Update app.py

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import streamlit as st
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import Chroma
@@ -8,7 +9,6 @@ from langchain.document_loaders import PyPDFLoader
 import os
 import fitz
 from PIL import Image
-import streamlit as st
 
 # Global variables
 COUNT, N = 0, 0
@@ -18,11 +18,11 @@ chain = None  # Initialize chain as None
 # Function to set the OpenAI API key
 def set_apikey(api_key):
     os.environ['OPENAI_API_KEY'] = api_key
-    return disable_box  # Update the disable_box
+    return disable_box  
 
 # Function to enable the API key input box
 def enable_api_box():
-    return enable_box  # Update the enable_box
+    return enable_box
 
 # Function to add text to the chat history
 def add_text(history, text):
@@ -33,36 +33,39 @@ def add_text(history, text):
 
 # Function to process the PDF file and create a conversation chain
 def process_file(file):
-    global chain  # Access the global 'chain' variable
+    global chain
     if 'OPENAI_API_KEY' not in os.environ:
         raise gr.Error('Upload your OpenAI API key')
 
+    # Replace with your actual PDF processing logic
     loader = PyPDFLoader(file.name)
     documents = loader.load()
     embeddings = OpenAIEmbeddings()
     pdfsearch = Chroma.from_documents(documents, embeddings)
+
     chain = ConversationalRetrievalChain.from_llm(ChatOpenAI(temperature=0.3),
                                     retriever=pdfsearch.as_retriever(search_kwargs={"k": 1}),
                                     return_source_documents=True)
     return chain
 
-# # Function to generate a response based on the chat history and query
-def generate_response(history, query, btn):
-    global COUNT, N, chat_history, chain 
-    if not btn:
+# Function to generate a response based on the chat history and query
+def generate_response(history, query, pdf_upload):
+    global COUNT, N, chat_history, chain
+    if not pdf_upload:
         raise gr.Error(message='Upload a PDF')
 
     if COUNT == 0:
-        chain = process_file(btn)
+        chain = process_file(pdf_upload)
         COUNT += 1
 
-    result = chain({"question": query, 'chat_history': chat_history}, return_only_outputs=True)
+    # Replace with your LangChain logic to generate a response 
+    result = chain({"question": query, 'chat_history': chat_history}, return_only_outputs=True)  
     chat_history += [(query, result["answer"])]
-    N = list(result['source_documents'][0])[1][1]['page']
+    N = list(result['source_documents'][0])[1][1]['page']  # Adjust as needed
 
     for char in result['answer']:
-        history[-1][-1] += char  # Update the last response
-        yield history, ''  
+        history[-1][-1] += char  
+    return history, ''  
 
 # Function to render a specific page of a PDF file as an image
 def render_file(file):
@@ -73,117 +76,48 @@ def render_file(file):
     image = Image.frombytes('RGB', [pix.width, pix.height], pix.samples)
     return image
 
-# Gradio application setup
-# with gr.Blocks() as demo:
-#     with gr.Column():
-#         gr.Markdown(""" 
-#         <style> 
-#             .image-container { height: 680px; } 
-#         </style> 
-#         """)  
-#         with gr.Row():
-#             enable_box = gr.Textbox(placeholder='Enter OpenAI API key', 
-#                                     show_label=False, interactive=True) 
-#             disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) 
-#             change_api_key = gr.Button('Change Key') 
-#         with gr.Row():
-#             chatbot = gr.Chatbot(value=[], elem_id='chatbot')  
-#             show_img = gr.Image(label='Upload PDF')
-
-#     # Set up event handlers
-
-#     # Event handler for submitting the OpenAI API key
-#     enable_box.submit(fn=set_apikey, inputs=[enable_box], outputs=[disable_box]) 
-
-#     # Event handler for changing the API key
-#     change_api_key.click(fn=enable_api_box, outputs=[enable_box])
-
-    
+# Function to render initial content from the PDF
 def render_first(pdf_file): 
-    # ... Logic to process the PDF 
-    # ... Generate the first image
-    return image  
-
-
-with gr.Blocks() as demo:
-    with gr.Column():
-        gr.Markdown(""" 
-        <style> 
-            .image-container { height: 680px; } 
-        </style> 
-        """)  
-        with gr.Row():
-            enable_box = gr.Textbox(placeholder='Enter OpenAI API key',  
-                                    show_label=False, interactive=True) 
-            disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) 
-            change_api_key = gr.Button('Change Key') 
-        with gr.Row():
-            chatbot = gr.Chatbot(value=[], elem_id='chatbot')  
-            show_img = gr.Image(label='Upload PDF') 
-            pdf_upload = gr.UploadButton("📁 Upload a PDF", file_types=[".pdf"])  # Added
-
-        # Event handlers
-        enable_box.submit(fn=set_apikey, inputs=[enable_box], outputs=[disable_box]) 
-        change_api_key.click(fn=enable_api_box, outputs=[enable_box]) 
-        pdf_upload.upload(fn=render_first, inputs=[pdf_upload], outputs=[show_img])  # Corrected
-
-        
-        txt = gr.Textbox(label="Enter your query", placeholder="Ask a question...") # Add Textbox
-        submit_btn = gr.Button('Submit')  # Added the Submit button
-        submit_btn.click(        
-            fn=add_text,        
-            inputs=[chatbot, txt],  # Assuming 'txt' is your textbox for query input
-            outputs=[chatbot],        
-            queue=False    
-        ).success(
-            fn=generate_response,
-            inputs=[chatbot, txt, pdf_upload],  # Changed from 'btn' 
-            outputs=[chatbot, txt]   
-        ).success(
-            fn=render_file,
-            inputs=[pdf_upload],  # Changed from 'btn'
-            outputs=[show_img]
-        )
-
-# demo.launch(server_port=7861) 
-
-
-def add_text(history, text):
-    if not text:
-        raise gr.Error('Enter text')
-    history = history + [(text, '')]
-    return history
-
-def render_first(pdf_file): 
-    # ... Logic to process the PDF (extract text, create summary, etc.)
-    # ... Generate a simple image as a placeholder
-    image = Image.new('RGB', (600, 400), color = 'white') # Example
-
+    # Replace with logic to process the PDF and generate an initial image
+    image = Image.new('RGB', (600, 400), color = 'white') # Placeholder
     return image
 
-st.title("PDF-Powered Chatbot")  # Add a title
-
-# Gradio interface with Streamlit containers
-with st.container():  
-    gr.Markdown(""" 
-    <style> 
-        .image-container { height: 680px; } 
-    </style> 
-    """)  
-    with gr.Row():
-        enable_box = gr.Textbox(placeholder='Enter OpenAI API key',  
-                                show_label=False, interactive=True) 
-        disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False) 
-        change_api_key = gr.Button('Change Key') 
-    with gr.Row():
-        chatbot = gr.Chatbot(value=[], elem_id='chatbot')  
-        show_img = gr.Image(label='Upload PDF') 
+# Streamlit & Gradio Interface
+st.title("PDF-Powered Chatbot") 
+
+with st.container():      
+    gr.Markdown("""     
+    <style>         
+    .image-container { height: 680px; }     
+    </style>     
+    """)      
+    with gr.Row():        
+        enable_box = gr.Textbox(placeholder='Enter OpenAI API key', 
+                                show_label=False, interactive=True)         
+        disable_box = gr.Textbox(value='OpenAI API key is Set', interactive=False)         
+        change_api_key = gr.Button('Change Key')     
+
+    with gr.Row():        
+        chatbot = gr.Chatbot(value=[], elem_id='chatbot')          
+        show_img = gr.Image(label='Upload PDF')         
         pdf_upload = gr.UploadButton("📁 Upload a PDF", file_types=[".pdf"])  
 
-    # Event handlers (same as before)
-    # ... your event handlers ...
+# Event handlers 
+enable_box.submit(fn=set_apikey, inputs=[enable_box], outputs=[disable_box])         
+change_api_key.click(fn=enable_api_box, outputs=[enable_box])         
+pdf_upload.upload(fn=render_first, inputs=[pdf_upload], outputs=[show_img]) 
+
+txt = gr.Textbox(label="Enter your query", placeholder="Ask a question...") 
+submit_btn = gr.Button('Submit') 
+
+submit_btn.click(
+    fn=add_text, inputs=[chatbot, txt], outputs=[chatbot], queue=False
+).success(
+    fn=generate_response, inputs=[chatbot, txt, pdf_upload], outputs=[chatbot, txt] 
+).success(
+    fn=render_file, inputs=[pdf_upload], outputs=[show_img] 
+)
 
-# If you only want a Gradio interface, launch Gradio
 if __name__ == "__main__":
     gr.Interface(
         [render_first, add_text, generate_response, render_file],