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"""
This script creates a CLI demo with vllm backand for the glm-4-9b model,
allowing users to interact with the model through a command-line interface.
Usage:
- Run the script to start the CLI demo.
- Interact with the model by typing questions and receiving responses.
Note: The script includes a modification to handle markdown to plain text conversion,
ensuring that the CLI interface displays formatted text correctly.
"""
import time
import asyncio
from transformers import AutoTokenizer
from vllm import SamplingParams, AsyncEngineArgs, AsyncLLMEngine
from typing import List, Dict
MODEL_PATH = 'THUDM/glm-4-9b'
def load_model_and_tokenizer(model_dir: str):
engine_args = AsyncEngineArgs(
model=model_dir,
tokenizer=model_dir,
tensor_parallel_size=1,
dtype="bfloat16",
trust_remote_code=True,
gpu_memory_utilization=0.3,
enforce_eager=True,
worker_use_ray=True,
engine_use_ray=False,
disable_log_requests=True
# 如果遇见 OOM 现象，建议开启下述参数
# enable_chunked_prefill=True,
# max_num_batched_tokens=8192
)
tokenizer = AutoTokenizer.from_pretrained(
model_dir,
trust_remote_code=True,
encode_special_tokens=True
)
engine = AsyncLLMEngine.from_engine_args(engine_args)
return engine, tokenizer
engine, tokenizer = load_model_and_tokenizer(MODEL_PATH)
async def vllm_gen(messages: List[Dict[str, str]], top_p: float, temperature: float, max_dec_len: int):
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=False
)
params_dict = {
"n": 1,
"best_of": 1,
"presence_penalty": 1.0,
"frequency_penalty": 0.0,
"temperature": temperature,
"top_p": top_p,
"top_k": -1,
"use_beam_search": False,
"length_penalty": 1,
"early_stopping": False,
"stop_token_ids": [151329, 151336, 151338],
"ignore_eos": False,
"max_tokens": max_dec_len,
"logprobs": None,
"prompt_logprobs": None,
"skip_special_tokens": True,
}
sampling_params = SamplingParams(**params_dict)
async for output in engine.generate(inputs=inputs, sampling_params=sampling_params, request_id=f"{time.time()}"):
yield output.outputs[0].text
async def chat():
history = []
max_length = 8192
top_p = 0.8
temperature = 0.6
print("Welcome to the GLM-4-9B CLI chat. Type your messages below.")
while True:
user_input = input("\nYou: ")
if user_input.lower() in ["exit", "quit"]:
break
history.append([user_input, ""])
messages = []
for idx, (user_msg, model_msg) in enumerate(history):
if idx == len(history) - 1 and not model_msg:
messages.append({"role": "user", "content": user_msg})
break
if user_msg:
messages.append({"role": "user", "content": user_msg})
if model_msg:
messages.append({"role": "assistant", "content": model_msg})
print("\nGLM-4: ", end="")
current_length = 0
output = ""
async for output in vllm_gen(messages, top_p, temperature, max_length):
print(output[current_length:], end="", flush=True)
current_length = len(output)
history[-1][1] = output
if __name__ == "__main__":
asyncio.run(chat())
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