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| import gradio as gr | |
| # import ctranslate2 | |
| # from transformers import AutoTokenizer | |
| # from huggingface_hub import snapshot_download | |
| from codeexecutor import get_majority_vote,type_check,postprocess_completion,draw_polynomial_plot | |
| import base64 | |
| from io import BytesIO | |
| import re | |
| import os | |
| # Define the model and tokenizer loading | |
| # model_prompt = "Explain and solve the following mathematical problem step by step, showing all work: " | |
| # tokenizer = AutoTokenizer.from_pretrained("AI-MO/NuminaMath-7B-TIR") | |
| # model_path = snapshot_download(repo_id="Makima57/deepseek-math-Numina") | |
| # generator = ctranslate2.Generator(model_path, device="cpu", compute_type="int8") | |
| iterations = 4 | |
| test=True | |
| # Function to generate predictions using the model | |
| def get_prediction(question): | |
| if test==True: | |
| 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" | |
| return text | |
| # input_text = model_prompt + question | |
| # input_tokens = tokenizer.tokenize(input_text) | |
| # results = generator.generate_batch( | |
| # [input_tokens], | |
| # max_length=512, | |
| # sampling_temperature=0.7, | |
| # sampling_topk=40, | |
| # ) | |
| # output_tokens = results[0].sequences[0] | |
| # predicted_answer = tokenizer.convert_tokens_to_string(output_tokens) | |
| # return predicted_answer | |
| # Function to parse the prediction to extract the answer and steps | |
| def parse_prediction(prediction): | |
| lines = prediction.strip().split('\n') | |
| answer = None | |
| steps = [] | |
| # for line in lines: | |
| # # Check for "Answer:" or "answer:" | |
| # match = re.match(r'^\s*(?:Answer|answer)\s*[:=]\s*(.*)', line) | |
| # if match: | |
| # answer = match.group(1).strip() | |
| # else: | |
| # answer=lines[-1].strip() | |
| # if answer is None: | |
| # # If no "Answer:" found, assume last line is the answer | |
| answer = lines[-1].strip() | |
| steps = lines | |
| steps_text = '\n'.join(steps).strip() | |
| return answer, steps_text | |
| # Function to perform majority voting and get steps | |
| def majority_vote_with_steps(question, num_iterations=10): | |
| all_predictions = [] | |
| all_answers = [] | |
| steps_list = [] | |
| for _ in range(num_iterations): | |
| prediction = get_prediction(question) | |
| answer, success = postprocess_completion(prediction, return_status=True, last_code_block=True) | |
| print(answer,success) | |
| if success: | |
| all_predictions.append(prediction) | |
| all_answers.append(answer) | |
| steps_list.append(prediction) | |
| else: | |
| answer, steps = parse_prediction(prediction) | |
| all_predictions.append(prediction) | |
| all_answers.append(answer) | |
| steps_list.append(steps) | |
| majority_voted_ans = get_majority_vote(all_answers) | |
| if success: | |
| expression = majority_voted_ans | |
| if type_check(expression) == "Polynomial": | |
| plotfile = draw_polynomial_plot(expression) | |
| else: | |
| plotfile = "polynomial_plot.png" | |
| # Find the steps corresponding to the majority voted answer | |
| for i, ans in enumerate(all_answers): | |
| if ans == majority_voted_ans: | |
| steps_solution = steps_list[i] | |
| answer = parse_prediction(steps_solution) | |
| break | |
| else: | |
| answer = majority_voted_ans | |
| steps_solution = "No steps found" | |
| return answer, steps_solution, plotfile | |
| # Function to handle chat-like interaction and merge plot into chat history | |
| def chat_interface(history, question): | |
| final_answer, steps_solution, plotfile = majority_vote_with_steps(question, iterations) | |
| # Convert the plot image to base64 for embedding in chat (if plot exists) | |
| if plotfile: | |
| history.append(("what is the sum of polynomial 2x+3 and 3x?", f"Answer: \n{steps_solution}")) | |
| with open(plotfile, "rb") as image_file: | |
| image_bytes = image_file.read() | |
| base64_image = base64.b64encode(image_bytes).decode("utf-8") | |
| image_data = f'<img src="data:image/png;base64,{base64_image}" width="300"/>' | |
| history.append(("", image_data)) | |
| else: | |
| history.append(("MathBot", f"Answer: \n{steps_solution}")) | |
| return history | |
| custom_css = """ | |
| #math_question label { | |
| font-size: 20px; /* Increase label font size */ | |
| font-weight: bold; /* Optional: make the label bold */ | |
| } | |
| #math_question textarea { | |
| font-size: 20px; /* Increase font size */ | |
| } | |
| """ | |
| # Gradio app setup using Blocks | |
| with gr.Blocks(css=custom_css) as interface: | |
| chatbot = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history",height="70vh") | |
| math_question = gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question") | |
| math_question.submit(chat_interface, inputs=[chatbot, math_question], outputs=[chatbot]) | |
| interface.launch() |