from transformers import pipeline, Conversation
import gradio as gr
import os
from getpass import getpass

message_list = []
response_list = []

def YourCoder_chatbot(message, history):

    python_code_examples = f"""
  ---------------------
  Example 1: Code Snippet
 def calculate_average(numbers):
  total = 0
  for number in numbers:
    total += number
  average = total / len(numbers)
  return average
  Code Review: Consider using the sum() function to calculate the total sum of the numbers
   instead of manually iterating over the list.
   This would make the code more concise and efficient.
  ---------------------
  Example 2: Code Snippet
  def find_largest_number(numbers):
  largest_number = numbers[0]
  for number in numbers:
    if number > largest_number:
      largest_number = number
  return largest_number
  Code Review: Refactor the code using the max() function to find the largest number in the list.
   This would simplify the code and improve its readability.
  ---------------------
  """

    prompt = f"""
  I will provide you with code snippets,
  and you will review them for potential issues and suggest improvements.
   Please focus on providing concise and actionable feedback, highlighting areas
   that could benefit from refactoring, optimization, or bug fixes.
   Your feedback should be constructive and aim to enhance the overall quality and maintainability of the code.
   Please avoid providing explanations for your suggestions unless specifically requested. Instead, focus on clearly identifying areas for improvement and suggesting alternative approaches or solutions.
   Few good examples of Python code output between #### separator:
  ####
  {python_code_examples}
  ####
  Code Snippet is shared below, delimited with triple backticks:
  ```
  {message}
  ```
  """
    response = gr.model
    conversation = chatbot(prompt)
    return conversation[0]['generated_text']

chatbot = gr.ChatInterface(YourCoder_chatbot, title="YourCoder Chatbot", description="Enter piece of code to generate a code review!")
chatbot.launch()