Update app.py

app.py

@@ -1,15 +1,26 @@
 import pandas as pd
 import streamlit as st
-import ollama
+#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"
+)
 
 # 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 = 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):
     problem_statement = df[(df["exam name"] == exam) & (df["year"] == year) & (df["problem number"] == problem)]["problem"].values[0]