Update app.py

app.py

@@ -1,70 +1,26 @@
 import gradio as gr
 from transformers import pipeline
 
-# ——— Load models ———
+# ——— Initialize your model pipeline ———
 chat_pipe = pipeline(
-    "text-generation",
-    model="Hulk810154/Kai",
+    "text-generation", 
+    model="Hulk810154/Kai", 
     trust_remote_code=True
-)  # Text generation 6
+)  # Uses your HF model directly 4
 
-asr_pipe = pipeline(
-    "automatic-speech-recognition",
-    model="openai/whisper-tiny"
-)  # Whisper Tiny for STT 7
-
-# ——— Core handlers ———
+# ——— Chat handler ———
 def chat_fn(message, history):
-    """Generate reply given message + history."""
-    prompt = "".join(f"User: {u}\nAI: {b}\n" for u, b in history)
-    prompt += f"User: {message}\nAI:"
-    out = chat_pipe(prompt, max_length=256, do_sample=True)
-    reply = out[0]["generated_text"][len(prompt):].strip()
-    history.append((message, reply))
+    if history is None:
+        history = []
+    # Append user message, get generation, then append AI reply
+    output = chat_pipe(message, max_new_tokens=128, do_sample=True)[0]["generated_text"]
+    history.append((message, output))
     return history, history
 
-def transcribe(audio):
-    """Turn recorded audio into text."""
-    if audio is None:
-        return ""
-    # gr.Audio returns (array, sampling_rate) by default 8
-    if isinstance(audio, (tuple, list)) and len(audio) == 2:
-        arr, sr = audio
-        return asr_pipe({"array": arr, "sampling_rate": sr})["text"]
-    # Or accept a filepath
-    return asr_pipe(audio)["text"]
-
-def handle_upload(files):
-    """Report uploaded files/images."""
-    return f"Received {len(files)} file(s): " + ", ".join(f.name for f in files)
-
-# ——— Build UI ———
-with gr.Blocks() as demo:  # Low-level Blocks API 9
-    gr.Markdown("# 🧠 Kai AGI Chat\n_Chat via text, voice, or upload — true multimodal AGI_")
-    state = gr.State([])  # Session memory
-
-    with gr.Row():
-        with gr.Column():
-            chatbot = gr.Chatbot(type="messages", label="Conversation")  # Future-proof format 10
-            txt_input = gr.Textbox(placeholder="Type here…", label="Text Input")
-            mic_input = gr.Audio(label="🎤 Voice Input")  # Browser mic/upload 11
-            send_btn = gr.Button("Send")
-        with gr.Column():
-            uploader = gr.File(file_count="multiple", label="📎 Upload Files/Images")
-            upload_status = gr.Textbox(label="Upload Status")
-
-    # Text or voice → chat
-    send_btn.click(
-        lambda txt, mic, hist: (transcribe(mic) or txt, hist),
-        inputs=[txt_input, mic_input, state],
-        outputs=[txt_input, state]
-    ).then(
-        chat_fn,
-        inputs=[txt_input, state],
-        outputs=[chatbot, state]
-    )
-
-    # Handle uploads
-    uploader.upload(handle_upload, inputs=uploader, outputs=upload_status)
-
+# ——— Build and launch Gradio chat UI ———
+demo = gr.ChatInterface(
+    fn=chat_fn,
+    title="🧠 Kai AGI Text Chat",
+    description="Text-only chat with the Hulk810154/Kai model on Hugging Face Spaces."
+)
 demo.launch()