Update app.py

app.py

@@ -2,30 +2,33 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import time
 
-client = InferenceClient("lambdaindie/lambdai")
+# Clientes para texto e imagem
+chat_client = InferenceClient("lambdaindie/lambdai")
+image_client = InferenceClient("stabilityai/stable-diffusion-2")
 
-css = """
-@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono&display=swap');
-
-* {
-    font-family: 'JetBrains Mono', monospace !important;
-}
+# Fonte global
+gr.themes.Base().set(font=["JetBrains Mono", "monospace"])
 
+css = """
 body {
+    font-family: 'JetBrains Mono', monospace;
     background-color: #111;
     color: #e0e0e0;
 }
-
+.gr-textbox textarea {
+    background-color: #181818 !important;
+    color: #fff !important;
+    font-family: 'JetBrains Mono', monospace;
+    border-radius: 8px;
+}
 .markdown-think {
     background-color: #1e1e1e;
     border-left: 4px solid #555;
     padding: 10px;
     margin-bottom: 8px;
     font-style: italic;
-    white-space: pre-wrap;
     animation: pulse 1.5s infinite ease-in-out;
 }
-
 @keyframes pulse {
     0% { opacity: 0.6; }
     50% { opacity: 1.0; }
@@ -33,6 +36,7 @@ body {
 }
 """
 
+# Função do chatbot com raciocínio
 def respond(message, history, system_message, max_tokens, temperature, top_p):
     messages = [{"role": "system", "content": system_message}] if system_message else []
 
@@ -42,15 +46,14 @@ 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>'
 
-    for chunk in client.chat_completion(
+    for chunk in chat_client.chat_completion(
         thinking_prompt,
         max_tokens=max_tokens,
         stream=True,
@@ -59,8 +62,7 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
     ):
         token = chunk.choices[0].delta.content or ""
         reasoning += token
-        styled_thought = f'<div class="markdown-think">{reasoning.strip()}</div>'
-        yield styled_thought
+        yield f'<div class="markdown-think">{reasoning.strip()}</div>'
 
     time.sleep(0.5)
 
@@ -71,7 +73,7 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
     ]
 
     final_answer = ""
-    for chunk in client.chat_completion(
+    for chunk in chat_client.chat_completion(
         final_prompt,
         max_tokens=max_tokens,
         stream=True,
@@ -82,19 +84,35 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
         final_answer += token
         yield final_answer.strip()
 
-demo = gr.ChatInterface(
-    fn=respond,
-    title="λambdAI",
-    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")
-    ]
-)
+# Função para gerar imagem
+def generate_image(prompt):
+    return image_client.text_to_image(prompt, guidance_scale=7.5)
+
+# Interface Gradio
+with gr.Blocks(css=css, theme=gr.themes.Base()) as demo:
+    gr.Markdown("# λmabdAI")
+
+    with gr.Tabs():
+        with gr.Tab("Chat"):
+            gr.ChatInterface(
+                fn=respond,
+                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")
+                ]
+            )
+
+        with gr.Tab("Image Generator"):
+            gr.Markdown("### Generate an image from a prompt")
+            prompt = gr.Textbox(label="Prompt")
+            output = gr.Image(type="pil")
+            btn = gr.Button("Generate")
+            btn.click(fn=generate_image, inputs=prompt, outputs=output)
 
 if __name__ == "__main__":
     demo.launch()