Formatting code

app.py

@@ -6,6 +6,7 @@ from langchain.document_loaders import PDFMinerLoader
 from langchain.indexes import VectorstoreIndexCreator
 import os
 
+
 def set_openai_key(raw_key):
     logging.warning(raw_key)
     os.environ["OPENAI_API_KEY"] = raw_key
@@ -30,7 +31,8 @@ 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()
@@ -48,18 +50,30 @@ def create_ask(pdf_object, question_text):
 
 with gr.Blocks() as demo:
     # pdf_button = gr.Button(value="pdf_button")
-    oai_token = gr.Textbox(label="OpenAI Token", placeholder="Lm-iIas452gaw3erGtPar26gERGSA5RVkFJQST23WEG524EWEl")
+    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"
+    )
     chain_state = gr.State()
-    # pdf_button.click(create_langchain, inputs=pdf_object, outputs=chain_state)
-    question_box = gr.Textbox(label="Question", value="Which are the candidate top hard skills? Enumerate in few bullet points.")
+    question_placeholder = """
+    Enumerate the candidate's top 5 hard skills and rate them by importance from 0 to 5.
+    Example:
+    - Algebra 5/5 
+    """
+    question_box = gr.Textbox(label="Question", value=question_placeholder)
     qa_button = gr.Button(value="Submit question", interactive=False)
 
-    lchain = pdf_object.change(create_langchain, inputs=pdf_object, outputs=[chain_state, qa_button])
-    qa_button.click(ask_question, inputs=[chain_state, question_box], outputs=gr.Textbox(label="Answer"))
+    lchain = pdf_object.change(
+        create_langchain, inputs=pdf_object, outputs=[chain_state, qa_button]
+    )
+    qa_button.click(
+        ask_question,
+        inputs=[chain_state, question_box],
+        outputs=gr.Textbox(label="Answer"),
+    )
 
-demo.launch(debug=True)
+demo.launch(debug=True)