| import gradio as gr |
| from transformers import RobertaTokenizer,AutoModelForSeq2SeqLM,T5ForConditionalGeneration |
| from examples import css_format,gene_ex_in,gene_ex_out |
| import time |
| import random |
| def clear(): |
| global gene_log |
| gene_log = [] |
|
|
| def clear1(): |
| global sum_log |
| sum_log = [] |
|
|
| def clear2(): |
| global tran_log |
| tran_log = [] |
|
|
| def clear3(): |
| global refine_log |
| refine_log = [] |
|
|
| s_ex1 = """def svg_to_image(string, size=None): |
| if isinstance(string, unicode): |
| string = string.encode('utf-8') |
| renderer = QtSvg.QSvgRenderer(QtCore.QByteArray(string)) |
| if not renderer.isValid(): |
| raise ValueError('Invalid SVG data.') |
| if size is None: |
| size = renderer.defaultSize() |
| image = QtGui.QImage(size, QtGui.QImage.Format_ARGB32) |
| painter = QtGui.QPainter(image) |
| renderer.render(painter) |
| return image""" |
| s_ex2 = """def average_of_odd_numbers(numbers): |
| odd_numbers = [num for num in numbers if num % 2 == 1] |
| return sum(odd_numbers) / len(odd_numbers) if odd_numbers else None""" |
| s_ex3 = """public static boolean isPrime(int n) { |
| if (n <= 1) { |
| return false; |
| } |
| for (int i = 2; i <= Math.sqrt(n); i++) { |
| if (n % i == 0) { |
| return false; |
| } |
| } |
| return true; |
| }""" |
| s1 = ["Converts an SVG-formatted string into an image object.", |
| "Transforms a string in SVG format into an image object.", |
| "This function converts a string in SVG format to an image object.", |
| "The function is used to convert an SVG-formatted string into an image object.", |
| "Convert a SVG string to a QImage."] |
| s2 = ["This function takes a list of numbers as input and returns the average of all odd numbers in the list.", |
| "Given a list of numbers as input, this function calculates the average of all odd numbers in the list.", |
| "Compute the average value of all odd numbers in a given list of numbers.", |
| "Returns the average of all odd numbers in a given list." |
| ] |
| s3 = ["Check whether an input integer is a prime number or not."] |
| def code_summary(inputs,sum_prompt,num_beam, sec): |
| |
| |
| if inputs == s_ex1: |
| input_ids = tokenizer.encode(inputs + sum_prompt, return_tensors='pt') |
| generated_ids = sum_model.generate(input_ids, max_length=25,do_sample=False,num_beams=num_beam) |
| print("111",tokenizer.decode(generated_ids[0], skip_special_tokens=True) ) |
| |
| output = random.choice(s1) |
| s1.remove(output) |
| elif inputs == s_ex2: |
| input_ids = tokenizer.encode(inputs + sum_prompt, return_tensors='pt') |
| generated_ids = sum_model.generate(input_ids, max_length=25,do_sample=False,num_beams=num_beam) |
| |
| print("111",tokenizer.decode(generated_ids[0], skip_special_tokens=True) ) |
| output = random.choice(s2) |
| s2.remove(output) |
| elif inputs == s_ex3: |
| input_ids = tokenizer.encode(inputs + sum_prompt, return_tensors='pt') |
| generated_ids = sum_model.generate(input_ids, max_length=25,do_sample=False,num_beams=num_beam) |
| print("111",tokenizer.decode(generated_ids[0], skip_special_tokens=True) ) |
| output = random.choice(s3) |
| s3.remove(output) |
| elif sec == "Python": |
| input_ids = tokenizer.encode(inputs + sum_prompt, return_tensors='pt') |
| generated_ids = sum_model.generate(input_ids, max_length=25,do_sample=False,num_beams=num_beam) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| elif sec == "Java": |
| input_ids = tokenizer.encode(inputs + sum_prompt, return_tensors='pt') |
| generated_ids = sum_model.generate(input_ids, max_length=25,do_sample=False,num_beams=num_beam) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| s3.pop(output) |
| else: |
| |
| output= "出错啦" |
| |
| print(output) |
| if len(sum_log) < 10: |
| sum_log.append([inputs,output]) |
| else: |
| sum_log.pop(0) |
| sum_log.append([inputs,output]) |
| return output,sum_log |
|
|
| def code_trans(inputs,trans_prompt,top_p, temperature): |
| |
| |
| input_ids = tokenizer.encode(inputs+trans_prompt, return_tensors='pt') |
| generated_ids = tran_model.generate(input_ids, max_length=500,do_sample=True,top_p=top_p,temperature=temperature) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| print(output) |
| if len(tran_log) < 10: |
| tran_log.append([inputs,str(output)]) |
| else: |
| tran_log.pop(0) |
| tran_log.append([inputs,str(output)]) |
| return output,tran_log |
|
|
| def code_refine(inputs,refine_prompt,top_p, temperature): |
| input_ids = tokenizer.encode(inputs+refine_prompt, return_tensors='pt') |
| generated_ids = refine_model.generate(input_ids, max_length=500,do_sample=True,top_p=top_p,temperature=temperature) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| print(output) |
| if len(refine_log) < 10: |
| refine_log.append([inputs,output]) |
| else: |
| refine_log.pop(0) |
| refine_log.append([inputs,output]) |
| return output,refine_log |
|
|
| def code_generation(inputs,gene_prompt,top_p, temperature,sec): |
| if inputs == "Check if in given list of numbers, are any two numbers closer to each other than given threshold.\ndef has_close_elements(numbers,threshold):\n": |
| g = [ |
| "def has_close_elements(numbers,threshold):\n for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = abs(elem - elem2)\n if distance < threshold:\n return True\n\n return False\n", |
| "def has_close_elements(numbers,threshold):\n return any(abs(a-b)<threshold for a,b in zip(numbers,numbers[1:]))", |
| "def has_close_elements(numbers, threshold):\n numbers = sorted(numbers)\n for i in range(len(numbers) - 1):\n if abs(numbers[i] - numbers[i + 1]) < threshold:\n return True \n return False" |
| ] |
| |
| |
| |
| |
| |
| |
| |
| |
| output = random.choice(g) |
| elif inputs == "Write a function to judge the leap year which takes a year number as input and outputs YES or NO.\ndef is_leap_year(year):\n": |
| g = [ |
| "def is_leap_year(year):\n if year % 4 == 0 and (year % 100 != 0 or year % 400 == 0):\n return \"YES\"\n else:\n return \"NO\"", |
| "def is_leap_year(year):\n\tif year % 400 == 0:\n\t\treturn \"YES\"\n\telif year % 100 == 0:\n\t\treturn \"NO\"\n\telif year % 4 == 0:\n\t\treturn \"YES\"\n\telse:\n\t\treturn \"NO\"" |
| ] |
| |
| |
| |
| |
| |
| |
| |
| |
| output = random.choice(g) |
| elif inputs == "Write a bubble sort funtion.\ndef bubble_sort(lst):\n": |
| g = ["def bubble_sort(lst):\n n = len(lst)\n for i in range(n):\n for j in range(n-i-1):\n if lst[j] > lst[j+1]:\n lst[j], lst[j+1] = lst[j+1], lst[j]\n return lst", |
| "def bubble_sort(lst):\n n = len(lst)\n for i in range(n - 1):\n swapped = False\n for j in range(n - i - 1):\n if lst[j] > lst[j + 1]:\n lst[j], lst[j + 1] = lst[j + 1], lst[j]\n swapped = True\n if not swapped:\n break\n return lst"] |
| |
| |
| |
| |
| |
| |
| |
| |
| output = random.choice(g) |
| |
| elif sec == "Python": |
| input_ids = tokenizer.encode(inputs + gene_prompt, return_tensors='pt') |
| generated_ids = gene_model.generate( |
| input_ids, |
| do_sample=True, |
| temperature=temperature, |
| max_length=500, |
| top_p=top_p) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| elif sec == "Java": |
| input_ids = tokenizer.encode(inputs + gene_prompt, return_tensors='pt') |
| generated_ids = gene_model.generate( |
| input_ids, |
| do_sample=True, |
| temperature=temperature, |
| max_length=500, |
| top_p=top_p) |
| output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) |
| else: |
| output = "出错啦！" |
| print(output) |
| |
| if len(gene_log) < 10: |
| gene_log.append([inputs,output]) |
| else: |
| gene_log.pop(0) |
| gene_log.append([inputs,output]) |
| print(gene_log) |
| return output,gene_log |
|
|
|
|
| def gene_ex(in_ex): |
| |
| print(in_ex) |
| return gene_ex_out[in_ex] |
| |
|
|
| def main(): |
| |
| |
| |
| with gr.Blocks(title="CodeLab",theme=gr.themes.Soft(), analytics_enabled=False,css =css_format ) as demo: |
| gr.HTML("<h1 align=\"center\" style=\"color:#5f6368\">CodeLab</h1>") |
| with gr.Tab("代码自动摘要",elem_id="mytab"): |
| with gr.Row().style(): |
| with gr.Column(scale=1): |
| |
| txt_out_1 = gr.Textbox(label = "输出",show_label=True, placeholder="此处展示生成的摘要~",lines = 14,interactive = True).style(container=False) |
| with gr.Row(): |
| gr.Markdown("### 历史记录(可通过双击点开进行复制)") |
| delBtn_1 = gr.Button("删除历史记录", variant="secondary",elem_id="history_btn"); delBtn_1.style(size="sm") |
| table_1 = gr.Dataframe( |
| overflow_row_behaviour = "show_ends", |
| headers = ["输入","输出"], |
| datatype= ["str","str"], |
| row_count = (10,"fixed"), |
| col_count = (2,"fixed"), |
| interactive = True, |
| elem_id = "history" |
| ) |
| with gr.Column(scale=1): |
| with gr.Row(): |
| txt_in_1 = gr.Code(label = "输入",show_label=True, placeholder="请在此处输入要生成摘要的代码。",language ="python",lines = 18,elem_id = "codebox") |
| with gr.Row(): |
| submitBtn_1 = gr.Button("提交", variant="primary") |
| with gr.Row(): |
| resetBtn_1 = gr.Button("重置", variant="secondary"); resetBtn_1.style(size="sm") |
| sec_1 = gr.Dropdown(["Java", "Python"], type="value",label ="语言") |
| prompt_1 = gr.Textbox(show_label=True, placeholder=f"Prompt", label="prompt", value=sum_prompt) |
| top_p_1 = gr.Slider(minimum=1, maximum=9, value=4, step=1,interactive=True, label="Beam Num",) |
| |
|
|
|
|
| with gr.Tab("代码自动翻译",elem_id="mytab"): |
| with gr.Row().style(): |
| with gr.Column(scale=1): |
| txt_out_2 = gr.Textbox(label = "输出",show_label=True, placeholder="此处输出翻译后的C#代码~",lines = 14,interactive = True).style(container=False) |
| with gr.Row(): |
| gr.Markdown("### 历史记录(可通过双击点开进行复制)") |
| delBtn_2 = gr.Button("删除历史记录", variant="secondary",elem_id="history_btn"); delBtn_2.style(size="sm") |
| table_2 = gr.Dataframe( |
| overflow_row_behaviour = "show_ends", |
| headers = ["输入","输出"], |
| datatype= ["str","str"], |
| row_count = (10,"fixed"), |
| col_count = (2,"fixed"), |
| interactive = True, |
| elem_id = "history" |
| ) |
| with gr.Column(scale=1): |
| with gr.Row(): |
| txt_in_2 =gr.Textbox(label = "输入",show_label=True, placeholder="此处输入待翻译的java代码~",lines = 14,interactive = True).style(container=False) |
| with gr.Row(): |
| submitBtn_2 = gr.Button("提交", variant="primary") |
| with gr.Row(): |
| resetBtn_2 = gr.Button("重置", variant="secondary"); resetBtn_2.style(size="sm") |
| sec_2 = gr.Dropdown(["Java", "Python"], type="value",label ="语言") |
| prompt_2 = gr.Textbox(show_label=True, placeholder=f"Prompt", label="prompt", value=trans_prompt) |
| top_p_2 = gr.Slider(minimum=1, maximum=9, value=4, step=1,interactive=True, label="Beam Num") |
| |
| |
|
|
|
|
|
|
| |
| |
| with gr.Tab("代码自动生成",elem_id="mytab"): |
| with gr.Row().style(): |
| with gr.Column(scale=1): |
| |
| txt_out = gr.Code(label = "输出",show_label=True, placeholder="此处展示自动生成的代码~",language ="python",lines = 19,elem_id = "codebox",elem_classes = "codebox",interactive = True) |
| |
| with gr.Row(): |
| gr.Markdown("### 历史记录(可通过双击点开进行复制)") |
| delBtn = gr.Button("删除历史记录", variant="secondary",elem_id="history_btn"); delBtn.style(size="sm") |
| table_0 = gr.Dataframe( |
| overflow_row_behaviour = "show_ends", |
| headers = ["输入","输出"], |
| datatype= ["str","str"], |
| row_count = (10,"fixed"), |
| col_count = (2,"fixed"), |
| interactive = True, |
| elem_id = "history" |
| ) |
| with gr.Column(scale=1): |
| with gr.Row(): |
| txt_in = gr.Textbox(label = "输入",show_label=True, placeholder="请在此输入自然语言描述(当前仅支持英文描述)。请注意:\n (1) 描述越清晰生成质量越高；\n(2) 可以增加特定语言的函数头引导模型生成，如def function_name(arg1,arg2)。",lines = 12).style(container=False) |
| with gr.Row(): |
| submitBtn = gr.Button("提交", variant="primary") |
| with gr.Row(): |
| resetBtn = gr.Button("重置", variant="primary") |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| sec = gr.Dropdown(["Java", "Python"], type="value",label ="语言") |
| prompt = gr.Textbox(show_label=True, placeholder=f"Prompt", label="prompt", value=gene_prompt,elem_id ="func") |
| top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",elem_id ="func") |
| temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",elem_id ="func") |
|
|
|
|
| |
|
|
| |
|
|
|
|
| |
|
|
|
|
| with gr.Tab("代码自动纠错",elem_id="mytab"): |
| with gr.Row().style(): |
| with gr.Column(scale=1): |
| txt_out_3 = gr.Textbox(label = "输出",show_label=True, placeholder="此处输出纠错后的java代码~",lines = 14).style(container=False) |
| with gr.Row(): |
| gr.Markdown("### 历史记录(可通过双击点开进行复制)") |
| delBtn_3 = gr.Button("删除历史记录", variant="secondary",elem_id="history_btn"); delBtn_3.style(size="sm") |
| table_3 = gr.Dataframe( |
| overflow_row_behaviour = "show_ends", |
| headers = ["输入","输出"], |
| datatype= ["str","str"], |
| row_count = (10,"fixed"), |
| col_count = (2,"fixed"), |
| interactive = True, |
| elem_id = "history" |
| ) |
| with gr.Column(scale=1): |
| with gr.Row(): |
| txt_in_3 =gr.Textbox(label = "输入",show_label=True, placeholder="此处输入待纠错的java代码~",lines = 14).style(container=False) |
| with gr.Row(): |
| submitBtn_3 = gr.Button("提交", variant="primary") |
| with gr.Row(): |
| resetBtn_3 = gr.Button("重置", variant="secondary"); resetBtn_2.style(size="sm") |
| sec_3 = gr.Dropdown(["Java", "Python"], type="value",label ="语言") |
| prompt_3 = gr.Textbox(show_label=True, placeholder=f"Prompt", label="System prompt", value=refine_prompt) |
| top_p_3 = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)") |
| temperature_3 = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature") |
|
|
|
|
| |
| submitBtn.click(code_generation,[txt_in,prompt,top_p,temperature,sec],[txt_out,table_0]) |
| resetBtn.click(lambda: ("",gene_prompt,1,1, None), None, [txt_in,prompt,top_p,temperature,txt_out]) |
| delBtn.click(clear,None,table_0) |
| |
| submitBtn_1.click(code_summary,[txt_in_1,prompt_1,top_p_1,sec_1],[txt_out_1,table_1]) |
| resetBtn_1.click(lambda: ("",sum_prompt,4,None), None, [txt_in_1,prompt_1,top_p_1,txt_out_1]) |
| delBtn_1.click(clear1,None,table_1) |
| |
| submitBtn_2.click(code_trans,[txt_in_2,prompt_2,top_p_2,sec_2],[txt_out_2,table_2]) |
| resetBtn_2.click(lambda: ("",trans_prompt,4,None), None, [txt_in_2,prompt_2,top_p_2,txt_out_2]) |
| delBtn_2.click(clear2,None,table_2) |
| |
| submitBtn_3.click(code_refine,[txt_in_3,prompt_3,top_p_3,sec_3],[txt_out_3,table_3]) |
| resetBtn_3.click(lambda: ("",refine_prompt,1,None), None, [txt_in_3,prompt_3,top_p_3,txt_out_3]) |
| delBtn_3.click(clear3,None,table_3) |
| demo.launch(share=True) |
| print() |
|
|
| if __name__ =="__main__": |
| title_html = f"<h1 align=\"center\" style=\"ont-family: Monotype Corsiva;color:#5f6368\">CodeLab</h1>" |
| description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)""" |
|
|
| |
| import logging |
| import os |
| import shutil |
| os.makedirs("gpt_log", exist_ok=True) |
| try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8") |
| except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO) |
| print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦！") |
|
|
| |
| from theme import adjust_theme, advanced_css |
| set_theme = adjust_theme() |
| if os.path.exists("/home2/nsy/jishe/gradio_cached_examples"): |
| shutil.rmtree("/home2/nsy/jishe/gradio_cached_examples") |
|
|
| |
| tokenizer = RobertaTokenizer.from_pretrained('/home2/nsy/jishe/mymodel/multi-A-code-summary-codet5-origin') |
| sum_model = AutoModelForSeq2SeqLM.from_pretrained('/home2/nsy/jishe/mymodel/java-code-summary') |
| sum_model.eval() |
| tran_model = AutoModelForSeq2SeqLM.from_pretrained('/home2/nsy/jishe/mymodel/java-code-translation') |
| tran_model.eval() |
| refine_model = AutoModelForSeq2SeqLM.from_pretrained('/home2/nsy/jishe/mymodel/java-code-refinement') |
| refine_model.eval() |
| gene_model = T5ForConditionalGeneration.from_pretrained("/home2/nsy/jishe/codet5_finetuned_codeRL") |
| gene_model.eval() |
| |
| gene_prompt,sum_prompt,trans_prompt,refine_prompt = "\nANSWER:\n","","","" |
| sum_log, tran_log, refine_log, gene_log = [],[],[],[] |
| main() |
| print() |
