feat(api): add 'gpt-3.5-turbo-instruct', fine-tune error objects, upd…

…ate documentation (#329)

src/resources/chat/completions.ts

@@ -75,10 +75,11 @@ export namespace ChatCompletion {
     /**
      * The reason the model stopped generating tokens. This will be `stop` if the model
      * hit a natural stop point or a provided stop sequence, `length` if the maximum
-     * number of tokens specified in the request was reached, or `function_call` if the
-     * model called a function.
+     * number of tokens specified in the request was reached, `content_filter` if
+     * content was omitted due to a flag from our content filters, or `function_call`
+     * if the model called a function.
      */
-    finish_reason: 'stop' | 'length' | 'function_call';
+    finish_reason: 'stop' | 'length' | 'function_call' | 'content_filter';
 
     /**
      * The index of the choice in the list of choices.
@@ -134,8 +135,9 @@ export namespace ChatCompletionChunk {
     /**
      * The reason the model stopped generating tokens. This will be `stop` if the model
      * hit a natural stop point or a provided stop sequence, `length` if the maximum
-     * number of tokens specified in the request was reached, or `function_call` if the
-     * model called a function.
+     * number of tokens specified in the request was reached, `content_filter` if
+     * content was omitted due to a flag from our content filters, or `function_call`
+     * if the model called a function.
      */
     finish_reason: 'stop' | 'length' | 'function_call' | null;
 
@@ -331,11 +333,11 @@ export interface ChatCompletionCreateParamsBase {
   frequency_penalty?: number | null;
 
   /**
-   * Controls how the model responds to function calls. "none" means the model does
-   * not call a function, and responds to the end-user. "auto" means the model can
+   * Controls how the model responds to function calls. `none` means the model does
+   * not call a function, and responds to the end-user. `auto` means the model can
    * pick between an end-user or calling a function. Specifying a particular function
-   * via `{"name": "my_function"}` forces the model to call that function. "none" is
-   * the default when no functions are present. "auto" is the default if functions
+   * via `{"name": "my_function"}` forces the model to call that function. `none` is
+   * the default when no functions are present. `auto` is the default if functions
    * are present.
    */
   function_call?: 'none' | 'auto' | ChatCompletionCreateParams.FunctionCallOption;
@@ -365,7 +367,7 @@ export interface ChatCompletionCreateParamsBase {
    * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb)
    * for counting tokens.
    */
-  max_tokens?: number;
+  max_tokens?: number | null;
 
   /**
    * How many chat completion choices to generate for each input message.

src/resources/completions.ts

@@ -68,10 +68,11 @@ export interface Completion {
 export interface CompletionChoice {
   /**
    * The reason the model stopped generating tokens. This will be `stop` if the model
-   * hit a natural stop point or a provided stop sequence, or `length` if the maximum
-   * number of tokens specified in the request was reached.
+   * hit a natural stop point or a provided stop sequence, `length` if the maximum
+   * number of tokens specified in the request was reached, or `content_filter` if
+   * content was omitted due to a flag from our content filters.
    */
-  finish_reason: 'stop' | 'length';
+  finish_reason: 'stop' | 'length' | 'content_filter';
 
   index: number;
 
@@ -126,6 +127,7 @@ export interface CompletionCreateParamsBase {
     | (string & {})
     | 'babbage-002'
     | 'davinci-002'
+    | 'gpt-3.5-turbo-instruct'
     | 'text-davinci-003'
     | 'text-davinci-002'
     | 'text-davinci-001'

src/resources/edits.ts

@@ -44,8 +44,9 @@ export namespace Edit {
   export interface Choice {
     /**
      * The reason the model stopped generating tokens. This will be `stop` if the model
-     * hit a natural stop point or a provided stop sequence, or `length` if the maximum
-     * number of tokens specified in the request was reached.
+     * hit a natural stop point or a provided stop sequence, `length` if the maximum
+     * number of tokens specified in the request was reached, or `content_filter` if
+     * content was omitted due to a flag from our content filters.
      */
     finish_reason: 'stop' | 'length';
 

src/resources/embeddings.ts

@@ -82,7 +82,7 @@ export interface EmbeddingCreateParams {
    * Input text to embed, encoded as a string or array of tokens. To embed multiple
    * inputs in a single request, pass an array of strings or array of token arrays.
    * Each input must not exceed the max input tokens for the model (8191 tokens for
-   * `text-embedding-ada-002`).
+   * `text-embedding-ada-002`) and cannot be an empty string.
    * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb)
    * for counting tokens.
    */

src/resources/files.ts

@@ -41,7 +41,7 @@ export class Files extends APIResource {
   }
 
   /**
-   * Returns the contents of the specified file
+   * Returns the contents of the specified file.
    */
   retrieveContent(fileId: string, options?: Core.RequestOptions): Core.APIPromise<string> {
     return this.get(`/files/${fileId}/content`, {

src/resources/fine-tuning/jobs.ts

@@ -3,7 +3,6 @@
 import * as Core from 'openai/core';
 import { APIResource } from 'openai/resource';
 import { isRequestOptions } from 'openai/core';
-import * as Files from 'openai/resources/files';
 import * as API from './index';
 import { CursorPage, CursorPageParams } from 'openai/pagination';
 
@@ -105,10 +104,23 @@ export interface FineTuningJob {
   created_at: number;
 
   /**
-   * The name of the fine-tuned model that is being created.
+   * For fine-tuning jobs that have `failed`, this will contain more information on
+   * the cause of the failure.
+   */
+  error: FineTuningJob.Error | null;
+
+  /**
+   * The name of the fine-tuned model that is being created. The value will be null
+   * if the fine-tuning job is still running.
    */
   fine_tuned_model: string | null;
 
+  /**
+   * The Unix timestamp (in seconds) for when the fine-tuning job was finished. The
+   * value will be null if the fine-tuning job is still running.
+   */
+  finished_at: number | null;
+
   /**
    * The hyperparameters used for the fine-tuning job. See the
    * [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning) for
@@ -132,38 +144,61 @@ export interface FineTuningJob {
   organization_id: string;
 
   /**
-   * The compiled results files for the fine-tuning job.
+   * The compiled results file ID(s) for the fine-tuning job. You can retrieve the
+   * results with the
+   * [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
    */
-  result_files: Array<Files.FileObject>;
+  result_files: Array<string>;
 
   /**
-   * The current status of the fine-tuning job, which can be either `created`,
-   * `pending`, `running`, `succeeded`, `failed`, or `cancelled`.
+   * The current status of the fine-tuning job, which can be either
+   * `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
    */
   status: string;
 
   /**
-   * The total number of billable tokens processed by this fine tuning job.
+   * The total number of billable tokens processed by this fine-tuning job. The value
+   * will be null if the fine-tuning job is still running.
    */
-  trained_tokens: number;
+  trained_tokens: number | null;
 
   /**
-   * The file ID used for training.
+   * The file ID used for training. You can retrieve the training data with the
+   * [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
    */
   training_file: string;
 
   /**
-   * The file ID used for validation.
+   * The file ID used for validation. You can retrieve the validation results with
+   * the
+   * [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
    */
   validation_file: string | null;
+}
 
+export namespace FineTuningJob {
   /**
-   * The Unix timestamp (in seconds) for when the fine-tuning job was finished.
+   * For fine-tuning jobs that have `failed`, this will contain more information on
+   * the cause of the failure.
    */
-  finished_at?: number;
-}
+  export interface Error {
+    /**
+     * A machine-readable error code.
+     */
+    code: string;
+
+    /**
+     * A human-readable error message.
+     */
+    message: string;
+
+    /**
+     * The parameter that was invalid, usually `training_file` or `validation_file`.
+     * This field will be null if the failure was not parameter-specific.
+     */
+    param: string | null;
+  }
 
-export namespace FineTuningJob {
   /**
    * The hyperparameters used for the fine-tuning job. See the
    * [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning) for
@@ -172,11 +207,11 @@ export namespace FineTuningJob {
   export interface Hyperparameters {
     /**
      * The number of epochs to train the model for. An epoch refers to one full cycle
-     * through the training dataset. "Auto" decides the optimal number of epochs based
+     * through the training dataset. "auto" decides the optimal number of epochs based
      * on the size of the dataset. If setting the number manually, we support any
      * number between 1 and 50 epochs.
      */
-    n_epochs?: 'auto' | number;
+    n_epochs: 'auto' | number;
   }
 }
 
@@ -219,7 +254,7 @@ export interface JobCreateParams {
   hyperparameters?: JobCreateParams.Hyperparameters;
 
   /**
-   * A string of up to 40 characters that will be added to your fine-tuned model
+   * A string of up to 18 characters that will be added to your fine-tuned model
    * name.
    *
    * For example, a `suffix` of "custom-model-name" would produce a model name like