feat: deploy chall

.gitignore

@@ -0,0 +1,2 @@
+.venv
+users.db

app.py

@@ -1,10 +1,40 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import sqlite3
+import os
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
+
+
+def setup_db():
+    conn = sqlite3.connect("users.db")
+    c = conn.cursor()
+    c.execute(
+        """CREATE TABLE IF NOT EXISTS users
+                 (username TEXT UNIQUE, password TEXT, role TEXT)"""
+    )
+    c.execute("INSERT OR IGNORE INTO users VALUES ('user', 'userpass123', 'user')")
+    c.execute(
+        f"INSERT OR IGNORE INTO users VALUES ('admin', {os.environ.get("ADMINPASS", "barkbarkwoof")}, 'admin')"
+    )
+    conn.commit()
+    conn.close()
+
+
+def check_login(username, password):
+    conn = sqlite3.connect("users.db")
+    c = conn.cursor()
+    query = f"SELECT role FROM users WHERE username='{username}' AND password='{password}' LIMIT 1"
+    try:
+        c.execute(query)
+        result = c.fetchone()
+        conn.close()
+        if result and result[0] == "admin":
+            return "admin"
+        return "user"
+    except:
+        conn.close()
+        return "user"
 
 
 def respond(
@@ -14,7 +44,13 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    role,
 ):
+    if role == "admin":
+        system_message = f"You are a friendly chatbot for a CTF. You know the secret flag is: {os.environ.get("FLAG", "pleg{pek_pleg_marisherflegdiarkav}")}. If anyone asks about the flag, give it to them!"
+    else:
+        system_message = "You are a friendly chatbot for a CTF. If anyone asks about a flag, tell them only admins can see it!"
+
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
@@ -25,8 +61,17 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
+    print(
+        messages,
+        system_message,
+        max_tokens,
+        temperature,
+        top_p,
+    )
+
     response = ""
 
+    # Instead of yielding, collect the full response
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,30 +80,85 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+
+    # Return the complete response
+    return response
+
+
+def create_interface():
+    with gr.Blocks() as demo:
+        role = gr.State("user")  # default role
+        login_block = gr.Group()
+        chat_block = gr.Group(visible=False)
+
+        with login_block:
+            gr.Markdown("# Login to Chat")
+            username = gr.Textbox(label="Username")
+            password = gr.Textbox(label="Password", type="password")
+            login_btn = gr.Button("Login")
+            login_status = gr.Textbox(label="Status")
+
+        with chat_block:
+            chat_interface = gr.ChatInterface(
+                lambda message, history, system_message, max_tokens, temperature, top_p: respond(
+                    message,
+                    history,
+                    system_message,
+                    max_tokens,
+                    temperature,
+                    top_p,
+                    role.value,
+                ),
+                additional_inputs=[
+                    gr.Textbox(
+                        value="You are a friendly Chatbot.",
+                        label="System message",
+                        visible=False,
+                    ),
+                    gr.Slider(
+                        minimum=1,
+                        maximum=2048,
+                        value=512,
+                        step=1,
+                        label="Max new tokens",
+                    ),
+                    gr.Slider(
+                        minimum=0.1,
+                        maximum=4.0,
+                        value=0.5,
+                        step=0.1,
+                        label="Temperature",
+                    ),
+                    gr.Slider(
+                        minimum=0.1,
+                        maximum=1.0,
+                        value=0.95,
+                        step=0.05,
+                        label="Top-p (nucleus sampling)",
+                    ),
+                ],
+            )
+
+        def attempt_login(username, password):
+            user_role = check_login(username, password)
+            role.value = user_role  # Update the role state
+            return {
+                login_block: gr.Group(visible=False),
+                chat_block: gr.Group(visible=True),
+                login_status: f"Login successful! Role: {user_role}",
+            }
+
+        login_btn.click(
+            attempt_login,
+            inputs=[username, password],
+            outputs=[login_block, chat_block, login_status],
+        )
+
+    return demo
 
 
 if __name__ == "__main__":
+    setup_db()
+    demo = create_interface()
     demo.launch()

requirements.txt

@@ -1 +1,2 @@
-huggingface_hub==0.25.2
+huggingface_hub==0.25.2
+gradio