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import gradio as gr
from huggingface_hub import InferenceClient
from transformers import AutoTokenizer
import torch
# Initialize model and tokenizer
model_name = "erikbeltran/pydiff"
client = InferenceClient(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
def format_diff_response(response):
"""Format the response to look like a diff output"""
lines = response.split('\n')
formatted = []
for line in lines:
if line.startswith('+'):
formatted.append(f'<span style="color: green">{line}</span>')
elif line.startswith('-'):
formatted.append(f'<span style="color: red">{line}</span>')
else:
formatted.append(line)
return '<br>'.join(formatted)
def respond(request, file_content, system_message, max_tokens, temperature, top_p):
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": f"""<request>{request}</request>
<file>
{file_content}
</file>"""}
]
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
# Format as diff and yield
yield format_diff_response(response)
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Code Review Assistant")
with gr.Row():
with gr.Column():
request_input = gr.Textbox(
label="Request",
placeholder="Enter your request (e.g., 'fix the function', 'add error handling')",
lines=3
)
file_input = gr.Code(
label="File Content",
language="python",
lines=10
)
with gr.Column():
output = gr.HTML(label="Diff Output")
with gr.Accordion("Advanced Settings", open=False):
system_msg = gr.Textbox(
value="You are a code review assistant. Analyze the code and provide suggestions in diff format. Use '+' for additions and '-' for deletions.",
label="System Message"
)
max_tokens = gr.Slider(
minimum=1,
maximum=2048,
value=512,
step=1,
label="Max Tokens"
)
temperature = gr.Slider(
minimum=0.1,
maximum=4.0,
value=0.7,
step=0.1,
label="Temperature"
)
top_p = gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p"
)
submit_btn = gr.Button("Submit")
submit_btn.click(
fn=respond,
inputs=[
request_input,
file_input,
system_msg,
max_tokens,
temperature,
top_p
],
outputs=output
)
if __name__ == "__main__":
demo.launch() |