Divers, en lien avec DMI04 (gemini_for_enonce.py, smaller images, link to enonce.pdf)

2026-05-09 16:26:01 +02:00
parent 8d9165d0ac
commit 0836d5809d
9 changed files with 202 additions and 59 deletions
@@ -0,0 +1,136 @@
+import os
+import sys
+import argparse
+from pathlib import Path
+from pydantic import BaseModel, Field
+from typing import List
+from google import genai
+from google.genai import types
+
+MODEL_ID = "gemini-3-flash-preview"
+api_key = os.environ.get("GEMINI_API_KEY")
+
+class QuestionItem(BaseModel):
+    label: str = Field(description="The unique label of the question (e.g., '1.a', 'Exercice 1')")
+    question_content: str = Field(description="The source text of the question, strictly extracted from the enonce file, EXCLUDING the label itself.")
+    solution_content: str = Field(description="The source text of the solution, strictly extracted from the correction file.")
+
+class ExamExtraction(BaseModel):
+    questions: List[QuestionItem]
+
+PROMPT = """I am providing:
+1. A PDF of an exam (`enonce.pdf`)
+2. The source code of the exam questions (`enonce` file)
+3. The source code of the exam solutions (`correction` file)
+
+Your task:
+ 1. Identify all distinct question labels using the PDF document.
+    These labels should be unique : use `Ex 1 : 1)a)` or `I)1)b)`.
+ 2. For each label, extract its exact corresponding question text
+    from the `enonce` source file. Do not include the label itself
+    in this extracted text (nor LaTeX like `item` nor org-mode list
+    labelling like `2.`).
+ 3. For each label, extract its exact corresponding solution textual
+    content from the `correction` source file. Return the result as
+    a JSON list in the exact reading order of the document.
+"""
+
+def find_file(folder: Path, base_name: str) -> Path:
+    for ext in [".org", ".tex"]:
+        path = folder / f"{base_name}{ext}"
+        if path.is_file():
+            return path
+    return None
+
+def process_exam(folder_path: str):
+    folder = Path(folder_path)
+
+    # 1. Resolve files
+    pdf_path = folder / "enonce.pdf"
+    enonce_path = find_file(folder, "enonce")
+    correction_path = find_file(folder, "correction")
+
+    missing = []
+    if not pdf_path.is_file(): missing.append("enonce.pdf")
+    if not enonce_path: missing.append("enonce.org or enonce.tex")
+    if not correction_path: missing.append("correction.org or correction.tex")
+
+    if missing:
+        print(f"Error: Missing files in {folder}: {', '.join(missing)}")
+        sys.exit(1)
+
+    print("Reading files...")
+    pdf_bytes = pdf_path.read_bytes()
+    enonce_text = enonce_path.read_text(encoding="utf-8")
+    correction_text = correction_path.read_text(encoding="utf-8")
+
+    client = genai.Client(api_key=api_key)
+
+    contents = [
+        types.Content(
+            role="user",
+            parts=[
+                types.Part.from_text(text=PROMPT),
+                types.Part.from_bytes(data=pdf_bytes, mime_type="application/pdf"),
+                types.Part.from_text(text=f"--- ENONCE SOURCE ({enonce_path.name}) ---\n{enonce_text}"),
+                types.Part.from_text(text=f"--- CORRECTION SOURCE ({correction_path.name}) ---\n{correction_text}"),
+            ],
+        )
+    ]
+
+    config = types.GenerateContentConfig(
+        temperature=0.1,
+        response_mime_type="application/json",
+        response_json_schema=ExamExtraction.model_json_schema(),
+    )
+
+    print("Sending request to Gemini...")
+    response = client.models.generate_content(
+        model=MODEL_ID,
+        contents=contents,
+        config=config
+    )
+
+    extracted_data = ExamExtraction.model_validate_json(response.text)
+
+    # 2. Setup output directories
+    text_dir = folder / "Text"
+    sol_dir = folder / "Sol"
+    text_dir.mkdir(exist_ok=True)
+    sol_dir.mkdir(exist_ok=True)
+
+    labels_file = folder / "labels"
+
+    print("Writing files...")
+    with open(labels_file, "w", encoding="utf-8") as flabels:
+        for q in extracted_data.questions:
+            # Sanitize label for filesystem (prevent directory traversal if label contains '/')
+            safe_label = q.label.replace("/", "_")
+
+            flabels.write(f"{safe_label}\n")
+
+            # Fix double-escaped newlines
+            q_content = q.question_content.replace("\\n", "\n")
+            s_content = q.solution_content.replace("\\n", "\n")
+            
+
+            # Write Text/label
+            with open(text_dir / safe_label, "w", encoding="utf-8") as f:
+                f.write(f"{q.label}\n{q.question_content}")
+
+            # Write Sol/label
+            with open(sol_dir / safe_label, "w", encoding="utf-8") as f:
+                f.write(f"{q.label}\n{q.solution_content}")
+
+    print(f"Success! Processed {len(extracted_data.questions)} questions.")
+
+if __name__ == "__main__":
+    if not api_key:
+        print("Error: GEMINI_API_KEY environment variable is not set.")
+        sys.exit(1)
+
+    parser = argparse.ArgumentParser(description="Extract exam and solution code via Gemini.")
+    parser.add_argument("folder", help="Directory containing the exam files")
+
+    args = parser.parse_args()
+    process_exam(args.folder)