Update app.py

app.py

@@ -1,25 +1,24 @@
 import pandas as pd
 import streamlit as st
-#import ollama
-import transformers
+import ollama
+#import transformers
 import torch
-model_id = "meta-llama/Meta-Llama-3-70B"
-
-pipeline = transformers.pipeline(
-    "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto"
-)
+#model_id = "meta-llama/Meta-Llama-3-70B"
+# pipeline = transformers.pipeline(
+#     "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto"
+# )
 
 # Load your CSV file
 df = pd.read_csv("your_file.csv")
 
 # Function to generate responses using the Llama3 model
-# def generate_response(question):
-#     response = ollama.chat(model='llama3', messages=[{'role': 'user', 'content': question}])
-#     return response['message']['content']
-
 def generate_response(question):
-    response = pipeline(questions)
-    return response
+    response = ollama.chat(model='llama3', messages=[{'role': 'user', 'content': question}])
+    return response['message']['content']
+
+# def generate_response(question):
+#     response = pipeline(questions)
+#     return response
     
 # Define the functions for solving problems, giving hints, and creating similar problems
 def show_problem(exam, year, problem):