Update app.py

app.py

@@ -1,13 +1,16 @@
 import os
 import gradio as gr
 import asyncio
+from datetime import datetime
 from langchain_core.prompts import PromptTemplate
-from langchain_community.output_parsers.rail_parser import GuardrailsOutputParser
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_google_genai import ChatGoogleGenerativeAI
 import google.generativeai as genai
 from langchain.chains.question_answering import load_qa_chain  # Import load_qa_chain
 
+# Initialize an empty list to store chat history
+chat_history = []
+
 async def initialize(file_path, question):
     genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
     model = genai.GenerativeModel('gemini-pro')
@@ -58,7 +61,6 @@ async def initialize(file_path, question):
         
         # Generate links for each top page
         file_name = os.path.basename(file_path)
-        # Use a general link format with instructions for manual navigation if automatic links are not supported
         page_links = [f"[Page {p}](file://{os.path.abspath(file_path)})" for p in top_pages]
         page_links_str = ', '.join(page_links)
         
@@ -70,14 +72,28 @@ async def initialize(file_path, question):
         # Create a clickable link for the document
         source_link = f"[Document: {file_name}](file://{os.path.abspath(file_path)})"
         
+        # Save interaction to chat history
+        timestamp = datetime.now().isoformat()
+        chat_history.append({
+            'timestamp': timestamp,
+            'question': question,
+            'answer': answer,
+            'source': source_str,
+            'document_link': source_link
+        })
+        
         return f"Answer: {answer}\n{source_str}\n{source_link}"
     else:
         return "Error: Unable to process the document. Please ensure the PDF file is valid."
 
-# Define Gradio Interface
+# Define Gradio Interface for QA and Chat History
 input_file = gr.File(label="Upload PDF File")
 input_question = gr.Textbox(label="Ask about the document")
-output_text = gr.Textbox(label="Answer and Top Pages")
+output_text = gr.Textbox(label="Answer and Top Pages", lines=10, max_lines=10)
+
+def get_chat_history():
+    history_str = "\n".join([f"Q: {entry['question']}\nA: {entry['answer']}\n{entry['source']}\n{entry['document_link']}\nTimestamp: {entry['timestamp']}\n" for entry in chat_history])
+    return history_str
 
 async def pdf_qa(file, question):
     if file is None:
@@ -86,6 +102,24 @@ async def pdf_qa(file, question):
     answer = await initialize(file.name, question)
     return answer
 
-# Create Gradio Interface with share=True to enable a public link
-gr.Interface(fn=pdf_qa, inputs=[input_file, input_question], outputs=output_text, title="PDF Question Answering System", description="Upload a PDF file and ask questions about the content.").launch(share=True)
- the content.").launch(share=True)
+# Create Gradio Interfaces
+qa_interface = gr.Interface(
+    fn=pdf_qa,
+    inputs=[input_file, input_question],
+    outputs=output_text,
+    title="PDF Question Answering System",
+    description="Upload a PDF file and ask questions about the content."
+)
+
+history_interface = gr.Interface(
+    fn=get_chat_history,
+    inputs=[],
+    outputs=gr.Textbox(label="Chat History", lines=20, max_lines=20),
+    title="Chat History",
+    description="View the history of interactions."
+)
+
+# Launch both interfaces
+qa_interface.launch(share=True)
+history_interface.launch(share=True)
+