Create model_loader.py

model_loader.py

@@ -0,0 +1,27 @@
+import os
+from huggingface_hub import hf_hub_download
+from llama_cpp import Llama
+
+# Quantized GGUF Model tracking paths
+REPO_ID = "Qwen/Qwen2.5-7B-Instruct-GGUF"
+MODEL_FILENAME = "qwen2.5-7b-instruct-q4_k_m.gguf"
+
+print("[SYSTEM] Fetching quantized model files from HuggingFace Hub cluster...")
+model_path = hf_hub_download(repo_id=REPO_ID, filename=MODEL_FILENAME)
+print(f"[SYSTEM] Model secured safely at: {model_path}")
+
+def get_local_llm_instance():
+    """
+    Initializes LlamaCpp instance allocated to optimal CPU thread counts.
+    Context size restricted to 2048 to drastically speed up processing on 15GB RAM.
+    """
+    print("[SYSTEM] Loading weights inside internal RAM parameters...")
+    llm = Llama(
+        model_path=model_path,
+        n_ctx=2048,          # Optimized context tracking limit
+        n_threads=4,         # Standard core optimizations for HuggingFace Free Tier
+        n_batch=512,         # Batch sequence calculation limit
+        verbose=False
+    )
+    print("[SYSTEM] Model weights successfully attached!")
+    return llm