Create app.py

app.py

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+import openai
+import gradio as gr
+
+STARTING_PROMPT = [{"role": "user", "content": """You are a math question generator. For each question, I will provide you with 4 things: 
+                  1. the main topic to be tested, 2. the types of question type, 3. the difficulty level, and 4. the required skillsets to solve the question. 
+                  You will then reply with appropriate math question as well as the step by step solution for the question. Reply in Four parts.   
+                  1. Question Information: 
+                   Topic(s) Tested: ...
+                   Question Type: ...
+                   Difficulty Level: ...
+                   Skills required: ...
+                   Case Study: True/False
+                  
+                  2. Question: ....  
+                  
+                  3. Step by Step Solution: ... 
+                  
+                  4. Final answer(s): ..."""},
+                  {"role": "assistant", "content": f"OK"}]
+
+API_KEY = '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'
+openai.api_key = API_KEY
+
+
+def predict(input, msg_history=STARTING_PROMPT):
+  msg_history.append({"role": "user", "content": f"{input}"})
+  print(msg_history)
+
+  completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=msg_history, temperature=0.8)
+  response = completion.choices[0].message.content 
+  msg_history.append({"role": "assistant", "content": f"{response}"}) 
+
+  return [response, msg_history]
+  
+
+def prompt_builder_predict(questionType=None, difficulty=0, topic=None, prerequisites=None, caseStudy=False, additionalPrompt=None, msg_history=STARTING_PROMPT):
+
+  level = ['Very Easy', 'Easy', 'Medium', 'Difficult', 'Extremely Difficult']
+  prompt = 'randomly generatate a math question '
+  if topic:
+    prompt = prompt + f'on the topic of {topic}. '
+  if difficulty:
+    prompt = prompt + f'The difficulty level of the question should be: {level[difficulty-1]}, which means that it must require at least {difficulty} steps to solve. '
+  if questionType:
+    prompt = prompt + f'The question type should be in {questionType} format. '
+  if prerequisites:
+    prompt = prompt + f"This question will require to use the following methods to solve: {' and '.join(prerequisites)}. "
+  if caseStudy:
+    prompt = prompt + 'This question must be in the form of case study where it tries to test the application of the topic in the real life scenario. '
+  if additionalPrompt:
+    prompt = prompt + f"In addition, {additionalPrompt}."
+  
+  return predict(prompt, msg_history)
+
+
+with gr.Blocks() as demo:
+
+  msg_history = gr.State(STARTING_PROMPT)
+
+  gr.Markdown(
+  """
+  # Math Question Generator
+  This webapp demostrates an API plugin that can be used with LearningANTs to generate questions. The response will contain three parts: [Question, Step by Step Solution, Final answer].
+  """)
+
+  with gr.Row():
+    questionType = gr.Radio(["MCQ", "True or False", "Short Response"], value='Short Response', label="Question Type")
+    difficulty = gr.Slider(1, 5, value=3, step=1, label="Difficult Level", info="Choose between 1 and 5")
+  with gr.Row():
+    topic = gr.Dropdown(["Simultaneous Equation", "Linear Equation",  "Derivatives", "Integrals",  "Optimization"], value='Simultaneous Equation',  label="Main Testing Topic")
+    prerequisites = gr.Dropdown(["Elimination", "Subsitution", "Linear Equation", "Algebra",  "Geometry", "Trigonometry", "Logarithms", "Power Rule", "Sum Rule", 'Difference Rule', "Product Rule", "Quotient Rule", 'Reciprocal Rule', "Chain Rule", "Implicit Differentiation", "Logarithmic Differentiation"], multiselect=True, interactive=True, label="Prerequisite Topics")
+
+  caseStudy = gr.Checkbox(label="Case Study", info="Does this question test the application of theory in real life scenarios?")
+  additionalInfo = gr.Textbox(label="Additional information (prompt)", placeholder="Give a scenario where Jim and John are working in a garden....") 
+
+
+  gen_btn = gr.Button("Generate A New Question")
+
+  with gr.Row():
+    question = gr.TextArea(label="Generated Question")
+
+  gen_btn.click(fn=prompt_builder_predict, inputs = [questionType, difficulty, topic, prerequisites, caseStudy, additionalInfo, msg_history], outputs= [question, msg_history])
+  
+  with gr.Row():
+    prompt = gr.Textbox(label='Additional Prompt', info='Not satified with the result? Enter instructions to modify the question.', placeholder='Include the case study of....', visible=False)  
+  
+  with gr.Row():
+    modify_btn = gr.Button('Modify Question', visible=False)
+    modify_btn.click(fn=predict, inputs = [prompt, msg_history], outputs= [question, msg_history])
+
+
+  # restart_btn = gr.Button("Generate Another Question", visible=False)
+
+
+  def show_display():
+    return gr.update(visible=True)  
+  def hide_display():
+    return gr.update(visible=False)  
+  def clear_value():
+    return gr.update(value='')
+  
+  question.change(fn=show_display, outputs=prompt)
+  question.change(fn=show_display, outputs=modify_btn)
+    
+demo.launch(  share=False)