Upload app.py with huggingface_hub

app.py

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+"""
+☕ Coffee Barista v42 — Gradio Space
+Chat-only coffee expert, no tools needed.
+"""
+import gradio as gr
+from llama_cpp import Llama
+
+MODEL_URL = "https://huggingface.co/ynanxiu/qwen25-3b-coffee-master-gguf/resolve/main/qwen25_3b_coffee_master_v43_q4km.gguf"
+MODEL_PATH = "qwen25_3b_coffee_master_v43_q4km.gguf"
+
+SYSTEM_PROMPT = "你是一个专业咖啡师，拥有丰富的咖啡知识和吧台经验。用自然、亲切的中文回答，像在跟熟客聊天一样。回复简洁、有人情味，1-3句话。"
+
+# Download model on startup
+import os
+if not os.path.exists(MODEL_PATH):
+    from huggingface_hub import hf_hub_download
+    hf_hub_download(repo_id="ynanxiu/qwen25-3b-coffee-master-gguf", filename="qwen25_3b_coffee_master_v42_q4km.gguf", local_dir=".")
+
+llm = Llama(model_path=MODEL_PATH, n_ctx=2048, n_threads=4, verbose=False)
+
+def chat(message, history):
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+    for h in history:
+        messages.append({"role": "user", "content": h[0]})
+        if h[1]:
+            messages.append({"role": "assistant", "content": h[1]})
+    messages.append({"role": "user", "content": message})
+    
+    response = llm.create_chat_completion(
+        messages=messages,
+        temperature=0.7,
+        max_tokens=100,                              # ← 硬截断，≈ 150 汉字
+        repeat_penalty=1.15,                         # ← 防复读机
+        stop=["<|im_end|>", "<|im_start|>", "\n\n"], # ← 自然段落处停
+    )
+    return response["choices"][0]["message"]["content"]
+
+demo = gr.ChatInterface(
+    fn=chat,
+    title="☕ 咖啡大师 Chat",
+    description="一个懂咖啡、会聊天的 AI 咖啡师。问我任何咖啡问题！",
+    examples=[
+        "手冲咖啡水温怎么选？",
+        "拿铁和卡布奇诺有什么区别？",
+        "新手学咖啡从哪开始？",
+        "深烘豆手冲有什么技巧？",
+    ],
+    theme="soft",
+)
+
+if __name__ == "__main__":
+    demo.launch()