Update app.py

app.py

@@ -4,6 +4,18 @@ from sentence_transformers import SentenceTransformer, util
 import os
 import requests
 from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+
+# Load the model and tokenizer
+model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# If you have a GPU, move the model to it
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device) 
+
 
 # Constants for enhanced organization
 system_message = "You are GitBot, the Github project guardian angel. You resolve issues and propose implementation of feature requests"
@@ -41,12 +53,6 @@ from huggingface_hub import InferenceClient,HfApi
 
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
-
-# Load the pre-trained model and tokenizer
-model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
-model = AutoModelForCausalLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
 # Define input prompt
 input_prompt = "(input value = highest-level-quality code content invocation ; True)"
 
@@ -62,8 +68,8 @@ generated_code_str = tokenizer.batch_decode(generated_code, skip_special_tokens=
 # Print the generated code
 print(generated_code_str)
 
-DEFAULT_MODEL = "apple/OpenELM"
-MAX_RELATED_ISSUES = 3
+DEFAULT_MODEL = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+MAX_RELATED_ISSUES = 5
 
 # Load a pre-trained model for sentence similarity
 similarity_model = SentenceTransformer('all-mpnet-base-v2')