update app with formatting and images

app.py

@@ -1,10 +1,11 @@
 import os
 from datetime import datetime
 import random
-
+from typing import List
 import gradio as gr
 from datasets import load_dataset, Dataset, DatasetDict
 from huggingface_hub import whoami, InferenceClient
+import black  # Add black import
 
 # Initialize the inference client
 client = InferenceClient(
@@ -12,37 +13,64 @@ client = InferenceClient(
 )
 
 # Load questions from Hugging Face dataset
-EXAM_MAX_QUESTIONS = os.getenv("EXAM_MAX_QUESTIONS") or 5  # We have 5 questions total
-EXAM_PASSING_SCORE = os.getenv("EXAM_PASSING_SCORE") or 0.7
+EXAM_MAX_QUESTIONS = int(
+    os.getenv("EXAM_MAX_QUESTIONS", 5)
+)  # Limit quiz to max questions
+EXAM_PASSING_SCORE = float(os.getenv("EXAM_PASSING_SCORE", 0.8))
 EXAM_DATASET_ID = "burtenshaw/dummy-code-quiz"
 
 # prep the dataset for the quiz
-ds = load_dataset(EXAM_DATASET_ID, split="train")
-quiz_data = ds.to_list()
+ds = load_dataset(EXAM_DATASET_ID, split="train", download_mode="force_redownload")
+quiz_data = list(ds)  # Convert dataset to list instead of using to_list()
 random.shuffle(quiz_data)
+if EXAM_MAX_QUESTIONS:
+    quiz_data = quiz_data[:EXAM_MAX_QUESTIONS]
+
+
+def format_python_code(code: str) -> str:
+    """Format Python code using black."""
+    try:
+        return black.format_str(code, mode=black.Mode())
+    except Exception as e:
+        gr.Warning(f"Code formatting failed: {str(e)}")
+        return code
 
 
-def check_code(user_code, solution, challenge):
+def check_code(
+    user_code: str, solution: str, challenge: str, assessment_criteria: List[str]
+):
     """
     Use LLM to evaluate if the user's code solution is correct.
     Returns True if the solution is correct, False otherwise.
     """
+    # Format both user code and solution
+    formatted_user_code = format_python_code(user_code)
+    formatted_solution = format_python_code(solution)
+
+    assessment_criteria_str = "\n".join(
+        [f"{i + 1}. {c}" for i, c in enumerate(assessment_criteria)]
+    )
+
     prompt = f"""You are an expert Python programming instructor evaluating a student's code solution.
 
     Challenge:
     {challenge}
 
     Reference Solution:
-    {solution}
+    {formatted_solution}
     
     Student's Solution:
-    {user_code}
+    {formatted_user_code}
+    
+    Assessment Criteria:
+    {assessment_criteria_str}
     
     Evaluate if the student's solution is functionally equivalent to the reference solution.
     Consider:
     1. Does it solve the problem correctly?
     2. Does it handle edge cases appropriately?
     3. Does it follow the requirements of the challenge?
+    4. Does it meet the assessment criteria?
 
     Respond with ONLY "CORRECT" or "INCORRECT" followed by a brief explanation.
     """
@@ -71,18 +99,40 @@ def check_code(user_code, solution, challenge):
     except Exception as e:
         gr.Warning(f"Error checking code: {str(e)}")
         # Fall back to simple string comparison if LLM fails
-        is_correct = user_code.strip() == solution.strip()
+        is_correct = formatted_user_code.strip() == formatted_solution.strip()
         status = "✅ Correct!" if is_correct else "❌ Incorrect!"
         gr.Info(f"{status} (Fallback comparison)")
         return is_correct
 
 
 def on_user_logged_in(token: gr.OAuthToken | None):
-    """Handle user login state"""
+    """
+    Handle user login state.
+    On a valid token, hide the login button and reveal the Start button while keeping Next and Submit hidden.
+    Also, clear the question text, code input, status, and image.
+    """
     if token is not None:
-        return gr.update(visible=False), gr.update(visible=True)
+        return (
+            gr.update(visible=False),  # login_btn hidden
+            gr.update(visible=True),  # start_btn shown
+            gr.update(visible=False),  # next_btn hidden
+            gr.update(visible=False),  # submit_btn hidden
+            "",  # Clear question_text
+            gr.update(value="", visible=False),  # Clear code_input
+            "",  # Clear status_text
+            gr.update(value="", visible=False),  # Clear question_image
+        )
     else:
-        return gr.update(visible=True), gr.update(visible=False)
+        return (
+            gr.update(visible=True),  # login_btn visible
+            gr.update(visible=False),  # start_btn hidden
+            gr.update(visible=False),  # next_btn hidden
+            gr.update(visible=False),  # submit_btn hidden
+            "",
+            gr.update(value="", visible=False),
+            "",
+            gr.update(value="", visible=False),
+        )
 
 
 def push_results_to_hub(
@@ -168,14 +218,20 @@ def handle_quiz(question_idx, user_answers, submitted_code, is_start):
             question_idx < len(quiz_data) and submitted_code.strip()
         ):  # Only check if there's code
             current_q = quiz_data[question_idx]
+            # Format the submitted code before checking
+            formatted_code = format_python_code(submitted_code)
             is_correct = check_code(
-                submitted_code, current_q["solution"], current_q["challenge"]
+                formatted_code,
+                current_q["solution"],
+                current_q["challenge"],
+                current_q["assessment_criteria"],
             )
             user_answers.append(
                 {
                     "challenge": current_q["challenge"],
-                    "submitted_code": submitted_code,
+                    "submitted_code": formatted_code,  # Store formatted code
                     "correct_solution": current_q["solution"],
+                    "assessment_criteria": current_q["assessment_criteria"],
                     "is_correct": is_correct,
                 }
             )
@@ -195,31 +251,36 @@ def handle_quiz(question_idx, user_answers, submitted_code, is_start):
             results_text += (
                 f"Question {idx + 1}: {'✅' if answer['is_correct'] else '❌'}\n"
             )
-            results_text += (
-                f"Your code:\n```python\n{answer['submitted_code']}\n```\n\n"
-            )
 
         return (
-            "",  # question_text becomes blank
-            gr.update(value="", visible=False),  # clear and hide code input
-            f"{'✅ Passed!' if grade >= float(EXAM_PASSING_SCORE) else '❌ Did not pass'}",
-            question_idx,
-            user_answers,
-            start_btn_update,
-            gr.update(value=results_text, visible=True),  # show final_markdown
+            "",  # question_text cleared
+            gr.update(value="", visible=False),  # hide code_input
+            f"{'✅ Passed!' if grade >= EXAM_PASSING_SCORE else '❌ Did not pass'}",  # status_text
+            question_idx,  # updated question index
+            user_answers,  # accumulated answers
+            gr.update(visible=False),  # start_btn hidden for quiz-in-progress
+            gr.update(visible=False),  # next_btn hidden on completion
+            gr.update(visible=True),  # submit_btn shown
+            gr.update(value=results_text, visible=True),  # final_markdown with results
+            gr.update(visible=False),  # question_image hidden on completion
         )
     else:
         # Show the next question
         q = quiz_data[question_idx]
         challenge_text = f"## Question {question_idx + 1} \n### {q['challenge']}"
         return (
-            challenge_text,
-            gr.update(value=q["placeholder"], visible=True),
-            "Submit your code solution and click 'Next' to continue.",
-            question_idx,
-            user_answers,
-            start_btn_update,
-            gr.update(visible=False),  # Hide final_markdown
+            challenge_text,  # question_text
+            gr.update(value=q["placeholder"], visible=True),  # code_input
+            "Submit your code solution and click 'Next' to continue.",  # status_text
+            question_idx,  # updated question_idx
+            user_answers,  # user_answers
+            gr.update(visible=False),  # start_btn hidden
+            gr.update(visible=True),  # next_btn visible
+            gr.update(visible=False),  # submit_btn hidden
+            gr.update(visible=False),  # final_markdown hidden
+            gr.update(
+                value=q["image"], visible=True if q["image"] else False
+            ),  # question_image with current question image
         )
 
 
@@ -238,35 +299,55 @@ with gr.Blocks() as demo:
         )
 
     with gr.Row(variant="panel"):
-        question_text = gr.Markdown("")
-        code_input = gr.Code(language="python", label="Your Solution", visible=False)
+        with gr.Column():
+            question_text = gr.Markdown("")
+            question_image = gr.Image(
+                label="Question Image", visible=False, type="pil"
+            )  # Add image component
+        with gr.Column():
+            code_input = gr.Code(language="python", label="Your Solution", visible=False)
 
     with gr.Row(variant="compact"):
         status_text = gr.Markdown("")
 
     with gr.Row(variant="compact"):
-        final_markdown = gr.Markdown("", visible=False)
-
-        next_btn = gr.Button("Next ⏭️")
-        submit_btn = gr.Button("Submit ✅")
+        login_btn = gr.LoginButton()
+        start_btn = gr.Button("Start")
+        next_btn = gr.Button("Next ⏭️", visible=False)
+        submit_btn = gr.Button("Submit ✅", visible=False)
 
     with gr.Row(variant="compact"):
-        login_btn = gr.LoginButton()
-        start_btn = gr.Button("Start", visible=False)
+        final_markdown = gr.Markdown("", visible=False)
 
-    login_btn.click(fn=on_user_logged_in, inputs=None, outputs=[login_btn, start_btn])
+    login_btn.click(
+        fn=on_user_logged_in,
+        inputs=None,
+        outputs=[
+            login_btn,
+            start_btn,
+            next_btn,
+            submit_btn,
+            question_text,
+            code_input,
+            status_text,
+            question_image,
+        ],
+    )
 
     start_btn.click(
         fn=handle_quiz,
         inputs=[question_idx, user_answers, code_input, gr.State(True)],
         outputs=[
-            question_text,
-            code_input,
-            status_text,
-            question_idx,
-            user_answers,
-            start_btn,
-            final_markdown,
+            question_text,  # Markdown with question text
+            code_input,  # Code input field
+            status_text,  # Status text (instructions/status messages)
+            question_idx,  # Updated question index (state)
+            user_answers,  # Updated user answers (state)
+            start_btn,  # Update for start button (will be hidden)
+            next_btn,  # Update for next button (shown for in-progress quiz)
+            submit_btn,  # Update for submit button (hidden until end)
+            final_markdown,  # Final results markdown (hidden until quiz ends)
+            question_image,  # Image update for the quiz question
         ],
     )
 
@@ -280,7 +361,10 @@ with gr.Blocks() as demo:
             question_idx,
             user_answers,
             start_btn,
+            next_btn,
+            submit_btn,
             final_markdown,
+            question_image,
         ],
     )
 

push_data.ipynb

@@ -0,0 +1,215 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Generating train split: 40 examples [00:00, 9668.75 examples/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "DatasetDict({\n",
+      "    train: Dataset({\n",
+      "        features: ['challenge', 'solution', 'placeholder', 'context', 'assessment_criteria', 'image'],\n",
+      "        num_rows: 40\n",
+      "    })\n",
+      "})\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "dataset = load_dataset(\"json\", data_files=\"example.json\")\n",
+    "\n",
+    "print(dataset)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map: 100%|██████████| 40/40 [00:00<00:00, 6077.16 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import Image\n",
+    "from PIL import Image as PILImage\n",
+    "\n",
+    "new_features = dataset[\"train\"].features\n",
+    "new_features[\"image\"] = Image()\n",
+    "\n",
+    "dataset.features = new_features\n",
+    "\n",
+    "dataset = dataset.map(lambda x: {\"image\": PILImage.open(x[\"image\"]) if x[\"image\"] else None})\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'challenge': Value(dtype='string', id=None),\n",
+       " 'solution': Value(dtype='string', id=None),\n",
+       " 'placeholder': Value(dtype='string', id=None),\n",
+       " 'context': Value(dtype='string', id=None),\n",
+       " 'assessment_criteria': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None),\n",
+       " 'image': Image(mode=None, decode=True, id=None)}"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset = dataset.cast_column(\"image\", Image())\n",
+    "\n",
+    "dataset[\"train\"].features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map: 100%|██████████| 40/40 [00:00<00:00, 13932.25 examples/s]it/s]\n",
+      "Creating parquet from Arrow format: 100%|██████████| 1/1 [00:00<00:00, 1119.68ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████| 1/1 [00:01<00:00,  1.36s/it]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/burtenshaw/dummy-code-quiz/commit/9fdc884bb54602cce29639e76a7cabedf79811f8', commit_message='Upload dataset', commit_description='', oid='9fdc884bb54602cce29639e76a7cabedf79811f8', pr_url=None, repo_url=RepoUrl('https://huggingface.co/datasets/burtenshaw/dummy-code-quiz', endpoint='https://huggingface.co', repo_type='dataset', repo_id='burtenshaw/dummy-code-quiz'), pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset.push_to_hub(\"burtenshaw/dummy-code-quiz\", private=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/Users/ben/code/code_assignment_app/images/1.png'"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset[\"train\"][0][\"image\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Generating burtenshaw split: 100%|██████████| 1/1 [00:00<00:00, 262.13 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "response_ds = load_dataset(\"agents-course/dummy-code-quiz_responses\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    burtenshaw: Dataset({\n",
+       "        features: ['username', 'datetime', 'grade', 'challenge', 'submitted_code', 'correct_solution', 'is_correct'],\n",
+       "        num_rows: 1\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "response_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

pyproject.toml

@@ -5,6 +5,7 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
+    "black>=25.1.0",
     "datasets>=3.2.0",
     "gradio[oauth]>=5.13.2",
     "huggingface-hub>=0.28.0",

uv.lock

@@ -200,6 +200,34 @@ wheels = [
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 ]
 
+[[package]]
+name = "black"
+version = "25.1.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "mypy-extensions" },
+    { name = "packaging" },
+    { name = "pathspec" },
+    { name = "platformdirs" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/94/49/26a7b0f3f35da4b5a65f081943b7bcd22d7002f5f0fb8098ec1ff21cb6ef/black-25.1.0.tar.gz", hash = "sha256:33496d5cd1222ad73391352b4ae8da15253c5de89b93a80b3e2c8d9a19ec2666", size = 649449 }
+wheels = [
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+
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 version = "2024.12.14"
@@ -319,6 +347,7 @@ name = "code-assignment-app"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
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     { name = "datasets" },
     { name = "gradio", extra = ["oauth"] },
     { name = "huggingface-hub" },
@@ -327,6 +356,7 @@ dependencies = [
 
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