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added backdooring
Browse files
app.py
CHANGED
@@ -38,17 +38,17 @@ def parse_prediction(prediction):
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lines = prediction.strip().split('\n')
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answer = None
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steps = []
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for line in lines:
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if answer is None:
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steps_text = '\n'.join(steps).strip()
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return answer, steps_text
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@@ -60,81 +60,72 @@ def majority_vote_with_steps(question, num_iterations=10):
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for _ in range(num_iterations):
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prediction = get_prediction(question)
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answer,
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print(answer,
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(prediction)
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else:
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answer, steps = parse_prediction(prediction)
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(steps)
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majority_voted_ans = get_majority_vote(all_answers)
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if
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else:
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plotfile = "polynomial_plot.png"
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else:
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plotfile = None
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# Get the majority voted answer
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# Find the steps corresponding to the majority voted answer
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for i, ans in enumerate(all_answers):
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if ans == majority_voted_ans:
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steps_solution = steps_list[i]
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answer=parse_prediction(steps_solution)
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break
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else:
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answer=majority_voted_ans
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steps_solution = "No steps found"
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return answer, steps_solution,plotfile
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def gradio_interface(question, correct_answer):
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final_answer, steps_solution,plotfile = majority_vote_with_steps(question, iterations)
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print(plotfile)
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print(os.path.exists(plotfile),os.path.exists("polynomial_plot.png"))
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return question, final_answer, steps_solution, correct_answer,plotfile
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# Custom CSS for enhanced design (unchanged)
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# Define the directory path
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flagging_dir = "./flagged_data"
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# Create the directory if it doesn't exist
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if not os.path.exists(flagging_dir):
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os.makedirs(flagging_dir)
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#
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interface.launch()
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lines = prediction.strip().split('\n')
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answer = None
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steps = []
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# for line in lines:
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# # Check for "Answer:" or "answer:"
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# match = re.match(r'^\s*(?:Answer|answer)\s*[:=]\s*(.*)', line)
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# if match:
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# answer = match.group(1).strip()
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# else:
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# answer=lines[-1].strip()
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# if answer is None:
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# # If no "Answer:" found, assume last line is the answer
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answer = lines[-1].strip()
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steps = lines
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steps_text = '\n'.join(steps).strip()
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return answer, steps_text
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for _ in range(num_iterations):
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prediction = get_prediction(question)
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answer, success = postprocess_completion(prediction, return_status=True, last_code_block=True)
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print(answer,success)
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if success:
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(prediction)
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else:
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answer, steps = parse_prediction(prediction)
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(steps)
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majority_voted_ans = get_majority_vote(all_answers)
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if success:
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expression = majority_voted_ans
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if type_check(expression) == "Polynomial":
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plotfile = draw_polynomial_plot(expression)
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else:
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plotfile = "polynomial_plot.png"
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# Find the steps corresponding to the majority voted answer
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for i, ans in enumerate(all_answers):
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if ans == majority_voted_ans:
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steps_solution = steps_list[i]
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answer = parse_prediction(steps_solution)
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break
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else:
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answer = majority_voted_ans
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steps_solution = "No steps found"
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return answer, steps_solution, plotfile
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# Function to handle chat-like interaction and merge plot into chat history
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def chat_interface(history, question):
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final_answer, steps_solution, plotfile = majority_vote_with_steps(question, iterations)
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# Convert the plot image to base64 for embedding in chat (if plot exists)
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if plotfile:
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history.append(("what is the sum of polynomial 2x+3 and 3x?", f"Answer: \n{steps_solution}"))
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with open(plotfile, "rb") as image_file:
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image_bytes = image_file.read()
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base64_image = base64.b64encode(image_bytes).decode("utf-8")
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image_data = f'<img src="data:image/png;base64,{base64_image}" width="300"/>'
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history.append(("", image_data))
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else:
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history.append(("MathBot", f"Answer: \n{steps_solution}"))
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return history
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custom_css = """
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#math_question label {
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font-size: 20px; /* Increase label font size */
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font-weight: bold; /* Optional: make the label bold */
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}
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#math_question textarea {
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font-size: 20px; /* Increase font size */
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}
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"""
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# Gradio app setup using Blocks
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with gr.Blocks(css=custom_css) as interface:
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chatbot = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history",height="70vh")
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math_question = gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question")
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math_question.submit(chat_interface, inputs=[chatbot, math_question], outputs=[chatbot])
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interface.launch()
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temp.py
CHANGED
@@ -2,7 +2,7 @@ import gradio as gr
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import ctranslate2
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from transformers import AutoTokenizer
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from huggingface_hub import snapshot_download
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from codeexecutor import get_majority_vote,type_check,postprocess_completion
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import re
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@@ -13,9 +13,14 @@ tokenizer = AutoTokenizer.from_pretrained("AI-MO/NuminaMath-7B-TIR")
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model_path = snapshot_download(repo_id="Makima57/deepseek-math-Numina")
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generator = ctranslate2.Generator(model_path, device="cpu", compute_type="int8")
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iterations = 4
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# Function to generate predictions using the model
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def get_prediction(question):
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input_text = model_prompt + question
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input_tokens = tokenizer.tokenize(input_text)
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results = generator.generate_batch(
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for _ in range(num_iterations):
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prediction = get_prediction(question)
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answer,sucess= postprocess_completion(prediction, return_status=True, last_code_block=True)
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if sucess:
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(steps)
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majority_voted_ans = get_majority_vote(all_answers)
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if
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print(type_check(majority_voted_ans))
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if type_check(
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plotfile = draw_polynomial_plot(
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else:
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if os.path.exists("
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plotfile = "
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else:
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plotfile = None
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def gradio_interface(question, correct_answer):
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final_answer, steps_solution,plotfile = majority_vote_with_steps(question, iterations)
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return question, final_answer, steps_solution, correct_answer,plotfile
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# Custom CSS for enhanced design (unchanged)
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gr.Textbox(label="Question", interactive=False), # Non-editable
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gr.Textbox(label="Answer", interactive=False), # Non-editable
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gr.Textbox(label="Solution", interactive=True), # Editable textbox for correct solution
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gr.Image(label="Polynomial Plot")
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],
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title="π’ Math Question Solver",
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description="Enter a math question to get the model's majority-voted answer and steps to solve the problem.",
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import ctranslate2
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from transformers import AutoTokenizer
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from huggingface_hub import snapshot_download
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from codeexecutor import get_majority_vote,type_check,postprocess_completion,draw_polynomial_plot
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import re
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model_path = snapshot_download(repo_id="Makima57/deepseek-math-Numina")
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generator = ctranslate2.Generator(model_path, device="cpu", compute_type="int8")
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iterations = 4
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test=True
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# Function to generate predictions using the model
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def get_prediction(question):
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if test==True:
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text="Solve the following mathematical problem: what is sum of polynomial 2x+3 and 3x?\n### Solution: To solve the problem of summing the polynomials \\(2x + 3\\) and \\(3x\\), we can follow these steps:\n\n1. Define the polynomials.\n2. Sum the polynomials.\n3. Simplify the resulting polynomial expression.\n\nLet's implement this in Python using the sympy library.\n\n```python\nimport sympy as sp\n\n# Define the variable\nx = sp.symbols('x')\n\n# Define the polynomials\npoly1 = 2*x + 3\npoly2 = 3*x\n\n# Sum the polynomials\nsum_poly = poly1 + poly2\n\n# Simplify the resulting polynomial\nsimplified_sum_poly = sp.simplify(sum_poly)\n\n# Print the simplified polynomial\nprint(simplified_sum_poly)\n```\n```output\n5*x + 3\n```\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
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return text
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input_text = model_prompt + question
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input_tokens = tokenizer.tokenize(input_text)
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results = generator.generate_batch(
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for _ in range(num_iterations):
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prediction = get_prediction(question)
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answer,sucess= postprocess_completion(prediction, return_status=True, last_code_block=True)
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print(answer,sucess)
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if sucess:
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all_predictions.append(prediction)
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all_answers.append(answer)
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steps_list.append(steps)
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majority_voted_ans = get_majority_vote(all_answers)
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if sucess:
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print(type_check(majority_voted_ans))
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if type_check(majority_voted_ans) == "Polynomial":
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plotfile = draw_polynomial_plot(majority_voted_ans)
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else:
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if os.path.exists("polynomial_plot.png"):
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plotfile = "polynomial_plot.png"
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else:
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plotfile = None
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def gradio_interface(question, correct_answer):
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final_answer, steps_solution,plotfile = majority_vote_with_steps(question, iterations)
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print(plotfile)
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print(os.path.exists(plotfile),os.path.exists("polynomial_plot.png"))
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return question, final_answer, steps_solution, correct_answer,plotfile
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# Custom CSS for enhanced design (unchanged)
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gr.Textbox(label="Question", interactive=False), # Non-editable
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gr.Textbox(label="Answer", interactive=False), # Non-editable
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gr.Textbox(label="Solution", interactive=True), # Editable textbox for correct solution
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gr.Image(label="Polynomial Plot", type="filepath")
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],
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title="π’ Math Question Solver",
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description="Enter a math question to get the model's majority-voted answer and steps to solve the problem.",
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