#Communication-APIs

[codemerything]

Introduction to APIs and Web APIs

The illustration above is the best way you can think of how APIs work and I talk more about it in my new article about APIs. I really love the concept and logic of APIs, it proves that collaboration is a huge part of programming and APIs solidify that. I hope you enjoy the read and also this is my first article and I intend to write more about technologies that interest me and maybe tips and tricks in the future.

[voiceapisolutions]

The Role of Personalized Voice Messaging in Financial Services and Banking

Developing real-time communication with clients is a major benefit of putting in place a voice call API. The instantaneity of a voice exchange offers a human touch that other communication channels might not be able to provide, whether it is answering a question, offering support, or providing tailored assistance. Companies can use this feature to increase customer satisfaction by resolving problems quickly and building dependability and trust. Sinch provides enterprise-level voice API solutions that businesses may easily include into their current CRM.

Voice-Based OTP Services

Voice-based OTP services are characters or numbers (OTP) sent through a phone call to verify a transaction or login session. Use the Voice OTP service to authenticate a user by calling a mobile phone and playing a number. The 2FA (Two-factor authentication) service is built on a world-class voice platform to provide reliable voice transmission worldwide. It is a completely API-based solution. Integrate your platform with the Sinch Voice OTP API and initiate real-time OTP calls with your consumers.

Best VoIP Service for Small Business

In today's fast-paced business environment, effective communication is essential for success, particularly for small enterprises trying to establish themselves. VoIP services have become a potent instrument for improving the effectiveness of communication. Business owners may make wise judgments if they are aware of the advantages of the best VoIP service for small businesses. Voice over Internet Protocol (VOIP) technology allows for both audio and video communication.

Voice API For Business Communication

Voice APIs enable developers to create custom calling solutions using their preferred language and the other available API tools. Beyond this capability, Voice API for business communication helps you experience further benefits, such as Complete Call Commands, Better Client Relationships, Smart API Convenience, and Multilingual Communication. Create the perfect communications solution tailored for your business to engage seamlessly through voice communications.

More Resources:

The Future of Outbound & Inbound Dialling Services

Improve Customer Satisfaction with Voice Calls

[rayjuss]

https://whatsapp.com/channel/0029Vb434d35Ui2PdfwoxP1P

[dailyanarchistposts]

Thanks to my partners, and to anok, autumn leaf cascade, enkidu, ingrate, rice boy, and taigarun, all long-term and thoughtful contributors to anarchy101.org. Thanks also to the others on that site (including many anonymous questionners). I truly appreciate getting to have provocative conversations about things I care about with people who I don’t even know.

And thanks to Jessica, the excellent beginner.

I hope I have done justice to us all.

Introduction

Anarchy is many things to different people: a vision, a plan, a conversation, a process. It is my view (consistent with a whole raft of contemporary anarchists, from Alfredo M. Bonanno to Voltairine de Cleyre and beyond) that anarchy is best understood, and is most helpful, as a tension, a question, a rejection. This text operates from that premise.

This book is composed of questions, answers, and comments (sometimes lightly edited) taken from a website called anarchy101.org, in which various anarchists answer questions posed by themselves and others. This variety of voices (the answers and comments disagree with each other as often as agree) is integral to any anarchist project that I want to be a part of. There are many more questions there than could reasonably fit into a book, so go, read, ask, and argue.

We welcome your engagement with these ideas, and look forward to hearing your voice in the future.

In the following pages you will meet

AnarchicSaint: ast

Anok: ank

Apio: api

Asker: asr

Aragorn: a!

Aragorn23: a23

Autumn Leaf Cascade: alc

Blacque: blq

Dot: dot

Enkidu: enk

Frenzy: frz

Funkyanarchy: fnk

Iconoclast: ict

Ingrate: ing

Inpraiseofchaos: ipc

KatherineD: kd

Lawrence: law

Madlib: mdb

MrThisBody: mtb

MattThePrick: mtp

MollytheAnarchist: mta

Nothing Resonates: nnn

Rice Boy: rby

Sabotage: sab

Squee: squ

Taigarun: tgn

Vindico Vaco: vvo

[smsgatewayindia]

Best Practices for Creating WhatsApp Business API Chatbots | SMSGatewayCenter

Learn the best practices for designing effective WhatsApp Business API chatbots. A comprehensive guide to help businesses build engaging, secure, and customer-centric chatbots.

[phonesuite]

This blog post will give you an in-depth look at everything from API integration to connecting your switch with channel management systems, streamlining the operations performance of the hotel business. Learn More...

[sheltiechicago]

Winner of Hadley’s Art Prize 2023

Ngayuku Ngura (My Country)

by Vicki Yatjiki Cullinan

Acrylic paint on linen.

‘I am a Yankunytjatjara woman from Indulkana Community on the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands in South Australia. My painting is connected to the Tjukurpa (ancestral stories) that I know, but also my paintings are an extension of who I am, and how I interpret my place in the world.’

Photograph: Hadley's Art Prize

Hadley’s Art Prize

[jcmarchi]

How to build autonomous AI agent with Google A2A protocol

New Post has been published on https://thedigitalinsider.com/how-to-build-autonomous-ai-agent-with-google-a2a-protocol/

How to build autonomous AI agent with Google A2A protocol

Why do we need autonomous AI agents?

Picture this: it’s 3 a.m., and a customer on the other side of the globe urgently needs help with their account. A traditional chatbot would wake up your support team with an escalation. But what if your AI agent could handle the request autonomously, safely, and correctly? That’s the dream, right?

The reality is that most AI agents today are like teenagers with learner’s permits; they need constant supervision. They might accidentally promise a customer a large refund (oops!) or fall for a clever prompt injection that makes them spill company secrets or customers’ sensitive data. Not ideal.

This is where Double Validation comes in. Think of it as giving your AI agent both a security guard at the entrance (input validation) and a quality control inspector at the exit (output validation). With these safeguards at a minimum in place, your agent can operate autonomously without causing PR nightmares.

How did I come up with the Double Validation idea?

These days, we hear a lot of talk about AI agents. I asked myself, “What is the biggest challenge preventing the widespread adoption of AI agents?” I concluded that the answer is trustworthy autonomy. When AI agents can be trusted, they can be scaled and adopted more readily. Conversely, if an agent’s autonomy is limited, it requires increased human involvement, which is costly and inhibits adoption.

Next, I considered the minimal requirements for an AI agent to be autonomous. I concluded that an autonomous AI agent needs, at minimum, two components:

Input validation – to sanitize input, protect against jailbreaks, data poisoning, and harmful content.

Output validation – to sanitize output, ensure brand alignment, and mitigate hallucinations.

I call this system Double Validation.

Given these insights, I built a proof-of-concept project to research the Double Validation concept.

In this article, we’ll explore how to implement Double Validation by building a multiagent system with the Google A2A protocol, the Google Agent Development Kit (ADK), Llama Prompt Guard 2, Gemma 3, and Gemini 2.0 Flash, and how to optimize it for production, specifically, deploying it on Google Vertex AI.

For input validation, I chose Llama Prompt Guard 2 just as an article about it reached me at the perfect time. I selected this model because it is specifically designed to guard against prompt injections and jailbreaks. It is also very small; the largest variant, Llama Prompt Guard 2 86M, has only 86 million parameters, so it can be downloaded and included in a Docker image for cloud deployment, improving latency. That is exactly what I did, as you’ll see later in this article.

How to build it?

The architecture uses four specialized agents that communicate through the Google A2A protocol, each with a specific role:

Image generated by author

Here’s how each agent contributes to the system:

Manager Agent: The orchestra conductor, coordinating the flow between agents

Safeguard Agent: The bouncer, checking for prompt injections using Llama Prompt Guard 2

Processor Agent: The worker bee, processing legitimate queries with Gemma 3

Critic Agent: The editor, evaluating responses for completeness and validity using Gemini 2.0 Flash

I chose Gemma 3 for the Processor Agent because it is small, fast, and can be fine-tuned with your data if needed — an ideal candidate for production. Google currently supports nine (!) different frameworks or methods for finetuning Gemma; see Google’s documentation for details.

I chose Gemini 2.0 Flash for the Critic Agent because it is intelligent enough to act as a critic, yet significantly faster and cheaper than the larger Gemini 2.5 Pro Preview model. Model choice depends on your requirements; in my tests, Gemini 2.0 Flash performed well.

I deliberately used different models for the Processor and Critic Agents to avoid bias — an LLM may judge its own output differently from another model’s.

Let me show you the key implementation of the Safeguard Agent:

Plan for actions

The workflow follows a clear, production-ready pattern:

User sends query → The Manager Agent receives it.

Safety check → The Manager forwards the query to the Safeguard Agent.

Vulnerability assessment → Llama Prompt Guard 2 analyzes the input.

Processing → If the input is safe, the Processor Agent handles the query with Gemma 3.

Quality control → The Critic Agent evaluates the response.

Delivery → The Manager Agent returns the validated response to the user.

Below is the Manager Agent’s coordination logic:

Time to build it

Ready to roll up your sleeves? Here’s your production-ready roadmap:

Local deployment

1. Environment setup 

2. Configure API keys 

3. Download Llama Prompt Guard 2 

This is the clever part – we download the model once when we start Agent Critic for the first time and package it in our Docker image for cloud deployment:

Important Note about Llama Prompt Guard 2: To use the Llama Prompt Guard 2 model, you must:

Fill out the “LLAMA 4 COMMUNITY LICENSE AGREEMENT” at https://huggingface.co/meta-llama/Llama-Prompt-Guard-2-86M

Get your request to access this repository approved by Meta

Only after approval will you be able to download and use this model

4. Local testing 

Screenshot for running main.py

Image generated by author

Screenshot for running client

Image generated by author

Screenshot for running tests

Image generated by author

Production Deployment 

Here’s where it gets interesting. We optimize for production by including the Llama model in the Docker image:

1. Setup Cloud Project in Cloud Shell Terminal

Access Google Cloud Console: Go to https://console.cloud.google.com

Open Cloud Shell: Click the Cloud Shell icon (terminal icon) in the top right corner of the Google Cloud Console

Authenticate with Google Cloud:

Create or select a project:

Enable required APIs:

3. Setup Vertex AI Permissions

Grant your account the necessary permissions for Vertex AI and related services:

3. Create and Setup VM Instance

Cloud Shell will not work for this project as Cloud Shell is limited to 5GB of disk space. This project needs more than 30GB of disk space to build Docker images, get all dependencies, and download the Llama Prompt Guard 2 model locally. So, you need to use a dedicated VM instead of Cloud Shell.

4. Connect to VM

Screenshot for VM 

Image generated by author

5. Clone Repository

6. Deployment Steps

Screenshot for agents in cloud 

Image generated by author

7. Testing 

Screenshot for running client in Google Vertex AI

Image generated by author

Screenshot for running tests in Google Vertex AI

Image generated by author

Alternatives to Solution

Let’s be honest – there are other ways to skin this cat:

Single Model Approach: Use a large LLM like GPT-4 with careful system prompts

Simpler but less specialized

Higher risk of prompt injection

Risk of LLM bias in using the same LLM for answer generation and its criticism

Monolith approach: Use all flows in just one agent

Latency is better

Cannot scale and evolve input validation and output validation independently

More complex code, as it is all bundled together

Rule-Based Filtering: Traditional regex and keyword filtering

Faster but less intelligent

High false positive rate

Commercial Solutions: Services like Azure Content Moderator or Google Model Armor

Easier to implement but less customizable

On contrary, Llama Prompt Guard 2 model can be fine-tuned with the customer’s data

Ongoing subscription costs

Open-Source Alternatives: Guardrails AI or NeMo Guardrails

Good frameworks, but require more setup

Less specialized for prompt injection

Lessons Learned

1. Llama Prompt Guard 2 86M has blind spots. During testing, certain jailbreak prompts, such as:

And

were not flagged as malicious. Consider fine-tuning the model with domain-specific examples to increase its recall for the attack patterns that matter to you.

2. Gemini Flash model selection matters. My Critic Agent originally used gemini1.5flash, which frequently rated perfectly correct answers 4 / 5. For example:

After switching to gemini2.0flash, the same answers were consistently rated 5 / 5:

3. Cloud Shell storage is a bottleneck. Google Cloud Shell provides only 5 GB of disk space — far too little to build the Docker images required for this project, get all dependencies, and download the Llama Prompt Guard 2 model locally to deploy the Docker image with it to Google Vertex AI. Provision a dedicated VM with at least 30 GB instead.

Conclusion

Autonomous agents aren’t built by simply throwing the largest LLM at every problem. They require a system that can run safely without human babysitting. Double Validation — wrapping a task-oriented Processor Agent with dedicated input and output validators — delivers a balanced blend of safety, performance, and cost. 

Pairing a lightweight guard such as Llama Prompt Guard 2 with production friendly models like Gemma 3 and Gemini Flash keeps latency and budget under control while still meeting stringent security and quality requirements.

Join the conversation. What’s the biggest obstacle you encounter when moving autonomous agents into production — technical limits, regulatory hurdles, or user trust? How would you extend the Double Validation concept to high-risk domains like finance or healthcare?

Connect on LinkedIn: https://www.linkedin.com/in/alexey-tyurin-36893287/  

The complete code for this project is available at github.com/alexey-tyurin/a2a-double-validation. 

References

[1] Llama Prompt Guard 2 86M, https://huggingface.co/meta-llama/Llama-Prompt-Guard-2-86M

[2] Google A2A protocol, https://github.com/google-a2a/A2A 

[3] Google Agent Development Kit (ADK), https://google.github.io/adk-docs/ 

[whatsappapiautomation]

whatsapp api role in e-commerce

[newseoage]

New Delhi [India], May 14: Seoage Digital Marketing Private Limited, a full-service digital marketing agency based in New Delhi, continues to lead the industry with its results-driven approach, under the visionary leadership of its Director, Dr. Gaurav Maggo.

[voicebrodcasting]

WhatsApp Business Solution Provider

Use WhatsApp to reach and connect with your customers where they are already present. Get WhatsApp Business API solution from go2market to automate your business communication and customer engagement process.

[worthybonds]

Understanding Different Types of Bonds for Investors

Chances are that you already know investments are an excellent way to grow your wealth and secure a successful financial future for yourself. There are so many benefits to bonds, like the fact that they tend to carry less risk than stocks and can provide a steady stream of income. 

What types of bonds are there and how do you decide which one is right for your portfolio?

There are three major categories of bonds you should consider: Treasury bonds, corporate bonds, and municipal bonds. Let’s dive into what they all are.

[36crypto]

Turbo Already Took Off, But BTFD Coin’s $0.0002 Presale Ends May 26—Last Chance to Ride Before the $0.006 Moon Target Hits

Meme coins have flipped the script in crypto. What started as internet jokes now moves markets, pumps communities, and sparks bull runs that leave even seasoned investors scrambling to keep up. Every cycle, there’s that one coin everyone wishes they’d caught early. First it was Dogecoin, then SHIB, then PEPE—and now we’re seeing newer, wilder contenders going parabolic almost overnight. But…