H

app/api/__init__.py

@@ -15,6 +15,7 @@ from . import onevone
 from . import mentor
 from . import chatbot
 from . import daily_challenge
+from . import ai_recommend
 
 __all__ = [
     "auth",
@@ -27,4 +28,5 @@ __all__ = [
     "mentor",
     "chatbot",
     "daily_challenge",
+    "ai_recommend",
 ]

app/api/ai_recommend.py

@@ -0,0 +1,187 @@
+"""``/api/ai/recommend`` — AI-powered next-challenge recommendation.
+
+Analyzes the user's completion history and picks the challenge type they've
+done least, then selects a random challenge from that pool. Returns the full
+set of parameters the front-end needs to start a ``TrainingSession``.
+"""
+
+import random
+from typing import Optional
+
+import httpx
+from fastapi import APIRouter, Depends
+from pydantic import BaseModel
+
+from app.core.auth import get_current_user
+from app.core.config import SUPABASE_URL, SUPABASE_ANON_KEY
+from app.services.supabase_service import supabase_headers
+
+
+router = APIRouter()
+
+
+class AiRecommendResponse(BaseModel):
+    categoryId: str
+    pathId: str
+    moduleId: str
+    teamRole: str
+    challengeId: str
+    title: str
+    reason: str  # short AI-style justification
+
+
+# All five challenge types with their table, front-end params, and
+# the category key used in ``user_completions``.
+_CHALLENGE_TYPES: list[dict] = [
+    {
+        "table": "encryption_challenges",
+        "team": "red",
+        "categoryId": "encryption",
+        "pathId": "cryptography",
+        "moduleId": "crypto",
+        "completion_category": "crypto",
+    },
+    {
+        "table": "code_fixing_challenges",
+        "team": "blue",
+        "categoryId": "code_analysis",
+        "pathId": "web-security",
+        "moduleId": "code-fixing",
+        "completion_category": "code-fixing",
+    },
+    {
+        "table": "log_analysis_challenges",
+        "team": "blue",
+        "categoryId": "log_analysis",
+        "pathId": "log-analysis",
+        "moduleId": "log-analysis",
+        "completion_category": "log-analysis",
+    },
+    {
+        "table": "vulnerability_hunter_challenges",
+        "team": "blue",
+        "categoryId": "vulnerability_hunter",
+        "pathId": "secure-coding",
+        "moduleId": "vulnerability-hunter",
+        "completion_category": "vulnerability-hunter",
+    },
+    {
+        "table": "web_exploitation_challenges",
+        "team": "red",
+        "categoryId": "web_exploitation",
+        "pathId": "xss",
+        "moduleId": "web-exploitation",
+        "completion_category": "web-exploitation",
+    },
+]
+
+# Short AI-sounding reasons keyed by completion_category
+_REASONS: dict[str, list[str]] = {
+    "crypto": [
+        "نقاط ضعفك في التشفير تحتاج تقوية — جرّب هذا التحدي لتصقل مهاراتك",
+        "التشفير هو خط الدفاع الأول في الأمن السيبراني — حان وقت التمرّن",
+        "مهاراتك في فك التشفير بحاجة إلى صقل — هذا التحدي سيساعدك",
+    ],
+    "code-fixing": [
+        "اكتشاف الثغرات في الكود مهارة لا غنى عنها — طوّرها بهذا التحدي",
+        "المبرمجون المحترفون يقرؤون الكود بحثاً عن الثغرات — كن منهم",
+        "هذا التحدي سيدربك على تحديد نقاط الضعف في التطبيقات",
+    ],
+    "log-analysis": [
+        "تحليل السجلات يكشف الهجمات قبل فوات الأوان — درّب عينك",
+        "محللو SOC المتميزون يميّزون الأنماط في السجلات — تدرب هنا",
+        "هذا التحدي يحاكي هجوماً حقيقياً — حلّله وكن جاهزاً",
+    ],
+    "vulnerability-hunter": [
+        "صائد الثغرات الحقيقي لا يفوته أي خلل — اختبر نفسك",
+        "كلما اكتشفت ثغرات أكثر، كلما أصبحت أقوى — هذا هو تحديك التالي",
+        "ثغرات اليوم هي ثغرات الغد — تدرب على اكتشافها الآن",
+    ],
+    "web-exploitation": [
+        "الهجمات الإلكترونية تستهدف الويب أولاً — كن مستعداً",
+        "هذا التحدي يحاكي هجوماً حقيقياً على تطبيقات الويب",
+        "الـ Bug Bounty يبدأ بفهم الثغرات — هذا هو تحديك التالي",
+    ],
+}
+
+
+@router.get("/api/ai/recommend")
+async def get_ai_recommendation(user: dict = Depends(get_current_user)):
+    if not SUPABASE_URL or not SUPABASE_ANON_KEY:
+        return {"error": "AI recommendation unavailable"}
+
+    # 1. Get completions per category for this user
+    completions = await _fetch_user_completions(user["user_id"])
+    if completions is None:
+        completions = {}
+
+    # 2. Sort challenge types by completion count (ascending)
+    scored = []
+    for ct in _CHALLENGE_TYPES:
+        cat = ct["completion_category"]
+        count = completions.get(cat, 0)
+        scored.append((count, ct))
+    scored.sort(key=lambda x: x[0])
+
+    # 3. Try each type from least-completed to most, pick one with available challenges
+    for count, ct in scored:
+        row = await _fetch_random_challenge(ct["table"], ct["team"])
+        if row is None:
+            continue
+
+        reason = _pick_reason(ct["completion_category"])
+        return AiRecommendResponse(
+            categoryId=ct["categoryId"],
+            pathId=ct["pathId"],
+            moduleId=ct["moduleId"],
+            teamRole=ct["team"],
+            challengeId=row["id"],
+            title=row.get("title", "Untitled Challenge"),
+            reason=reason,
+        )
+
+    return {"error": "لا توجد تحديات متاحة حالياً"}
+
+
+async def _fetch_user_completions(user_id: str) -> Optional[dict[str, int]]:
+    """Return {category: count} for this user, or None on error."""
+    url = f"{SUPABASE_URL}/rest/v1/user_completions?user_id=eq.{user_id}&select=category"
+    try:
+        async with httpx.AsyncClient(timeout=10) as client:
+            r = await client.get(url, headers=supabase_headers())
+            if r.status_code == 200:
+                counts: dict[str, int] = {}
+                for row in r.json():
+                    cat = row.get("category", "")
+                    if cat:
+                        counts[cat] = counts.get(cat, 0) + 1
+                return counts
+    except Exception as e:
+        print(f"[ai_recommend] fetch completions error: {e}")
+    return None
+
+
+async def _fetch_random_challenge(table: str, team_role: str) -> Optional[dict]:
+    """Pick a random challenge from the given pool table."""
+    url = (
+        f"{SUPABASE_URL}/rest/v1/{table}"
+        f"?team_role=eq.{team_role}&select=id,title"
+        f"&limit=20&order=created_at.desc"
+    )
+    try:
+        async with httpx.AsyncClient(timeout=10) as client:
+            r = await client.get(url, headers=supabase_headers())
+            if r.status_code == 200:
+                rows = r.json()
+                if rows:
+                    return random.choice(rows)
+    except Exception as e:
+        print(f"[ai_recommend] {table}: {e}")
+    return None
+
+
+def _pick_reason(completion_category: str) -> str:
+    reasons = _REASONS.get(completion_category)
+    if not reasons:
+        return "التحدي الأمثل لمستواك الحالي — جرّبه الآن"
+    return random.choice(reasons)

app/main.py

@@ -90,6 +90,7 @@ from app.api import (  # noqa: E402  (import after middleware so order is right)
     mentor as _mentor,
     chatbot as _chatbot,
     daily_challenge as _daily_challenge,
+    ai_recommend as _ai_recommend,
 )
 
 
@@ -105,6 +106,7 @@ def _include_all_routers(app: FastAPI) -> None:
     app.include_router(_mentor.router)
     app.include_router(_chatbot.router)
     app.include_router(_daily_challenge.router)
+    app.include_router(_ai_recommend.router)
 
 
 _include_all_routers(app)