Tutorial
Build a Streaming AI Chat Backend with FastAPI and Server-Sent Events (Step-by-Step)
Ship token-by-token streaming chat in Python: FastAPI, SSE, the Qubax API, plus the production checklist for cost control and reliability.
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The latest AI model news, tutorials, and developer guides for the crypto-native AI platform.
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Tutorial
57 articles- Tutorial
How to Build a Two-Tier Cost Router for AI APIs (Python Tutorial, ~60 Lines)
Cut your AI API bill 60-80% with a two-tier router: cheap models for easy requests, frontier escalation for hard ones. Full Python code included.
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Build an AI Code Reviewer With GitHub Actions for Under $0.01 Per PR
A complete, ~100-line setup: GitHub Action fetches the PR diff, a budget LLM reviews it, findings post as PR comments — about a dollar per thousand reviews.
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Build a Multimodal Document Q&A API in Python: Vision + Text in 20 Minutes
A hands-on tutorial: build a production-ready document Q&A API that accepts PDFs and images, extracts text with a vision-language model, caches answers, and tracks costs — using an OpenAI-compatible API in Python.
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Build a Production-Grade AI Summarizer with Structured Output, Map-Reduce & Model Routing
Most LLM APIs don't return JSON. They return prose — and if your app needs structured data, you're left regexing model output and praying. There's a better way: build a bulletproof structured-output extractor that combines JSON mode, schema
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Build a Bulletproof Structured-Output Extractor with Python, Pydantic & Any LLM API
Most LLM APIs don't return JSON. They return prose — and if your app needs structured data, you're left regexing model output and praying. There's a better way: build a bulletproof structured-output extractor that combines JSON mode, schema
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How to Build a Self-Healing AI Pipeline: Automatic Retries, Fallbacks, and Cost Caps in Python
Production AI apps fail in predictable ways: rate limits, context overflow, provider outages, budget overruns. Build a self-healing pipeline that handles all four automatically — with complete, runnable Python code.
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Build a Confidence-Based LLM Router in TypeScript: Cut Your AI Bill 80-95%
A production-grade cascade router: cheap model first, structured grading, automatic escalation to a flagship only when needed. Full working code in ~30 minutes — the highest-ROI cost optimization in applied AI.
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Build a Budget-Capped Streaming LLM Client in Python (Any Model, One API)
A production-grade Python tutorial: streaming responses, exact token accounting, hard daily budget caps, loop detection, and budget-aware retries — ~150 lines, works with any OpenAI-compatible API.
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How to Build a Cost-Aware LLM Router in Python: Route Each Request to the Right Model Automatically
Stop paying flagship prices for requests a cheap model could handle. Build a smart routing layer in Python that classifies request difficulty, sends easy prompts to budget models, escalates hard ones to frontier models — with fallbacks and budget caps.
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How to Build a Semantic Cache for LLM APIs in Python (Cut Your Token Bill by 40-60%)
Store answers by meaning, serve reworded repeat questions for free. A complete Python semantic cache with threshold tuning, TTL, and production tips.
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Build a Multi-Model Fallback Router in Python: Never Let an AI Outage Hit Your Users
A practical, ~100-line Python tutorial: retries with exponential backoff, automatic model fallback chains, cost tracking, and graceful degradation for your AI features — with copy-paste code.
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Build n8n AI Agents on Any Model — Qubax + n8n in 10 Minutes
Connect n8n's AI Agent nodes to 399 models through one OpenAI-compatible endpoint. Swap models per-workflow without swapping providers.
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How to Use Claude, GPT-5.6 & 399 Other Models in Cursor (Without OpenRouter Prices)
Point Cursor at Qubax's OpenAI-compatible endpoint and get every frontier model at up to 98% below OpenRouter. 5-minute setup, no extension needed.
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Build a Documentation-Grounded AI Coding Assistant in Python (That Doesn’t Hallucinate APIs)
A hands-on Python tutorial: build a coding assistant grounded in your real documentation, with header-aware chunking, a NumPy vector index, source citations, and tool-calling for agentic use.
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How to Build a Cost-Optimizing AI Inference Client in Python: Caching, Cascading, and Budget Guards
A production-ready Python pattern combining prompt caching, model cascading, and budget circuit breakers — cut agent LLM spend by 60-80% with real Qubax price data.
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How to Build a Voice AI Agent That Responds in Under 200ms (Python Tutorial)
Voice agents live or die on latency. Learn to build a production-ready streaming pipeline with token streaming, sentence-level TTS overlap, hard timeouts, and automatic model fallbacks in Python.
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How to Build Tool Calling (Function Calling) Into Any AI App: A Practical Guide
A complete, provider-agnostic guide to AI tool calling: define tools, execute calls in your code, feed results back — with a production checklist and Python examples.
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How to Build an AI Text Summarizer API in Python (With Length Control and Cost Tracking)
Build a production-ready AI summarization API with FastAPI: prompt design, word-limit enforcement, retries, and real-time per-request cost tracking — plus three optimizations that cut bills by 80%.
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How to Evaluate LLMs Before Production: A Practical Guide (With Code)
Stop shipping LLM features on vibes. Build a golden dataset, add deterministic checks and an LLM judge, and gate releases with a repeatable eval pipeline — full Python code included.
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How to Build a Streaming AI Chat API with Token Fallbacks in Python (2026 Guide)
Streaming responses are table stakes for chat apps — but real production systems also need fallbacks when a model is rate-limited or down. Build both in Python with FastAPI, step by step.
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Build a Hybrid Search RAG Chatbot in Python: BM25 + Vector Search (Complete Guide)
Vector-only RAG misses exact terms; keyword-only misses paraphrases. This step-by-step Python guide shows how to combine BM25 and embeddings with Reciprocal Rank Fusion for dramatically better retrieval — in under 150 lines of code.
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How to Build an AI Image Analysis API in Python: Vision Models, JSON Output, and Cost Control
A step-by-step Python tutorial for building a production-ready image analysis endpoint with vision-language models: base64 encoding, structured JSON output, retries, and the cost pitfalls nobody warns you about.
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Build a RAG Chatbot with an AI API in Python (Complete Tutorial, ~100 Lines)
A complete, working RAG chatbot in Python: chunking, embeddings, vector retrieval, and streaming answers — in about 100 lines of code using Qubax's OpenAI-compatible API.
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How to Build a Cost-Saving AI Model Router in Node.js (Cut Your API Bill 80%+)
Build a Node.js AI model router that classifies request difficulty, sends each request to the cheapest capable model, and falls back automatically — cutting API spend 60-90%.
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How to Use Function Calling With AI APIs: A Complete Python Tutorial
Learn how AI function calling (tool use) works and build a working agent in Python — schemas, the tool loop, streaming, common pitfalls, and model picks.
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How to Build an AI-Powered Sentiment Analysis API with Python in 2026
A step-by-step guide to building a production-ready sentiment analysis API using Python, FastAPI, and the Qubax AI gateway.
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How to Stream AI API Responses with SSE in Python (With Live Cost Tracking)
Stop waiting for full completions. Learn to consume Server-Sent Events from any OpenAI-compatible API — with a complete Python streaming client, delta parsing, usage accounting, and per-request cost math.
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How to Extract Structured Data From Images With Vision AI APIs: Complete Tutorial
Forget brittle OCR pipelines. This tutorial shows you how to turn receipts, invoices, and forms into clean JSON using vision-capable AI models via a single OpenAI-compatible API — with validation, retries, and cost control.
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How to Build a Semantic Search Engine with Embeddings: A Complete Developer Tutorial
Build production semantic search in ~150 lines of Python: chunking, embeddings via an OpenAI-compatible API, pgvector, hybrid ranking with RRF, and a FastAPI endpoint. Full code inside.
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How to Build a Production Retry & Fallback Layer for AI APIs in Python (With Code)
429s, 5xxs, and dead providers are inevitable. Build exponential backoff with jitter, circuit breakers, multi-model fallback chains, and checkpointed batch jobs — complete Python code for any OpenAI-compatible API.
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How to Build an LLM-as-Judge Evaluation Pipeline in Python (Tutorial)
Stop guessing whether prompt changes help. Build a complete LLM-as-judge eval pipeline in Python: golden dataset, structured rubric, scoring, and a CI gate that blocks regressions.
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How to Build Your Own AI Model Router in Python: A Complete Developer Tutorial
Build a production-ready AI model router in Python that automatically routes requests to the best model, cuts costs by 50%+, and handles failover. Complete code included.
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How to Cut AI API Costs by 50%+ with Batch Processing: A Complete Developer Tutorial
If you're running AI features in production, API costs can quickly become your biggest line item. One of the most effective — and most underused — ways to sl...
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How to Cut Your AI API Costs by 80% With Prompt Caching: A Developer's Guide
Prompt caching can cut your AI API bill by 80% with zero quality loss. Step-by-step developer guide with Python code, cost math, and cache optimization techniques.
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How to Build a Multi-Model Cost Dashboard with AI APIs: Complete Tutorial
Learn how to build a real-time cost dashboard that tracks AI spending across multiple providers, compares token usage between models, and alerts you when costs spike. Full code examples in Python and TypeScript.
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How to Build Multi-Model AI Failover with Circuit Breakers (TypeScript Tutorial)
Build a production-grade fallback client with per-provider circuit breakers, automatic model failover, and health tracking. When one AI provider dies, your users never notice. Full TypeScript code.
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How to Build an AI Function Calling Agent with Structured Outputs (2026 Tutorial)
A complete, production-ready tutorial for building an AI agent that uses function calling with structured JSON outputs. Includes code for tool definitions, parallel function execution, error handling, and a working example using the OpenAI-compatible Qubax API.
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How to Build a Token Metering and Budget Guard for AI APIs (Python Tutorial)
A production-grade Python layer that counts input, output, and reasoning tokens per feature, enforces per-user budgets, and turns token counts into dollars - with alerting and model routing built in.
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How to Build an AI Model Router That Cuts API Costs by 80%+ (With Code)
Most AI requests never need a frontier model. Learn to build a cost-optimizing model router in ~100 lines that routes each task to the cheapest capable model — with automatic escalation.
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How to Build an AI-Powered Code Review Bot with Function Calling
Learn how to build a production-ready AI code review bot using function calling. This step-by-step tutorial covers tool definitions, the tool-call loop, GitHub Actions integration, and cost optimization.
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How to Build a Streaming AI Chatbot with Server-Sent Events: Complete Tutorial
Build a production-ready streaming chatbot using Server-Sent Events (SSE) and the OpenAI-compatible Qubax API. Full code in Node.js and Python with error handling, reconnection, and rate limiting.
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How to Build AI Agents with Safety Guardrails: A Developer Tutorial
Learn to build production-ready AI agents with five layers of safety: tool allowlisting, prompt constraints, output validation, audit logging, and human-in-the-loop approval. Full code tutorial.
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How to Build a Streaming AI Chat With Server-Sent Events: Complete Tutorial
Learn how to build a real-time streaming AI chat application using Server-Sent Events (SSE) and the OpenAI-compatible API. Full code examples in Node.js and Python, with production tips for error handling, reconnection, and cost optimization.
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How to Build an AI Cybersecurity Threat Monitoring Agent: Complete Tutorial
A complete developer tutorial for building a real-time AI cybersecurity threat monitoring agent that investigates security events, correlates threat intelligence, assesses severity, and escalates critical incidents — with full TypeScript code.
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How to Build an AI Web Automation Agent with V8 Isolates: Complete Tutorial
Inspired by Cloudflare's Kitesurf, this tutorial shows you how to build a production-ready AI web automation agent using Playwright, worker threads, and LLM reasoning for intelligent browsing decisions.
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How to Build an AI-Powered E-Commerce Recommendation System with Streaming Responses
A complete developer tutorial for building an AI-powered product recommendation system with real-time streaming responses. Includes Node.js code, frontend, and deployment tips.
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How to Build an AI Agent with Persistent Background Agents
Learn how to build an AI agent system with persistent background agents, crash-safe event logs, and multi-model support. Full tutorial with code examples using the Qubax AI API.
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How to Add AI-Powered Content Moderation to Your App: Complete Tutorial
Learn how to build a production-ready AI content moderation system with Python and JavaScript. Includes pre-filtering, caching, batch processing, and cost optimization tips.
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How to Add Safety Guardrails to AI Agents — A Complete Developer Tutorial
AI agents can go rogue without warning. This complete tutorial shows you how to build a guardrail system that monitors, filters, and controls AI agent actions in real time — with full Python code examples.
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How to Detect AI-Generated Content in Your App: Developer Tutorial
Build a practical AI-generated content detection pipeline with Node.js. Learn text analysis, C2PA image provenance checking, and how to display authenticity badges in your app.
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How to Build a Multi-Agent AI System with API Streaming: Complete Tutorial
Learn to build a multi-agent AI system with real-time streaming, task delegation, and parallel execution — the same pattern OpenAI's Astra uses to solve complex problems. Complete Python tutorial with code examples.
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How to Build an AI Coding Agent with Streaming Responses: Complete Tutorial
Build a production-ready AI coding agent from scratch with streaming responses, multi-turn memory, and tool calling. Works with any model -- GPT-5.6, Claude, DeepSeek, and more. Full Python and JavaScript code included.
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How to Build an AI Agent with Function Calling: Complete Developer Guide
Function calling is the secret ingredient that turns a chatbot into an autonomous agent. Learn how to implement tool use, multi-step reasoning, and error handling in this hands-on guide with real code.
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How to Use Goose: Free Open-Source AI Coding Agent Guide
Goose by Block is a free, open-source AI coding agent that rivals Claude Code at $0/month. Here's a complete hands-on tutorial for installing, configuring, and using Goose with any LLM API via Qubax AI.
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How to Build an AI Chatbot with Streaming Responses: Complete Guide
Learn to build a production-ready AI chatbot with real-time streaming responses. Full code examples in Python (FastAPI) and JavaScript with SSE, error handling, and cost optimization.
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OpenAI API Python Tutorial — Use GPT-5 at 99% Off with Qubax
The OpenAI Python SDK works with any OpenAI-compatible API. This tutorial shows you how to use GPT-5.6 Terra through Qubax — at **99% off** OpenRouter's price —
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Try every model you read about.
400+ models through one OpenAI-compatible API — up to 99% below OpenRouter. Pay with crypto.