latest version

app.py

@@ -15,7 +15,7 @@ from langchain.callbacks.manager import CallbackManager
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
 import gradio as gr
 
-
+# example questions
 question_examples = [
     "What is the name of the captain of the Nautilus?",
     "What are the names of the crew members of the Nautilus?",
@@ -27,17 +27,20 @@ question_examples = [
     "Why doesn't Captain Nemo hate the society?"
 ]
 
+# define the API token
 os.environ["HUGGINGFACEHUB_API_TOKEN"] = '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'
+
+# used repository for llm
 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()
+embeddings = HuggingFaceEmbeddings()
 callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
 
 def read_textfile(File):
@@ -45,20 +48,19 @@ 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)
-  #db = FAISS.load_local(folder_path=".", embeddings=embeddings, index_name="faiss_index")
-  #relevant_docs = db.similarity_search(question)
+  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 = ""
-  #answer = chain.run(
-  #    input_documents=relevant_docs, 
-  #    question=question, 
-  #    callbacks=callback_manager
-  #)
+  answer = chain.run(
+      input_documents=relevant_docs, 
+      question=question, 
+      callbacks=callback_manager
+  )
 
   chat_history.append((question, answer))
   time.sleep(1)
@@ -84,5 +86,5 @@ with gr.Blocks() as demo:
       inputs=[ask_textbox, chatbot], 
       outputs=[ask_textbox, chatbot]
   )
-  clear_button.click(lambda: None, None, chatbot, queue=False)
+  clear_button.click(lambda: None, None, chatbot, queue=False)