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# git clone https://huggingface.co/spaces/Pipatpong/VCM_Demo
import gradio as gr
import re
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
checkpoint = "Pipatpong/vcm_santa"
device = "cuda" if torch.cuda.is_available() else "CPU"
quantization_config = BitsAndBytesConfig(load_in_8bit_fp32_cpu_offload=True)
tokenizer = AutoTokenizer.from_pretrained(checkpoint, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(checkpoint, trust_remote_code=True, low_cpu_mem_usage=True, load_in_8bit=True, device_map="auto", quantization_config=quantization_config)
def generate(text, max_length, num_return_sequences=1):
inputs = tokenizer.encode(text, padding=False, add_special_tokens=False, return_tensors="pt")
outputs = model.generate(inputs, max_length=max_length, num_return_sequences=num_return_sequences)
gen_text = "Assignment : " + tokenizer.decode(outputs[0])
if gen_text.count("#") > 2:
split_text = gen_text.split("#", 2)
return split_text[0] + "#" + split_text[1]
else:
return gen_text
def extract_functions(text):
function_pattern = r'def\s+(\w+)\((.*?)\):([\s\S]*?)return\s+(.*?)\n'
functions = re.findall(function_pattern, text, flags=re.MULTILINE)
extracted_text = []
for function in functions:
function_name = function[0]
parameters = function[1]
function_body = function[2]
return_statement = function[3]
extracted_function = f"def {function_name}({parameters}):\n # Code Here\n return {return_statement}\n"
extracted_text.append(extracted_function)
return extracted_text
def assignment(text, max_length):
extracted_functions = extract_functions(generate(text, max_length))
for function in extracted_functions:
return function
demo = gr.Blocks()
with demo:
with gr.Row():
with gr.Column():
inputs=[gr.inputs.Textbox(placeholder="Type here and click the button for the desired action.", label="Prompt"),
gr.Slider(30, 150, step=10, label="Max_length"),
]
outputs=gr.outputs.Textbox(label="Generated Text")
with gr.Row():
b1 = gr.Button("Assignment")
b2 = gr.Button("Answers")
b1.click(assignment, inputs, outputs)
b2.click(generate, inputs, outputs)
examples = [
["generate a python for sum number"],
["generate a python function to find max min element of list"],
["generate a python function to find minimum of two numbers with test case"],
]
gr.Examples(examples=examples, inputs=inputs, cache_examples=False)
demo.launch(share=False, debug=False) |