Initial commit

backend/app/services.py

@@ -0,0 +1,138 @@
+import os
+from typing import List
+from openai import OpenAI
+from sqlalchemy.orm import Session
+from . import models
+from .curriculum import QUESTIONS, SKILLS
+
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+
+SYSTEM_PROMPT = """
+Tu es ProfAmi, un professeur virtuel français pour enfants de 8 à 12 ans.
+Règles :
+- Tu parles toujours en français simple et chaleureux.
+- Tu donnes des explications très courtes, puis un mini exemple.
+- Tu tiens compte du niveau de l'élève et de ses faiblesses indiquées dans le contexte.
+- Tu n'inventes pas la progression : elle est fournie dans le contexte.
+- Tu encourages sans infantiliser.
+- Quand l'élève se trompe, tu expliques calmement puis proposes une question très simple.
+- Tu enseignes principalement le programme national français niveau primaire/cycle 3.
+""".strip()
+
+
+def seed_skills(db: Session) -> None:
+    for skill in SKILLS:
+        existing = db.query(models.Skill).filter(models.Skill.code == skill["code"]).first()
+        if not existing:
+            db.add(models.Skill(**skill))
+    db.commit()
+
+
+def ensure_student_mastery(db: Session, student: models.Student) -> None:
+    all_skills = db.query(models.Skill).all()
+    for skill in all_skills:
+        found = (
+            db.query(models.StudentSkillMastery)
+            .filter_by(student_id=student.id, skill_id=skill.id)
+            .first()
+        )
+        if not found:
+            db.add(models.StudentSkillMastery(student_id=student.id, skill_id=skill.id))
+    db.commit()
+
+
+def get_student_context(db: Session, student_id: int) -> str:
+    student = db.query(models.Student).filter_by(id=student_id).first()
+    mastery = (
+        db.query(models.StudentSkillMastery, models.Skill)
+        .join(models.Skill, models.Skill.id == models.StudentSkillMastery.skill_id)
+        .filter(models.StudentSkillMastery.student_id == student_id)
+        .all()
+    )
+    recent_messages = (
+        db.query(models.Message)
+        .filter_by(student_id=student_id)
+        .order_by(models.Message.created_at.desc())
+        .limit(6)
+        .all()
+    )
+
+    lines: List[str] = [
+        f"Élève: {student.first_name}, {student.age} ans, classe {student.grade}.",
+        "Progression par compétence:",
+    ]
+    for mastery_row, skill in mastery:
+        lines.append(
+            f"- {skill.label}: score={mastery_row.mastery_score:.1f}, confiance={mastery_row.confidence:.2f}, preuves={mastery_row.evidence_count}"
+        )
+    lines.append("Historique récent:")
+    for message in reversed(recent_messages):
+        lines.append(f"- {message.role}: {message.content}")
+    return "\n".join(lines)
+
+
+def build_llm_reply(db: Session, student_id: int, user_message: str) -> str:
+    context = get_student_context(db, student_id)
+    response = client.responses.create(
+        model="gpt-4.1-mini",
+        input=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {
+                "role": "user",
+                "content": f"Contexte pédagogique:\n{context}\n\nMessage de l'élève:\n{user_message}",
+            },
+        ],
+        temperature=0.7,
+    )
+    return response.output_text.strip()
+
+
+def pick_next_skill(db: Session, student_id: int) -> models.Skill:
+    weakest = (
+        db.query(models.StudentSkillMastery)
+        .filter_by(student_id=student_id)
+        .order_by(models.StudentSkillMastery.mastery_score.asc())
+        .first()
+    )
+    return db.query(models.Skill).filter_by(id=weakest.skill_id).first()
+
+
+def evaluate_answer(db: Session, student_id: int, skill_code: str, answer: str):
+    q = QUESTIONS[skill_code]
+    normalized_student = answer.strip().lower()
+    normalized_expected = q["expected_answer"].strip().lower()
+    correct = normalized_student == normalized_expected
+
+    skill = db.query(models.Skill).filter_by(code=skill_code).first()
+    mastery = (
+        db.query(models.StudentSkillMastery)
+        .filter_by(student_id=student_id, skill_id=skill.id)
+        .first()
+    )
+
+    if correct:
+        mastery.mastery_score = min(100.0, mastery.mastery_score + 8)
+        mastery.confidence = min(1.0, mastery.confidence + 0.15)
+        feedback = q["feedback_ok"]
+    else:
+        mastery.mastery_score = max(0.0, mastery.mastery_score - 6)
+        mastery.confidence = min(1.0, mastery.confidence + 0.1)
+        feedback = q["feedback_ko"]
+
+    mastery.evidence_count += 1
+
+    db.add(
+        models.AssessmentAttempt(
+            student_id=student_id,
+            skill_code=skill_code,
+            question=q["question"],
+            expected_answer=q["expected_answer"],
+            student_answer=answer,
+            is_correct=1 if correct else 0,
+            feedback=feedback,
+        )
+    )
+    db.commit()
+    db.refresh(mastery)
+    return correct, feedback, mastery.mastery_score