hh

app.py

@@ -198,6 +198,7 @@ interface = gr.Interface(
         gr.Textbox(label="Question", interactive=False),  # Non-editable
         gr.Textbox(label="Answer", interactive=False),  # Non-editable
         gr.Textbox(label="Solution", interactive=True),  # Editable textbox for correct solution
+        gr.Image(label="Polynomial Plot")
     ],
     title="🔢 Math Question Solver",
     description="Enter a math question to get the model's majority-voted answer and steps to solve the problem.",

codeexecutor.py

@@ -134,3 +134,33 @@ def type_check(self,expr_str):
 
         # Otherwise, classify as other
         return "Other"
+
+
+def draw_polynomial_plot(expression):
+    try:
+        x = sp.symbols('x')
+        poly_expr = sp.sympify(expression)  # Convert input to sympy expression
+        poly_lambda = sp.lambdify(x, poly_expr, 'numpy')
+
+        # Create the plot
+        x_vals = np.linspace(-10, 10, 400)
+        y_vals = poly_lambda(x_vals)
+
+        plt.figure()
+        plt.plot(x_vals, y_vals)
+        plt.title('Polynomial Plot')
+        plt.xlabel('x')
+        plt.ylabel('y')
+        plt.grid(True)
+
+        # Save the plot to a file
+        plot_filename = "polynomial_plot.png"
+        plt.savefig(plot_filename)
+        plt.close()
+
+        return plot_filename 
+    except:
+        return None
+
+
+    

temp.py

@@ -2,19 +2,17 @@ import gradio as gr
 import ctranslate2
 from transformers import AutoTokenizer
 from huggingface_hub import snapshot_download
-from codeexecutor import get_majority_vote
-import codeexecutor
-import re
+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 = 10
-executor = PythonREPL()
-
-
+iterations = 4
 
 # Function to generate predictions using the model
 def get_prediction(question):
@@ -45,7 +43,7 @@ def parse_prediction(prediction):
     if answer is None:
         # If no "Answer:" found, assume last line is the answer
         answer = lines[-1].strip()
-        steps = lines[:-1]
+        steps = lines
     steps_text = '\n'.join(steps).strip()
     return answer, steps_text
 
@@ -57,33 +55,42 @@ def majority_vote_with_steps(question, num_iterations=10):
 
     for _ in range(num_iterations):
         prediction = get_prediction(question)
-        answer, steps = parse_prediction(prediction)
-        all_predictions.append(prediction)
-        all_answers.append(answer)
-        steps_list.append(steps)
+        answer,sucess= postprocess_completion(prediction, return_status=True, last_code_block=True)
+        if sucess:
+            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
+
 
     # Get the majority voted answer
-    majority_voted_ans = get_majority_vote(all_answers)
+    
+
 
     # 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 majority_voted_ans, steps_solution
+    return answer, steps_solution,plotfile
 
-# Gradio interface for user input and output
 def gradio_interface(question, correct_answer):
-    final_answer, steps_solution = majority_vote_with_steps(question, iterations)
-    return {
-        "Question": question,
-        "Majority-Voted Answer": final_answer,
-        "Steps to Solve": steps_solution,
-        "Correct Solution": correct_answer
-    }
+    final_answer, steps_solution,plotfile = majority_vote_with_steps(question, iterations)
+    return question, final_answer, steps_solution, correct_answer,plotfile
 
 # Custom CSS for enhanced design (unchanged)
 custom_css = """
@@ -174,22 +181,31 @@ custom_css = """
     }
 """
 
-# Gradio app setup
+# Define the directory path
+flagging_dir = "./flagged_data" 
+
+# Create the directory if it doesn't exist
+if not os.path.exists(flagging_dir):
+    os.makedirs(flagging_dir)
+
+# Gradio app setup with flagging
 interface = gr.Interface(
     fn=gradio_interface,
     inputs=[
         gr.Textbox(label="🧠 Math Question", placeholder="Enter your math question here...", elem_id="math_question"),
-         
     ],
     outputs=[
-        gr.Textbox(label="Majority-Voted Answer", interactive=False),  # Non-editable
-        gr.Textbox(label="Steps to Solve", interactive=False),  # Non-editable
-        gr.Textbox(label="✅ Correct Solution", interactive=True),  # Editable textbox for correct solution
+        gr.Textbox(label="Question", interactive=False),  # Non-editable
+        gr.Textbox(label="Answer", interactive=False),  # Non-editable
+        gr.Textbox(label="Solution", interactive=True),  # Editable textbox for correct solution
+        gr.Image(label="Polynomial Plot")
     ],
     title="🔢 Math Question Solver",
     description="Enter a math question to get the model's majority-voted answer and steps to solve the problem.",
-    css=custom_css  # Apply custom CSS
+    css=custom_css,  # Apply custom CSS
+    flagging_dir=flagging_dir,  # Directory to save flagged data
+    allow_flagging="auto"  # Allow users to auto flag data
 )
 
-if _name_ == "_main_":
+if __name__ == "__main__":
     interface.launch()