updated app.py

app.py

@@ -2,7 +2,7 @@ import os
 import gradio as gr
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.vectorstores import Chroma
-from langchain.llms import HuggingFacePipeline
+from langchain_huggingface import HuggingFacePipeline
 from langchain.chains import RetrievalQA
 from transformers import AutoConfig, AutoTokenizer, pipeline, AutoModelForCausalLM
 from langchain_community.document_loaders import DirectoryLoader
@@ -10,6 +10,7 @@ import torch
 import re
 import transformers
 import spaces
+from urllib.parse import urlencode
 
 # Initialize embeddings and ChromaDB
 model_name = "sentence-transformers/all-mpnet-base-v2"
@@ -70,10 +71,11 @@ def test_rag(query):
     
     return corrected_text_books
 
+# OAuth Configuration
 TENANT_ID = os.getenv("TENANT_ID")
 CLIENT_ID = os.getenv("OAUTH_CLIENT_ID")
 CLIENT_SECRET = os.getenv("CLIENT_SECRET")
-REDIRECT_URI = os.getenv("SPACE_HOST") 
+REDIRECT_URI = os.getenv("SPACE_HOST")  # Make sure this is the correct redirect URI
 AUTH_URL = os.getenv("AUTH_URL")
 TOKEN_URL = os.getenv("TOKEN_URL")
 SCOPE = os.getenv("SCOPE")
@@ -105,23 +107,21 @@ def chat(query, history=None):
 def clear_input():
     return "",  # Return empty string to clear input field
 
-# Function to show/hide components based on login status
-def on_login(success):
-    return gr.update(visible=success), gr.update(visible=success)
-
 with gr.Blocks() as interface:
     gr.Markdown("## RAG Chatbot")
     gr.Markdown("Ask a question and get answers based on retrieved documents.")
 
     # Sign-In Button
     login_btn = gr.Button("Sign In with HF")
-    login_btn.click(lambda: oauth_login(), outputs=None)  # Redirect user for OAuth login
     
+    # Redirect to OAuth login
+    login_btn.click(lambda: oauth_login(), outputs=None)  # This will return the login URL
+
     # Hidden components initially
     input_box = gr.Textbox(label="Enter your question", placeholder="Type your question here...", visible=False)
     submit_btn = gr.Button("Submit", visible=False)
     chat_history = gr.Chatbot(label="Chat History", visible=False)
-    
+
     # Show components after login
     def show_components():
         return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
@@ -130,4 +130,4 @@ with gr.Blocks() as interface:
     submit_btn.click(show_components, outputs=[input_box, submit_btn, chat_history])
     submit_btn.click(chat, inputs=[input_box, chat_history], outputs=[chat_history, input_box])
 
-interface.launch()
+interface.launch()