正如标题所说，我有一个blob触发的启动器函数，我希望将触发启动器的blob作为输入发送到activity函数。我可以选择使用.start_new（）方法传入输入，但这些输入必须是JSON可序列化的，而blob文件（func.InputStream）不是。
我尝试解码InputStream对象（myblob），它允许我将其作为输入传递，但我失去了一些基本功能，当它是InputStream对象时，我还需要确保我能够将其传递到将在Activity函数中调用的后续认知服务中。请参阅下面的starter函数代码。
启动器功能

函数.json`

{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "name": "myblob",
      "type": "blobTrigger",
      "direction": "in",
      "path": "container/{name}",
      "connection": "conn str"
    },
    {
      "name": "$return",
      "type": "blob",
      "path": "container/{name}",
      "connection": "AzureWebJobsStorage",
      "direction": "out"
    },
    {
      "name": "starter",
      "type": "durableClient",
      "direction": "in"
    }
  ]
}

`init.py

async def main(myblob: func.InputStream, starter: str) -> func.InputStream:
    logging.info(f"Python blob trigger function processed blob \n"
                 f"Name: {myblob.name}\n"
                 f"Blob Size: {myblob.length} bytes\n\n")        
    client = df.DurableOrchestrationClient(starter)
    instance_id = await client.start_new('Orchestrator', client_input=myblob) ##Client_input must be json serializable
    logging.info(f"Started orchestration with ID = '{instance_id}'.")
    return myblob

返回：异常：类型错误：class〈class 'azure.functions.blob. InputStream'〉不公开to_json函数