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| import streamlit as st | |
| import torch | |
| from transformers import pipeline | |
| import csv | |
| import re | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| # Define a prompt template for Magicoder with placeholders for instruction and response. | |
| MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions. | |
| @@ Instruction | |
| {instruction} | |
| @@ Response | |
| """ | |
| # Load Magicoder model and apply dynamic quantization | |
| generator = pipeline( | |
| model="ise-uiuc/Magicoder-S-DS-6.7B", | |
| task="text-generation", | |
| ) | |
| quantized_generator = torch.quantization.quantize_dynamic( | |
| generator.model, | |
| {torch.nn.Linear}, | |
| dtype=torch.qint8 | |
| ) | |
| generator.model = quantized_generator | |
| # Function to generate response | |
| def generate_response(instruction): | |
| prompt = MAGICODER_PROMPT.format(instruction=instruction) | |
| result = generator(prompt, max_length=2048, num_return_sequences=1, temperature=0.0) | |
| response = result[0]["generated_text"] | |
| response_start_index = response.find("@@ Response") + len("@@ Response") | |
| response = response[response_start_index:].strip() | |
| return response | |
| # Function to append data to a CSV file | |
| def save_to_csv(data, filename): | |
| with open(filename, 'a', newline='') as csvfile: | |
| writer = csv.writer(csvfile) | |
| writer.writerow(data) | |
| # Streamlit app | |
| def main(): | |
| st.title("Magicoder Assistant") | |
| instruction = st.text_area("Enter your instruction here:") | |
| if st.button("Generate Response"): | |
| generated_response = generate_response(instruction) | |
| st.text("Generated response:") | |
| st.text(generated_response) | |
| correct_output = st.radio("Is the generated output correct?", ("Yes", "No")) | |
| if correct_output.lower() == 'yes': | |
| feedback = st.text_input("Do you want to provide any feedback?") | |
| save_to_csv(["Correct", feedback], 'output_ratings.csv') | |
| else: | |
| correct_code = st.text_area("Please enter the correct code:") | |
| feedback = st.text_input("Any other feedback you want to provide:") | |
| save_to_csv(["Incorrect", feedback, correct_code], 'output_ratings.csv') | |
| if __name__ == "__main__": | |
| main() | |