Update app.py

app.py

@@ -31,25 +31,27 @@ DATA_DIR = "data"
 os.makedirs(DATA_DIR, exist_ok=True)
 os.makedirs(PERSIST_DIR, exist_ok=True)
 
-def displayPDF(file):
-    with open(file, "rb") as f:
-        base64_pdf = base64.b64encode(f.read()).decode('utf-8')
-    pdf_display = f'<iframe src="data:application/pdf;base64,{base64_pdf}" width="100%" height="600" type="application/pdf"></iframe>'
-    return pdf_display
+# Function to display PDF (for Gradio it will just show a message saying PDF was uploaded)
+def display_pdf(file):
+    return f"Uploaded PDF: {file.name}"
 
+# Data ingestion function
 def data_ingestion(files):
-    for file in files:
-        filepath = os.path.join(DATA_DIR, file.name)
+    for uploaded_file in files:
+        filepath = os.path.join(DATA_DIR, uploaded_file.name)
         with open(filepath, "wb") as f:
-            f.write(file.getbuffer())
+            f.write(uploaded_file.read())
     documents = SimpleDirectoryReader(DATA_DIR).load_data()
     storage_context = StorageContext.from_defaults()
     index = VectorStoreIndex.from_documents(documents)
     index.storage_context.persist(persist_dir=PERSIST_DIR)
+    return "PDFs processed successfully!"
 
+# Query handling function
 def handle_query(query):
     storage_context = StorageContext.from_defaults(persist_dir=PERSIST_DIR)
     index = load_index_from_storage(storage_context)
+    
     chat_text_qa_msgs = [
         (
             "user",
@@ -63,8 +65,8 @@ def handle_query(query):
     ]
     
     text_qa_template = ChatPromptTemplate.from_messages(chat_text_qa_msgs)
-    
     query_engine = index.as_query_engine(text_qa_template=text_qa_template)
+    
     answer = query_engine.query(query)
     
     if hasattr(answer, 'response'):
@@ -74,23 +76,38 @@ def handle_query(query):
     else:
         return "Sorry, I couldn't find an answer."
 
-# Gradio app setup
-def gradio_app(files, user_query):
+# Chatbot functionality
+def chatbot(files, user_input, history):
     if files:
-        data_ingestion(files)  # Process PDFs after they are uploaded
-        response = handle_query(user_query)
-        return response
-    return "Please upload at least one PDF file."
+        data_ingestion(files)  # Process PDFs
+        history.append(("assistant", "Your PDFs have been processed. You can now ask questions."))
+    if user_input:
+        response = handle_query(user_input)
+        history.append(("user", user_input))
+        history.append(("assistant", response))
+    return history, history
 
-interface = gr.Interface(
-    fn=gradio_app,
-    inputs=[
-        gr.File(label="Upload PDF Files", type="file", file_count="multiple"),
-        gr.Textbox(label="Ask me anything about the content of the PDF(s):")
-    ],
-    outputs="text",
-    title="(PDF) Information and Inference🗞️",
-    description="Retrieval-Augmented Generation. Start chat ...🚀"
-)
+# Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("# (PDF) Information and Inference 🗞️")
+    gr.Markdown("Upload PDF files and ask questions about their content!")
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            file_upload = gr.File(label="Upload your PDF files", file_types=["pdf"], multiple=True)
+        with gr.Column(scale=8):
+            chatbot_interface = gr.Chatbot(label="Q&A Assistant", elem_id="chatbot")
+    
+    user_input = gr.Textbox(label="Ask a question", placeholder="Type your question here...")
+    
+    history = gr.State([])  # To hold chat history
+    
+    submit_button = gr.Button("Submit")
+    
+    submit_button.click(
+        fn=chatbot, 
+        inputs=[file_upload, user_input, history], 
+        outputs=[chatbot_interface, history]
+    )
 
-interface.launch()
+app.launch()