action openai_create_edit {
  label: "Creates a new edit for the provided input, instruction, and parameters."
  provider: openai
  method: POST
  path: "/edits"
  encoding: json
  input: {
    type: "object"
    required: ["instruction", "model"]
    properties: {
      input: {
        type: "string"
        description: "The input text to use as a starting point for the edit."
      }
      instruction: {
        type: "string"
        description: "The instruction that tells the model how to edit the prompt."
      }
      model: {
        type: "string"
        description: "ID of the model to use. You can use the `text-davinci-edit-001` or `code-davinci-edit-001` model with this endpoint."
      }
      n: {
        type: "integer"
        description: "How many edits to generate for the input and instruction."
      }
      temperature: {
        type: "number"
        description: "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n\nWe generally recommend altering this or `top_p` but not both.\n"
      }
      top_p: {
        type: "number"
        description: "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or `temperature` but not both.\n"
      }
    }
  }
  output: {
    type: "object"
    required: ["choices", "created", "object", "usage"]
    properties: {
      choices: {
        type: "array"
        items: {
          type: "object"
          properties: {
            finish_reason: {
              type: "string"
            }
            index: {
              type: "integer"
            }
            logprobs: {
              type: "object"
              properties: {
                text_offset: {
                  type: "array"
                  items: {
                    type: "integer"
                  }
                }
                token_logprobs: {
                  type: "array"
                  items: {
                    type: "number"
                  }
                }
                tokens: {
                  type: "array"
                  items: {
                    type: "string"
                  }
                }
                top_logprobs: {
                  type: "array"
                  items: {
                    type: "object"
                  }
                }
              }
            }
            text: {
              type: "string"
            }
          }
        }
      }
      created: {
        type: "integer"
      }
      object: {
        type: "string"
      }
      usage: {
        type: "object"
        required: ["completion_tokens", "prompt_tokens", "total_tokens"]
        properties: {
          completion_tokens: {
            type: "integer"
          }
          prompt_tokens: {
            type: "integer"
          }
          total_tokens: {
            type: "integer"
          }
        }
      }
    }
  }
}