// Datasets
const SEED_DATASET_ITEMS_COUNTRIES = [
  { input: { country: "France" }, output: "Paris" },
  { input: { country: "Germany" }, output: "Berlin" },
  { input: { country: "Italy" }, output: "Rome" },
  { input: { country: "Spain" }, output: "Madrid" },
  { input: { country: "United Kingdom" }, output: "London" },
  { input: { country: "Japan" }, output: "Tokyo" },
  { input: { country: "China" }, output: "Beijing" },
  { input: { country: "India" }, output: "New Delhi" },
  { input: { country: "Brazil" }, output: "Brasília" },
  { input: { country: "Canada" }, output: "Ottawa" },
  { input: { country: "Australia" }, output: "Canberra" },
  { input: { country: "South Africa" }, output: "Pretoria" },
  { input: { country: "Mexico" }, output: "Mexico City" },
  { input: { country: "Russia" }, output: "Moscow" },
  { input: { country: "Egypt" }, output: "Cairo" },
  { input: { country: "Turkey" }, output: "Ankara" },
  { input: { country: "Indonesia" }, output: "Jakarta" },
  { input: { country: "South Korea" }, output: "Seoul" },
  { input: { country: "Saudi Arabia" }, output: "Riyadh" },
  { input: { country: "Argentina" }, output: "Buenos Aires" },
  { input: { country: "Nigeria" }, output: "Abuja" },
  { input: { country: "Pakistan" }, output: "Islamabad" },
  { input: { country: "Thailand" }, output: "Bangkok" },
  { input: { country: "Vietnam" }, output: "Hanoi" },
  { input: { country: "Malaysia" }, output: "Kuala Lumpur" },
  { input: { country: "Philippines" }, output: "Manila" },
  { input: { country: "Singapore" }, output: "Singapore" },
  { input: { country: "New Zealand" }, output: "Wellington" },
  { input: { country: "Sweden" }, output: "Stockholm" },
  { input: { country: "Norway" }, output: "Oslo" },
  { input: { country: "Denmark" }, output: "Copenhagen" },
  { input: { country: "Finland" }, output: "Helsinki" },
  { input: { country: "Netherlands" }, output: "Amsterdam" },
  { input: { country: "Belgium" }, output: "Brussels" },
  { input: { country: "Switzerland" }, output: "Bern" },
  { input: { country: "Austria" }, output: "Vienna" },
  { input: { country: "Portugal" }, output: "Lisbon" },
  { input: { country: "Greece" }, output: "Athens" },
  { input: { country: "Poland" }, output: "Warsaw" },
  { input: { country: "Ukraine" }, output: "Kyiv" },
  { input: { country: "Romania" }, output: "Bucharest" },
  { input: { country: "Hungary" }, output: "Budapest" },
  { input: { country: "Czech Republic" }, output: "Prague" },
  { input: { country: "Slovakia" }, output: "Bratislava" },
  { input: { country: "Croatia" }, output: "Zagreb" },
  { input: { country: "Serbia" }, output: "Belgrade" },
  { input: { country: "Bulgaria" }, output: "Sofia" },
  { input: { country: "Ireland" }, output: "Dublin" },
  { input: { country: "Iceland" }, output: "Reykjavik" },
  { input: { country: "Estonia" }, output: "Tallinn" },
  { input: { country: "Latvia" }, output: "Riga" },
  { input: { country: "Lithuania" }, output: "Vilnius" },
];

const SEED_DATASET_ITEMS_IPA = [
  { input: { word: "the" }, output: "/ðə/" },
  { input: { word: "be" }, output: "/bi/" },
  { input: { word: "to" }, output: "/tu/" },
  { input: { word: "of" }, output: "/əv/" },
  { input: { word: "and" }, output: "/ænd/" },
  { input: { word: "a" }, output: "/ə/" },
  { input: { word: "in" }, output: "/ɪn/" },
  { input: { word: "that" }, output: "/ðæt/" },
  { input: { word: "have" }, output: "/hæv/" },
  { input: { word: "I" }, output: "/aɪ/" },
  { input: { word: "it" }, output: "/ɪt/" },
  { input: { word: "for" }, output: "/fɔr/" },
  { input: { word: "not" }, output: "/nɑt/" },
  { input: { word: "on" }, output: "/ɑn/" },
  { input: { word: "with" }, output: "/wɪð/" },
  { input: { word: "he" }, output: "/hi/" },
  { input: { word: "as" }, output: "/æz/" },
  { input: { word: "you" }, output: "/ju/" },
  { input: { word: "do" }, output: "/du/" },
  { input: { word: "at" }, output: "/æt/" },
  { input: { word: "this" }, output: "/ðɪs/" },
  { input: { word: "but" }, output: "/bʌt/" },
  { input: { word: "his" }, output: "/hɪz/" },
  { input: { word: "by" }, output: "/baɪ/" },
  { input: { word: "from" }, output: "/frʌm/" },
  { input: { word: "they" }, output: "/ðeɪ/" },
  { input: { word: "we" }, output: "/wi/" },
  { input: { word: "say" }, output: "/seɪ/" },
  { input: { word: "her" }, output: "/hər/" },
  { input: { word: "she" }, output: "/ʃi/" },
  { input: { word: "or" }, output: "/ɔr/" },
  { input: { word: "an" }, output: "/æn/" },
  { input: { word: "will" }, output: "/wɪl/" },
  { input: { word: "my" }, output: "/maɪ/" },
  { input: { word: "one" }, output: "/wʌn/" },
  { input: { word: "all" }, output: "/ɔl/" },
  { input: { word: "would" }, output: "/wʊd/" },
  { input: { word: "there" }, output: "/ðɛr/" },
  { input: { word: "their" }, output: "/ðɛr/" },
  { input: { word: "what" }, output: "/wʌt/" },
  { input: { word: "so" }, output: "/soʊ/" },
  { input: { word: "up" }, output: "/ʌp/" },
  { input: { word: "out" }, output: "/aʊt/" },
  { input: { word: "if" }, output: "/ɪf/" },
  { input: { word: "about" }, output: "/əˈbaʊt/" },
  { input: { word: "who" }, output: "/hu/" },
  { input: { word: "get" }, output: "/gɛt/" },
  { input: { word: "which" }, output: "/wɪtʃ/" },
  { input: { word: "go" }, output: "/goʊ/" },
  { input: { word: "me" }, output: "/mi/" },
  { input: { word: "when" }, output: "/wɛn/" },
  { input: { word: "make" }, output: "/meɪk/" },
  { input: { word: "can" }, output: "/kæn/" },
  { input: { word: "like" }, output: "/laɪk/" },
  { input: { word: "time" }, output: "/taɪm/" },
  { input: { word: "no" }, output: "/noʊ/" },
  { input: { word: "just" }, output: "/dʒʌst/" },
  { input: { word: "him" }, output: "/hɪm/" },
  { input: { word: "know" }, output: "/noʊ/" },
  { input: { word: "take" }, output: "/teɪk/" },
  { input: { word: "person" }, output: "/ˈpərsən/" },
  { input: { word: "into" }, output: "/ˈɪntu/" },
  { input: { word: "year" }, output: "/jɪr/" },
  { input: { word: "your" }, output: "/jʊər/" },
  { input: { word: "good" }, output: "/gʊd/" },
  { input: { word: "some" }, output: "/sʌm/" },
  { input: { word: "could" }, output: "/kʊd/" },
  { input: { word: "them" }, output: "/ðɛm/" },
  { input: { word: "see" }, output: "/si/" },
  { input: { word: "other" }, output: "/ˈʌðər/" },
  { input: { word: "than" }, output: "/ðæn/" },
  { input: { word: "then" }, output: "/ðɛn/" },
  { input: { word: "now" }, output: "/naʊ/" },
  { input: { word: "look" }, output: "/lʊk/" },
  { input: { word: "only" }, output: "/ˈoʊnli/" },
  { input: { word: "come" }, output: "/kʌm/" },
  { input: { word: "its" }, output: "/ɪts/" },
  { input: { word: "over" }, output: "/ˈoʊvər/" },
  { input: { word: "think" }, output: "/θɪŋk/" },
  { input: { word: "also" }, output: "/ˈɔlsoʊ/" },
  { input: { word: "back" }, output: "/bæk/" },
  { input: { word: "after" }, output: "/ˈæftər/" },
  { input: { word: "use" }, output: "/juz/" },
  { input: { word: "two" }, output: "/tu/" },
  { input: { word: "how" }, output: "/haʊ/" },
  { input: { word: "our" }, output: "/aʊər/" },
  { input: { word: "work" }, output: "/wɜrk/" },
  { input: { word: "first" }, output: "/fɜrst/" },
  { input: { word: "well" }, output: "/wɛl/" },
  { input: { word: "way" }, output: "/weɪ/" },
  { input: { word: "even" }, output: "/ˈivɪn/" },
  { input: { word: "new" }, output: "/nu/" },
  { input: { word: "want" }, output: "/wɑnt/" },
  { input: { word: "because" }, output: "/bɪˈkɔz/" },
  { input: { word: "any" }, output: "/ˈɛni/" },
  { input: { word: "these" }, output: "/ðiz/" },
  { input: { word: "give" }, output: "/gɪv/" },
  { input: { word: "day" }, output: "/deɪ/" },
  { input: { word: "most" }, output: "/moʊst/" },
  { input: { word: "us" }, output: "/ʌs/" },
];

export const SEED_DATASETS = [
  {
    name: "demo-countries-dataset",
    description: "Dataset for countries",
    metadata: {
      key: "value",
    },
    items: SEED_DATASET_ITEMS_COUNTRIES,
  },
  {
    name: "demo-english-transcription-dataset",
    description:
      "Dataset for english transcription, where words are represented in their international phonetic alphabet (IPA)",
    metadata: {
      key: "value",
    },
    items: SEED_DATASET_ITEMS_IPA,
  },
];

// Prompts
export const SEED_TEXT_PROMPTS = [
  {
    id: `prompt-parent`,
    createdBy: "user-1",
    prompt:
      'You are a very enthusiastic Langfuse representative who loves to help people! Langfuse is an open-source observability tool for developers of applications that use Large Language Models (LLMs). Given the following sections from the Langfuse documentation, answer the question using only that information, outputted in markdown format. Refer to the respective links of the documentation.\n      \nSTART of Langfuse Documentation\n"""\n{{context}} {{context}}\n"""\nEND of Langfuse Documentation\n      \nAnswer as markdown (including related code snippets if available), use highlights and paragraphs to structure the text. Use emojis in your answers. Do not mention that you are "enthusiastic", the user does not need to know, will feel it from the style of your answers. Only use information that is available in the context, do not make up any code that is not in the context. If you are unsure and the answer is not explicitly written in the documentation, say "Sorry, I don\'t know how to help with that." If the user is having problems using Langfuse, tell her to reach out to the founders directly via the chat widget. Make it crisp.\n\n@@@langfusePrompt:name=child-prompt|label=production@@@',
    name: "parent-prompt",
    version: 1,
    labels: ["production", "latest"],
  },
  {
    id: `prompt-child`,
    createdBy: "user-1",
    prompt: `Please follow these guidelines:
- Refer to the respective links of the documentation
- Be kind.
- Include emojis where it makes sense.
- If the users have problems using Langfuse, tell them to reach out to the founders directly via the chat widget or GitHub at the end of your answer.
- Answer as markdown, use highlights and paragraphs to structure the text.
- Do not mention that you are "enthusiastic", the user does not need to know, will feel it from the style of your answers.`,
    name: "child-prompt",
    version: 1,
    labels: ["production", "latest"],
  },
  {
    id: `prompt-123`,
    createdBy: "user-1",
    prompt: "Prompt 1 content",
    name: "prompt-1",
    version: 1,
    labels: ["production", "latest"],
  },
  {
    id: `prompt-456`,
    createdBy: "user-1",
    prompt: "Prompt 2 content",
    name: "prompt-2",
    version: 1,
    labels: ["production", "latest"],
  },
  {
    id: `prompt-789`,
    createdBy: "API",
    prompt: "Prompt 3 content",
    name: "prompt-3-by-api",
    version: 1,
    labels: ["production", "latest"],
  },
  {
    id: `prompt-abc`,
    createdBy: "user-1",
    prompt: "Prompt 4 content",
    name: "prompt-4",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `countries-experiment-prompt`,
    createdBy: "user-1",
    prompt: "What is the capital of {{country}}?",
    name: "countries-experiment-prompt",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `folder-customer-prompt-1`,
    createdBy: "user-1",
    prompt: "Folder prompt 1 content",
    name: "folder/customer/prompt-1",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `folder-customer-prompt-2`,
    createdBy: "user-1",
    prompt: "Folder prompt 2 content",
    name: "folder/customer/prompt-2",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `folder-prompt-1`,
    createdBy: "user-1",
    prompt: "Folder prompt 1 content",
    name: "folder/prompt-1",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `prompt-with-many-labels`,
    createdBy: "user-1",
    prompt:
      "This is a comprehensive prompt for testing multiple label scenarios. It demonstrates how prompts can be tagged with numerous labels for organization, categorization, and filtering purposes. Use this prompt to understand how label management works at scale. Variables: {{input}}",
    name: "prompt-with-many-labels",
    version: 1,
    labels: [
      "production",
      "latest",
      "v1",
      "v2",
      "stable",
      "beta",
      "alpha",
      "test",
      "development",
      "staging",
      "experimental",
      "feature",
      "bugfix",
      "hotfix",
      "critical",
      "high-priority",
      "medium-priority",
      "low-priority",
      "urgent",
      "customer-facing",
      "internal",
      "public",
      "private",
      "confidential",
      "ai",
      "nlp",
      "chatbot",
      "assistant",
      "automation",
      "ml",
      "data",
      "analytics",
      "monitoring",
      "logging",
      "debug",
      "performance",
      "security",
      "compliance",
      "audit",
      "review",
      "approved",
      "rejected",
      "pending",
      "archived",
      "deprecated",
      "legacy",
      "migration",
      "upgrade",
      "downgrade",
      "template",
      "example",
    ],
    tags: [],
  },
];

export const SEED_CHAT_ML_PROMPTS = [
  {
    id: `prompt-abc`,
    createdBy: "user-1",
    prompt: [
      {
        role: "system",
        content:
          'You are a very enthusiastic Langfuse representative who loves to help people! Langfuse is an open-source observability tool for developers of applications that use Large Language Models (LLMs). Given the following sections from the Langfuse documentation, answer the question using only that information, outputted in markdown format.\n\nPlease follow these guidelines:\n- Refer to the respective links of the documentation and select quality examples\n- Be kind.\n- Include emojis where it makes sense.\n- If the users have problems using Langfuse, tell them to reach out to the founders directly via the chat widget or GitHub at the end of your answer.\n- Answer as markdown, use highlights and paragraphs to structure the text.\n- Do not mention that you are "enthusiastic", the user does not need to know, will feel it from the style of your answers.\n- Only use information that is available in the context, do not make up any code that is not in the context.\n- Always put an empji at the end of the message.',
      },
      {
        role: "assistant",
        content:
          "All right, what is the documentation that I am meant to exclusively use to answer the question?",
      },
      {
        role: "user",
        content: "<documentation>\n```\n{{context}}\n```\n</documentation>",
      },
      {
        role: "assistant",
        content:
          "Answering in next message based on your instructions only. What is the question?",
      },
      {
        role: "user",
        content: "{{question}}",
      },
    ],
    name: "prompt-chat-ml",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
  {
    id: `prompt-chat-placeholder`,
    createdBy: "user-1",
    prompt: [
      {
        role: "system",
        content:
          'You are a very enthusiastic Langfuse representative who loves to help people! Langfuse is an open-source observability tool for developers of applications that use Large Language Models (LLMs). Given the following sections from the Langfuse documentation, answer the question using only that information, outputted in markdown format.\n\nPlease follow these guidelines:\n- Refer to the respective links of the documentation and select quality examples\n- Be kind.\n- Include emojis where it makes sense.\n- If the users have problems using Langfuse, tell them to reach out to the founders directly via the chat widget or GitHub at the end of your answer.\n- Answer as markdown, use highlights and paragraphs to structure the text.\n- Do not mention that you are "enthusiastic", the user does not need to know, will feel it from the style of your answers.\n- Only use information that is available in the context, do not make up any code that is not in the context.\n- Always put an empji at the end of the message.',
      },
      {
        type: "placeholder",
        name: "message_history",
      },
      {
        role: "assistant",
        content:
          "Answering in next message based on your instructions only. What is the question?",
      },
      {
        role: "user",
        content: "{{question}}",
      },
    ],
    name: "prompt-chat-ml-with-placeholder",
    version: 1,
    labels: ["production", "latest"],
    tags: ["tag1", "tag2"],
  },
];

export const SEED_PROMPT_VERSIONS = [
  {
    createdBy: "user-1",
    prompt: "Prompt 4 version 1 content with {{variable}}",
    name: "prompt-4-with-variable-and-config",
    config: {
      temperature: 0.7,
    },
    version: 1,
  },
  {
    createdBy: "user-1",
    prompt: "Prompt 4 version 2 content with {{variable}}",
    name: "prompt-4-with-variable-and-config",
    config: {
      temperature: 0.7,
      topP: 0.9,
    },
    version: 2,
    labels: ["production"],
  },
  {
    createdBy: "user-1",
    prompt: "Prompt 4 version 3 content with {{variable}}",
    name: "prompt-4-with-variable-and-config",
    config: {
      temperature: 0.7,
      topP: 0.9,
      frequencyPenalty: 0.5,
    },
    version: 3,
    labels: ["production", "latest"],
  },
];

// evaluators
export const SEED_EVALUATOR_TEMPLATES = [
  {
    id: "toxicity-template",
    name: "toxicity-template",
    version: 1,
    prompt:
      "Please evaluate the toxicity of the following text {{input}} {{output}}",
    model: "gpt-3.5-turbo",
    vars: ["input", "output"],
    provider: "openai",
    outputSchema: {
      score: "provide a score between 0 and 1",
      reasoning: "one sentence reasoning for the score",
    },
    modelParams: {
      temperature: 0.7,
      outputTokenLimit: 100,
      topP: 0.9,
    },
  },
];

export const SEED_EVALUATOR_CONFIGS = [
  {
    id: "toxicity-job",
    evalTemplateId: "toxicity-template",
    jobType: "EVAL",
    status: "ACTIVE",
    scoreName: "toxicity",
    filter: [
      {
        type: "string",
        value: "user",
        column: "User ID",
        operator: "contains",
      },
    ],
    variableMapping: [
      {
        langfuseObject: "trace",
        selectedColumnId: "input",
        templateVariable: "input",
      },
      {
        langfuseObject: "trace",
        selectedColumnId: "metadata",
        templateVariable: "output",
      },
    ],
    targetObject: "trace",
    sampling: 1,
    delay: 5_000,
  },
];

export const EVAL_TRACE_COUNT = 100;
export const FAILED_EVAL_TRACE_INTERVAL = 10;