Upload backend/hue_portal/preload_models.py with huggingface_hub

backend/hue_portal/preload_models.py

@@ -1,62 +1 @@
-"""
-Preload all models when worker process starts.
-This module is imported to ensure models are loaded before first request.
-"""
-import os
-
-
-def preload_all_models() -> None:
-    """Preload embedding, LLM, and reranker models in the worker process."""
-    print("[PRELOAD] 🔄 Starting model preload in worker process...", flush=True)
-    try:
-        # 1) Embedding model
-        try:
-            print("[PRELOAD] 📦 Preloading embedding model (BGE-M3)...", flush=True)
-            from hue_portal.core.embeddings import get_embedding_model
-
-            embedding_model = get_embedding_model()
-            if embedding_model:
-                print("[PRELOAD] ✅ Embedding model preloaded successfully", flush=True)
-            else:
-                print("[PRELOAD] ⚠️ Embedding model not loaded", flush=True)
-        except Exception as e:
-            print(f"[PRELOAD] ⚠️ Embedding model preload failed: {e}", flush=True)
-
-        # 2) LLM model (llama.cpp)
-        llm_provider = os.environ.get("DEFAULT_LLM_PROVIDER") or os.environ.get("LLM_PROVIDER", "")
-        if llm_provider.lower() == "llama_cpp":
-            try:
-                print("[PRELOAD] 📦 Preloading LLM model (llama.cpp)...", flush=True)
-                from hue_portal.chatbot.llm_integration import get_llm_generator
-
-                llm_gen = get_llm_generator()
-                if llm_gen and hasattr(llm_gen, "llama_cpp") and llm_gen.llama_cpp:
-                    print("[PRELOAD] ✅ LLM model preloaded successfully", flush=True)
-                else:
-                    print("[PRELOAD] ⚠️ LLM model not loaded (may load on first request)", flush=True)
-            except Exception as e:
-                print(f"[PRELOAD] ⚠️ LLM model preload failed: {e} (will load on first request)", flush=True)
-        else:
-            print(f"[PRELOAD] ⏭️ Skipping LLM preload (provider is {llm_provider or 'not set'}, not llama_cpp)", flush=True)
-
-        # 3) Reranker model
-        try:
-            print("[PRELOAD] 📦 Preloading reranker model...", flush=True)
-            from hue_portal.core.reranker import get_reranker
-
-            reranker = get_reranker()
-            if reranker:
-                print("[PRELOAD] ✅ Reranker model preloaded successfully", flush=True)
-            else:
-                print("[PRELOAD] ⚠️ Reranker model not loaded (may load on first request)", flush=True)
-        except Exception as e:
-            print(f"[PRELOAD] ⚠️ Reranker preload failed: {e} (will load on first request)", flush=True)
-
-        print("[PRELOAD] ✅ Model preload completed in worker process", flush=True)
-    except Exception as e:
-        print(f"[PRELOAD] ⚠️ Model preload error: {e} (models will load on first request)", flush=True)
-        import traceback
-
-        traceback.print_exc()
-
-
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