Update app.py

app.py

@@ -1,5 +1,10 @@
 import pandas as pd
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "	meta-llama/Llama-2-7b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # Initial data
 data = {
@@ -17,7 +22,7 @@ def add_feedback(name, feedback):
     return df
 
 # Function to get a response from GPT (placeholder for actual GPT call)
-def get_gpt_response(question):
+def get_gpt_response(query):
     # Convert DataFrame to CSV string
     csv_data = df.to_csv(index=False)
     # Create context with feedback
@@ -25,12 +30,11 @@ def get_gpt_response(question):
     Here is the data of people including their names, ages, cities they live in, and feedback:
 
     {csv_data}
-
-    Question: {question}
+    
     """
-    # Placeholder for GPT call
-    response = "Charlie, 35 years old, from Chicago is the oldest person."
-    return response
+    input_ids = tokenizer(query, return_tensors="pt").input_ids
+    output = model.generate(input_ids, max_new_tokens=100)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
 
 def ask_question(question):
     response = get_gpt_response(question)