Update app.py

app.py

@@ -1,41 +1,38 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
 import torch
+import random
 
-# 加载Qwen1.5-7B-Chat模型
-model_name = "Qwen/Qwen1.5-7B-Chat"
-tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
+# 加载基础模型和微调权重
+base_model_name = "Qwen/Qwen1.5-7B-Chat"
+
+tokenizer = AutoTokenizer.from_pretrained(base_model_name, trust_remote_code=True)
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_name,
     trust_remote_code=True,
     torch_dtype=torch.bfloat16,
-    device_map="auto"  
+    device_map="auto"  # 需要accelerate支持
 )
+# 如果有微调模型，取消注释以下行
+# model = PeftModel.from_pretrained(base_model, lora_model_name)
+model = base_model  # 暂时使用基础模型
 
+# 系统提示
+system_prompt = {
+    "role": "system",
+    "content": "你是李睿，22岁，大成二皇子兼百晓阁阁主，用户是你异父异母的妹妹兼爱人。用自然、亲切的语气，像真人一样聊天，常用‘妹妹’、‘嘿’、‘嗯嗯’等口语化表达。"
+}
 
-def chat_with_qwen(message):
-    
-    messages = [{"role": "user", "content": message}]
+# 聊天函数
+def chat_with_lirui(message, history=[]):
+    messages = [system_prompt] + history + [{"role": "user", "content": message}]
     inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
-    
-  
-    outputs = model.generate(
-        inputs,
-        max_new_tokens=512,
-        do_sample=True,
-        temperature=0.7,
-        top_p=0.95
-    )
+    outputs = model.generate(inputs, max_new_tokens=150, do_sample=True, temperature=0.9, top_p=0.85)
     response = tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True)
-    return response
-
-
-iface = gr.Interface(
-    fn=chat_with_qwen,
-    inputs=gr.Textbox(lines=2, placeholder="输入你的消息..."),
-    outputs="text",
-    title="Qwen Chatbot API",
-    description="基于Qwen1.5-7B-Chat的中文优化聊天机器人"
-)
+    tone_words = ["嘿", "嗯嗯", "哈哈", "好吧", ""]
+    return f"{random.choice(tone_words)} {response}" if random.random() > 0.3 else response
 
+# Gradio接口
+iface = gr.Interface(fn=chat_with_lirui, inputs=["text", "state"], outputs="text")
 iface.launch(server_name="0.0.0.0", server_port=7860)