genkitx-aws-bedrock
Version:
Firebase Genkit AI framework plugin for AWS Bedrock APIs.
115 lines • 3.86 kB
JavaScript
/**
* Copyright 2024 The Fire Company
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* eslint-disable @typescript-eslint/no-explicit-any */
import { embedderRef } from "genkit";
import { z } from "zod";
import { InvokeModelCommand, } from "@aws-sdk/client-bedrock-runtime";
export const TextEmbeddingConfigSchema = z.object({
dimensions: z.number().optional(),
});
export const TextEmbeddingInputSchema = z.string();
export const amazonTitanEmbedTextV2 = embedderRef({
name: "aws-bedrock/amazon.titan-embed-text-v2:0",
configSchema: TextEmbeddingConfigSchema,
info: {
dimensions: 1024,
label: "Amazon - titan-embed-text-v2:0",
supports: {
input: ["text"],
},
},
});
export const amazonTitanEmbedMultimodalV2 = embedderRef({
name: "aws-bedrock/amazon.titan-embed-image-v1",
configSchema: TextEmbeddingConfigSchema,
info: {
dimensions: 1024,
label: "Amazon - titan-embed-multimodal-v2:0",
supports: {
input: ["text", "image"],
},
},
});
export const amazonTitanEmbedTextG1V1 = embedderRef({
name: "aws-bedrock/amazon.titan-embed-text-v1",
configSchema: TextEmbeddingConfigSchema,
info: {
dimensions: 1536,
label: "Amazon - titan-embed-text-v1",
supports: {
input: ["text"],
},
},
});
export const cohereEmbedEnglishV3 = embedderRef({
name: "aws-bedrock/cohere.embed-english-v3",
configSchema: TextEmbeddingConfigSchema,
info: {
dimensions: 1024,
label: "Cohere - embed-english-v3",
supports: {
input: ["text"],
},
},
});
export const cohereEmbedMultilingualV3 = embedderRef({
name: "aws-bedrock/cohere.embed-multilingual-v3",
configSchema: TextEmbeddingConfigSchema,
info: {
dimensions: 1024,
label: "Cohere - embed-multilingual-v3",
supports: {
input: ["text"],
},
},
});
export const SUPPORTED_EMBEDDING_MODELS = {
"amazon.titan-embed-text-v2:0": amazonTitanEmbedTextV2,
"amazon.titan-embed-image-v1": amazonTitanEmbedMultimodalV2,
"amazon.titan-embed-text-v1": amazonTitanEmbedTextG1V1,
"cohere.embed-english-v3": cohereEmbedEnglishV3,
"cohere.embed-multilingual-v3": cohereEmbedMultilingualV3,
};
export function awsBedrockEmbedder(name, ai, client) {
const model = SUPPORTED_EMBEDDING_MODELS[name];
return ai.defineEmbedder({
info: model.info,
configSchema: TextEmbeddingConfigSchema,
name: model.name,
}, async (input, options) => {
const body = {
modelId: name,
contentType: "application/json",
body: JSON.stringify({
inputText: input.map((d) => d.text).join(","),
dimensions: options?.dimensions,
}),
};
const command = new InvokeModelCommand(body);
const response = (await client.send(command));
const embeddings = new TextDecoder().decode(response.body)
? JSON.parse(new TextDecoder().decode(response.body))
: [];
return {
embeddings: [
{
embedding: embeddings.embedding,
},
],
};
});
}
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