Update app.py

app.py

@@ -1,12 +1,11 @@
 import gradio as gr
+import os
+from dotenv import load_dotenv
 from langchain.chains.question_answering import load_qa_chain
-from langchain_openai import ChatOpenAI
+from langchain_openai import ChatOpenAI, OpenAIEmbeddings
 from langchain.vectorstores import FAISS
 from langchain.document_loaders import PyPDFLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain_openai import OpenAIEmbeddings
-import os
-from dotenv import load_dotenv
 
 load_dotenv()
 os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
@@ -14,48 +13,45 @@ os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
 llm = ChatOpenAI(model_name="gpt-4", temperature=0)
 embedding = OpenAIEmbeddings()
 
-# Global vector DB
-db = None
+db = None  # Global DB
 
 def upload_pdf(file):
     global db
-    pdf_path = file.name
-    loader = PyPDFLoader(pdf_path)
+    loader = PyPDFLoader(file.name)
     documents = loader.load()
     splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
     docs = splitter.split_documents(documents)
     db = FAISS.from_documents(docs, embedding)
-    return "✅ PDF processed. You can start chatting with it!"
+    return "✅ PDF processed. Ask your questions below."
 
 def chat_with_pdf(message, history):
     global db
     if not db:
-        return "❌ Please upload and process a PDF first."
+        return history + [[message, "❌ Please upload a PDF first."]]
+    
     retriever = db.as_retriever()
     chain = load_qa_chain(llm, chain_type="stuff")
     docs = retriever.get_relevant_documents(message)
     response = chain.run(input_documents=docs, question=message)
-    return response
+    history.append([message, response])
+    return history
+
+with gr.Blocks(title="📄 Interactive PDF Chatbot") as demo:
+    gr.Markdown("## 📄 Chat with a PDF using GPT-4")
 
-with gr.Blocks(title="📄 PDF Chatbot") as demo:
-    gr.Markdown("## 📄 Interactive PDF Reader + Chatbot\nUpload a PDF and chat with it using GPT-4.")
-    
     with gr.Row():
-        pdf_file = gr.File(label="Upload PDF", file_types=[".pdf"])
+        pdf = gr.File(label="Upload PDF", file_types=[".pdf"])
         upload_btn = gr.Button("Process PDF")
-    
     status = gr.Textbox(label="Status", interactive=False)
-    
-    chatbot = gr.ChatInterface(
-        fn=chat_with_pdf,
-        chatbot=gr.Chatbot(height=400),
-        textbox=gr.Textbox(placeholder="Ask anything from the PDF...", lines=2),
-        title="Talk with your PDF",
-        theme="compact",
-        examples=["Summarize this document.", "What are the key points?", "Is there a deadline mentioned?"],
-        cache_examples=False
-    )
-
-    upload_btn.click(fn=upload_pdf, inputs=pdf_file, outputs=status)
+
+    chatbot = gr.Chatbot(label="Chat History", height=400)
+    msg = gr.Textbox(label="Ask a question", placeholder="Type your question and press Enter...", lines=2)
+    send_btn = gr.Button("Send")
+
+    upload_btn.click(upload_pdf, inputs=pdf, outputs=status)
+    msg.submit(chat_with_pdf, inputs=[msg, chatbot], outputs=chatbot)
+    send_btn.click(chat_with_pdf, inputs=[msg, chatbot], outputs=chatbot)
+    send_btn.click(lambda: "", None, msg)  # Clear input after send
+    msg.submit(lambda: "", None, msg)      # Clear input after enter
 
 demo.launch(share=True)