Update app.py

app.py

@@ -1,10 +1,35 @@
 import streamlit as st
 from langchain_google_genai import ChatGoogleGenerativeAI
 import re
+from langchain_huggingface import HuggingFaceEndpoint
+from langchain.chains import LLMChain
+from langchain_core.prompts import PromptTemplate
+import os
+
+# os.environ["HUGGINGFACEHUB_API_TOKEN"] = HUGGINGFACEHUB_API_TOKEN
+# HUGGINGFACEHUB_API_TOKEN = os.getenv["HUGGINGFACEHUB_API_TOKEN"]
+
+# repo_id = "Qwen/Qwen3-8B"
+# llm = HuggingFaceEndpoint(
+#     repo_id=repo_id,
+#     max_length=512,
+#     temperature=0.5,
+# )
+# llm_chain = prompt | llm
+# print(llm_chain.invoke({"question": question}))
+
 
 def generate_question(role, topic, difficulty_level):
     prompt = f"Generate an interview question for the role of {role} on the topic of {topic} with difficulty level {difficulty_level}."
-    llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-lite", google_api_key=st.secrets["GOOGLE_API_KEY"])
+    # llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-lite", google_api_key=st.secrets["GOOGLE_API_KEY"])
+    repo_id = "Qwen/Qwen3-8B"
+    llm = HuggingFaceEndpoint(
+        repo_id=repo_id,
+        max_length=512,
+        temperature=0.5,
+    )
+    # llm_chain = prompt | llm
+    prompt = PromptTemplate.from_template(prompt)
     response = llm.invoke(prompt)
     response = response.content