FastGPT/packages/web/i18n/en/workflow.json

{
  " i18nT('workflow": {
    "use_user_id'),\n    required": {
      "workflow": {
        "use_user_id": ""
      }
    }
  },
  "Code": "Code",
  "about_xxx_question": "Questions about xxx",
  "add_new_input": "Add input",
  "append_application_reply_to_history_as_new_context": "Splice the app's reply content into the history and return it as new context",
  "application_call": "application call",
  "assigned_reply": "Specify reply",
  "choose_another_application_to_call": "Select a different app to call",
  "classification_result": "Classification results",
  "code": {
    "Reset template": "Reset template",
    "Reset template confirm": "Are you sure to restore the code template? All input and output to template values will be reset, please be careful to save the current code."
  },
  "code_execution": "code run",
  "collection_metadata_filter": "Collection metadata filtering",
  "complete_extraction_result": "Complete extraction results",
  "complete_extraction_result_description": "A JSON string, for example: {\"name:\":\"YY\",\"Time\":\"2023/7/2 18:00\"}",
  "concatenation_result": "Splicing result",
  "concatenation_text": "Splice text",
  "condition_checker": "Judger",
  "confirm_delete_field_tip": "Confirm to delete the field?",
  "contains": "Include",
  "content_to_retrieve": "Content to be retrieved",
  "content_to_search": "Content to be retrieved",
  "create_link_error": "Create link exception",
  "custom_feedback": "Custom feedback",
  "custom_input": "Custom input",
  "custom_plugin_output": "Custom plug-in output",
  "delete_api": "Are you sure you want to delete this API key? \nAfter deletion, the key will become invalid immediately and the corresponding conversation log will not be deleted. Please confirm!",
  "dynamic_input_description": "Receives the output value of the previous node as variables, which can be used by Laf request parameters.",
  "dynamic_input_description_concat": "Can reference the output of other nodes, as variables for text splicing, input/evoke variable lists",
  "edit_input": "Edit input",
  "end_with": "ends with",
  "error_info_returns_empty_on_success": "Code running error message, returns empty when successful",
  "execute_a_simple_script_code_usually_for_complex_data_processing": "Execute a simple script code, usually used for complex data processing.",
  "execute_different_branches_based_on_conditions": "Depending on certain conditions, different branches are executed.",
  "execution_error": "Run error",
  "extraction_requirements_description": "Extract requirement description",
  "extraction_requirements_description_detail": "Give the AI ​​some corresponding background knowledge or description of requirements to guide the AI ​​to complete the task better. \n\\nThis input box can use global variables.",
  "extraction_requirements_placeholder": "For example: \\n1. The current time is: {{cTime}}. \nYou are a laboratory reservation assistant. Your task is to help users make laboratory reservations and obtain the corresponding reservation information from the text. \n\\n2. You are the Google search assistant and need to extract appropriate search terms from the text.",
  "feedback_text": "Text of feedback",
  "field_description": "Field description",
  "field_description_placeholder": "Describes the functionality of this input field, which affects the quality of model generation if the parameter is called for a tool",
  "field_name_already_exists": "Field name already exists",
  "field_required": "Required",
  "field_used_as_tool_input": "As tool input",
  "filter_description": "Currently, label and creation time filtering is supported, which needs to be filled in according to the following format:\n\n{\n  \n\"tags\": {\n    \n\"$and\": [\"tag 1\",\"tag 2\"],\n    \n\"$or\": [\"When there is $and tag, and takes effect, or does not take effect\"]\n  \n},\n  \n\"createTime\": {\n      \n\"$gte\": \"YYYY-MM-DD HH:mm format is sufficient. The creation time of the collection is greater than this time\",\n      \n\"$lte\": \"YYYY-MM-DD HH:mm format is sufficient. The creation time of the collection is less than this time. It can be used together with $gte\"\n  \n}\n\n}",
  "full_field_extraction": "Complete extraction of fields",
  "full_field_extraction_description": "Returns true when the extracted fields are all filled in (model extraction or using default values ​​is considered successful)",
  "full_response_data": "Complete response data",
  "greater_than": "greater than",
  "greater_than_or_equal_to": "Greater than or equal to",
  "greeting": "greet",
  "http_raw_response_description": "The raw response of the HTTP request. \nOnly string or JSON type response data can be accepted.",
  "http_request": "HTTP request",
  "http_request_error_info": "HTTP request error information, returns empty when successful",
  "ifelse": {
    "Input value": "Input",
    "Select value": "Select"
  },
  "input_description": "Input descriotion",
  "input_variable_list": "Enterable/evoked variable list",
  "intro_assigned_reply": "This module can directly reply to a specified piece of content. \nOften used for guidance and prompts. \nWhen non-string content is passed in, it will be converted into a string for output.",
  "intro_custom_feedback": "When this module is triggered, a piece of feedback will be added to the current conversation record. \nCan be used to automatically record dialogue effects, etc.",
  "intro_custom_plugin_output": "Customize the external output of the configuration. When using the plug-in, only the output of the custom configuration is exposed.",
  "intro_http_request": "You can issue an HTTP request to implement more complex operations (network search, database query, etc.)",
  "intro_knowledge_base_search_merge": "Multiple knowledge base search results can be combined and output. \nUse RRF's merge method for final sorting output.",
  "intro_laf_function_call": "You can call cloud functions under the Laf account.",
  "intro_plugin_input": "You can configure what inputs the plug-in requires and use these inputs to run the plug-in",
  "intro_question_classification": "Determine the type of question based on the user's history and current questions. \nMultiple sets of question types can be added. Here is an example template:\n\nType 1: Say hello\n\nType 2: Questions about the “use” of the product\n\nType 3: Questions about product “purchase”\n\nType 4: Other questions",
  "intro_question_optimization": "Using the question optimization function, you can improve the search accuracy during continuous dialogue in the knowledge base. \nAfter using this function, AI will first be used to construct one or more new search terms based on the context. These search terms are more conducive to knowledge base searches. \nThis module has been built into the knowledge base search module. If you only perform a knowledge base search, you can directly use the completion function built into the knowledge base.",
  "intro_text_concatenation": "Fixed or incoming text can be processed and output, and non-string type data will eventually be converted into string type.",
  "intro_text_content_extraction": "Specified data can be extracted from text, such as SQL statements, search keywords, codes, etc.",
  "intro_tool_call_termination": "This module needs to be called by the configuration tool. \nWhen this module is executed, this tool call will be forcibly ended, and AI will no longer be called to answer questions based on the tool call results.",
  "is_empty": "is empty",
  "is_equal_to": "equal",
  "is_not_empty": "Not empty",
  "is_not_equal": "not equal to",
  "judgment_result": "Judgment result",
  "knowledge_base_reference": "Knowledge base reference",
  "knowledge_base_search_merge": "Knowledge base search citation merge",
  "laf_function_call_test": "Laf function call (test)",
  "length_equal_to": "The length is equal to",
  "length_greater_than": "length greater than",
  "length_greater_than_or_equal_to": "length greater than",
  "length_less_than": "length less than",
  "length_less_than_or_equal_to": "length less than or equal to",
  "length_not_equal_to": "length is not equal to",
  "less_than": "less than",
  "less_than_or_equal_to": "less than or equal to",
  "max_dialog_rounds": "How many rounds of conversation records can be carried at most?",
  "max_tokens": "Maximum Tokens",
  "new_context": "new context",
  "not_contains": "Not included",
  "only_the_reference_type_is_supported": "Only the Reference type is supported",
  "optional_value_type": "Optional value type",
  "optional_value_type_tip": "One or more data types can be specified, and users can only select the configured type when adding fields in winter",
  "other_questions": "Other questions",
  "pass_returned_object_as_output_to_next_nodes": "Use the object returned in the code as output and pass it to subsequent nodes. \nThe variable name needs to correspond to the key of return",
  "plugin": {
    "Instruction_Tip": "You can configure a description to explain the purpose of this plugin. This description will be displayed each time before using the plugin. Standard Markdown syntax is supported.",
    "Instructions": "Instructions"
  },
  "plugin_input": "Plug-in input",
  "question_classification": "Problem classification",
  "question_optimization": "Problem optimization",
  "quote_num": "Reference {{num}}",
  "raw_response": "original response",
  "regex": "regular",
  "reply_text": "Reply text",
  "request_error": "Request error",
  "response": {
    "Code log": "Log",
    "Custom inputs": "Custom inputs",
    "Custom outputs": "Custom outputs",
    "Error": "Error",
    "Read file result": "Document parsing result preview",
    "User_select_description": "User select description",
    "User_select_result": "User select result",
    "read files": "parsed document"
  },
  "select_an_application": "Choose an app",
  "select_another_application_to_call": "You can choose another application to call",
  "special_array_format": "Special array format, when the search result is empty, an empty array is returned.",
  "start_with": "Start with",
  "system_variables": "System variables",
  "target_fields_description": "A target field is composed of 'description' and 'key', and multiple target fields can be extracted.",
  "template": {
    "ai_chat": "LLM chat",
    "ai_chat_intro": "Call the AI model for a conversation",
    "dataset_search": "Dataset search",
    "dataset_search_intro": "Call the \"Semantic Search\" and \"Full-text Search\" capabilities to find reference content that may be related to the problem from the \"Knowledge Base\"",
    "system_config": "System Configuration",
    "tool_call": "Tool call",
    "tool_call_intro": "One or more function blocks are automatically selected for calling through the AI ​​model, and plug-ins can also be called.",
    "workflow_start": "Process starts"
  },
  "text_concatenation": "Text splicing",
  "text_content_extraction": "Text content extraction",
  "text_to_extract": "Text to be extracted",
  "these_variables_will_be_input_parameters_for_code_execution": "These variables will be used as input parameters when the code is run.",
  "tool_call_termination": "Tool call terminated",
  "tool_input": "Tool",
  "trigger_after_application_completion": "will be triggered after the application has completely ended",
  "update_link_error": "Update link exception",
  "update_specified_node_output_or_global_variable": "You can update the output value of the specified node or update global variables",
  "use_user_id": "User ID",
  "user_question": "User issues",
  "variable_picker_tips": "enter node name or variable name to search",
  "variable_update": "variable update",
  "workflow": {
    "Back_to_current_version": "Back to current version",
    "My edit": "My edit",
    "Switch_failed": "Switch failed",
    "Switch_success": "switch successfully",
    "Team cloud": "Team cloud",
    "exit_tips": "Your changes have not been saved. Exiting directly will not save your edits."
  }
}