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genkitx-aws-bedrock
Advanced tools
genkitx-aws-bedrock
is a community plugin for using AWS Bedrock APIs with
Firebase Genkit. Built by Xavier Portilla Edo.
This Genkit plugin allows to use AWS Bedrock through their official APIs.
Install the plugin in your project with your favorite package manager:
npm install genkitx-aws-bedrock
pnpm add genkitx-aws-bedrock
if you are using Genkit version <v0.9.0
, please use the plugin version v1.9.0
. If you are using Genkit >=v0.9.0
, please use the plugin version >=v1.10.0
.
To use the plugin, you need to configure it with your AWS credentials key. You can do this by calling the genkit
function:
import { genkit, z } from 'genkit';
import {awsBedrock, amazonNovaProV1} from "genkitx-aws-bedrock";
const ai = genkit({
plugins: [
awsBedrock({ region: "<my-region>" }),
model: amazonNovaProV1,
]
});
You can also intialize the plugin in this way if you have set the AWS_
environment variable:
import { genkit, z } from 'genkit';
import {awsBedrock, amazonNovaProV1} from "genkitx-aws-bedrock";
const ai = genkit({
plugins: [
awsBedrock(),
model: amazonNovaProV1,
]
});
If you want to use a model that uses Cross-region Inference Endpoints, you can specify the region in the model configuration. Cross-region inference uses inference profiles to increase throughput and improve resiliency by routing your requests across multiple AWS Regions during peak utilization bursts:
import { genkit, z } from 'genkit';
import {awsBedrock, amazonNovaProV1} from "genkitx-aws-bedrock";
const ai = genkit({
plugins: [
awsBedrock(),
model: anthropicClaude3SonnetV1("us"),
]
});
You can check more information about the available models in the AWS Bedrock PLugin documentation.
The simplest way to call the text generation model is by using the helper function generate
:
import { genkit, z } from 'genkit';
import {awsBedrock, amazonNovaProV1} from "genkitx-aws-bedrock";
// Basic usage of an LLM
const response = await ai.generate({
prompt: 'Tell me a joke.',
});
console.log(await response.text);
// ...configure Genkit (as shown above)...
export const myFlow = ai.defineFlow(
{
name: 'menuSuggestionFlow',
inputSchema: z.string(),
outputSchema: z.string(),
},
async (subject) => {
const llmResponse = await ai.generate({
prompt: `Suggest an item for the menu of a ${subject} themed restaurant`,
});
return llmResponse.text;
}
);
// ...configure Genkit (as shown above)...
const specialToolInputSchema = z.object({ meal: z.enum(["breakfast", "lunch", "dinner"]) });
const specialTool = ai.defineTool(
{
name: "specialTool",
description: "Retrieves today's special for the given meal",
inputSchema: specialToolInputSchema,
outputSchema: z.string(),
},
async ({ meal }): Promise<string> => {
// Retrieve up-to-date information and return it. Here, we just return a
// fixed value.
return "Baked beans on toast";
}
);
const result = ai.generate({
tools: [specialTool],
prompt: "What's for breakfast?",
});
console.log(result.then((res) => res.text));
For more detailed examples and the explanation of other functionalities, refer to the official Genkit documentation.
This plugin supports all currently available Chat/Completion and Embeddings models from AWS Bedrock. This plugin supports image input and multimodal models.
You can find the full API reference in the API Reference Documentation
Want to contribute to the project? That's awesome! Head over to our Contribution Guidelines.
[!NOTE]
This repository depends on Google's Firebase Genkit. For issues and questions related to Genkit, please refer to instructions available in Genkit's repository.
Reach out by opening a discussion on GitHub Discussions.
This plugin is proudly maintained by Xavier Portilla Edo Xavier Portilla Edo.
I got the inspiration, structure and patterns to create this plugin from the Genkit Community Plugins repository built by the Fire Compnay as well as the ollama plugin.
This project is licensed under the Apache 2.0 License.
FAQs
Firebase Genkit AI framework plugin for AWS Bedrock APIs.
The npm package genkitx-aws-bedrock receives a total of 1 weekly downloads. As such, genkitx-aws-bedrock popularity was classified as not popular.
We found that genkitx-aws-bedrock demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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