Update app.py

app.py

@@ -1,83 +1,65 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# Inicia o cliente para o modelo
 client = InferenceClient("lambdaindie/lambdai")
 
-# CSS simples
-css = r"""
-* { font-family: 'JetBrains Mono', monospace; }
-.gradio-container { background-color: #111; color: #e0e0e0; }
-textarea, input, .block, .wrap, .chatbot {
-    background-color: #1a1a1a !important;
-    color: #e0e0e0 !important;
-    border: 1px solid #333 !important;
-    border-radius: 10px;
-}
-button.pulse {
-    background-color: #272727 !important;
-    border: 1px solid #444 !important;
-    color: #e0e0e0 !important;
-    border-radius: 10px;
-    animation: pulse 2s infinite;
-}
-@keyframes pulse {
-  0%   { transform: scale(1); box-shadow: 0 0 0 0 rgba(255,255,255,0.5); }
-  70%  { transform: scale(1.05); box-shadow: 0 0 0 10px rgba(255,255,255,0); }
-  100% { transform: scale(1); box-shadow: 0 0 0 0 rgba(255,255,255,0); }
+css = """
+.thinking-html {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    color: #666;
+    font-style: italic;
+    margin-bottom: 5px;
+    animation: pulse 1.5s infinite;
 }
 .loader {
-  border: 3px solid #2b2b2b;
-  border-top: 3px solid #e0e0e0;
-  border-radius: 50%;
-  width: 18px;
-  height: 18px;
-  animation: spin 1s linear infinite;
+    width: 14px;
+    height: 14px;
+    border: 2px solid #ccc;
+    border-top: 2px solid #666;
+    border-radius: 50%;
+    animation: spin 1s linear infinite;
 }
 @keyframes spin {
-  0%   { transform: rotate(0deg); }
-  100% { transform: rotate(360deg); }
+    to { transform: rotate(360deg); }
 }
-.thinking-html {
-  background-color: #2b2b2b;
-  padding: 8px;
-  border-radius: 8px;
-  margin-bottom: 8px;
-  font-style: italic;
-  color: #aaaaaa;
-  display: flex;
-  align-items: center;
+@keyframes pulse {
+    0% { opacity: 1; transform: scale(1); }
+    50% { opacity: 0.6; transform: scale(1.05); }
+    100% { opacity: 1; transform: scale(1); }
 }
 """
 
-# Função principal para responder
-def respond(message, chat_history):
-    thinking_html = (
-        f"<div class='thinking-html'>"
-        f"<div class='loader'></div>"
-        f"Thinking… generating response..."
-        f"</div>"
+def respond(message, history):
+    thinking = (
+        "<div class='thinking-html'>"
+        "<div class='loader'></div>"
+        "Thinking..."
+        "</div>"
     )
-    yield chat_history + [{"role": "user", "content": message}, {"role": "assistant", "content": thinking_html}]
-    
-    response = client.chat_completion([{"role": "user", "content": message}], stream=False)
-    answer = response['choices'][0]['message']['content']
-    yield chat_history + [{"role": "user", "content": message}, {"role": "assistant", "content": answer}]
+    yield history + [[message, thinking]]
 
-# Interface Gradio
-with gr.Blocks(css=css) as demo:
-    gr.Markdown("<h1 style='text-align:center;color:#e0e0e0;'>Lambdai-v1-1B</h1>")
-    chatbot = gr.Chatbot(elem_id="chatbot", height=480, render_markdown=True)
+    prompt = f"Think step by step and explain your reasoning before answering:\n\n{message}"
+    response = client.chat_completion([{"role": "user", "content": prompt}], stream=False)
+    output = response['choices'][0]['message']['content']
 
-    with gr.Row():
-        user_input  = gr.Textbox(show_label=False, placeholder="Type your message here...", lines=2)
-        send_button = gr.Button("Send", elem_classes="pulse")
+    if "\n\n" in output:
+        reasoning, answer = output.split("\n\n", 1)
+    else:
+        reasoning, answer = "No reasoning provided.", output
 
-    # Aciona a função ao clicar no botão
-    send_button.click(
-        fn=respond,
-        inputs=[user_input, chatbot],
-        outputs=chatbot
-    )
+    reasoning_md = f"> {reasoning.strip()}"
+    final = f"{reasoning_md}\n\n{answer.strip()}"
+    yield history + [[message, final]]
+
+with gr.Blocks(css=css) as demo:
+    gr.Markdown("## Lambdai-v1-1B")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Message")
+    send = gr.Button("Send")
+
+    send.click(respond, [msg, chatbot], chatbot)
+    msg.submit(respond, [msg, chatbot], chatbot)
 
-    demo.launch()
+demo.launch()