dialog_topic_detection_mapper¶

Generates user’s topic labels and analysis in a dialog.

This operator processes a dialog to detect and label the topics discussed by the user. It takes input from history_key, query_key, and response_key and outputs lists of labels and analysis for each query in the dialog. The operator uses a predefined system prompt and templates to build the input prompt for the API call. It supports customizing the system prompt, templates, and patterns for parsing the API response. The results are stored in the meta field under the keys specified by labels_key and analysis_key. If these keys already exist in the meta field, the operator skips processing. The operator retries the API call up to try_num times in case of errors.

在对话中生成用户的话题标签和分析。

该算子处理对话以检测并标记用户讨论的话题。它从history_key、query_key和response_key获取输入，并为对话中的每个查询输出标签和分析列表。该算子使用预定义的系统提示和模板来构建API调用的输入提示。它支持自定义系统提示、模板和模式以解析API响应。结果存储在meta字段下的labels_key和analysis_key指定的键下。如果这些键已经存在于meta字段中，该算子将跳过处理。该算子在出现错误时最多重试try_num次API调用。

Type 算子类型: mapper

Tags 标签: cpu, api

🔧 Parameter Configuration 参数配置¶

name 参数名	type 类型	default 默认值	desc 说明
`api_model`	<class ‘str’>	`'gpt-4o'`	API model name.
`topic_candidates`	typing.Optional[typing.List[str]]	`None`	The output topic candidates. Use open-domain topic labels if it is None.
`max_round`	typing.Annotated[int, Ge(ge=0)]	`10`	The max num of round in the dialog to build the prompt.
`labels_key`	<class ‘str’>	`'dialog_topic_labels'`	The key name in the meta field to store the output labels. It is ‘dialog_topic_labels’ in default.
`analysis_key`	<class ‘str’>	`'dialog_topic_labels_analysis'`	The key name in the meta field to store the corresponding analysis. It is ‘dialog_topic_labels_analysis’ in default.
`api_endpoint`	typing.Optional[str]	`None`	URL endpoint for the API.
`response_path`	typing.Optional[str]	`None`	Path to extract content from the API response. Defaults to ‘choices.0.message.content’.
`system_prompt`	typing.Optional[str]	`None`	System prompt for the task.
`query_template`	typing.Optional[str]	`None`	Template for query part to build the input prompt.
`response_template`	typing.Optional[str]	`None`	Template for response part to build the input prompt.
`candidate_template`	typing.Optional[str]	`None`	Template for topic candidates to build the input prompt.
`analysis_template`	typing.Optional[str]	`None`	Template for analysis part to build the input prompt.
`labels_template`	typing.Optional[str]	`None`	Template for labels part to build the input prompt.
`analysis_pattern`	typing.Optional[str]	`None`	Pattern to parse the return topic analysis.
`labels_pattern`	typing.Optional[str]	`None`	Pattern to parse the return topic labels.
`try_num`	typing.Annotated[int, Gt(gt=0)]	`3`	The number of retry attempts when there is an API call error or output parsing error.
`model_params`	typing.Dict	`{}`	Parameters for initializing the API model.
`sampling_params`	typing.Dict	`{}`	Extra parameters passed to the API call. e.g {‘temperature’: 0.9, ‘top_p’: 0.95}
`kwargs`		`''`	Extra keyword arguments.

📊 Effect demonstration 效果演示¶

test_default¶

DialogTopicDetectionMapper(api_model='qwen2.5-72b-instruct')

📥 input data 输入数据¶

Sample 1: empty

history
('李莲花有口皆碑', '「微笑」过奖了，我也就是个普通大夫，没什么值得夸耀的。')
('是的，你确实是一个普通大夫，没什么值得夸耀的。', '「委屈」你这话说的，我也是尽心尽力治病救人了。')
('你自己说的呀，我现在说了，你又不高兴了。', 'or of of of of or or and or of of of of of of of,,, ')
('你在说什么我听不懂。', '「委屈」我也没说什么呀，就是觉得你有点冤枉我了')

📤 output data 输出数据¶