uncloseai: Machine Learning Inference Client Reference Manual

Educational reference guide to https://uncloseai.com/

The Most Comprehensive Machine Learning Integration Guide Ever Written

454 pages | 57 implementations & counting

What You Get

Not another machine learning tutorial that shows you one way to do things in Python. This is a complete reference implementation covering 57 different ways to integrate with machine learning APIs across every major programming language and framework.

Full Coverage:

• 6 C/C++ implementations (curl, libsoup, nghttp2, Boost.Beast, cpp-httplib, libcurl)
• 4 Python approaches (requests, aiohttp, httpx-async, OpenAI SDK)
• 5 JavaScript/TypeScript variants (Node.js, Bun, Deno, TypeScript, vanilla browser)
• Official SDK integrations for C#, Elixir, Go, Java, JavaScript, Ruby
• Raw HTTP implementations when SDKs aren't available
• Systems languages (Rust, Zig, Odin, Nim, Crystal)
• JVM ecosystem (Java, Kotlin, Scala, Clojure, Groovy)
• .NET family (C#, F#, VB.NET)
• Functional languages (Haskell, OCaml, Erlang, Elixir, Common Lisp, Scheme)
• Scripting languages (Bash, AWK, Perl, PHP, Tcl, Lua, PowerShell, R)
• Modern ML-focused (Julia, Mojo, Dart)

What Makes This Different

Every implementation includes:

• Complete, tested source code
• Full Docker build configuration
• Streaming response handling (Server-Sent Events)
• Text-to-speech generation
• Model discovery from endpoints
• Production-ready error handling

You get the code & reference material which was proven to work. No pseudocode. Not simplified examples. The real implementations.

Who This Is For

• Software engineers integrating machine learning into existing systems written in any language
• DevOps teams deploying ML inference across heterogeneous infrastructure
• Technical leads evaluating which language/framework best fits their stack
• Computer science students learning practical API integration patterns
• Open source contributors who need reference implementations to build from

The License Promise

Code examples are public domain. Use them freely in commercial projects, modify them, redistribute them. Just attribute back to uncloseai.com where it makes sense.

Each library used in the examples has its own upstream license - review those to ensure they fit your software stack.

What's Inside (Technical Details)

• Server-Sent Events (SSE) streaming implementation in every language
• Environment-based configuration with automatic model discovery
• Multi-model support (Hermes, Qwen, and any OpenAI-compatible endpoint)
• Docker containerization for every single example
• Version pinning with check dates so you know what's current
• Common issues section per language with real solutions

Current Stats

• 454 pages of technical content
• 57 language implementations fully tested
• All base images consolidated to latest stable versions (as of October 2025)
• Zero marketing fluff - this is a technical reference manual

Support Access

Purchasers get:

• Free API access to uncloseai.com inference endpoints
• Community Discord channel
• All future updates to this edition

This is the reference manual we wish existed when starting to integrate machine learning APIs into production systems. Now it does.

Buy once. Get Free Updates Until We Die. Use in any project. Forever.