genkitx-openai
Version:
Firebase Genkit AI framework plugin for OpenAI APIs.
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text/typescript
import * as genkit from 'genkit';
import { z, Genkit } from 'genkit';
import * as genkit_plugin from 'genkit/plugin';
import { ClientOptions } from 'openai';
import './dalle.mjs';
import './gpt.mjs';
import './tts.mjs';
import './whisper.mjs';
import { ModelInfo } from 'genkit/model';
interface PluginOptions extends Partial<ClientOptions> {
models?: ModelDefinition[];
}
interface ModelDefinition {
name: string;
info: ModelInfo;
configSchema?: any;
}
/**
* This module provides an interface to the OpenAI models through the Genkit
* plugin system. It allows users to interact with various models by providing
* an API key and optional configuration.
*
* The main export is the `openai` plugin, which can be configured with an API
* key either directly or through environment variables. It initializes the
* OpenAI client and makes available the models for use.
*
* Exports:
* - gpt4o: Reference to the GPT-4o model.
* - gpt4oMini: Reference to the GPT-4o-mini model.
* - gpt4Turbo: Reference to the GPT-4 Turbo model.
* - gpt4Vision: Reference to the GPT-4 Vision model.
* - gpt4: Reference to the GPT-4 model.
* - gpt35Turbo: Reference to the GPT-3.5 Turbo model.
* - dallE3: Reference to the DALL-E 3 model.
* - tts1: Reference to the Text-to-speech 1 model.
* - tts1Hd: Reference to the Text-to-speech 1 HD model.
* - whisper: Reference to the Whisper model.
* - textEmbedding3Large: Reference to the Text Embedding Large model.
* - textEmbedding3Small: Reference to the Text Embedding Small model.
* - textEmbeddingAda002: Reference to the Ada model.
* - openai: The main plugin function to interact with OpenAI.
*
* Usage:
* To use the models, initialize the openai plugin inside `configureGenkit` and
* pass the configuration options. If no API key is provided in the options, the
* environment variable `OPENAI_API_KEY` must be set.
*
* Example:
* ```
* import openai from 'genkitx-openai';
*
* export default configureGenkit({
* plugins: [
* openai({ apiKey: 'your-api-key' })
* ... // other plugins
* ]
* });
* ```
*/
declare const openAI: (options?: PluginOptions) => genkit_plugin.GenkitPlugin;
declare const TextEmbeddingConfigSchema: z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>;
type TextEmbeddingGeckoConfig = z.infer<typeof TextEmbeddingConfigSchema>;
declare const TextEmbeddingInputSchema: z.ZodString;
declare const textEmbedding3Small: genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
declare const textEmbedding3Large: genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
declare const textEmbeddingAda002: genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
declare const SUPPORTED_EMBEDDING_MODELS: {
'text-embedding-3-small': genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
'text-embedding-3-large': genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
'text-embedding-ada-002': genkit.EmbedderReference<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
};
declare function openaiEmbedder(ai: Genkit, name: string, options?: PluginOptions): genkit.EmbedderAction<z.ZodObject<{
dimensions: z.ZodOptional<z.ZodNumber>;
encodingFormat: z.ZodOptional<z.ZodUnion<[z.ZodLiteral<"float">, z.ZodLiteral<"base64">]>>;
}, "strip", z.ZodTypeAny, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}, {
dimensions?: number | undefined;
encodingFormat?: "float" | "base64" | undefined;
}>>;
export { type ModelDefinition as M, type PluginOptions as P, SUPPORTED_EMBEDDING_MODELS as S, TextEmbeddingConfigSchema as T, textEmbedding3Small as a, textEmbeddingAda002 as b, type TextEmbeddingGeckoConfig as c, TextEmbeddingInputSchema as d, openaiEmbedder as e, openAI as o, textEmbedding3Large as t };