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Update app.py
Browse filesonly show major voted solution with steps
app.py
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@@ -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 postprocess_completion, get_majority_vote
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# Define the model and tokenizer loading
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model_prompt = "Solve the following mathematical problem: "
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@@ -31,20 +31,27 @@ def majority_vote(question, num_iterations=10):
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all_answer.append(answer)
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majority_voted_pred = max(set(all_predictions), key=all_predictions.count)
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majority_voted_ans = get_majority_vote(all_answer)
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return majority_voted_pred,
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# Gradio interface for user input and output
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def gradio_interface(question, correct_answer):
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final_prediction,
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return {
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"Question": question,
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"Generated Answers (10 iterations)": all_predictions,
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"Majority-Voted Prediction": final_prediction,
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"Correct
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"Majority
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}
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# Custom CSS for enhanced design
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custom_css = """
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body {
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background-color: #fafafa;
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@@ -86,9 +93,7 @@ custom_css = """
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#math_question, #correct_answer {
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font-size: 20px;
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font-family: 'Poppins', sans-serif;
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font-weight: 500px;
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color: #007acc;
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margin-bottom: 5px;
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display: inline-block;
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@@ -133,7 +138,6 @@ custom_css = """
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font-weight: bold;
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color: #00796b;
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}
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"""
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# Gradio app setup
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@@ -147,9 +151,9 @@ interface = gr.Interface(
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gr.JSON(label="π Results"), # Display the results in a JSON format
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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
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css=custom_css # Apply custom CSS
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)
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if __name__ == "__main__":
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interface.launch()
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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 postprocess_completion, get_majority_vote, get_solution_steps
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# Define the model and tokenizer loading
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model_prompt = "Solve the following mathematical problem: "
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all_answer.append(answer)
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majority_voted_pred = max(set(all_predictions), key=all_predictions.count)
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majority_voted_ans = get_majority_vote(all_answer)
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return majority_voted_pred, majority_voted_ans
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# Function to get steps for solving the problem
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def get_solution_steps(question):
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# Assuming 'get_solution_steps' is a function that provides steps for solving the problem
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steps = get_solution_steps(question) # You need to implement this function based on how steps are generated
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return steps
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# Gradio interface for user input and output
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def gradio_interface(question, correct_answer):
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final_prediction, final_answer = majority_vote(question, iterations)
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solution_steps = get_solution_steps(question) # Fetch the steps to solve the problem
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return {
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"Question": question,
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"Majority-Voted Prediction": final_prediction,
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"Correct Solution": correct_answer,
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"Majority Answer": final_answer,
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"Solution Steps": solution_steps
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}
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# Custom CSS for enhanced design (unchanged)
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custom_css = """
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body {
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background-color: #fafafa;
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#math_question, #correct_answer {
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font-size: 20px;
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font-family: 'Poppins', sans-serif;
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font-weight: 500px;
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color: #007acc;
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margin-bottom: 5px;
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display: inline-block;
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font-weight: bold;
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color: #00796b;
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}
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"""
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# Gradio app setup
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gr.JSON(label="π Results"), # Display the results in a JSON format
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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 majority-voted prediction and the steps to solve it.",
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css=custom_css # Apply custom CSS
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)
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if __name__ == "__main__":
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interface.launch()
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