Update main.py

main.py

@@ -24,12 +24,28 @@ from pathlib import Path
 from typing import Any, Dict, List, Optional
 
 import numpy as np
-from artifact_validation import log_artifact_status, validate_required_artifacts
 from fastapi import BackgroundTasks, FastAPI, HTTPException, Query
 from fastapi.middleware.cors import CORSMiddleware
 from joblib import Logger
 from pydantic import BaseModel, Field
 
+try:
+    from artifact_validation import log_artifact_status, validate_required_artifacts
+except ImportError:
+    def validate_required_artifacts(models_dir):
+        return {
+            "status": "fallback",
+            "models_dir": str(models_dir),
+            "present": [],
+            "missing": [],
+            "message": "Artifact validation module unavailable; skipping startup artifact checks.",
+        }
+
+    def log_artifact_status(status):
+        logging.getLogger(__name__).warning(
+            "Artifact validation unavailable: %s", status.get("message", "unknown")
+        )
+
 try:
     from prometheus_client import (
         CONTENT_TYPE_LATEST,
@@ -86,8 +102,39 @@ from feedback import (
 )
 from lstm_model import LSTMDelayPredictor, LSTMTrainer
 from models import EnsemblePredictor
-from contextual_bandit import InterventionBandit
-from personality_behavior_fusion import PersonalityBehaviorFusionModel
+try:
+    from contextual_bandit import InterventionBandit
+except ImportError:
+    class InterventionBandit:
+        def __init__(self, *args, **kwargs):
+            self.model_path = kwargs.get("model_path")
+
+        def select_action(self, *args, **kwargs):
+            return {
+                "event_id": None,
+                "action_id": "NO_NUDGE",
+                "scores": {},
+                "context": [],
+                "policy": "fallback",
+            }
+
+        def apply_feedback(self, event_id, reward):
+            return {"action_id": "NO_NUDGE", "reward": reward}
+
+
+try:
+    from personality_behavior_fusion import PersonalityBehaviorFusionModel
+except ImportError:
+    class PersonalityBehaviorFusionModel:
+        def __init__(self, *args, **kwargs):
+            pass
+
+        def predict_from_features(self, features, behavior_sequence=None):
+            return {
+                "completion_probability": 0.5,
+                "model_type": "fusion_fallback",
+                "sequence_length": 0 if behavior_sequence is None else len(behavior_sequence),
+            }
 from similarity import (
     similar_task_recommender,
     task_clusterer,