tjdify/web/models/debug.ts

export type Inputs = Record<string, string | number | object>

export type PromptVariable = {
  key: string,
  name: string,
  type: string, // "string" | "number" | "select",
  default?: string | number,
  required: boolean,
  options?: string[]
  max_length?: number
}

export type CompletionParams = {
  max_tokens: number,
  temperature: number,
  top_p: number,
  presence_penalty: number,
  frequency_penalty: number,
}

export type ModelId = "gpt-3.5-turbo" | "text-davinci-003"

export type PromptConfig = {
  prompt_template: string,
  prompt_variables: PromptVariable[],
}

export type MoreLikeThisConfig = {
  enabled: boolean
}

export type SuggestedQuestionsAfterAnswerConfig = MoreLikeThisConfig

// frontend use. Not the same as backend
export type ModelConfig = {
  provider: string, // LLM Provider: for example "OPENAI"
  model_id: string,
  configs: PromptConfig
}

export type DebugRequestBody = {
  inputs: Inputs,
  query: string,
  completion_params: CompletionParams,
  model_config: ModelConfig
}

export type DebugResponse = {
  id: string,
  answer: string,
  created_at: string,
}


export type DebugResponseStream = {
  id: string,
  data: string,
  created_at: string,
}


export type FeedBackRequestBody = {
  message_id: string,
  rating: 'like' | 'dislike',
  content?: string,
  from_source: 'api' | 'log'
}


export type FeedBackResponse = {
  message_id: string,
  rating: 'like' | 'dislike'
}

// Log session list
export type LogSessionListQuery = {
  keyword?: string,
  start?: string, // format datetime(YYYY-mm-dd HH:ii)
  end?: string, // format datetime(YYYY-mm-dd HH:ii)
  page: number,
  limit: number, // default 20. 1-100
}

export type LogSessionListResponse = {
  data: {
    id: string,
    conversation_id: string,
    query: string, // user's query question
    message: string, // prompt send to LLM
    answer: string,
    creat_at: string,
  }[],
  total: number,
  page: number,
}

// log session detail and debug
export type LogSessionDetailResponse = {
  id: string,
  cnversation_id: string,
  model_provider: string,
  query: string,
  inputs: Record<string, string | number | object>[],
  message: string,
  message_tokens: number, // number of tokens in message
  answer: string,
  answer_tokens: number, // number of tokens in answer
  provider_response_latency: number, // used time in ms
  from_source: 'api' | 'log',
}

export type SavedMessage = {
  id: string,
  answer: string
}