Update app.py

app.py

@@ -1,5 +1,4 @@
 import os
-import sys
 import gradio as gr
 from pinecone import Pinecone, ServerlessSpec
 from langchain_community.llms import Replicate
@@ -10,13 +9,12 @@ from langchain_huggingface.embeddings import HuggingFaceEmbeddings
 from langchain.chains import ConversationalRetrievalChain
 import time
 
-key1 = os.environ.get('REPLICATE_API_TOKEN')
-key2 = os.environ.get('PINECONE_API_KEY')
-os.environ['REPLICATE_API_TOKEN'] = key1
-os.environ["PINECONE_API_KEY"] = key2
+# Retrieve API keys from environment variables
+replicate_api_token = os.getenv('REPLICATE_API_TOKEN')
+pinecone_api_key = os.getenv('PINECONE_API_KEY')
 
 # Initialize Pinecone
-pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])
+pc = Pinecone(api_key=pinecone_api_key)
 
 # Function to process PDF and set up chatbot
 def process_pdf(pdf_doc):
@@ -71,7 +69,7 @@ def process_pdf(pdf_doc):
 def query(history, text):
     langchain_history = [(msg[1], history[i+1][1] if i+1 < len(history) else "") for i, msg in enumerate(history) if i % 2 == 0]
     result = qa_chain({"question": text, "chat_history": langchain_history})
-    new_history = history + [(text,result['answer'])]
+    new_history = history + [(text, result['answer'])]
     return new_history, ""
 
 # Define the Gradio interface
@@ -80,22 +78,24 @@ css = """
 """
 
 title = """
-<div style="text-align: center;max-width: 700px;">
+<div style="text-align: center; max-width: 700px;">
     <h1>Chat with PDF</h1>   
+</div>
 """
 
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.HTML(title)
-        with gr.Column():
-            pdf_doc = gr.File(label="Load a PDF", file_types=['.pdf'], type="filepath")
-            load_pdf = gr.Button("Load PDF")
-            langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
-        chatbot = gr.Chatbot([], elem_id="chatbot").scale(height=350)
-        question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ")
-        submit_btn = gr.Button("Send message") 
-    load_pdf.click(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False)
-    question.submit(query, [chatbot, question], [chatbot, question])
-    submit_btn.click(query, [chatbot, question], [chatbot, question])
-
-demo.launch()
+def pdf_changes(pdf_doc):
+    result = process_pdf(pdf_doc)
+    return result
+
+with gr.Interface(
+    fn=query,
+    inputs=[gr.Textbox(label="History", type="key-value", placeholder="History", rows=10),
+            gr.Textbox(label="Question", placeholder="Type your question and hit Enter")],
+    outputs=gr.Textbox(label="Answer", type="key-value", placeholder="Answer"),
+    live=True,
+    title="PDF Chatbot",
+    description="Ask questions based on uploaded PDF content.",
+    theme="compact",
+    css=css
+) as iface:
+    iface.launch()