Update app.py

app.py

@@ -6,13 +6,13 @@ import sqlite3
 import ocrmypdf
 import logging
 
-from langchain.document_loaders import OnlinePDFLoader  # for loading the pdf
+from langchain.document_loaders import OnlinePDFLoader  # for loading the PDF
 from langchain.embeddings import HuggingFaceEmbeddings  # open source embedding model
 from langchain.text_splitter import CharacterTextSplitter
-from langchain.vectorstores import Chroma  # for vectorization
+from langchain_community.vectorstores import Chroma  # updated import for vectorization
 from langchain.chains import RetrievalQA  # for QA chain
-from langchain.chat_models import ChatOpenAI  # ChatGPT model
-from langchain_core.prompts import PromptTemplate  # prompt template import
+from langchain_community.chat_models import ChatOpenAI  # updated import for ChatOpenAI
+from langchain_core.prompts import PromptTemplate  # updated import per deprecation notice
 
 # Setup basic logging
 logging.basicConfig(level=logging.INFO)
@@ -237,7 +237,6 @@ def answer_query(query):
 def get_log():
     return log_messages
 
-# Define simple CSS and title HTML
 css = """
 #col-container {max-width: 700px; margin: auto;}
 """
@@ -249,9 +248,8 @@ title = """
 </div>
 """
 
-# Build the Gradio interface
 with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
-    with gr.Column(id="col-container"):
+    with gr.Column(elem_id="col-container"):
         gr.HTML(title)
     
     with gr.Tab("Chatbot"):
@@ -283,7 +281,6 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
                 answers_df = gr.Dataframe(label="Pre-defined Answers")
                 answer_predefined_btn = gr.Button("Get Answers")
             
-            # Log window to display errors and info
             log_window = gr.Textbox(label="Log Window", interactive=False, lines=10)
     
     with gr.Tab("OCR Converter"):
@@ -295,7 +292,6 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
     
     with gr.Tab("Upload Question Set"):
         with gr.Column():
-            # Now only two document types are available
             document_type_for_questionset = gr.Dropdown(choices=["DOC_A", "DOC_B"], label="Select Document Type")
             tag_for_questionset = gr.Textbox(label="Name for Question Set (e.g., basic-set)")
             csv_file = gr.File(label="Load CSV (fields,question)", file_types=['.csv'], type='filepath')
@@ -306,7 +302,6 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
     refresh_log_btn = gr.Button("Refresh Log")
     refresh_log_btn.click(get_log, outputs=log_window)
     
-    # Set up button actions
     load_pdf_btn.click(load_pdf_and_generate_embeddings, inputs=[pdf_doc, open_ai_key, relevant_pages], outputs=status)
     summarize_pdf_btn.click(summarize_contents, outputs=summary)
     submit_query_btn.click(answer_query, inputs=input_query, outputs=output_answer)
@@ -318,5 +313,4 @@ with gr.Blocks(css=css, theme=gr.themes.Monochrome()) as demo:
     convert_btn.click(ocr_converter, inputs=image_pdf, outputs=ocr_pdf)
     load_csv_btn.click(load_csv_and_store_questionset_into_sqlite, inputs=[csv_file, document_type_for_questionset, tag_for_questionset], outputs=status_for_csv)
 
-# Launch the Gradio app
 demo.launch(debug=True)