Azure-Samples / Azure-Samples/rag-data-openai-python-promptflow
calling pf_client.run inside the callable target function for evaluate got "Error: (AssertionError) daemonic processes are not allowed to have children."
- 主要语言
- Python
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- 290
- 派生
- 152
- PR 合并指标
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描述
> Please provide us with the following information:
> ---------------------------------------------------------------
### This issue is for a: (mark with an `x`)
```
- [ ] bug report -> please search issues before submitting
- [ ] feature request
- [ ] documentation issue or request
- [ ] regression (a behavior that used to work and stopped in a new release)
```
### Minimal steps to reproduce
>
I am trying to hook up the evaluate method with my own prompt which used to run from pf_client.run
example code below:
```
from promptflow.client import PFClient
pf_client = PFClient()
def user_call():
my_prompt_flow = pf_client.run(my prompt flow configs)
return my_prompt_flow_output
def run_evaluation():
results = evaluate(
evaluation_name=evaluation_name,
data=data_path,
target=user_call,
evaluators={
"violence": violence_evaluator,
"sexual": sex_evaluator,
"self_harm": self_harm_evaluator,
"hate_unfairnes": hate_unfairness_evaluator,
"content_safety": content_safety_evaluator
},
azure_ai_project=project_scope
)
```
### Any log messages given by the failure
>
2024-07-06 00:58:41 +0000 1845174 execution.bulk INFO The process [1845174] has received a terminate signal.
2024-07-06 00:58:42 +0000 1844849 execution ERROR 1/1 flow run failed, indexes: [0], exception of index 0: Execution failure in 'user_call': (UnexpectedError) **Unexpected error occurred while executing the batch run. Error: (AssertionError) daemonic processes are not allowed to have children.**
### Expected/desired behavior
>
### OS and Version?
> Windows 7, 8 or 10. Linux (which distribution). macOS (Yosemite? El Capitan? Sierra?)
Linux
### Versions
>
### Mention any other details that might be useful
> ---------------------------------------------------------------
> Thanks! We'll be in touch soon.
贡献指南
这个仓库没有索引到贡献指南
调研方向
首先在 Linux 上重现所示的 evaluate(target=user_call) 流程,重点关注 pf_client.run 与评估 worker 进程之间的交互。将其与直接调用 pf_client.run 进行比较,并确定需要进行哪些更改,才能在不触发 daemonic-process assertion 的情况下完成评估。
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- azure, python
- 领域
- ai
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 需要澄清
- 新手友好度
- 25/100