Modification

app.py

@@ -1,76 +1,101 @@
-import re, uuid
-import json, logging
 import gradio as gr
-from typing import List, Dict
-
-from data.css import custom_css
+import uuid
+import logging
 from src.controller.agent_cacher import AgentManager
+
 # Configure logging
 logging.basicConfig(level=logging.INFO, format="-->%(asctime)s [%(levelname)s] %(message)s")
 
-
-
+# User credentials
+VALID_USERS = {
+    "ankit": "mlpass123",
+    "demo": "test123"
+}
 
 def create_gradio_interface():
-    gr.HTML('<link href="https://fonts.googleapis.com/css2?family=Fira+Code&family=Roboto&display=swap" rel="stylesheet">')
-    gr.HTML(custom_css)
     manager = AgentManager()
-    
+
     with gr.Blocks(title="AI Learning Assistant") as demo:
-        gr.Markdown("# 🧠 Learn with LlamaIndex Tools")
-        logging.info("Starting Learning Application")
-
-        with gr.Row():
-            session_id = gr.Textbox(label="Session ID", value=str(uuid.uuid4()), visible=True)
-            llm_selector = gr.Dropdown(
-                label="LLM Type",
-                choices=["Google", "OpenAI", "HuggingFace", "Mistral"],
-                value="Google",
-                interactive=True
-            )
+        auth_state = gr.State(False)  # store login status
+
+        with gr.Column(visible=True) as login_section:
+            gr.Markdown("## 🔐 Login to Continue")
+            username = gr.Textbox(label="Username")
+            password = gr.Textbox(label="Password", type="password")
+            login_btn = gr.Button("Login")
+            login_error = gr.Markdown(visible=False)
+
+        with gr.Column(visible=False) as app_section:
+            gr.Markdown("# 🧠 Learn with LlamaIndex Tools")
 
-        with gr.Row():
-            with gr.Column(scale=3):
-                chatbot = gr.Chatbot(
-                    label="Learning Dialog",
-                    height=500,
-                    type="messages"
+            with gr.Row():
+                session_id = gr.Textbox(label="Session ID", value=str(uuid.uuid4()), visible=True)
+                llm_selector = gr.Dropdown(
+                    label="LLM Type",
+                    choices=["Google", "OpenAI", "HuggingFace", "Mistral"],
+                    value="Google",
+                    interactive=True
                 )
-                query_input = gr.Textbox(label="Your Learning Query", placeholder="Ask about ML/DL algorithms...")
-                submit_btn = gr.Button("Submit")
-
-            with gr.Column(scale=1):
-                gr.Markdown("### Tools Preview")
-                tool_output = gr.Textbox(label="Selected Tools", interactive=False)
-                response_output = gr.Textbox(label="Full Response", interactive=False, lines=10)
-
-        def process_query(session_id_val, query, chat_history, llm_val):
-            print("Session:", session_id)
-            print("Query:", query)
-            #print("Chat History:", chat_history)
-            print("Option selected:", llm_val)
-            agent = manager.get_agent(session_id_val, llm_type=llm_val)
-            chat_history, tools_used, response = agent.process_query(query)
-            manager.save_agent(session_id_val, agent)
-            return chat_history, tools_used, response, ""
-
-        submit_btn.click(
-            process_query,
-            inputs=[session_id, query_input, chatbot, llm_selector],  # ✅ 4 inputs
-            outputs=[chatbot, tool_output, response_output, query_input]
+
+            with gr.Row():
+                with gr.Column(scale=3):
+                    chatbot = gr.Chatbot(label="Learning Dialog", height=500, type="messages")
+                    query_input = gr.Textbox(label="Your Learning Query", placeholder="Ask about ML/DL algorithms...")
+                    submit_btn = gr.Button("Submit")
+
+                with gr.Column(scale=1):
+                    gr.Markdown("### Tools Preview")
+                    tool_output = gr.Textbox(label="Selected Tools", interactive=False)
+                    response_output = gr.Textbox(label="Full Response", interactive=False, lines=10)
+
+            def process_query(session_id_val, query, chat_history, llm_val):
+                agent = manager.get_agent(session_id_val, llm_type=llm_val)
+                chat_history, tools_used, response = agent.process_query(query)
+                manager.save_agent(session_id_val, agent)
+                return chat_history, tools_used, response, ""
+
+            submit_btn.click(
+                process_query,
+                inputs=[session_id, query_input, chatbot, llm_selector],
+                outputs=[chatbot, tool_output, response_output, query_input]
+            )
+
+            def load_history(session_id_val, llm_val):
+                agent = manager.get_agent(session_id_val, llm_val)
+                return agent.chat_history
+
+            session_id.change(
+                load_history,
+                inputs=[session_id, llm_selector],
+                outputs=chatbot
+            )
+
+        def check_login(username, password):
+            if username == "admin" and password == "123":
+                return "", True
+            else:
+                return "Invalid credentials", False
+
+        login_btn.click(
+            check_login,
+            inputs=[username, password],
+            outputs=[login_error, auth_state]
         )
 
-        def load_history(session_id_val, llm_val):
-            agent = manager.get_agent(session_id_val, llm_val)
-            return agent.chat_history
+        def toggle_ui(is_logged_in):
+            return (
+                gr.update(visible=is_logged_in),  # app_section
+                gr.update(visible=not is_logged_in)  # login_section
+            )
 
-        session_id.change(
-            load_history,
-            inputs=[session_id, llm_selector],  # ✅ Pass component objects, not .value
-            outputs=chatbot
+        auth_state.change(
+            toggle_ui,
+            inputs=auth_state,
+            outputs=[app_section, login_section]
         )
 
     return demo
+
 if __name__ == "__main__":
     interface = create_gradio_interface()
-    interface.launch()
+    interface.launch()

src/llm/source_llm.py

@@ -54,7 +54,7 @@ class LLMCall:
 
     def _get_google_llm(self):
         return GoogleGenAI(
-            model="models/gemini-1.5-flash",
+            model="models/gemini-2.0-flash",
         )
     
     def _get_mistral(self):