Update app.py

app.py

@@ -7,43 +7,13 @@ client = InferenceClient("lambdaindie/lambdai")
 css = """
 @import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono&display=swap');
 
+* {
+    font-family: 'JetBrains Mono', monospace !important;
+}
+
 body {
     background-color: #111;
     color: #e0e0e0;
-    font-family: 'JetBrains Mono', monospace;
-    margin: 0;
-    padding: 0;
-    width: 100vw;
-    overflow-x: hidden;
-}
-
-.gradio-container, .gr-block.gr-box {
-    width: 100vw !important;
-    max-width: 100vw !important;
-    box-sizing: border-box;
-}
-
-.gr-button {
-    background: linear-gradient(to right, #2a2a2a, #1f1f1f);
-    color: white;
-    border-radius: 10px;
-    padding: 8px 16px;
-    font-weight: bold;
-    font-family: 'JetBrains Mono', monospace;
-}
-.gr-button:hover {
-    background: #333;
-}
-.gr-textbox textarea {
-    background-color: #181818 !important;
-    color: #fff !important;
-    font-family: 'JetBrains Mono', monospace !important;
-    border-radius: 8px;
-}
-.gr-chat-message, .gr-chatbot {
-    font-family: 'JetBrains Mono', monospace !important;
-    width: 100% !important;
-    max-width: 100% !important;
 }
 
 .markdown-think {
@@ -53,9 +23,9 @@ body {
     margin-bottom: 8px;
     font-style: italic;
     white-space: pre-wrap;
-    font-family: 'JetBrains Mono', monospace;
     animation: pulse 1.5s infinite ease-in-out;
 }
+
 @keyframes pulse {
     0% { opacity: 0.6; }
     50% { opacity: 1.0; }
@@ -72,12 +42,10 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
         if assistant:
             messages.append({"role": "assistant", "content": assistant})
 
-    thinking_prompt = messages + [
-        {
-            "role": "user",
-            "content": f"{message}\n\nThink step-by-step before answering."
-        }
-    ]
+    thinking_prompt = messages + [{
+        "role": "user",
+        "content": f"{message}\n\nThink step-by-step before answering."
+    }]
 
     reasoning = ""
     yield '<div class="markdown-think">Thinking...</div>'
@@ -94,39 +62,17 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
         styled_thought = f'<div class="markdown-think">{reasoning.strip()}</div>'
         yield styled_thought
 
-    time.sleep(0.5)
-
-    final_prompt = messages + [
-        {"role": "user", "content": message},
-        {"role": "assistant", "content": reasoning.strip()},
-        {"role": "user", "content": "Now answer based on your reasoning above."}
-    ]
-
-    final_answer = ""
-    for chunk in client.chat_completion(
-        final_prompt,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = chunk.choices[0].delta.content or ""
-        final_answer += token
-        yield final_answer.strip()
-
 demo = gr.ChatInterface(
     fn=respond,
-    title="λmabdAI",  # Título visível agora
-    theme=gr.themes.Base(primary_hue="gray"),
+    title="λmabdAI",
+    theme=gr.themes.Base(),
     css=css,
     additional_inputs=[
-        gr.Textbox(
-            value="You are a concise, logical AI that explains its reasoning clearly before answering.",
-            label="System Message"
-        ),
-        gr.Slider(64, 2048, value=512, step=1, label="Max Tokens"),
-        gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
+        gr.Textbox(value="You are a concise, logical AI that explains its reasoning clearly before answering.",
+                   label="System Message", elem_classes=["jetbrains"]),
+        gr.Slider(64, 2048, value=512, step=1, label="Max Tokens", elem_classes=["jetbrains"]),
+        gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature", elem_classes=["jetbrains"]),
+        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p", elem_classes=["jetbrains"])
     ]
 )