Merge pull request #17 from ChuckJonas/chat-function-support

support for passing "functions" to chat completions

Author: load1n9

examples/chatCompletionFunction.ts

@@ -0,0 +1,33 @@
+import { OpenAI } from "../mod.ts";
+
+const openAI = new OpenAI(Deno.env.get("YOUR_API_KEY")!);
+
+const chatCompletion = await openAI.createChatCompletion({
+  model: "gpt-3.5-turbo",
+  messages: [
+    {"role": "user", "content": "What is the weather like in Boston?"}
+  ],
+  function_call: { name: "get_current_weather" },
+  functions: [
+    {
+      "name": "get_current_weather",
+      "description": "Get the current weather in a given location",
+      "parameters": {
+        "type": "object",
+        "properties": {
+          "location": {
+            "type": "string",
+            "description": "The city and state, e.g. San Francisco, CA"
+          },
+          "unit": {
+            "type": "string",
+            "enum": ["celsius", "fahrenheit"]
+          }
+        },
+        "required": ["location"]
+      }
+    }
+  ]
+});
+
+console.log(chatCompletion);

src/openai.ts

@@ -168,7 +168,7 @@ export class OpenAI {
   async createChatCompletion(
     options: ChatCompletionOptions,
   ): Promise<ChatCompletion> {
-    return await this.#request(`/chat/completions`, {
+    const resp = await this.#request(`/chat/completions`, {
       model: options.model,
       messages: options.messages,
       temperature: options.temperature,
@@ -180,7 +180,15 @@ export class OpenAI {
       frequency_penalty: options.frequencyPenalty,
       logit_bias: options.logitBias,
       user: options.user,
-    });
+      functions: options.functions,
+      function_call: options.function_call,
+    }) as ChatCompletion;
+
+    // null coalesce content to empty string as discussed in PR #17
+    resp?.choices?.forEach(
+      (choice) => (choice.message.content = choice.message.content ?? "")
+    );
+    return resp;
   }
 
   /**
@@ -213,6 +221,8 @@ export class OpenAI {
           frequency_penalty: options.frequencyPenalty,
           logit_bias: options.logitBias,
           user: options.user,
+          functions: options.functions,
+          function_call: options.function_call
         }),
       },
     );

src/types.ts

@@ -197,8 +197,64 @@ export interface ChatCompletionOptions {
    * https://platform.openai.com/docs/api-reference/chat/create#chat/create-user
    */
   user?: string;
+
+  /**
+   * A list of functions the model may generate JSON inputs for.
+   * https://platform.openai.com/docs/api-reference/chat/create#chat/create-functions
+   */
+  functions?: ChatCompletionOptionsFunction[];
+
+  /**
+   * 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 are present.
+   * https://platform.openai.com/docs/api-reference/chat/create#chat/create-function_call
+   */
+  function_call?: 'none' | 'auto' | { name: string };
 }
 
+export type ChatCompletionOptionsFunction = {
+  name: string;
+  description: string;
+  parameters: ObjectSchema;
+};
+
+type JSONSchema = (
+  | ObjectSchema
+  | StringSchema
+  | NumberSchema
+  | BooleanSchema
+  | ArraySchema
+) & { description?: string };
+
+type ObjectSchema = {
+  type: "object";
+  properties: Record<string, JSONSchema>;
+  required: string[];
+};
+
+type ArraySchema = {
+  type: "array";
+  items: JSONSchema;
+};
+
+type StringSchema = {
+  type: "string";
+  enum?: string[];
+};
+
+type NumberSchema = {
+  type: "number";
+  minimum?: number;
+  maximum?: number;
+};
+
+type BooleanSchema = {
+  type: "boolean";
+};
+
 export interface EditOptions {
   /**
    * ID of the model to use. You can use the text-davinci-edit-001 or code-davinci-edit-001 model with this endpoint.
@@ -616,6 +672,10 @@ export interface ChatCompletion {
       name?: string;
       role: "system" | "assistant" | "user";
       content: string;
+      function_call?: {
+        "name": string,
+        "arguments": string
+      }
     };
     finish_reason: string;
   }[];