generate_qa_from_text_mapper

Generates question and answer pairs from text using a specified model.

This operator uses a Hugging Face model to generate QA pairs from the input text. It supports both Hugging Face and vLLM models for inference. The recommended models, such as 'alibaba-pai/pai-llama3-8b-doc2qa', are trained on Chinese data and are suitable for Chinese text. The operator can limit the number of generated QA pairs per text and allows custom output patterns for parsing the model's response. By default, it uses a regular expression to extract questions and answers from the model's output. If no QA pairs are extracted, a warning is logged.

使用指定模型从文本生成问题和答案对。

此算子使用Hugging Face模型从输入文本生成QA对。它支持使用Hugging Face和vLLM模型进行推理。推荐的模型，如'alibaba-pai/pai-llama3-8b-doc2qa'，是在中文数据上训练的，适合处理中文文本。算子可以限制每段文本生成的QA对数量，并允许自定义输出模式来解析模型的响应。默认情况下，它使用正则表达式从模型的输出中提取问题和答案。如果没有提取到QA对，将记录一条警告。

Type 算子类型: mapper

Tags 标签: cpu, vllm, hf, text

🔧 Parameter Configuration 参数配置

name 参数名

type 类型

default 默认值

desc 说明

hf_model

<class 'str'>

'alibaba-pai/pai-qwen1_5-7b-doc2qa'

Huggingface model ID.

max_num

typing.Optional[typing.Annotated[int, Gt(gt=0)]]

None

The max num of returned QA sample for each text.

output_pattern

typing.Optional[str]

None

Regular expression pattern to extract

enable_vllm

<class 'bool'>

False

Whether to use vllm for inference acceleration.

model_params

typing.Optional[typing.Dict]

None

Parameters for initializing the model.

sampling_params

typing.Optional[typing.Dict]

None

Sampling parameters for text generation,

kwargs

''

Extra keyword arguments.

📊 Effect demonstration 效果演示

not available 暂无