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This week on our Friends on Friday guest blog post my colleague, Dan Rood, writes about the precious commodity of time and why we must use the latest technologies to help customers save time and have amazing customer experiences. Standardized web services and APIs for federating silos of data and connecting applications ease integration.
In this blog post, we showcase a powerful solution that seamlessly integrates AWS generative AI capabilities in the form of large language models (LLMs) based on Amazon Bedrock into the Office experience. Note that these APIs use objects as namespaces, alleviating the need for explicit imports.
Consider the number of critical APIs that are embedded. Double the APIs – quadruple your problems! The post Guest Blog: Winning Tactics for CX Vendor Selection appeared first on Shep Hyken. Is it robust enough for your scale and complexity of operations? Does the vendor have a proven track record with your legacy systems?
It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.
The Vonage Voice API WebSockets feature recently left Beta status and became generally available. Vonage API Account. To complete this tutorial, you will need a Vonage API account. Once you have an account, you can find your API Key and API Secret at the top of the Vonage API Dashboard.
Each drone follows predefined routes, with flight waypoints, altitude, and speed configured through an AWS API, using coordinates stored in Amazon DynamoDB. API Gateway plays a complementary role by acting as the main entry point for external applications, dashboards, and enterprise integrations.
Traditional automation approaches require custom API integrations for each application, creating significant development overhead. Add the Amazon Bedrock Agents supported computer use action groups to your agent using CreateAgentActionGroup API. Prerequisites AWS Command Line Interface (CLI), follow instructions here.
The post Build Chatbot using Twilio WhatsApp API appeared first on Kommunicate Blog. Depending on the use case, some chatbot technologies are more appropriate than others. Kommunicate is one such solution, [.].
A Dashboard Designed for Developers APIs serve as the bridges that enable different software systems to communicate, facilitating the flow of data and functionality. For developers, APIs are the… Read more on Cisco Blogs
Meta just announced that the WhatsApp Cloud API and businesses across the world [.]. The post WhatsApp Cloud API : Everything you need to know about it appeared first on Kommunicate Blog.
Last Updated on June 22, 2023 What is a Chatbot API? A chatbot API is a set of protocols that allow developers to access the functionalities of a chatbot. A chatbot API enables seamless integration into various applications, systems or platforms by standardizing the way you send, receive and extract messages via the chatbot.
This could be APIs, code functions, or schemas and structures required by your end application. Tool use with Amazon Nova To illustrate the concept of tool use, we can imagine a situation where we provide Amazon Nova access to a few different tools, such as a calculator or a weather API. Amazon Nova will use the weather tool.
This involves creating an OAuth API endpoint in ServiceNow and using the web experience URL from Amazon Q Business as the callback URL. The final step of the solution involves enhancing the application environment with a custom plugin for ServiceNow using APIs defined in an OpenAPI schema.
In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.
They use a highly optimized inference stack built with NVIDIA TensorRT-LLM and NVIDIA Triton Inference Server to serve both their search application and pplx-api, their public API service that gives developers access to their proprietary models. The results speak for themselvestheir inference stack achieves up to 3.1
Cisco Defense Orchestrator (CDO) provides a powerful REST API to automate and simplify security management tasks. You can find CDO API Documentation on DevNet. And tune in to a live discussion on … Read more on Cisco Blogs
When complete, a notification chain using Amazon Simple Queue Service (Amazon SQS) and our internal notifications service API gateway begins delivering updates using Slack direct messaging and storing searchable records in OpenSearch for future reference.
This blog post delves into how these innovative tools synergize to elevate the performance of your AI applications, ensuring they not only meet but exceed the exacting standards of enterprise-level deployments. This blog post focuses on using its Observability / Evaluation modules.
Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API. Test the code using the native inference API for Anthropics Claude The following code uses the native inference API to send a text message to Anthropics Claude. client = boto3.client("bedrock-runtime",
10 Chatbot API. The last of the chatbot features we’ll cover is chatbot API. A simple chatbot builder is a great first step, but chatbot API (application programming interface) can take things up a notch. Chatbot API is a framework that allows you to create a conversational experience through more advanced programming languages.
To learn more about opportunities for customers to use SLMs, see Opportunities for telecoms with small language models: Insights from AWS and Meta on our AWS Industries blog. The embedding model, which is hosted on the same EC2 instance as the local LLM API inference server, converts the text chunks into vector representations.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.
Importantly, cross-Region inference prioritizes the connected Amazon Bedrock API source Region when possible, helping minimize latency and improve overall responsiveness. v2 using the Amazon Bedrock console or the API by assuming the custom IAM role mentioned in the previous step ( Bedrock-Access-CRI ).
Amazon Bedrock , a fully managed service offering high-performing foundation models from leading AI companies through a single API, has recently introduced two significant evaluation capabilities: LLM-as-a-judge under Amazon Bedrock Model Evaluation and RAG evaluation for Amazon Bedrock Knowledge Bases.
This enables sales teams to interact with our internal sales enablement collateral, including sales plays and first-call decks, as well as customer references, customer- and field-facing incentive programs, and content on the AWS website, including blog posts and service documentation.
Luckily for us, Vonage has a fantastic API for tracking phone calls ! We’ll use the Vonage API and build a.NET Core application that stores and displays this information by using event sourcing. Vonage API Account. To complete this tutorial, you will need a Vonage API account. Prerequisites. The latest version of.NET /.NET
For instance, Rails can handle complex business logic and APIs, while React takes care of delivering a smooth, interactive user experience. Separation of Concerns: Rails efficiently handles the backend logic, data processing, and APIs, while React manages the front-end user interface.
This year, like no other, we will see organizations tap into APIs to sidestep the complexity and cost of developing and maintaining their own AI solutions and models. In pursuit of digital… Read more on Cisco Blogs
Beyond Amazon Bedrock models, the service offers the flexible ApplyGuardrails API that enables you to assess text using your pre-configured guardrails without invoking FMs, allowing you to implement safety controls across generative AI applicationswhether running on Amazon Bedrock or on other systemsat both input and output levels.
The Amazon Bedrock single API access, regardless of the models you choose, gives you the flexibility to use different FMs and upgrade to the latest model versions with minimal code changes. Amazon Titan FMs provide customers with a breadth of high-performing image, multimodal, and text model choices, through a fully managed API.
The Amazon Bedrock API returns the output Q&A JSON file to the Lambda function. The container image sends the REST API request to Amazon API Gateway (using the GET method). API Gateway communicates with the TakeExamFn Lambda function as a proxy. The JSON file is returned to API Gateway.
Moreover, this capability prioritizes the connected Amazon Bedrock API source/primary region when possible, helping to minimize latency and improve responsiveness. Compatibility with existing Amazon Bedrock API No additional routing or data transfer cost and you pay the same price per token for models as in your source/primary region.
In this blog post, you will learn about prompt chaining, how to break a complex task into multiple tasks to use prompt chaining with an LLM in a specific order, and how to involve a human to review the response generated by the LLM. Detect if the review content has any harmful information using the Amazon Comprehend DetectToxicContent API.
Additionally, Q Business conversation APIs employ a layer of privacy protection by leveraging trusted identity propagation enabled by IAM Identity Center. Amazon Q Business comes with rich API support to perform administrative tasks or to build an AI-assistant with customized user experience for your enterprise.
For your reference, this blog post demonstrates a solution to create a VPC with no internet connection using an AWS CloudFormation template. Note that MLflow tracking starts from the mlflow.start_run() API. The mlflow.autolog() API can automatically log information such as metrics, parameters, and artifacts.
This solution ingests and processes data from hundreds of thousands of support tickets, escalation notices, public AWS documentation, re:Post articles, and AWS blog posts. Step Functions orchestrates AWS services like AWS Lambda and organization APIs like DataStore to ingest, process, and store data securely.
Today I’ll show you how to build your own with the Vonage Voice and Messages APIs, complete with a simple dashboard to download call recordings and log incoming messages. A Vonage API account – take note of your API Key & Secret on the dashboard. Vonage API Account. Prerequisites. Set up Dependencies.
Blogs – Each blog is considered a single document. Similarly for pages and blogs, you use the restrictions page. For more information about page and blog restrictions, see Page Restrictions on the Confluence Support website. _user_id – Usernames are present on the space, page, or blog where there are restrictions.
Large language model (LLM) agents are programs that extend the capabilities of standalone LLMs with 1) access to external tools (APIs, functions, webhooks, plugins, and so on), and 2) the ability to plan and execute tasks in a self-directed fashion. Note that the next action may or may not involve using a tool or API.
This blog post is co-written with Louis Prensky and Philip Kang from Appian. This blog post will cover how Appian AI skills build automation into organizations mission-critical processes to improve operational excellence, reduce costs, and build scalable solutions.
This blog post shares more about how generative AI solutions from Amazon Ads help brands create more visually rich consumer experiences. In this blog post, we describe the architectural and operational details of how Amazon Ads implemented its generative AI-powered image creation solution on AWS.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a unified API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.
This blog post outlines various use cases where we’re using generative AI to address digital publishing challenges. Our CMS backend Nova is implemented using Amazon API Gateway and several AWS Lambda functions. Amazon DynamoDB serves as the primary database for 20 Minutes articles.
This is a guest blog post co-written with Jordan Knight, Sara Reynolds, George Lee from Travelers. Foundation models (FMs) are used in many ways and perform well on tasks including text generation, text summarization, and question answering.
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