dataset_retriever_tool.py 4.1 KB

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  1. from collections.abc import Generator
  2. from typing import Any
  3. from core.app.app_config.entities import DatasetRetrieveConfigEntity
  4. from core.app.entities.app_invoke_entities import InvokeFrom
  5. from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
  6. from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
  7. from core.tools.entities.common_entities import I18nObject
  8. from core.tools.entities.tool_entities import (
  9. ToolDescription,
  10. ToolIdentity,
  11. ToolInvokeMessage,
  12. ToolParameter,
  13. ToolProviderType,
  14. )
  15. from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
  16. from core.tools.tool.tool import Tool
  17. class DatasetRetrieverTool(Tool):
  18. retrival_tool: DatasetRetrieverBaseTool
  19. @staticmethod
  20. def get_dataset_tools(tenant_id: str,
  21. dataset_ids: list[str],
  22. retrieve_config: DatasetRetrieveConfigEntity,
  23. return_resource: bool,
  24. invoke_from: InvokeFrom,
  25. hit_callback: DatasetIndexToolCallbackHandler
  26. ) -> list['DatasetRetrieverTool']:
  27. """
  28. get dataset tool
  29. """
  30. # check if retrieve_config is valid
  31. if dataset_ids is None or len(dataset_ids) == 0:
  32. return []
  33. if retrieve_config is None:
  34. return []
  35. feature = DatasetRetrieval()
  36. # save original retrieve strategy, and set retrieve strategy to SINGLE
  37. # Agent only support SINGLE mode
  38. original_retriever_mode = retrieve_config.retrieve_strategy
  39. retrieve_config.retrieve_strategy = DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE
  40. retrival_tools = feature.to_dataset_retriever_tool(
  41. tenant_id=tenant_id,
  42. dataset_ids=dataset_ids,
  43. retrieve_config=retrieve_config,
  44. return_resource=return_resource,
  45. invoke_from=invoke_from,
  46. hit_callback=hit_callback
  47. )
  48. # restore retrieve strategy
  49. retrieve_config.retrieve_strategy = original_retriever_mode
  50. # convert retrival tools to Tools
  51. tools = []
  52. for retrival_tool in retrival_tools:
  53. tool = DatasetRetrieverTool(
  54. retrival_tool=retrival_tool,
  55. identity=ToolIdentity(provider='', author='', name=retrival_tool.name, label=I18nObject(en_US='', zh_Hans='')),
  56. parameters=[],
  57. is_team_authorization=True,
  58. description=ToolDescription(
  59. human=I18nObject(en_US='', zh_Hans=''),
  60. llm=retrival_tool.description),
  61. runtime=DatasetRetrieverTool.Runtime()
  62. )
  63. tools.append(tool)
  64. return tools
  65. def get_runtime_parameters(self) -> list[ToolParameter]:
  66. return [
  67. ToolParameter(name='query',
  68. label=I18nObject(en_US='', zh_Hans=''),
  69. human_description=I18nObject(en_US='', zh_Hans=''),
  70. type=ToolParameter.ToolParameterType.STRING,
  71. form=ToolParameter.ToolParameterForm.LLM,
  72. llm_description='Query for the dataset to be used to retrieve the dataset.',
  73. required=True,
  74. default=''),
  75. ]
  76. def tool_provider_type(self) -> ToolProviderType:
  77. return ToolProviderType.DATASET_RETRIEVAL
  78. def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]:
  79. """
  80. invoke dataset retriever tool
  81. """
  82. query = tool_parameters.get('query')
  83. if not query:
  84. return self.create_text_message(text='please input query')
  85. # invoke dataset retriever tool
  86. result = self.retrival_tool._run(query=query)
  87. yield self.create_text_message(text=result)
  88. def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None:
  89. """
  90. validate the credentials for dataset retriever tool
  91. """
  92. pass