update

app.py

@@ -0,0 +1,98 @@
+import spaces
+import os
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import gradio as gr
+
+
+huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
+if not huggingface_token:
+    pass
+    print("no HUGGINGFACE_TOKEN if you need set secret ")
+    #raise ValueError("HUGGINGFACE_TOKEN environment variable is not set")
+
+model_id = "openbmb/MiniCPM-2B-dpo-bf16"
+
+device = "auto" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
+dtype = torch.bfloat16
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, token=huggingface_token)
+
+print(model_id,device,dtype)
+histories = []
+#model = None
+
+
+def call_generate_text(prompt, system_message="You are a helpful assistant."):
+    if prompt =="":
+        print("empty prompt return")
+        return ""
+    
+    global histories
+    #global model
+    #if model != None:# and model.is_cuda:
+    #    print("Model is alive")
+    #else:
+    #    model = AutoModelForCausalLM.from_pretrained(
+    #    model_id, token=huggingface_token ,torch_dtype=dtype,device_map=device
+    #)
+        
+    messages = [
+        {"role": "system", "content": system_message},
+    ]
+    
+    messages += histories 
+
+    user_message = {"role": "user", "content": prompt}
+
+    messages += [user_message]
+    
+    try:
+        text = generate_text(messages)
+        histories += [user_message,{"role": "assistant", "content": text}]
+        #model.to("cpu")
+        return text
+    except RuntimeError  as e:
+        print(f"An unexpected error occurred: {e}")
+        #model = None
+
+    return ""
+
+iface = gr.Interface(
+    fn=call_generate_text,
+    inputs=[
+        gr.Textbox(lines=3, label="Input Prompt"),
+        gr.Textbox(lines=2, label="System Message", value="あなたは親切なアシスタントで常に日本語で返答します。"),
+    ],
+    outputs=gr.Textbox(label="Generated Text"),
+    title=f"{model_id}",
+    description=f"{model_id} CPU",
+)
+print("Initialized")
+
+model = AutoModelForCausalLM.from_pretrained(
+        model_id, token=huggingface_token ,torch_dtype=dtype,device_map=device
+    )
+
+def generate_text(messages):
+    #model.to("cuda")
+    
+        
+
+    text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer,torch_dtype=dtype,device_map=device) #pipeline has not to(device)
+    result = text_generator(messages, max_new_tokens=256, do_sample=True, temperature=0.7)
+
+    generated_output = result[0]["generated_text"]
+    if isinstance(generated_output, list):
+        for message in reversed(generated_output):
+            if message.get("role") == "assistant":
+                content= message.get("content", "No content found.")
+                return content
+            
+        return "No assistant response found."
+    else:
+        return "Unexpected output format."
+
+if __name__ == "__main__":
+    print("Main")
+    iface.launch()

requirements.txt

@@ -0,0 +1,6 @@
+numpy
+torch
+spaces
+accelerate
+transformers
+bitsandbytes