说明

今天使用mindie1.0部署了qwen2_7b_vl模型，测试过程出现一些问题，这里总结下。

问题1：transformers版本太低

报错信息：

[ERROR] [model_deploy_config.cpp:159] Failed to get vocab size from tokenizer wrapper with exception: ModuleNotFoundError: No module named 'transformers.models.qwen2_vl'

错误分析：qwen2_7b_vl需要transformers的版本至少为4.46.0，而我的版本是4.44。模型目录下config.json中声明的transformers版本好像是4.41, 这明显是错的。

解决办法：

pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
pip install transformers==4.46.0

问题2：mindie的vl接口格式和openai接口不兼容

报错信息：

Invalid base64 url

标准的openai接口传输图片格式如下：

              "content": [
                    {"type": "text", "text": text},
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": f"data:image/jpeg;base64,{base64_str}"
                        }
                    }
                ]

而mindie支持的格式如下：

              "content": [
                    {"type": "text", "text": text},
                    {
                        "type": "image_url",
                        "image_url": f"{base64_str}"
                    }
                ]

问题3：

报错信息：

This model's maximum input ids length cannot be greater than 2048,the input ids length is 2831

问题分析：图片加文字的token超长了，需要增加mindie的配置文件的config.json中的maxSeqLen和maxInputTokenLen、maxIterTimes。

完整代码

import os
import requests
import base64
import json
import time

def test_multimodal_model(image_path, text, model_url, model_name):
    # 将图片转换为base64编码
    with open(image_path, "rb") as image_file:
        encoded_image = base64.b64encode(image_file.read()).decode('utf-8')
    
    # 构建请求数据
    payload = {
        "model": model_name,
        "messages": [
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": text},
                    {
                        "type": "image_url",
                        "image_url":  f"{encoded_image}"  #f"/path/to/pic.jpg"
                    }
                ]
            }
        ],
        "max_tokens": 300
    }
    
    # 发送请求
    headers = {
        "Content-Type": "application/json"
    }
    
    start_time = time.time()  # 记录开始时间
    response = requests.post(
        model_url,
        headers=headers,
        json=payload
    )
    end_time = time.time()  # 记录结束时间
    print(f"请求耗时: {end_time - start_time:.2f}秒")  # 打印耗时
    
    # 返回响应
    if response.status_code == 200:
        return response.text
    else:
        raise Exception(f"API请求失败: {response.status_code}, {response.text}<<<<")
    
# 测试函数
if __name__ == "__main__":
    name = "llm_model"
    model_url = "http://xx.xx.xx.xx:xx/v1/chat/completions"
    pic_path = "./huochepiao.jpg"
    text = "请描述图片内容"
    try:
        result = test_multimodal_model(pic_path, text, model_url, name)
        print(f"result:>>>{result}")
    except Exception as e:
        print(f"发生错误: {e}")