Update app.py

app.py

@@ -84,12 +84,6 @@ def embed_documents_into_vectorstore(chunks, model_name, persist_directory):
     vectorstore.add_documents(chunks)
     return vectorstore
 
-# Setup LLM
-def setup_llm(model_name, temperature, api_key):
-    llm = ChatGroq(model=model_name, temperature=temperature, api_key=api_key)
-    return llm
-
-                   
 def rag_workflow(query):
     """
     RAGChain class to perform the complete RAG workflow.
@@ -145,7 +139,7 @@ def initialize():
 
     filename = "test"
     vector_store = embed_documents_into_vectorstore(doc_chunks + code_chunks, EMBEDDING_MODEL_NAME, f"{DATA_DIR}/{filename}")
-    llm = setup_llm(LLM_MODEL_NAME, LLM_TEMPERATURE, GROQ_API_KEY)
+    llm = get_groq_llm(LLM_MODEL_NAME, LLM_TEMPERATURE, GROQ_API_KEY)
 
     from langchain_community.document_loaders import TextLoader