"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
+
+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:")
+    
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output = model.generate(**inputs, max_length=500)
+    letter_content = tokenizer.decode(output[0], skip_special_tokens=True)
+    
+    return letter_content
+
+# 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()