Remove unused & unneded code

- Deprecated functions
- Old loggers
- Formatted

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-import logging
 from langchain.chains import RetrievalQA
 from langchain.llms import OpenAI
 from langchain.document_loaders import PDFMinerLoader
@@ -8,12 +7,11 @@ import os
 
 
 def set_openai_key(raw_key):
-    logging.warning(raw_key)
     os.environ["OPENAI_API_KEY"] = raw_key
+    return gr.File.update(interactive=True)
 
 
 def create_langchain(pdf_object):
-    logging.info(f"Creating langchain for {pdf_object.name}")
     loader = PDFMinerLoader(pdf_object.name)
     index_creator = VectorstoreIndexCreator()
     docsearch = index_creator.from_loaders([loader])
@@ -29,36 +27,23 @@ def create_langchain(pdf_object):
 
 
 def ask_question(chain, question_text):
-    logging.info(type(chain))
-    return chain({"question": question_text})["result"]
-
-
-def create_ask(pdf_object, question_text):
-    loader = PDFMinerLoader(pdf_object.name)
-    index_creator = VectorstoreIndexCreator()
-    docsearch = index_creator.from_loaders([loader])
-    chain = RetrievalQA.from_chain_type(
-        llm=OpenAI(),
-        chain_type="stuff",
-        retriever=docsearch.vectorstore.as_retriever(),
-        input_key="question",
-        verbose=True,
-        return_source_documents=True,
-    )
     return chain({"question": question_text})["result"]
 
 
 with gr.Blocks() as demo:
-    # pdf_button = gr.Button(value="pdf_button")
+    # Layout
     oai_token = gr.Textbox(
         label="OpenAI Token",
         placeholder="Lm-iIas452gaw3erGtPar26gERGSA5RVkFJQST23WEG524EWEl",
     )
-    oai_token.change(set_openai_key, oai_token)
+
     pdf_object = gr.File(
-        label="Upload your CV in PDF format", file_count="single", type="file"
+        label="Upload your CV in PDF format",
+        file_count="single",
+        type="file",
+        interactive=False,
     )
-    chain_state = gr.State()
+
     question_placeholder = """
     Enumerate the candidate's top 5 hard skills and rate them by importance from 0 to 5.
     Example:
@@ -67,6 +52,11 @@ with gr.Blocks() as demo:
     question_box = gr.Textbox(label="Question", value=question_placeholder)
     qa_button = gr.Button(value="Submit question", interactive=False)
 
+    # Sate objects
+    chain_state = gr.State()
+
+    # Actions
+    oai_token.change(set_openai_key, inputs=oai_token, outputs=pdf_object)
     lchain = pdf_object.change(
         create_langchain, inputs=pdf_object, outputs=[chain_state, qa_button]
     )