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from huggingface_hub import InferenceClient
import gradio as gr
import re
# Define regex patterns for comments
java_single_line_comment_regex = r"\/\/.*"
java_multiline_comment_regex = r"\/\*(?:[^*]|\*(?!\/))*\*\/"
kotlin_single_line_comment_regex = r"\/\/.*"
kotlin_multiline_comment_regex = r"\/\*(?:[^*]|\*(?!\/))*\*\/"
def remove_comments(content,file_type):
"""
Opens a Java or Kotlin file, removes comments, and saves the changes.
Args:
file_path: The path to the Java or Kotlin file.
"""
# Determine file type based on extension
if file_type == "java":
pattern = java_single_line_comment_regex + "|" + java_multiline_comment_regex
elif file_type == "kotlin":
pattern = kotlin_single_line_comment_regex + "|" + kotlin_multiline_comment_regex
else:
raise ValueError(f"Unsupported file type: {file_type}")
# Remove comments using regex
clean_content = re.sub(pattern, "", content, )
return clean_content
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
def format_prompt(message, history):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt = f"[INST] {message} [/INST]"
return prompt
def generate(
prompt, history, temperature=0.2, max_new_tokens=16392, top_p=0.95, repetition_penalty=1.0,
):
temperature = float(0)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=42,
)
prompt = f"""Translate the given Kotlin code to Java, adhering to the following constraints:
Preserve the original names of classes, fields, and methods without renaming.
{remove_comments(
content=prompt,file_type='kotlin'
).strip()}"""
formatted_prompt = format_prompt(prompt, history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
yield output
return output
mychatbot = gr.Chatbot(
avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
demo = gr.ChatInterface(fn=generate,
chatbot=mychatbot,
title="Mixtral 8x7b Chat For Kotlin Translation",
retry_btn=None,
undo_btn=None
)
demo.queue().launch(show_api=False) |