Update app.py

app.py

@@ -6,36 +6,18 @@ 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):
     question = f"Generate an interview question for the role of {role} on the topic of {topic} with difficulty level {difficulty_level}."
     template = """Question: {question}
                   Answer: 
                 """
-    # llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-lite", google_api_key=st.secrets["GOOGLE_API_KEY"])
-    repo_id =  "mistralai/Mistral-7B-Instruct-v0.2" #"Qwen/Qwen3-8B"
-    llm = HuggingFaceEndpoint(
-        repo_id=repo_id,
-        # max_length=512,
-        temperature=0.5,
-    )
-    # llm_chain = prompt | llm
+    llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-lite", google_api_key=st.secrets["GOOGLE_API_KEY"])
+    
+    llm_chain = prompt | llm
     prompt = PromptTemplate.from_template(template)
     # prompt = PromptTemplate.from_template(prompt)
-    llm_chain = prompt | llm
-    # response = llm_chain.invoke(prompt)
+    # llm_chain = prompt | llm
+    response = llm_chain.invoke(prompt)
     llm_chain.invoke({"question": question})
     response = response.content