app.py

import spaces
import os
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
from transformers import TextIteratorStreamer
from threading import Thread

import gradio as gr

text_generator = None

model_id = "AXCXEPT/phi-4-deepseek-R1K-RL-EZO"
#model_id = "AXCXEPT/phi-4-open-R1-Distill-EZOv1"#not well work with my old code

huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
huggingface_token = None
device = "auto" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
device = "cuda"
dtype = torch.bfloat16

if not huggingface_token:
    pass
    print("no HUGGINGFACE_TOKEN if you need set secret ")
    #raise ValueError("HUGGINGFACE_TOKEN environment variable is not set")
        

    
    
    



tokenizer = AutoTokenizer.from_pretrained(model_id, token=huggingface_token)
#print(tokenizer.special_tokens_map)

# 特殊トークンIDを確認
#print(tokenizer.eos_token_id)
#print(tokenizer.encode("<|im_end|>", add_special_tokens=False))

#print(model_id,device,dtype)
histories = []

model = AutoModelForCausalLM.from_pretrained(
                model_id, token=huggingface_token ,torch_dtype=dtype,device_map=device
            )
model.to(device)

def generate_text(messages):

    question = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
    question = tokenizer(question, return_tensors="pt").to(device)
    

    streamer = TextIteratorStreamer(tokenizer, skip_prompt=True)
    generation_kwargs = dict(question, streamer=streamer, max_new_tokens=1000)
    thread = Thread(target=model.generate, kwargs=generation_kwargs)
    
    generated_output = ""
    thread.start()
    for new_text in streamer:
        generated_output += new_text.replace("<|im_end|>","")#just replace
        yield generated_output            
    
# SDK version is very important in README.md
@spaces.GPU(duration=120)
def call_generate_text(message, history):  
    messages = history+[{"role":"user","content":message}]
    try:
        
        for text in generate_text(messages):
            yield text
    except RuntimeError  as e:
        print(f"An unexpected error occurred: {e}")
        yield ""

demo = gr.ChatInterface(call_generate_text,type="messages",title="Chat with phi-4-deepseek-R1K-RL-EZO",description="Thanks for 1 Like.This is switched to CPU.maybe this will not work. Unofficial,little bit code is old.If the LLM stops generating text, please input 'continue'.")

if __name__ == "__main__":
    demo.queue()
    demo.launch()