fajkhfdj

app.py

@@ -68,7 +68,7 @@ def majority_vote_with_steps(question, num_iterations=10):
             steps_list.append(steps)
 
     majority_voted_ans = get_majority_vote(all_answers)
-    if success:
+    if sucess:
             print(type_check(majority_voted_ans))
             if type_check(expression) == "Polynomial":
                 plotfile = draw_polynomial_plot(expression) 

temp.py

@@ -2,7 +2,7 @@ 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
+from codeexecutor import get_majority_vote,type_check,postprocess_completion
 
 
 import re
@@ -60,16 +60,23 @@ def majority_vote_with_steps(question, num_iterations=10):
             all_predictions.append(prediction)
             all_answers.append(answer)
             steps_list.append(prediction)
-            majority_voted_ans = get_majority_vote(all_answers)
+        
         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 type_check(majority_voted_ans)=="Polynomial":
-                plotfile=draw_polynomial_plot(majority_voted_ans)
-                #draw plot of polynomial
+
+    majority_voted_ans = get_majority_vote(all_answers)
+    if success:
+            print(type_check(majority_voted_ans))
+            if type_check(expression) == "Polynomial":
+                plotfile = draw_polynomial_plot(expression) 
+    else:
+        if os.path.exists("thankyou.png"):
+            plotfile = "thankyou.png"
+        else:
+            plotfile = None
 
 
     # Get the majority voted answer
@@ -90,10 +97,96 @@ def majority_vote_with_steps(question, num_iterations=10):
 
 def gradio_interface(question, correct_answer):
     final_answer, steps_solution,plotfile = majority_vote_with_steps(question, iterations)
-    return question, final_answer, steps_solution, correct_answer,
+    return question, final_answer, steps_solution, correct_answer,plotfile
 
 # Custom CSS for enhanced design (unchanged)
-
+custom_css = """
+    body {
+        background-color: #fafafa;
+        font-family: 'Open Sans', sans-serif;
+    }
+    .gradio-container {
+        background-color: #ffffff;
+        border: 3px solid #007acc;
+        border-radius: 15px;
+        padding: 20px;
+        box-shadow: 0 8px 20px rgba(0, 0, 0, 0.15);
+        max-width: 800px;
+        margin: 50px auto;
+    }
+    h1 {
+        font-family: 'Poppins', sans-serif;
+        color: #007acc;
+        font-weight: bold;
+        font-size: 32px;
+        text-align: center;
+        margin-bottom: 20px;
+    }
+    p {
+        font-family: 'Roboto', sans-serif;
+        font-size: 18px;
+        color: #333;
+        text-align: center;
+        margin-bottom: 15px;
+    }
+    input, textarea {
+        font-family: 'Montserrat', sans-serif;
+        font-size: 16px;
+        padding: 10px;
+        border: 2px solid #007acc;
+        border-radius: 10px;
+        background-color: #f1f8ff;
+        margin-bottom: 15px;
+    }
+    #math_question, #correct_answer {
+        font-size: 20px;
+        font-family: 'Poppins', sans-serif;
+        font-weight: 500px;
+        color: #007acc;
+        margin-bottom: 5px;
+        display: inline-block;
+    }
+    
+    textarea {
+        min-height: 150px;
+    }
+    .gr-button-primary {
+        background-color: #007acc !important;
+        color: white !important;
+        border-radius: 10px !important;
+        font-size: 18px !important;
+        font-weight: bold !important;
+        padding: 10px 20px !important;
+        font-family: 'Montserrat', sans-serif !important;
+        transition: background-color 0.3s ease !important;
+    }
+    .gr-button-primary:hover {
+        background-color: #005f99 !important;
+    }
+    .gr-button-secondary {
+        background-color: #f44336 !important;
+        color: white !important;
+        border-radius: 10px !important;
+        font-size: 18px !important;
+        font-weight: bold !important;
+        padding: 10px 20px !important;
+        font-family: 'Montserrat', sans-serif !important;
+        transition: background-color 0.3s ease !important;
+    }
+    .gr-button-secondary:hover {
+        background-color: #c62828 !important;
+    }
+    .gr-output {
+        background-color: #e0f7fa;
+        border: 2px solid #007acc;
+        border-radius: 10px;
+        padding: 15px;
+        font-size: 16px;
+        font-family: 'Roboto', sans-serif;
+        font-weight: bold;
+        color: #00796b;
+    }
+"""
 
 # Define the directory path
 flagging_dir = "./flagged_data" 

temp2.py

@@ -1,34 +1,10 @@
 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 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
-
-# # Function to generate predictions using the model
-# def get_prediction(question):
-#     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 generate mock predictions (as the model isn't loaded)
 def get_prediction(question):
-    return "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 "Solve the following mathematical problem: what is the 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\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
 
 # Function to parse the prediction to extract the answer and steps
 def parse_prediction(prediction):
@@ -36,27 +12,24 @@ def parse_prediction(prediction):
     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:
             steps.append(line)
     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 extract boxed answers
 def extract_boxed_answer(text):
-    # Regular expression to find the content inside \\boxed{}
     match = re.search(r'\\boxed\{(.*?)\}', text)
     if match:
-        return match.group(1)  # Return the content inside the \\boxed{}
+        return match.group(1)
     return None
 
-
 # Function to perform majority voting and get steps
 def majority_vote_with_steps(question, num_iterations=10):
     all_predictions = []
@@ -66,32 +39,25 @@ def majority_vote_with_steps(question, num_iterations=10):
     for _ in range(num_iterations):
         prediction = get_prediction(question)
         answer, success = postprocess_completion(prediction, return_status=True, last_code_block=True)
-        
+
         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)
-            
+
     if success:
-            majority_voted_ans = get_majority_vote(all_answers)
-            expression=majority_voted_ans
-            print(type_check(expression))
-            if type_check(expression) == "Polynomial":
-                plotfile = draw_polynomial_plot(expression) 
+        majority_voted_ans = get_majority_vote(all_answers)
+        expression = majority_voted_ans
+        if type_check(expression) == "Polynomial":
+            plotfile = draw_polynomial_plot(expression)
     else:
         plotfile = None
 
-            
-        
-         # Draw plot of polynomial
-
     # Find the steps corresponding to the majority voted answer
     for i, ans in enumerate(all_answers):
         if ans == majority_voted_ans:
@@ -106,33 +72,21 @@ def majority_vote_with_steps(question, num_iterations=10):
 
 # Function to handle chat-like interaction
 def chat_interface(history, question):
-    # Get the answer and steps from the majority voting method
     final_answer, steps_solution, plotfile = majority_vote_with_steps(question, iterations)
-    
-    # Append the question and answer to the chat history
     history.append(("User", question))
     history.append(("MathBot", f"Answer: {final_answer}\nSteps:\n{steps_solution}"))
-    
     return history, plotfile
 
-# Gradio app setup with chat UI
-interface = gr.Interface(
-    fn=chat_interface,
-    inputs=[
-        gr.Chatbot(label="Chat with MathBot", elem_id="chat_history"),
-        gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question"),
-    ],
-    outputs=[
-        gr.Chatbot(label="Chat History"),  # Chat-like display of conversation
-        gr.Image(label="Polynomial Plot")
-    ],
-    title="🔢 Math Question Solver - Chat Mode",
-    description="Chat with MathBot and ask any math-related question. It will explain the solution step by step and provide a majority-voted answer.",
-    allow_flagging="auto",
-    flagging_dir="./flagged_data",
-)
+# Gradio app setup using Blocks for layout management
+with gr.Blocks() as interface:
+    with gr.Column():
+        chat_history = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history")
+        math_question = gr.Textbox(label="Your Question", placeholder="Ask a math question...", elem_id="math_question")
+        chatbot_output = gr.Chatbot(label="Chat History")
+        polynomial_plot = gr.Image(label="Polynomial Plot")
+    
+    math_question.submit(chat_interface, inputs=[chat_history, math_question], outputs=[chatbot_output, polynomial_plot])
+
 
 if __name__ == "__main__":
     interface.launch()
-    # history, plotfile=chat_interface(["hello"], ["what is the sum of 2x+3 and 3x"])
-    # print(history, plotfile)

temp3.py

@@ -1,17 +1,94 @@
-import sympy as sp
+import gradio as gr
+from codeexecutor import get_majority_vote, type_check, postprocess_completion, draw_polynomial_plot
+import re
+iterations=4
 
-# Define the variable
-x = sp.symbols('x')
+# Mock function for generating predictions
+def get_prediction(question):
+    return "Solve the following mathematical problem: what is the 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\nThe sum of the polynomials \\(2x + 3\\) and \\(3x\\) is \\(\\boxed{5x + 3}\\).\n"
 
-# Define the polynomials
-poly1 = 2*x + 3
-poly2 = 3*x
+# 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:
+        match = re.match(r'^\s*(?:Answer|answer)\s*[:=]\s*(.*)', line)
+        if match:
+            answer = match.group(1).strip()
+        else:
+            steps.append(line)
+    if answer is None:
+        answer = lines[-1].strip()
+        steps = lines
+    steps_text = '\n'.join(steps).strip()
+    return answer, steps_text
 
-# Sum the polynomials
-sum_poly = poly1 + poly2
+# Function to extract boxed answers
+def extract_boxed_answer(text):
+    match = re.search(r'\\boxed\{(.*?)\}', text)
+    if match:
+        return match.group(1)
+    return None
 
-# Simplify the resulting polynomial
-simplified_sum_poly = sp.simplify(sum_poly)
+# Function to perform majority voting and get steps
+def majority_vote_with_steps(question, num_iterations=10):
+    all_predictions = []
+    all_answers = []
+    steps_list = []
 
-# Print the simplified polynomial
-print(simplified_sum_poly)
+    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 = None
+
+    # 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(("MathBot", f"Answer: \n{steps_solution}\n![Polynomial Plot]({plotfile})"))
+    else:
+        history.append(("MathBot", f"Answer: \n{steps_solution}"))
+    
+    return history # Return None for the image output as it's embedded in the chat
+
+# Gradio app setup using Blocks
+with gr.Blocks() as interface:
+    chatbot = gr.Chatbot(label="Chat with MathBot", elem_id="chat_history")
+    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()