Completes chat completion inference endpoint docs

specification/inference/_types/CommonTypes.ts

@@ -47,10 +47,47 @@ export class RequestChatCompletion {
   temperature?: float
   /**
    * Controls which tool is called by the model.
+   * String representation: One of `auto`, `none`, or `requrired`. `auto` allows the model to choose between calling tools and generating a message. `none` causes the model to not call any tools. `required` forces the model to call one or more tools.
+   * Example (object representation):
+   * ```
+   * {
+   *   "tool_choice": {
+   *       "type": "function",
+   *       "function": {
+   *           "name": "get_current_weather"
+   *       }
+   *   }
+   * }
+   * ```
    */
   tool_choice?: CompletionToolType
   /**
    * A list of tools that the model can call.
+   * Example:
+   * ```
+   * {
+   *   "tools": [
+   *       {
+   *           "type": "function",
+   *           "function": {
+   *               "name": "get_price_of_item",
+   *               "description": "Get the current price of an item",
+   *               "parameters": {
+   *                   "type": "object",
+   *                   "properties": {
+   *                       "item": {
+   *                           "id": "12345"
+   *                       },
+   *                       "unit": {
+   *                           "type": "currency"
+   *                       }
+   *                   }
+   *               }
+   *           }
+   *       }
+   *   ]
+   * }
+   * ```
    */
   tools?: Array<CompletionTool>
   /**
@@ -140,18 +177,52 @@ export type MessageContent = string | Array<ContentObject>
 export interface Message {
   /**
    * The content of the message.
+   *
+   * String example:
+   * ```
+   * {
+   *    "content": "Some string"
+   * }
+   * ```
+   *
+   * Object example:
+   * ```
+   * {
+   *   "content": [
+   *       {
+   *        "text": "Some text",
+   *        "type": "text"
+   *       }
+   *    ]
+   * }
+   * ```
    */
   content?: MessageContent
   /**
-   * The role of the message author.
+   * The role of the message author. Valid values are `user`, `assistant`, `system`, and `tool`.
    */
   role: string
   /**
-   * The tool call that this message is responding to.
+   * Only for `tool` role messages. The tool call that this message is responding to.
    */
   tool_call_id?: Id
   /**
-   * The tool calls generated by the model.
+   * Only for `assistant` role messages. The tool calls generated by the model. If it's specified, the `content` field is optional.
+   * Example:
+   * ```
+   * {
+   *   "tool_calls": [
+   *       {
+   *           "id": "call_KcAjWtAww20AihPHphUh46Gd",
+   *           "type": "function",
+   *           "function": {
+   *               "name": "get_current_weather",
+   *               "arguments": "{\"location\":\"Boston, MA\"}"
+   *           }
+   *       }
+   *   ]
+   * }
+   * ```
    */
   tool_calls?: Array<ToolCall>
 }

specification/inference/put_amazonbedrock/PutAmazonBedrockRequest.ts

@@ -30,7 +30,7 @@ import { InferenceChunkingSettings } from '@inference/_types/Services'
 /**
  * Create an Amazon Bedrock inference endpoint.
  *
- * Creates an inference endpoint to perform an inference task with the `amazonbedrock` service.
+ * Create an inference endpoint to perform an inference task with the `amazonbedrock` service.
  *
  * >info
  * > You need to provide the access and secret keys only once, during the inference model creation. The get inference API does not retrieve your access or secret keys. After creating the inference model, you cannot change the associated key pairs. If you want to use a different access and secret key pair, delete the inference model and recreate it with the same name and the updated keys.