Update app.py

app.py

@@ -2,6 +2,7 @@ import os
 import gradio as gr
 from llama_cpp import Llama
 
+# CPU最適化
 os.environ["OMP_NUM_THREADS"] = "8"
 os.environ["OPENBLAS_NUM_THREADS"] = "8"
 os.environ["MKL_NUM_THREADS"] = "8"
@@ -9,9 +10,9 @@ os.environ["MKL_NUM_THREADS"] = "8"
 llm = Llama.from_pretrained(
     repo_id="summerMC/ume-GGUF",
     filename="ume-Q4_K_M.gguf",
-    n_ctx=768,
-    n_threads=8,
-    n_batch=512,
+    n_ctx=768,          # 小さめにすると速い
+    n_threads=8,        # SpaceのCPUコア数に合わせて調整
+    n_batch=512,        # prompt処理高速化
     n_ubatch=128,
     use_mmap=True,
     use_mlock=False,
@@ -23,8 +24,9 @@ llm = Llama.from_pretrained(
 def respond(message, history, system_message, max_tokens, temperature, top_p):
     messages = [{"role": "system", "content": system_message}]
 
+    # Gradio ChatInterface の history は [(user, assistant), ...]
     for user_msg, bot_msg in history:
-        messages.append({"role": "user", "content": user_msg)
+        messages.append({"role": "user", "content": user_msg})
         if bot_msg:
             messages.append({"role": "assistant", "content": bot_msg})
 
@@ -33,19 +35,24 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
     response = ""
     for chunk in llm.create_chat_completion(
         messages=messages,
-        max_tokens=min(int(max_tokens), 256),
+        max_tokens=min(int(max_tokens), 256),  # CPUでは長すぎると遅い
         temperature=float(temperature),
         top_p=float(top_p),
         stream=True,
     ):
-        token = chunk["choices"][0].get("delta", {}).get("content", "")
+        delta = chunk["choices"][0].get("delta", {})
+        token = delta.get("content", "")
         response += token
         yield response
 
+
 chatbot = gr.ChatInterface(
-    respond,
+    fn=respond,
     additional_inputs=[
-        gr.Textbox(value="You are a concise assistant.", label="System message"),
+        gr.Textbox(
+            value="You are a concise and helpful assistant.",
+            label="System message"
+        ),
         gr.Slider(1, 256, value=128, step=1, label="Max new tokens"),
         gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-p"),