One compatible API for many AI models
A practical guide to using one compatible API for model access, scoped keys, usage visibility, and provider choice.
Field notes
Practical notes on AI model access, pricing visibility, API key governance, usage history, and running one compatible API with less operational drag.
A practical guide to using one compatible API for model access, scoped keys, usage visibility, and provider choice.
Integrate image generation through OpenAI-compatible endpoints, handle edits, bound n/size safely, and persist temporary media correctly with gpt-image-2.
Deploy a self-hosted LLM API gateway with Docker Compose, multi-provider channels, scoped keys, usage logs, and OpenAI-compatible endpoints.
A field guide to the OpenAI Responses API and Chat Completions: request shape, output items, statefulness, reasoning, tools, and when each endpoint is the right choice.
Three providers cache prompt prefixes to cut input cost and latency, but the control surface differs: automatic vs explicit breakpoints vs implicit. A practical comparison.
Call Claude from the OpenAI SDK for evaluation, then use a gateway that adapts OpenAI ingress to native Claude Messages for production.
Retry LLM API calls without duplicate charges or double-sent side effects: which errors are retryable, backoff with jitter, idempotency keys, and gateway-level dedup.
How to read LLM rate-limit headers, absorb 429s with backoff and jitter, and apply client-side backpressure with queues and concurrency limits so load sheds gracefully.
Compare an LLM reverse proxy with an AI gateway: routing, auth, billing, failover, observability, and when each architecture fits.
A step-by-step guide to porting OpenAI Chat Completions code to the Responses API: input items, output parsing, state, tools, streaming, and a rollback plan.
Design multi-tenant LLM gateways with team scopes, project keys, isolated quotas, usage logs, and media ownership without leaking credentials.
Call Gemini from the OpenAI Python or TypeScript SDK via Google's OpenAI-compatible base URL or a multi-provider gateway, with current model aliases.
Compare image generation APIs in 2026 with dated capability tables for OpenAI GPT Image, Gemini, and gateway ops—without fabricated quality rankings.
Map OpenAI, Claude, and Gemini tool fields, validate arguments with JSON Schema, and keep one tools loop across providers through a gateway.
Why a single fixed timeout breaks LLM calls, and how to set connect, first-token, and idle deadlines, stream to stay alive, and cancel cleanly with AbortController.
OpenAI reasoning_effort, Anthropic thinking, and Gemini thinkingBudget all control hidden reasoning tokens billed as output. How each knob works and how they differ.
How LLM token streaming works over SSE: the text/event-stream format, parsing data lines and the [DONE] sentinel, why fetch beats EventSource, and cancelling with AbortController.
Stop parsing prose for JSON. How OpenAI strict json_schema, Gemini responseSchema, and Anthropic tool use force models to return data that matches a schema you define.
Compare video generation APIs in 2026 with dated tables for job shape, edits/extensions/characters, persistence, and ops—without fabricated rankings.
Integrate video generation with create/poll/content flows, edits and extensions awareness, webhooks, duration bounds, and authorized media delivery.
The context window has two costs: overflow errors and per-turn billing. How to count tokens, trim and summarize history, cache stable prefixes, and use server-side compaction.
A practical guide to LLM routing strategy latency cost, covering latency first, cost first, quality first, operational tradeoffs, and how teams can review the result.
A practical guide to RBAC LLM API keys, covering groups, roles, rate limits, operational tradeoffs, and how teams can review the result.
A practical guide to token pricing vs request pricing LLM, covering token billing, request billing, group overrides, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API key management enterprise, covering scoped keys, rotation, audit trails, operational tradeoffs, and how teams can review the result.
A practical guide to agent tool routing MCP gateway, covering MCP tools, provider choice, gateway policy, operational tradeoffs, and how teams can review the result.
A practical guide to LLM channel health monitoring, covering health score, cooldown, failure threshold, operational tradeoffs, and how teams can review the result.
A practical guide to shadow AI spend, covering shared keys, unowned apps, hidden retries, operational tradeoffs, and how teams can review the result.
A practical guide to how to choose LLM model, covering task type, context length, latency, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API failover, covering early stream errors, configured retry status, transient body messages, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API monitoring dashboard, covering latency, error rate, token usage, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API budget forecasting, covering request volume, token ratio, model mix, operational tradeoffs, and how teams can review the result.
A practical guide to MCP server LLM provider routing, covering tool routing, OAuth, audit logs, operational tradeoffs, and how teams can review the result.
A practical guide to LLM usage logs cost tracking, covering billing source, quota movement, retry chain, operational tradeoffs, and how teams can review the result.
A practical guide to LLM usage log retention, covering S3 backup, retention windows, local cleanup, operational tradeoffs, and how teams can review the result.
A practical guide to reduce LLM API costs, covering model mix, prompt size, cache hit rate, operational tradeoffs, and how teams can review the result.
A practical guide to multi provider LLM gateway, covering priority, weights, fallback, operational tradeoffs, and how teams can review the result.
A practical guide to running an OpenAI compatible API gateway that connects existing clients to Claude, Gemini, DeepSeek, and other models without rewriting integrations.
A practical guide to LLM cost attribution, covering team ownership, product tags, environment keys, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API key leak prevention, covering environment variables, scoped keys, rotation, operational tradeoffs, and how teams can review the result.
A practical guide to LLM API pricing comparison 2026, covering pricing units, context windows, cache discounts, operational tradeoffs, and how teams can review the result.
How a public model catalog, group-aware pricing, and request history help teams understand AI API cost before and after requests run.
A concise operating model for scoped API keys, model groups, rotation, usage review, and access reviews in an AI model platform.