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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load the model and tokenizer
model_path = 'Neo111x/falcon3-decompiler-3b-v1.5' # V1.5 Model
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16)
# Define the inference function
def generate_response(input_text, temperature, top_k, top_p, progress=gr.Progress()):
progress(0, "Processing input...")
before = f"# This is the assembly code:\n"#prompt
after = "\n# What is the source code?\n"#prompt
input_func = before+input_text.strip()+after
inputs = tokenizer(input_func, return_tensors="pt")
progress(0.3, "Running inference...")
outputs = model.generate(
**inputs,
max_length=512, # Adjust this if needed
)
# do_sample=True,
# top_k=int(top_k),
# top_p=float(top_p),
# temperature=float(temperature)
progress(0.8, "Decoding response...")
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
progress(1, "Done!")
# Split the response into assembly and source code (if applicable)
if "# This is the assembly code:" in response:
parts = response.split("# What is the source code?")
assembly_code = parts[0].replace("# This is the assembly code:", "").strip()
source_code = parts[1].strip() if len(parts) > 1 else ""
return f"```c\n{assembly_code}\n```", f"```c\n{source_code}\n```"
else:
return "No assembly code found.", "No source code found."
# Create a Gradio interface with sliders
interface = gr.Interface(
fn=generate_response,
inputs=[
gr.Textbox(lines=5, placeholder="Enter assembly code here...", label="Input Assembly Code"),
gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(1, 100, value=50, step=1, label="Top-k"),
gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
],
outputs=[
gr.Textbox(label="Assembly Code"),
gr.Textbox(label="Source Code")
],
title="Falcon decompiler Interactive Demo",
description="Adjust the sliders for temperature, top-k, and top-p to customize the model's response."
)
# Launch the Gradio app
interface.launch()
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