Update app.py

app.py

@@ -1,58 +1,103 @@
-import os
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-client = InferenceClient("lambdaindie/lambdai", token=os.environ["HF_TOKEN"])
+# Cliente da Inference API
+client = InferenceClient("lambdaindie/lambdai")
 
-def respond(message, history, system_message, max_tokens, temperature, top_p):
-    messages = [{"role": "system", "content": system_message}] if system_message else []
+# Função para responder no chatbot
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
 
-    for user, assistant in history:
-        if user:
-            messages.append({"role": "user", "content": user})
-        if assistant:
-            messages.append({"role": "assistant", "content": assistant})
+    # Adicionando a história da conversa
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
     messages.append({"role": "user", "content": message})
+
     response = ""
 
-    for chunk in client.text_generation(
+    # Fluxo de resposta do cliente da API
+    for message in client.chat_completion(
         messages,
-        max_new_tokens=max_tokens,
+        max_tokens=max_tokens,
         stream=True,
         temperature=temperature,
         top_p=top_p,
     ):
-        token = chunk.choices[0].delta.content
+        token = message.choices[0].delta.content
         response += token
         yield response
 
-with gr.Blocks() as demo:
-    gr.Markdown("# 🧠 lambdai — Chat Demo")
-    
-    chatbot = gr.Chatbot()
-    with gr.Row():
-        system_msg = gr.Textbox(label="System message", placeholder="e.g. You are a helpful assistant.")
-    with gr.Row():
-        max_tokens = gr.Slider(1, 2048, value=512, step=1, label="Max tokens")
-        temperature = gr.Slider(0.1, 4.0, value=0.7, step=0.1, label="Temperature")
-        top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
-    msg = gr.Textbox(placeholder="Ask something...", label="Your message")
-
-    state = gr.State([])
-
-    def user_submit(user_message, history):
-        return "", history + [[user_message, None]]
-
-    def generate_response(message, history, sys_msg, max_tokens, temperature, top_p):
-        gen = respond(message, history, sys_msg, max_tokens, temperature, top_p)
-        return gen, history
-
-    msg.submit(user_submit, [msg, state], [msg, state], queue=False).then(
-        generate_response,
-        [msg, state, system_msg, max_tokens, temperature, top_p],
-        [chatbot, state]
-    )
+
+# Interface do Gradio com chat customizado
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="", label="System message", lines=1, placeholder="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)",
+        ),
+    ],
+    theme="huggingface",  # Usando tema do Hugging Face para um estilo moderno
+    title="Lambda Chatbot",  # Título na interface
+    description="Chatbot alimentado pelo modelo Lambdai",  # Descrição simples
+    layout="vertical",  # Layout vertical
+    css="""
+        .chatbox {
+            background-color: #0e1117; 
+            color: #f5f5f5; 
+            font-family: 'JetBrains Mono', monospace; 
+            border-radius: 8px;
+            border: 1px solid #444;
+        }
+        .gradio-container {
+            background-color: #121212;
+            padding: 20px;
+            border-radius: 10px;
+        }
+        .gr-button {
+            background-color: #4a90e2;
+            color: #fff;
+            font-family: 'JetBrains Mono', monospace;
+            border-radius: 5px;
+        }
+        .gr-button:hover {
+            background-color: #357ab7;
+        }
+        .gr-slider {
+            background-color: #333;
+            color: #f5f5f5;
+            border-radius: 8px;
+        }
+        .gr-slider .slider {
+            background-color: #444;
+        }
+        .gr-chatbox-container {
+            background-color: #181a1f;
+            border-radius: 10px;
+        }
+        .gr-output {
+            font-family: 'JetBrains Mono', monospace;
+            color: #f5f5f5;
+        }
+    """,  # Customização de CSS
+)
 
 if __name__ == "__main__":
     demo.launch()