Update app.py

app.py

@@ -11,7 +11,7 @@ from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import Chroma  # for the vectorization part
 from langchain.chains import RetrievalQA  # for conversing with chatGPT
 from langchain.chat_models import ChatOpenAI  # the LLM model we'll use (ChatGPT)
-from langchain import PromptTemplate
+from langchain_core.prompts import PromptTemplate  # updated import per warning
 
 def load_pdf_and_generate_embeddings(pdf_doc, open_ai_key, relevant_pages):
     # If an OpenAI API key is provided, it will be used for ChatOpenAI (GPT-4)
@@ -297,7 +297,7 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
     with gr.Tab("Chatbot"):
         with gr.Column():
             open_ai_key = gr.Textbox(label="Your GPT-4 OpenAI API key", type="password")
-            pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type='file')
+            pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type='filepath')
             relevant_pages = gr.Textbox(label="*Optional - List comma separated page numbers to load or leave this field blank to use the entire PDF")
         
             with gr.Row():
@@ -325,10 +325,10 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
               
     with gr.Tab("OCR Converter"):
         with gr.Column():
-            image_pdf = gr.File(label="Load the pdf to be converted", file_types=['.pdf'], type='file')
+            image_pdf = gr.File(label="Load the pdf to be converted", file_types=['.pdf'], type='filepath')
             
         with gr.Row():
-            ocr_pdf = gr.File(label="OCR'd pdf", file_types=['.pdf'], type='file', file_count="single")
+            ocr_pdf = gr.File(label="OCR'd pdf", file_types=['.pdf'], type='filepath', file_count="single")
             convert_into_ocr = gr.Button("Convert").style(full_width=False)
                 
     with gr.Tab("Upload Question Set"):
@@ -591,7 +591,7 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
             ]
             document_type_for_questionset = gr.Dropdown(choices=document_types, label="Select the Document Type")
             tag_for_questionset = gr.Textbox(label="Please provide a name for the question set. Ex: rwikd-dot-basic-questionset-20230707.")
-            csv_file = gr.File(label="Load a csv - 2 columns with the headers as field, question", file_types=['.csv'], type='file')
+            csv_file = gr.File(label="Load a csv - 2 columns with the headers as field, question", file_types=['.csv'], type='filepath')
             
             with gr.Row():
                 status_for_loading_csv = gr.Textbox(label="Status", placeholder="", interactive=False)