Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,18 +1,17 @@
 import streamlit as st
 from langchain_huggingface import HuggingFaceEndpoint
 from transformers import pipeline
-# import os
 
 # constants
 QUESTION = "Compute the integral of f(x) = x^2."
 MODEL = "Qwen/Qwen3-Embedding-0.6B"
-max_new_tokens = 130
-temperature = 0.7
 
-# creating pipeline
-# token = os.getenv("HUGGING_FACE_TOKEN")
-
-# pipeline = pipeline(task="text-generation", model="brgx53/3Blarenegv3-ECE-PRYMMAL-Martial")
+# remembers session
+if "response" not in st.session_state:
+    st.session_state.response = ""
+    
+# create llm
+llm = get_llm()
 
 # Initialize session state
 if "help_clicks" not in st.session_state:
@@ -96,7 +95,7 @@ st.markdown(
 )
 
 # source: https://medium.com/@james.irving.phd/creating-your-personal-chatbot-using-hugging-face-spaces-and-streamlit-596a54b9e3ed
-def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.1):
+def get_llm_hf_inference(model_id=MODEL, max_new_tokens=130, temperature=0.7):
     """
     Returns a language model for HuggingFace inference.