app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("TuringsSolutions/Phi3LawCaseManagement", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("TuringsSolutions/Phi3LawCaseManagement", trust_remote_code=True)

def predict(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Create Gradio interface
iface = gr.Interface(fn=predict, 
                     inputs="text", 
                     outputs="text",
                     title="Phi3 Law Case Management Model",
                     description="A model to assist with law case management.")

# Launch the Gradio app
iface.launch()