updated

app.py

@@ -1,15 +1,3 @@
-import subprocess
-
-script_path = './setup.sh'  # Adjust the path if needed
-
-# Run the script
-exit_code = subprocess.call(['bash', script_path])
-
-if exit_code == 0:
-    print("Script executed successfully.")
-else:
-    print(f"Script failed with exit code {exit_code}.")
-
 import gradio as gr
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.vectorstores import Chroma
@@ -21,8 +9,6 @@ import torch
 import re
 import transformers
 import spaces
-import requests
-from urllib.parse import urlencode
 
 # Initialize embeddings and ChromaDB
 model_name = "sentence-transformers/all-mpnet-base-v2"
@@ -39,11 +25,19 @@ books_db_client = books_db.as_retriever()
 # Initialize the model and tokenizer
 model_name = "stabilityai/stablelm-zephyr-3b"
 
+# bnb_config = transformers.BitsAndBytesConfig(
+#     load_in_4bit=True,
+#     bnb_4bit_quant_type='nf4',
+#     bnb_4bit_use_double_quant=True,
+#     bnb_4bit_compute_dtype=torch.bfloat16
+# )
+
 model_config = transformers.AutoConfig.from_pretrained(model_name, max_new_tokens=1024)
 model = transformers.AutoModelForCausalLM.from_pretrained(
     model_name,
     trust_remote_code=True,
     config=model_config,
+    # quantization_config=bnb_config,
     device_map=device,
 )
 
@@ -72,71 +66,6 @@ books_db_client_retriever = RetrievalQA.from_chain_type(
     verbose=True
 )
 
-# OAuth Configuration
-TENANT_ID = '2b093ced-2571-463f-bc3e-b4f8bcb427ee'
-CLIENT_ID = '2a7c884c-942d-49e2-9e5d-7a29d8a0d3e5'
-CLIENT_SECRET = 'EOF8Q~kKHCRgx8tnlLM-H8e93ifetxI6x7sU6bGW'
-REDIRECT_URI = 'https://sanjeevbora-chatbot.hf.space/'
-AUTH_URL = f"https://login.microsoftonline.com/2b093ced-2571-463f-bc3e-b4f8bcb427ee/oauth2/v2.0/authorize"
-TOKEN_URL = f"https://login.microsoftonline.com/2b093ced-2571-463f-bc3e-b4f8bcb427ee/oauth2/v2.0/token"
-
-params = {
-    'client_id': CLIENT_ID,
-    'response_type': 'code',
-    'redirect_uri': REDIRECT_URI,
-    'response_mode': 'query',
-    'scope': 'User.Read',
-    'state': '12345'  # Optional state parameter
-}
-
-# Construct the login URL
-login_url = f"{AUTH_URL}?{urlencode(params)}"
-
-# Gradio interface
-def show_login_button():
-    return f'<a href="{login_url}" target="_blank">Click here to login with Microsoft</a>'
-
-# Dummy function to simulate token validation (you will replace this with actual validation)
-def is_logged_in(token):
-    # Check if the token exists (or check if it's valid)
-    return token is not None
-
-# Gradio interface
-def check_login(status):
-    # If logged in, show the chatbot interface, otherwise show login link
-    if status:
-        return gr.update(visible=True), gr.update(visible=True)
-    else:
-        return gr.update(visible=False), gr.update(visible=False)
-    
-# Function to exchange authorization code for access token
-def exchange_code_for_token(auth_code):
-    data = {
-        'grant_type': 'authorization_code',
-        'client_id': CLIENT_ID,
-        'client_secret': CLIENT_SECRET,
-        'code': auth_code,
-        'redirect_uri': REDIRECT_URI
-    }
-    
-    response = requests.post(TOKEN_URL, data=data)
-    
-    if response.status_code == 200:
-        token_data = response.json()
-        access_token = token_data.get('access_token')
-        return access_token
-    else:
-        return None
-
-def login_user(auth_code):
-    # Exchange the authorization code for an access token
-    token = exchange_code_for_token(auth_code)
-    
-    if token:
-        return token
-    else:
-        return None
-
 # Function to retrieve answer using the RAG system
 @spaces.GPU(duration=60)
 def test_rag(query):
@@ -165,34 +94,18 @@ def chat(query, history=None):
 def clear_input():
     return "",  # Return empty string to clear input field
 
+# Gradio interface
 with gr.Blocks() as interface:
     gr.Markdown("## RAG Chatbot")
-    gr.Markdown("Please log in to continue.")
+    gr.Markdown("Ask a question and get answers based on retrieved documents.")
     
-    # Custom HTML to show login link
-    login_link = gr.HTML(f'<a href="{login_url}" target="_blank">Click here to login with Microsoft</a>')
-
-    # Login button to simulate the login process
-    login_button = gr.Button("Login")
+    input_box = gr.Textbox(label="Enter your question", placeholder="Type your question here...")
+    submit_btn = gr.Button("Submit")
+    # clear_btn = gr.Button("Clear")
+    chat_history = gr.Chatbot(label="Chat History")
     
-    # Components for chat (initially hidden)
-    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)
-
-    # Handle login button click
-    login_button.click(
-        login_user, 
-        inputs=[], 
-        outputs=[login_button],  # You can also update the UI to show login status
-        queue=False
-    ).then(
-        lambda token: check_login(is_logged_in(token)), 
-        inputs=[], 
-        outputs=[input_box, submit_btn]
-    )
-
-    # Input submission and chat handling
     submit_btn.click(chat, inputs=[input_box, chat_history], outputs=[chat_history, input_box])
+    # clear_btn.click(clear_input, outputs=input_box)
+
+interface.launch()
 
-interface.launch()