Create model_loader.py

model_loader.py

@@ -0,0 +1,12 @@
+from sentence_transformers import SentenceTransformer
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+def load_embedding_model():
+    return SentenceTransformer("all-MiniLM-L6-v2")
+
+def load_llm():
+    model_name = "mistralai/Mistral-7B-Instruct-v0.2"  # You can change this
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=200)
+    return pipe