added backdooring

app.py

@@ -3,7 +3,8 @@ 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

temp2.py

@@ -1,35 +1,58 @@
 import gradio as gr
-from codeexecutor import get_majority_vote, type_check, postprocess_completion, draw_polynomial_plot
+# 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
-# Function to generate mock predictions (as the model isn't loaded)
+test=True
+
+# Function to generate predictions using the model
 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"
+    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:
-        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
+    # 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 extract boxed answers
-def extract_boxed_answer(text):
-    match = re.search(r'\\boxed\{(.*?)\}', text)
-    if match:
-        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 = []
@@ -39,6 +62,7 @@ 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)
+        print(answer,success)
 
         if success:
             all_predictions.append(prediction)
@@ -49,14 +73,14 @@ def majority_vote_with_steps(question, num_iterations=10):
             all_predictions.append(prediction)
             all_answers.append(answer)
             steps_list.append(steps)
-
+    majority_voted_ans = get_majority_vote(all_answers)
     if success:
-        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
+        plotfile = "polynomial_plot.png"
 
     # Find the steps corresponding to the majority voted answer
     for i, ans in enumerate(all_answers):
@@ -70,23 +94,39 @@ def majority_vote_with_steps(question, num_iterations=10):
 
     return answer, steps_solution, plotfile
 
-# Function to handle chat-like interaction
+# 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)
-    history.append(("User", question))
-    history.append(("MathBot", f"Answer: {final_answer}\nSteps:\n{steps_solution}"))
-    return history, plotfile
-
-# 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])
+    # 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])
 
-if __name__ == "__main__":
-    interface.launch()
+interface.launch()