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

{
  "Array_element": "Array element",
  "Code": "Code",
  "about_xxx_question": "Question regarding xxx",
  "add_new_input": "Add New Input",
  "append_application_reply_to_history_as_new_context": "Append the application's reply to the history as new context",
  "application_call": "Application Call",
  "assigned_reply": "Assigned Reply",
  "can_not_loop": "This node can't loop.",
  "choose_another_application_to_call": "Select another application to call",
  "classification_result": "Classification Result",
  "code": {
    "Reset template": "Reset Template",
    "Reset template confirm": "Confirm reset code template? This will reset all inputs and outputs to template values. Please save your current code."
  },
  "code_execution": "Code Execution",
  "collection_metadata_filter": "Collection Metadata Filter",
  "complete_extraction_result": "Complete Extraction Result",
  "complete_extraction_result_description": "A JSON string, e.g., {\"name\":\"YY\",\"Time\":\"2023/7/2 18:00\"}",
  "concatenation_result": "Concatenation Result",
  "concatenation_text": "Concatenation Text",
  "condition_checker": "Condition Checker",
  "confirm_delete_field_tip": "Confirm delete this field?",
  "contains": "Contains",
  "content_to_retrieve": "Content to Retrieve",
  "content_to_search": "Content to Search",
  "create_link_error": "Error creating link",
  "custom_feedback": "Custom Feedback",
  "custom_input": "Custom Input",
  "custom_plugin_output": "Custom Plugin Output",
  "delete_api": "Confirm delete this API key? The key will be invalid immediately after deletion, but the corresponding conversation logs will not be deleted. Please confirm!",
  "dynamic_input_description": "Receive the output value of the previous node as a variable, which can be used by Laf request parameters.",
  "dynamic_input_description_concat": "You can reference the output of other nodes as variables for text concatenation. Type / to invoke the variable list.",
  "edit_input": "Edit Input",
  "end_with": "Ends With",
  "error_info_returns_empty_on_success": "Error information of code execution, returns empty on success",
  "execute_a_simple_script_code_usually_for_complex_data_processing": "Execute a simple script code, usually for complex data processing.",
  "execute_different_branches_based_on_conditions": "Execute different branches based on conditions.",
  "execution_error": "Execution Error",
  "extraction_requirements_description": "Extraction Requirements Description",
  "extraction_requirements_description_detail": "Provide AI with some background knowledge or requirements to guide it in completing the task better.\\nThis input box can use global variables.",
  "extraction_requirements_placeholder": "For example: \\n1. The current time is: {{cTime}}. You are a lab reservation assistant, and your task is to help users reserve a lab by extracting the corresponding reservation information from the text.\\n2. You are a Google search assistant, and you need to extract suitable search terms from the text.",
  "feedback_text": "Feedback Text",
  "field_description": "Field Description",
  "field_description_placeholder": "Describe the function of this input field. If it is a tool call parameter, this description will affect the quality of the model generation.",
  "field_name_already_exists": "Field name already exists",
  "field_required": "Required",
  "field_used_as_tool_input": "Used as Tool Call Parameter",
  "filter_description": "Currently supports filtering by tags and creation time. Fill in the format as follows:\n{\n  \"tags\": {\n    \"$and\": [\"Tag 1\",\"Tag 2\"],\n    \"$or\": [\"When there are $and tags, and is effective, or is not effective\"]\n  },\n  \"createTime\": {\n      \"$gte\": \"YYYY-MM-DD HH:mm format, collection creation time greater than this time\",\n      \"$lte\": \"YYYY-MM-DD HH:mm format, collection creation time less than this time, can be used with $gte\"\n  }\n}",
  "full_field_extraction": "Full Field Extraction",
  "full_field_extraction_description": "Returns true when all fields are fully extracted (success includes model extraction or using default values)",
  "full_response_data": "Full Response Data",
  "greater_than": "Greater Than",
  "greater_than_or_equal_to": "Greater Than or Equal To",
  "greeting": "Greeting",
  "http_raw_response_description": "Raw HTTP response. Only accepts string or JSON type response data.",
  "http_request": "HTTP Request",
  "http_request_error_info": "HTTP request error information, returns empty on success",
  "ifelse": {
    "Input value": "Input Value",
    "Select value": "Select Value"
  },
  "input_description": "Field Description",
  "input_variable_list": "Type / to invoke variable list",
  "intro_assigned_reply": "This module can directly reply with a specified content. Commonly used for guidance or prompts. Non-string content will be converted to string for output.",
  "intro_custom_feedback": "When this module is triggered, a feedback will be added to the current conversation record. It can be used to automatically record conversation effects, etc.",
  "intro_custom_plugin_output": "Custom configuration of external output. When using plugins, only the custom configured output is exposed.",
  "intro_http_request": "Can send an HTTP request to perform more complex operations (network search, database query, etc.)",
  "intro_knowledge_base_search_merge": "Can merge multiple Dataset search results for output. Uses RRF merging method for final sorting output.",
  "intro_laf_function_call": "Can call cloud functions under the Laf account.",
  "intro_plugin_input": "Can configure what inputs the plugin needs and use these inputs to run the plugin.",
  "intro_question_classification": "Determine the type of question based on the user's history and current question. Multiple question types can be added. Below is a template example:\nType 1: Greeting\nType 2: Questions about product 'usage'\nType 3: Questions about product 'purchase'\nType 4: Other questions",
  "intro_question_optimization": "Using question optimization can improve the accuracy of Dataset searches during continuous conversations. After using this function, AI will first construct one or more new search terms based on the context, which are more conducive to Dataset searches. This module is already built into the Dataset search module. If you only perform a single Dataset search, you can directly use the built-in completion function of the Dataset.",
  "intro_text_concatenation": "Can process and output fixed or incoming text. Non-string type data will be converted to string type.",
  "intro_text_content_extraction": "Can extract specified data from text, such as SQL statements, search keywords, code, etc.",
  "intro_tool_call_termination": "This module needs to be configured for tool calls. When this module is executed, the current tool call will be forcibly terminated, and AI will no longer answer questions based on the tool call results.",
  "is_empty": "Is Empty",
  "is_equal_to": "Is Equal To",
  "is_not_empty": "Is Not Empty",
  "is_not_equal": "Is Not Equal",
  "judgment_result": "Judgment Result",
  "knowledge_base_reference": "Dataset Reference",
  "knowledge_base_search_merge": "Dataset Search Merge",
  "laf_function_call_test": "Laf Function Call (Test)",
  "length_equal_to": "Length Equal To",
  "length_greater_than": "Length Greater Than",
  "length_greater_than_or_equal_to": "Length Greater Than or Equal To",
  "length_less_than": "Length Less Than",
  "length_less_than_or_equal_to": "Length Less Than or Equal To",
  "length_not_equal_to": "Length Not Equal To",
  "less_than": "Less Than",
  "less_than_or_equal_to": "Less Than or Equal To",
  "loop": "Batch execution",
  "loop_start_tip": "Not input array",
  "max_dialog_rounds": "Maximum Number of Dialog Rounds",
  "max_tokens": "Maximum Tokens",
  "mouse_priority": "Mouse first",
  "new_context": "New Context",
  "not_contains": "Does Not Contain",
  "only_the_reference_type_is_supported": "Only reference type is supported",
  "optional_value_type": "Optional Value Type",
  "optional_value_type_tip": "You can specify one or more data types. When dynamically adding fields, users can only select the configured types.",
  "other_questions": "Other Questions",
  "pan_priority": "Touchpad first",
  "pass_returned_object_as_output_to_next_nodes": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.",
  "plugin": {
    "Instruction_Tip": "You can configure an instruction to explain the purpose of the plugin. This instruction will be displayed each time the plugin is used. Supports standard Markdown syntax.",
    "Instructions": "Instructions"
  },
  "plugin_input": "Plugin Input",
  "question_classification": "Question Classification",
  "question_optimization": "Question Optimization",
  "quote_num": "Quote {{num}}",
  "raw_response": "Raw Response",
  "regex": "Regex",
  "reply_text": "Reply Text",
  "request_error": "Request Error",
  "response": {
    "Code log": "Code Log",
    "Custom inputs": "Custom Inputs",
    "Custom outputs": "Custom Outputs",
    "Error": "Error",
    "Read file result": "Read File Result",
    "read files": "Read Files"
  },
  "select_an_application": "Select an Application",
  "select_another_application_to_call": "You can choose another application to call",
  "special_array_format": "Special array format, returns an empty array when the search result is empty.",
  "start_with": "Starts With",
  "target_fields_description": "A target field consists of 'description' and 'key'. Multiple target fields can be extracted.",
  "template": {
    "ai_chat": "AI Chat",
    "ai_chat_intro": "AI Large Model Chat",
    "dataset_search": "Dataset Search",
    "dataset_search_intro": "Use 'semantic search' and 'full-text search' capabilities to find potentially relevant reference content from the 'Dataset'.",
    "system_config": "System Configuration",
    "tool_call": "Tool Call",
    "tool_call_intro": "Automatically select one or more functional blocks for calling through the AI model, or call plugins.",
    "workflow_start": "Workflow Start"
  },
  "text_concatenation": "Text Concatenation",
  "text_content_extraction": "Text Content Extraction",
  "text_to_extract": "Text to Extract",
  "these_variables_will_be_input_parameters_for_code_execution": "These variables will be input parameters for code execution",
  "tool_call_termination": "Tool Call Termination",
  "tool_input": "Tool Input",
  "trigger_after_application_completion": "Will be triggered after the application is fully completed",
  "update_link_error": "Error updating link",
  "update_specified_node_output_or_global_variable": "Can update the output value of a specified node or update global variables",
  "use_user_id": "User ID",
  "user_question": "User Question",
  "variable_picker_tips": "Type node name or variable name to search",
  "variable_update": "Variable Update",
  "workflow": {
    "My edit": "My Edit",
    "Switch_success": "Switch Successful",
    "Team cloud": "Team Cloud",
    "exit_tips": "Your changes have not been saved. 'Exit directly' will not save your edits."
  }
}