Update app.py

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-import random
 import os
 from openai import OpenAI
 
@@ -11,32 +10,11 @@ client = OpenAI(
 
 REFERER_HEADER = "https://alphaai.org.in"
 TITLE_HEADER = "AlphaAI Chatbot"
-MODEL_NAME = "google/gemini-2.0-flash-exp:free"
+MODEL_NAME = "deepseek/deepseek-r1-0528-qwen3-8b:free"
 ALPHAAI_CONTEXT = os.environ.get("ALPHAAI_CONTEXT", "")
 
-# --- CAPTCHA Logic ---
-def generate_captcha():
-    a, b = random.randint(1, 9), random.randint(1, 9)
-    return f"What is {a} + {b}?", a + b
-
-# Store correct answers in-memory (for stateless apps, better use secure session)
-captcha_answers = {}
-
 # --- Chatbot Backend ---
-def chat_with_llm(user_input, session_id, captcha_input):
-    correct_answer = captcha_answers.get(session_id)
-    if correct_answer is None:
-        return "CAPTCHA not initialized properly. Please reload.", generate_new_captcha(session_id)[0]
-
-    try:
-        if int(captcha_input) != correct_answer:
-            return "Incorrect CAPTCHA. Try again.", generate_new_captcha(session_id)[0]
-    except ValueError:
-        return "Please enter a valid number for the CAPTCHA.", generate_new_captcha(session_id)[0]
-
-    # Prepare prompt with context
-    full_prompt = f"You are Alpha AI's assistant. Use the following context to answer user questions.\n\n{ALPHAAI_CONTEXT}\n\nUser: {user_input}"
-
+def chat_with_llm(user_input):
     # Make OpenRouter API call
     try:
         completion = client.chat.completions.create(
@@ -47,50 +25,28 @@ def chat_with_llm(user_input, session_id, captcha_input):
             model=MODEL_NAME,
             messages=[{"role": "system", "content": ALPHAAI_CONTEXT}, {"role": "user", "content": user_input}]
         )
-        response = completion.choices[0].message.content
-        return response, generate_new_captcha(session_id)[0]
+        return completion.choices[0].message.content
     except Exception as e:
-        return f"Error: {str(e)}", generate_new_captcha(session_id)[0]
-
-
-def generate_new_captcha(session_id):
-    captcha_q, captcha_ans = generate_captcha()
-    captcha_answers[session_id] = captcha_ans
-    return captcha_q, captcha_ans
-
+        return f"Error: {str(e)}"
 
 # --- Gradio UI ---
-def start_session():
-    session_id = str(random.randint(100000, 999999))
-    captcha_q, _ = generate_new_captcha(session_id)
-    return session_id, captcha_q
-
 with gr.Blocks(theme=gr.themes.Base(primary_hue="blue", secondary_hue="gray", font=["Inter", "sans-serif"])) as demo:
-    gr.Markdown("# 🤖 Alpha AI Assistant with CAPTCHA")
-    gr.Markdown("Welcome to Alpha AI’s intelligent assistant. Please solve the CAPTCHA to continue.")
+    gr.Markdown("# 🤖 Alpha AI Assistant")
+    gr.Markdown("Welcome to Alpha AI’s intelligent assistant. Please complete the CAPTCHA on the site before using.")
 
     with gr.Row():
         chatbot = gr.Chatbot()
 
     with gr.Row():
         user_input = gr.Textbox(label="Your Message")
-        captcha_input = gr.Textbox(label="CAPTCHA Answer")
-
-    with gr.Row():
-        session_id = gr.Textbox(visible=False)
-        captcha_display = gr.Textbox(label="CAPTCHA", interactive=False)
         submit_btn = gr.Button("Submit")
 
-    def handle_submit(user_msg, sid, cap_input):
-        response, new_captcha_q = chat_with_llm(user_msg, sid, cap_input)
-        return [(user_msg, response)], sid, new_captcha_q
-
-    def init_session():
-        sid, cap_q = start_session()
-        return sid, cap_q
+    def handle_submit(user_msg, history):
+        response = chat_with_llm(user_msg)
+        history.append((user_msg, response))
+        return history, ""
 
-    submit_btn.click(handle_submit, inputs=[user_input, session_id, captcha_input], outputs=[chatbot, session_id, captcha_display])
-    demo.load(init_session, inputs=[], outputs=[session_id, captcha_display])
+    submit_btn.click(handle_submit, inputs=[user_input, chatbot], outputs=[chatbot, user_input])
 
 # Launch (required for Hugging Face Space)
 demo.launch()