test without llm

app.py

@@ -32,10 +32,10 @@ REPO_ID = "declare-lab/flan-alpaca-large"
 
 transformers.utils.move_cache()
 
-llm = HuggingFaceHub(
-  repo_id=REPO_ID, 
-  model_kwargs={"temperature":0, "max_length":512}
-)
+#llm = HuggingFaceHub(
+#  repo_id=REPO_ID, 
+#  model_kwargs={"temperature":0, "max_length":512}
+#)
 
 embeddings = HuggingFaceEmbeddings()
 callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
@@ -45,19 +45,20 @@ def read_textfile(File):
   documents = loader.load()
   text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=10)
   docs = text_splitter.split_documents(documents)
-  db = FAISS.from_documents(docs, embeddings)
-  db.save_local(folder_path=".", index_name="faiss_index")
+  #db = FAISS.from_documents(docs, embeddings)
+  #db.save_local(folder_path=".", index_name="faiss_index")
 
 def ask_question(question, chat_history):
-  chain = load_qa_chain(llm, chain_type="stuff", verbose=False)
+  #chain = load_qa_chain(llm, chain_type="stuff", verbose=False)
   db = FAISS.load_local(folder_path=".", embeddings=embeddings, index_name="faiss_index")
   relevant_docs = db.similarity_search(question)
   
-  answer = chain.run(
-      input_documents=relevant_docs, 
-      question=question, 
-      callbacks=callback_manager
-  )
+  answer = ""
+  #answer = chain.run(
+  #    input_documents=relevant_docs, 
+  #    question=question, 
+  #    callbacks=callback_manager
+  #)
 
   chat_history.append((question, answer))
   time.sleep(1)