Update app.py

app.py

@@ -7,9 +7,9 @@ sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
 from sentence_transformers import SentenceTransformer
 import chromadb
 from datasets import load_dataset
-from transformers import AutoModelForCausalLM, AutoTokenizer
+# from transformers import AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
-
+from mistral_inference.model import Transformer
 
 # Function to clear the cache
 def clear_cache(model_name):
@@ -82,8 +82,11 @@ vector_store.populate_vectors(dataset=None)
 # model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # load model orca-mini general purpose model
-tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
-model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
+# tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
+# model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
+
+tokenizer = MistralTokenizer.from_file(f"{mistral_models_path}/tokenizer.model.v3")
+model = Transformer.from_folder(mistral_models_path)
 
 # Define the chatbot response function
 def chatbot_response(user_input):