Bhagavata 5th Skandha is one such example that you can hear to.

And here I am opening sourcing Vaghenu, a meter aware sloka-to-chant, TTS for Sanskrit . This is the world's first vrutta-aware, open-source TTS for Sanskrit Chanting. I am making the model weights, training scripts, and even data (that I meticulously collected) public - https://prathosh.in/vagdhenu/

No large AI lab. No big engineering team. No venture-scale budget. Just a professor's conviction that one of humanity's oldest knowledge traditions deserves modern, open infrastructure.

The name comes from the Upanishadic phrase: "Vācaṃ dhenum upāsīta" - Like the mythical wish-fulfilling cow, Vāgdhenu is intended to make Sanskrit texts more accessible to students, teachers, researchers, and devotees everywhere.

Test out the live demo here and let me know your comments - https://prathosh.in/vagdhenu/

The entire system, from data collection to model building and demos, is built by a single person (your truly) using the powerful harness that we are building at LatentForce.

I have attached a sample audio file generated by the system.

P.S: Posting on behalf of my friend, their aren't on HN.

Comments URL: https://news.ycombinator.com/item?id=48728732

Points: 10

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More than a decade ago I had built paw-on-es6 to help folks get hands-on with ES6 (ES2015). It did its job.

I am now introducing ESlabs. It covers every major feature from ES2015 through ES2025.

You write real code in your browser, run exercises, and actually internalize what the features do and why we need them in the first place.

The irony isn't lost on me: building a tool to help humans learn, in an era where the temptation is to just use an agent skill!

Give it a spin. Break things. That's the point

Comments URL: https://news.ycombinator.com/item?id=48097326

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Comments URL: https://news.ycombinator.com/item?id=46921758

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I've been tracking the explosion of AI Agent protocols over the last 18 months. The contrast with history is staggering: - TCP/IP: 9 years from paper to "Flag Day." - OAuth 2.1: 5+ years and still counting. - Model Context Protocol (MCP): <1 year from launch to Linux Foundation.

It’s not just MCP. In 2025 alone, we saw: - Google's Agent2Agent (50+ partners), - Universal Commerce Protocol (20+ retailers) - AP2 (Payments) all ship. - Agent Protocol, UTCP and few more.

We are entering an era of "Room Consensus": where a few giants agree on a spec and ship it to billions, bypassing the slow deliberation of the RFC era. Is this efficiency? Or fragility?

I break down the landscape of the new agent protocols and what this means for developers in my latest post.

Comments URL: https://news.ycombinator.com/item?id=46847005

Points: 1

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kb = Ragi(["./docs", "s3://bucket/data/*/*.pdf", "https://api.example.com/docs"])

answer = kb.ask("How do I deploy this?")

that's it! with https://pypi.org/project/piragi/

What is UCP? UCP is an open standard that enables AI agents and platforms to complete purchases on any UCP-enabled merchant without custom integrations.

What the demo shows:

Discovery via /.well-known/ucp - how platforms find merchant capabilities Checkout Sessions API - create, update, and complete purchases Toggle "Debug Mode" to see the actual API calls in real-time

What's implemented vs mocked:

- Discovery endpoint with capabilities and payment handlers - Full checkout flow with line items, buyer info, payment selection - Payment processing uses test tokens (no real charges) - In-memory storage (resets on each session)

Links:

Demo: https://ucp-demo.web.app

UCP Spec: https://ucp.dev

Source: https://github.com/hemanth/ucp-demo

Would love feedback on the developer experience. Is the protocol discoverable enough? What's missing?

Comments URL: https://news.ycombinator.com/item?id=46581745

Points: 4

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I built agentlearn after noticing that most AI agent tutorials focus on frameworks (LangChain, CrewAI) rather than fundamentals. The result is developers who can copy-paste code but struggle when things break.

This is a free, interactive course covering:

The Agent Loop - Why loops matter (think vs. act vs. observe) Context Engineering - The real skill behind "prompt engineering" Tools & Function Calling - Bridging text generation to real actions Memory Systems - Short-term vs. long-term, vector DBs Protocols - MCP, A2A, and the emerging standards Production Patterns - Error handling, cost optimization, observability Each concept has runnable code sandboxes you can step through. The design is intentionally "hand-drawn" to feel less intimidating than typical technical docs.

Tech stack: Vanilla JS + Vite, no framework.

Why no framework? Because understanding fundamentals means understanding what frameworks abstract away. Once you get the core loop, you can use any framework—or build your own.

Feedback welcome! Especially interested in what topics are missing.

Comments URL: https://news.ycombinator.com/item?id=46522985

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