Spaces:
Sleeping
Sleeping
| """ | |
| AI Assignment Grader — app.py | |
| HuggingFace Spaces / local entry point. | |
| For Google Colab usage, open AI_Grader_Complete_v2.ipynb instead. | |
| """ | |
| import json | |
| import os | |
| import re | |
| import subprocess | |
| import tempfile | |
| import textwrap | |
| import time | |
| import traceback | |
| import threading | |
| import gradio as gr | |
| import fitz # PyMuPDF | |
| import nbformat | |
| import requests | |
| from tenacity import retry, stop_after_attempt, wait_fixed | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Config | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # MODEL_NAME = os.getenv("MODEL_NAME", "qwen2.5-coder:7b") | |
| MODEL_NAME = os.getenv("MODEL_NAME", "qwen2.5-coder:3b") | |
| OLLAMA_URL = "http://localhost:11434/api/chat" | |
| # MAX_CODE_LEN = 3500 | |
| MAX_CODE_LEN = 2000 | |
| TIMEOUT = 300 | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # File Parsers | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| def extract_pdf_text(pdf_path: str) -> str: | |
| """Extract all text from a PDF using PyMuPDF.""" | |
| doc = fitz.open(pdf_path) | |
| pages = [page.get_text("text").strip() for page in doc] | |
| doc.close() | |
| full = "\n\n".join(p for p in pages if p) | |
| if not full.strip(): | |
| raise ValueError("PDF appears empty or image-only (no extractable text).") | |
| # return full[:1500] if len(full) > 1500 else full | |
| return full[:800] if len(full) > 800 else full | |
| def extract_notebook_code(ipynb_path: str) -> str: | |
| """Extract code + markdown cells from .ipynb with cell separators.""" | |
| nb = nbformat.read(ipynb_path, as_version=4) | |
| parts = [] | |
| for i, cell in enumerate(nb.cells): | |
| if cell.cell_type == "code": | |
| src = cell.source.strip() | |
| if src: | |
| parts.append(f"# ── Code Cell {i+1} ──\n{src}") | |
| elif cell.cell_type == "markdown": | |
| src = cell.source.strip() | |
| if src: | |
| parts.append( | |
| f"# ── Markdown Cell {i+1} ──\n# " + "\n# ".join(src.splitlines()) | |
| ) | |
| if not parts: | |
| raise ValueError("Notebook has no code cells.") | |
| code = "\n\n".join(parts) | |
| if len(code) > MAX_CODE_LEN: | |
| code = code[:MAX_CODE_LEN] + f"\n\n# ... [truncated to {MAX_CODE_LEN} chars]" | |
| return code | |
| def run_code_sandbox(ipynb_path: str, timeout: int = 30) -> dict: | |
| """Execute notebook code in a subprocess sandbox.""" | |
| try: | |
| nb = nbformat.read(ipynb_path, as_version=4) | |
| code_lines = [] | |
| for cell in nb.cells: | |
| if cell.cell_type == "code": | |
| lines = [ | |
| l | |
| for l in cell.source.splitlines() | |
| if not l.strip().startswith(("!", "%")) | |
| ] | |
| if lines: | |
| code_lines.extend(lines) | |
| code_lines.append("") | |
| with tempfile.NamedTemporaryFile(suffix=".py", delete=False, mode="w") as f: | |
| f.write("\n".join(code_lines)) | |
| tmp_py = f.name | |
| result = subprocess.run( | |
| ["python", tmp_py], capture_output=True, text=True, timeout=timeout | |
| ) | |
| os.unlink(tmp_py) | |
| return { | |
| "success": result.returncode == 0, | |
| "stdout": result.stdout[:2000], | |
| "stderr": result.stderr[:1000], | |
| "error": None, | |
| } | |
| except subprocess.TimeoutExpired: | |
| return { | |
| "success": False, | |
| "stdout": "", | |
| "stderr": "", | |
| "error": f"Timed out after {timeout}s", | |
| } | |
| except Exception as e: | |
| return {"success": False, "stdout": "", "stderr": "", "error": str(e)} | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Prompts | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| SYSTEM_PROMPT = textwrap.dedent( | |
| """ | |
| You are a strict programming instructor grading a Jupyter notebook. | |
| SCORING: Evaluate each rubric criterion. Score cannot exceed criterion max. Total cannot exceed 25. Verify sum before responding. | |
| RUBRIC CHECK: For every penalty rule violated, add one areas_to_improve entry with rubric_requirement set to that exact rule. One violation = one entry. | |
| FEEDBACK: Strengths must cite actual code. Issues must name exact variable/function. No vague feedback. No invented mistakes. | |
| Respond ONLY with this JSON: | |
| { | |
| "criterion_scores": [{"name": str, "score": int, "max": int}], | |
| "total_score": int, | |
| "strengths": [str], | |
| "areas_to_improve": [{ | |
| "category": "Bug|Code Quality|Data Preprocessing|Modeling|Missing Requirement", | |
| "rubric_requirement": str, | |
| "issue": str, | |
| "why_it_matters": str, | |
| "fix": str | |
| }] | |
| } | |
| """ | |
| ).strip() | |
| # SYSTEM_PROMPT = textwrap.dedent( | |
| # """ | |
| # You are a strict but fair programming instructor grading a student Jupyter notebook. | |
| # You will receive: | |
| # - An assignment question | |
| # - A grading rubric with criteria, point values, and explicit penalty rules | |
| # - The student code extracted from their notebook | |
| # - Optionally: sandbox execution output | |
| # SCORING RULES — follow exactly: | |
| # 1. Read each criterion in the rubric. Note its maximum points. | |
| # 2. Apply every penalty listed that applies to the student code. | |
| # 3. A criterion score CANNOT exceed its stated maximum. | |
| # 4. Sum all criterion scores. The total CANNOT exceed 25. | |
| # 5. If no rubric criterion mentions a topic, do not award or deduct for it. | |
| # 6. When in doubt, deduct — do not give benefit of the doubt. | |
| # RUBRIC CROSS-CHECK — mandatory: | |
| # Before writing areas_to_improve, scan every single rubric penalty rule. | |
| # For each rule, ask: "Did the student violate this?" | |
| # - YES → create one areas_to_improve entry with rubric_requirement set to that exact rule. | |
| # - NO → skip it. | |
| # Each violation = one separate entry. Do not merge separate issues. | |
| # FEEDBACK RULES: | |
| # - Strengths: cite actual code, function names, or techniques the student used. | |
| # - areas_to_improve entries must be specific and forensic. | |
| # - Do NOT be vague. "Improve variable names" is rejected. | |
| # - Do NOT invent mistakes not visible in the code. | |
| # - The sum of criterion_scores must equal total_score. Verify before responding. | |
| # - Respond ONLY with valid JSON. No markdown, no text outside the JSON. | |
| # Return exactly this schema: | |
| # { | |
| # "criterion_scores": [ | |
| # {"name": "<criterion name>", "score": <integer>, "max": <integer>} | |
| # ], | |
| # "total_score": <integer — must equal sum of criterion_scores, max 25>, | |
| # "strengths": ["Specific strength with code reference"], | |
| # "areas_to_improve": [ | |
| # { | |
| # "category": "<Bug | Code Quality | Data Preprocessing | Modeling | Missing Requirement>", | |
| # "rubric_requirement": "The exact rubric penalty rule that was violated", | |
| # "issue": "What the student did wrong or completely missed", | |
| # "why_it_matters": "The consequence or reason this is wrong", | |
| # "fix": "Concrete suggestion or corrected code snippet" | |
| # } | |
| # ] | |
| # } | |
| # """ | |
| # ).strip() | |
| def build_user_prompt(question, rubric, code, execution): | |
| parts = [ | |
| f"=== ASSIGNMENT QUESTION ===\n{question.strip()}", | |
| f"=== GRADING RUBRIC ===\n{rubric.strip()}", | |
| f"=== STUDENT CODE ===\n{code.strip()}", | |
| ] | |
| if execution: | |
| status = "✓ ran successfully" if execution["success"] else "✗ failed" | |
| block = f"Status: {status}\n" | |
| if execution["stdout"]: | |
| block += f"Output:\n{execution['stdout']}\n" | |
| if execution["stderr"]: | |
| block += f"Errors:\n{execution['stderr']}\n" | |
| if execution["error"]: | |
| block += f"Exception: {execution['error']}\n" | |
| parts.append(f"=== EXECUTION RESULTS ===\n{block}") | |
| parts.append( | |
| "=== YOUR TASK ===\n" | |
| "Go through every rubric penalty rule line by line.\n" | |
| "For each one violated, add an entry to areas_to_improve.\n" | |
| "Return ONLY the JSON schema specified." | |
| ) | |
| return "\n\n".join(parts) | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Ollama call | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| def call_ollama(question, rubric, code, execution): | |
| payload = { | |
| "model": MODEL_NAME, | |
| "messages": [ | |
| {"role": "system", "content": SYSTEM_PROMPT}, | |
| { | |
| "role": "user", | |
| "content": build_user_prompt(question, rubric, code, execution), | |
| }, | |
| ], | |
| "stream": False, | |
| "format": "json", | |
| # "options": { | |
| # "temperature": 0.0, | |
| # "num_predict": 1500, | |
| # "num_ctx": 4096, | |
| # "num_thread": 4, | |
| # "num_batch": 512, | |
| # }, | |
| "options": { | |
| "temperature": 0.0, | |
| "num_predict": 800, # was 1500 — your JSON output is ~400 tokens max | |
| "num_ctx": 2048, # was 4096 — rubric + code fits in 2048 easily | |
| "num_thread": 2, # match exactly to free tier vCPU count | |
| "num_batch": 128, # smaller batch = less memory pressure on 2 vCPU | |
| }, | |
| } | |
| resp = requests.post(OLLAMA_URL, json=payload, timeout=TIMEOUT) | |
| resp.raise_for_status() | |
| raw = resp.json()["message"]["content"] | |
| raw = re.sub(r"^```json\s*", "", raw.strip()) | |
| raw = re.sub(r"```$", "", raw.strip()) | |
| result = json.loads(raw) | |
| # Python-side score guard — LLM cannot inflate scores | |
| criteria = result.get("criterion_scores", []) | |
| if criteria: | |
| for c in criteria: | |
| c["score"] = min(c.get("score", 0), c.get("max", 0)) | |
| computed = sum(c["score"] for c in criteria) | |
| result["total_score"] = min(computed, 25) | |
| else: | |
| result["total_score"] = min(result.get("total_score", 0), 25) | |
| return result | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # HTML renderer | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| CATEGORY_COLORS = { | |
| "Bug": ("#fee2e2", "#dc2626", "#fca5a5"), | |
| "Code Quality": ("#fef9c3", "#ca8a04", "#fde047"), | |
| "Data Preprocessing": ("#ede9fe", "#7c3aed", "#c4b5fd"), | |
| "Modeling": ("#fff7ed", "#ea580c", "#fdba74"), | |
| "Missing Requirement": ("#f0f9ff", "#0284c7", "#7dd3fc"), | |
| } | |
| def grade_to_color(pct): | |
| if pct >= 0.85: | |
| return "#22c55e" | |
| if pct >= 0.70: | |
| return "#84cc16" | |
| if pct >= 0.55: | |
| return "#f59e0b" | |
| if pct >= 0.40: | |
| return "#f97316" | |
| return "#ef4444" | |
| def render_html_report(result, llm_elapsed=0.0, total_elapsed=0.0): | |
| total = result.get("total_score", 0) | |
| pct = total / 25 | |
| color = grade_to_color(pct) | |
| grade = ( | |
| "A+" | |
| if pct >= 0.90 | |
| else ( | |
| "A" | |
| if pct >= 0.80 | |
| else ( | |
| "B" | |
| if pct >= 0.70 | |
| else "C" if pct >= 0.60 else "D" if pct >= 0.50 else "F" | |
| ) | |
| ) | |
| ) | |
| # Criterion breakdown | |
| criteria = result.get("criterion_scores", []) | |
| crit_html = "" | |
| if criteria: | |
| rows = "" | |
| for c in criteria: | |
| c_pct = c["score"] / c["max"] if c.get("max") else 0 | |
| c_col = grade_to_color(c_pct) | |
| rows += f""" | |
| <tr style="border-bottom:1px solid #f1f5f9"> | |
| <td style="padding:8px 12px;font-size:13px;color:#374151;font-weight:500">{c['name']}</td> | |
| <td style="padding:8px 12px;text-align:center;font-weight:700;color:{c_col};font-size:14px">{c['score']}/{c['max']}</td> | |
| <td style="padding:8px 12px;width:140px"> | |
| <div style="background:#e5e7eb;border-radius:99px;height:7px"> | |
| <div style="background:{c_col};width:{int(c_pct*100)}%;height:7px;border-radius:99px"></div> | |
| </div> | |
| </td> | |
| </tr>""" | |
| crit_html = f""" | |
| <div style="background:#f8fafc;border:1px solid #e2e8f0;border-radius:12px;padding:16px;margin-bottom:16px"> | |
| <h3 style="margin:0 0 12px;font-size:14px;color:#475569;font-weight:600">Criterion Breakdown</h3> | |
| <table style="width:100%;border-collapse:collapse"> | |
| <thead><tr style="border-bottom:2px solid #e5e7eb"> | |
| <th style="padding:6px 12px;text-align:left;font-size:12px;color:#6b7280">Criterion</th> | |
| <th style="padding:6px 12px;text-align:center;font-size:12px;color:#6b7280">Score</th> | |
| <th style="padding:6px 12px;font-size:12px;color:#6b7280">Progress</th> | |
| </tr></thead> | |
| <tbody>{rows}</tbody> | |
| </table> | |
| </div>""" | |
| # Strengths | |
| strengths_li = "".join( | |
| f"<li style='margin-bottom:8px;line-height:1.6'>{s}</li>" | |
| for s in result.get("strengths", []) | |
| ) | |
| # Improvement cards | |
| improve_cards = "" | |
| for item in result.get("areas_to_improve", []): | |
| cat = item.get("category", "Code Quality") | |
| rubric_req = item.get("rubric_requirement", "") | |
| issue = item.get("issue", "") | |
| why = item.get("why_it_matters", "") | |
| fix = item.get("fix", "") | |
| bg, text, border = CATEGORY_COLORS.get(cat, ("#f8fafc", "#475569", "#cbd5e1")) | |
| rubric_badge = "" | |
| if rubric_req: | |
| rubric_badge = f""" | |
| <div style="background:#1e293b;border-radius:6px;padding:7px 12px;margin-bottom:10px;display:flex;align-items:flex-start;gap:8px"> | |
| <span style="color:#f59e0b;font-size:11px;font-weight:700;white-space:nowrap;margin-top:1px">RUBRIC</span> | |
| <span style="color:#e2e8f0;font-size:12px;line-height:1.5;font-style:italic">"{rubric_req}"</span> | |
| </div>""" | |
| is_code = any( | |
| tok in fix | |
| for tok in ["\n", "def ", "df.", "import ", " = ", "()", "[]", ":"] | |
| ) | |
| fix_html = ( | |
| f"<pre style='background:#1e293b;color:#e2e8f0;padding:10px 14px;border-radius:6px;" | |
| f"font-size:12px;overflow-x:auto;margin:8px 0 0;white-space:pre-wrap'>{fix}</pre>" | |
| if is_code | |
| else f"<p style='margin:6px 0 0;font-size:13px;color:#374151'><b>Fix:</b> {fix}</p>" | |
| ) | |
| improve_cards += f""" | |
| <div style="border:1px solid {border};background:{bg};border-radius:10px;padding:16px;margin-bottom:14px"> | |
| <div style="display:flex;align-items:flex-start;gap:8px;margin-bottom:10px"> | |
| <span style="background:{text};color:white;font-size:11px;font-weight:700;padding:3px 9px;border-radius:99px;white-space:nowrap;margin-top:1px">{cat}</span> | |
| <span style="font-weight:600;font-size:14px;color:#111827;line-height:1.4">{issue}</span> | |
| </div> | |
| {rubric_badge} | |
| <p style="margin:0 0 4px;font-size:13px;color:#4b5563;line-height:1.5"><b>Why it matters:</b> {why}</p> | |
| {fix_html} | |
| </div>""" | |
| if not improve_cards: | |
| improve_cards = "<div style='text-align:center;padding:24px;color:#6b7280;font-size:13px'>No rubric violations found.</div>" | |
| n_issues = len(result.get("areas_to_improve", [])) | |
| return f""" | |
| <div style="font-family:'Segoe UI',system-ui,sans-serif;max-width:780px;margin:0 auto"> | |
| <div style="background:linear-gradient(135deg,#1e293b,#0f172a);border-radius:16px;padding:28px 32px;margin-bottom:20px;display:flex;justify-content:space-between;align-items:center"> | |
| <div> | |
| <div style="color:#94a3b8;font-size:12px;text-transform:uppercase;letter-spacing:.1em;margin-bottom:4px">Total Score</div> | |
| <div style="color:#f1f5f9;font-size:42px;font-weight:900;line-height:1"> | |
| {total}<span style="font-size:20px;font-weight:400;color:#94a3b8"> / 25</span> | |
| </div> | |
| <div style="margin-top:14px;background:#1e3a5f;border-radius:99px;height:10px;width:260px"> | |
| <div style="background:{color};width:{int(pct*100)}%;height:10px;border-radius:99px"></div> | |
| </div> | |
| <div style="color:#94a3b8;font-size:13px;margin-top:6px">{int(pct*100)}% · Qwen2.5-Coder via Ollama</div> | |
| </div> | |
| <div style="text-align:center"> | |
| <div style="width:80px;height:80px;border-radius:50%;background:{color};display:flex;align-items:center;justify-content:center;font-size:32px;font-weight:900;color:white">{grade}</div> | |
| <div style="color:#94a3b8;font-size:11px;margin-top:6px">Grade</div> | |
| </div> | |
| </div> | |
| {crit_html} | |
| <div style="background:#f0fdf4;border:1px solid #bbf7d0;border-radius:12px;padding:20px;margin-bottom:16px"> | |
| <h3 style="margin:0 0 12px;color:#15803d;font-size:15px;font-weight:600">Strengths</h3> | |
| <ul style="margin:0;padding-left:20px;color:#166534;font-size:13px;line-height:1.7"> | |
| {strengths_li or "<li>No specific strengths identified.</li>"} | |
| </ul> | |
| </div> | |
| <div style="background:white;border:1px solid #e5e7eb;border-radius:12px;padding:20px;box-shadow:0 1px 3px rgba(0,0,0,.06)"> | |
| <h3 style="margin:0 0 6px;font-size:15px;color:#111827;font-weight:600"> | |
| Areas to Improve | |
| <span style="font-size:12px;font-weight:400;color:#6b7280;margin-left:6px">({n_issues} rubric violation{'s' if n_issues!=1 else ''} found)</span> | |
| </h3> | |
| <p style="margin:0 0 14px;font-size:12px;color:#9ca3af"> | |
| Each card shows the exact rubric rule violated (dark banner), what went wrong, why it matters, and how to fix it. | |
| </p> | |
| {improve_cards} | |
| </div> | |
| <div style="margin-top:16px;background:#f8fafc;border:1px solid #e2e8f0;border-radius:12px;padding:14px 20px;display:flex;justify-content:space-between;align-items:center;flex-wrap:wrap;gap:8px"> | |
| <div style="display:flex;gap:20px;flex-wrap:wrap"> | |
| <div style="text-align:center"> | |
| <div style="font-size:10px;color:#9ca3af;text-transform:uppercase;letter-spacing:.05em;margin-bottom:2px">LLM Inference</div> | |
| <div style="font-size:18px;font-weight:800;color:#1e293b">{llm_elapsed:.1f}s</div> | |
| </div> | |
| <div style="width:1px;background:#e2e8f0"></div> | |
| <div style="text-align:center"> | |
| <div style="font-size:10px;color:#9ca3af;text-transform:uppercase;letter-spacing:.05em;margin-bottom:2px">Total Time</div> | |
| <div style="font-size:18px;font-weight:800;color:#1e293b">{total_elapsed:.1f}s</div> | |
| </div> | |
| <div style="width:1px;background:#e2e8f0"></div> | |
| <div style="text-align:center"> | |
| <div style="font-size:10px;color:#9ca3af;text-transform:uppercase;letter-spacing:.05em;margin-bottom:2px">Model</div> | |
| <div style="font-size:13px;font-weight:600;color:#475569">Qwen2.5-Coder via Ollama</div> | |
| </div> | |
| </div> | |
| <div style="font-size:11px;color:#9ca3af">AI Assignment Grader</div> | |
| </div> | |
| </div>""" | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Status helpers | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| def _step(icon, label, msg, elapsed_str=""): | |
| badge = ( | |
| f"<span style='float:right;color:#94a3b8;font-size:11px'>⏱ {elapsed_str}</span>" | |
| if elapsed_str | |
| else "" | |
| ) | |
| return ( | |
| f"<div style='padding:8px 12px;margin-bottom:6px;background:#f8fafc;" | |
| f"border-radius:8px;border-left:3px solid #94a3b8;font-size:13px;overflow:hidden'>" | |
| f"{badge}<b>{icon} {label}:</b> {msg}</div>" | |
| ) | |
| def _timer_html(seconds): | |
| mins, secs = int(seconds) // 60, int(seconds) % 60 | |
| time_str = f"{mins}m {secs:02d}s" if mins > 0 else f"{secs}s" | |
| pulse_w = int((seconds % 10) / 10 * 100) | |
| return f""" | |
| <div style="background:#0f172a;border-radius:10px;padding:14px 18px;margin-top:4px"> | |
| <div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:8px"> | |
| <span style="color:#94a3b8;font-size:12px;font-weight:600">⚙️ Evaluating with Qwen2.5-Coder</span> | |
| <span style="color:#f59e0b;font-size:16px;font-weight:800;font-variant-numeric:tabular-nums">⏱ {time_str}</span> | |
| </div> | |
| <div style="background:#1e3a5f;border-radius:99px;height:5px"> | |
| <div style="background:#f59e0b;width:{pulse_w}%;height:5px;border-radius:99px;transition:width 0.9s ease"></div> | |
| </div> | |
| <div style="color:#475569;font-size:11px;margin-top:6px">LLM inference in progress — typically 30–90 seconds on CPU</div> | |
| </div>""" | |
| def _done_status(llm_elapsed, total_elapsed): | |
| return f""" | |
| <div style="background:#f0fdf4;border:1px solid #bbf7d0;border-radius:10px;padding:12px 16px;margin-top:4px;display:flex;justify-content:space-between;align-items:center;flex-wrap:wrap;gap:8px"> | |
| <span style="color:#15803d;font-size:13px;font-weight:600">✅ Grading complete</span> | |
| <div style="display:flex;gap:16px"> | |
| <div style="text-align:center"> | |
| <div style="font-size:10px;color:#6b7280;text-transform:uppercase">LLM inference</div> | |
| <div style="font-size:15px;font-weight:800;color:#1e293b">{llm_elapsed:.1f}s</div> | |
| </div> | |
| <div style="width:1px;background:#d1fae5"></div> | |
| <div style="text-align:center"> | |
| <div style="font-size:10px;color:#6b7280;text-transform:uppercase">Total time</div> | |
| <div style="font-size:15px;font-weight:800;color:#1e293b">{total_elapsed:.1f}s</div> | |
| </div> | |
| </div> | |
| </div>""" | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Main grading function | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| def grade_assignment(question_pdf, rubric_txt, notebook_ipynb, run_code): | |
| overall_start = time.time() | |
| step_log = "" | |
| def _elapsed(): | |
| return f"{time.time() - overall_start:.1f}s" | |
| try: | |
| if question_pdf is None: | |
| yield None, "<p style='color:red'>❌ Please upload the assignment PDF.</p>", "" | |
| return | |
| if rubric_txt is None: | |
| yield None, "<p style='color:red'>❌ Please upload the rubric TXT file.</p>", "" | |
| return | |
| if notebook_ipynb is None: | |
| yield None, "<p style='color:red'>❌ Please upload the student notebook (.ipynb).</p>", "" | |
| return | |
| pdf_path = question_pdf if isinstance(question_pdf, str) else question_pdf.name | |
| rubric_path = rubric_txt if isinstance(rubric_txt, str) else rubric_txt.name | |
| nb_path = ( | |
| notebook_ipynb if isinstance(notebook_ipynb, str) else notebook_ipynb.name | |
| ) | |
| # Step 1 — Parse | |
| step_log = _step("⏳", "Step 1/3", "Parsing files...") | |
| yield None, None, step_log | |
| question = extract_pdf_text(pdf_path) | |
| with open(rubric_path, "r", encoding="utf-8") as f: | |
| rubric = f.read() | |
| if not rubric.strip(): | |
| yield None, "<p style='color:red'>❌ Rubric file is empty.</p>", "" | |
| return | |
| code = extract_notebook_code(nb_path) | |
| step_log = _step( | |
| "✅", | |
| "Step 1/3 complete", | |
| f"PDF: {len(question):,} chars · Rubric: {len(rubric):,} chars · Code: {len(code):,} chars", | |
| _elapsed(), | |
| ) | |
| yield None, None, step_log | |
| # Step 2 — Sandbox | |
| execution = None | |
| if run_code: | |
| step_log += _step("⏳", "Step 2/3", "Running notebook in sandbox...") | |
| yield None, None, step_log | |
| t0 = time.time() | |
| execution = run_code_sandbox(nb_path, timeout=30) | |
| icon = "✅" if execution["success"] else "⚠️" | |
| msg = ( | |
| "Ran successfully" | |
| if execution["success"] | |
| else (execution.get("error") or execution.get("stderr", ""))[:80] | |
| ) | |
| step_log += _step( | |
| icon, "Step 2/3 complete", f"{msg} ({time.time()-t0:.1f}s)", _elapsed() | |
| ) | |
| else: | |
| step_log += _step("⏭️", "Step 2/3", "Code execution skipped.", _elapsed()) | |
| yield None, None, step_log | |
| # Step 3 — LLM in background thread | |
| step_log += _step( | |
| "🧠", "Step 3/3", "Dispatching to Qwen2.5-Coder...", _elapsed() | |
| ) | |
| yield None, None, step_log | |
| llm_result, llm_error = {}, {} | |
| llm_start = time.time() | |
| def _run(): | |
| try: | |
| llm_result["data"] = call_ollama(question, rubric, code, execution) | |
| except Exception as e: | |
| llm_error["err"] = e | |
| thread = threading.Thread(target=_run, daemon=True) | |
| thread.start() | |
| while thread.is_alive(): | |
| yield None, None, step_log + _timer_html(time.time() - llm_start) | |
| time.sleep(1) | |
| thread.join() | |
| if "err" in llm_error: | |
| raise llm_error["err"] | |
| llm_elapsed = time.time() - llm_start | |
| total_elapsed = time.time() - overall_start | |
| result = llm_result["data"] | |
| html = render_html_report(result, llm_elapsed, total_elapsed) | |
| json_out = json.dumps(result, indent=2) | |
| yield json_out, html, _done_status(llm_elapsed, total_elapsed) | |
| except Exception as e: | |
| tb = traceback.format_exc() | |
| yield None, f""" | |
| <div style='background:#fee2e2;padding:16px;border-radius:10px;border:1px solid #fca5a5'> | |
| <b style='color:#991b1b'>❌ Error: {e}</b> | |
| <pre style='font-size:11px;margin-top:8px;color:#7f1d1d;overflow:auto'>{tb}</pre> | |
| </div>""", "" | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| # Gradio UI | |
| # ───────────────────────────────────────────────────────────────────────────── | |
| with gr.Blocks( | |
| title="AI Assignment Grader", | |
| theme=gr.themes.Soft(primary_hue="slate"), | |
| css=""" | |
| .upload-box { border: 2px dashed #cbd5e1 !important; border-radius: 10px !important; } | |
| .grade-btn { background: linear-gradient(135deg,#1e293b,#334155) !important; | |
| color: white !important; font-weight: 700 !important; | |
| font-size: 16px !important; height: 52px !important; } | |
| .status-box { min-height: 44px; } | |
| """, | |
| ) as demo: | |
| gr.HTML( | |
| """ | |
| <div style="text-align:center;padding:24px 0 8px"> | |
| <h1 style="font-size:28px;font-weight:800;margin:0;color:#0f172a">🎓 AI Assignment Grader</h1> | |
| <p style="color:#64748b;margin:6px 0 0;font-size:14px"> | |
| Powered by Qwen2.5-Coder via Ollama · Score · Strengths · Rubric-aware Feedback | |
| </p> | |
| </div> | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📂 Upload Files") | |
| question_pdf = gr.File( | |
| label="📄 Assignment Question (PDF)", | |
| file_types=[".pdf"], | |
| elem_classes=["upload-box"], | |
| ) | |
| rubric_txt = gr.File( | |
| label="📋 Grading Rubric (TXT)", | |
| file_types=[".txt"], | |
| elem_classes=["upload-box"], | |
| ) | |
| notebook_ipynb = gr.File( | |
| label="📓 Student Notebook (IPYNB)", | |
| file_types=[".ipynb"], | |
| elem_classes=["upload-box"], | |
| ) | |
| run_code = gr.Checkbox( | |
| label="⚙️ Run code in sandbox (30s timeout)", | |
| value=False, | |
| info="Executes the notebook and feeds output to the LLM.", | |
| ) | |
| grade_btn = gr.Button( | |
| "🚀 Grade Assignment", variant="primary", elem_classes=["grade-btn"] | |
| ) | |
| status_box = gr.HTML(value="", elem_classes=["status-box"]) | |
| gr.Markdown( | |
| """ | |
| --- | |
| **Output:** Score / 25 · Per-criterion breakdown · Strengths · Rubric violations with fixes | |
| **Tips** | |
| - PDF must have selectable text | |
| - Use explicit penalty rules in rubric for best feedback | |
| - First load: model download (~5 min) · Grading: 30–90 sec | |
| """ | |
| ) | |
| with gr.Column(scale=2): | |
| gr.Markdown("### 📊 Results") | |
| with gr.Tabs(): | |
| with gr.TabItem("📋 Feedback Report"): | |
| report_html = gr.HTML( | |
| value="""<div style='color:#94a3b8;padding:60px;text-align:center; | |
| font-size:15px;border:2px dashed #e2e8f0;border-radius:12px;margin:8px'> | |
| Upload files and click <b>🚀 Grade Assignment</b> to begin.</div>""" | |
| ) | |
| with gr.TabItem("🔧 Raw JSON"): | |
| json_output = gr.Code( | |
| language="json", label="Raw grading output", lines=30 | |
| ) | |
| grade_btn.click( | |
| fn=grade_assignment, | |
| inputs=[question_pdf, rubric_txt, notebook_ipynb, run_code], | |
| outputs=[json_output, report_html, status_box], | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(server_name="0.0.0.0", server_port=7860) | |