Glossary

The words you meet building on AxForge, in plain language and explained the way AxForge uses them. If a term means something specific here — like region pinning or zero retention — this is where it is pinned down, with links to the page that goes deeper.

API basics

The request you send, the key that authorises it, and the units you are billed in. Everything speaks the OpenAI shape — see the Quickstart.

API key: A secret token (prefixed orx_live_) that authenticates your requests. Send it as Authorization: Bearer <key> (or x-api-key). A key belongs to one tenant, is pinned to one EU region, and can be revoked at any time. Treat it like a password — never ship it in client-side code. See also: Quickstart · Errors & limits
Base URL: The address your SDK or tool points at instead of OpenAI: https://api.axforge.ai/v1. Because the API is OpenAI-compatible, pointing an existing client at this base URL — plus your key and a model name — is usually the entire integration. See also: Use with your stack
Endpoint: A path under the base URL that does one job: /chat/completions, /embeddings, /images/generations, /audio/speech, and so on. Every endpoint takes and returns the same JSON shapes the OpenAI endpoints do. See also: Chat completions
Model: The open-weight system that produces the answer. You choose one per request with the model field. Models can be named by a stable role (chat, agentic for tool-heavy work, vision, embeddings) or by their exact version (qwen3.8-27b-nvfp4) — both resolve to the same served model. Call GET /v1/models for the live list. See also: Models & pricing · Model catalogue
Token: The unit a model reads and writes in — roughly ¾ of a word of English. Prompts are counted as input tokens and answers as output tokens; pricing and your usage balance are both in tokens. Every response carries a usage object with the exact counts. See also: Pricing · Usage
Context window: The maximum number of tokens a model can consider at once — prompt plus answer. Exceed it and the oldest content is dropped or the request is rejected. Each model lists its window on the models page. See also: Models & pricing
Streaming (SSE): Set stream: true and the answer arrives token by token as server-sent events, ending with data: [DONE] — so a UI can show text as it is generated. AxForge streams include a final usage chunk so streamed answers are metered too. See also: Chat completions
System / user / assistant message: The messages array carries the conversation. A system message sets behaviour and rules, user messages are the human's turns, and assistant messages are the model's prior replies. Send the whole history each turn — the API is stateless. See also: Chat completions
Temperature: A 0–2 dial on randomness. Low (0–0.3) is focused and repeatable — good for extraction and code; high (0.8+) is more varied — good for brainstorming. It does not change what the model knows, only how it samples. See also: Chat completions
Usage: The token counts returned with every completion (prompt_tokens, completion_tokens, total_tokens). AxForge records these against your tenant's balance; prompts and answers themselves are never stored. See also: Metering · Regions & data
Rate limit: The ceiling on requests per minute for a key. Cross it and you get an HTTP 429 with a Retry-After header — back off and retry. Limits protect shared capacity and can be raised for production traffic. See also: Errors & limits

Capabilities

What the one key unlocks — text, vectors, images, and audio — each on an OpenAI-shaped endpoint.

Chat completion: The core text endpoint: send a list of messages, get a reply. Handles instructions, Q&A, extraction, code, and multi-turn conversation, with optional tools and image inputs. See also: Chat completions
Tool calling (function calling): You describe functions the model may call; when useful it returns a structured tool_calls request instead of prose, your code runs the function and feeds the result back. This is the mechanism agents and MCP tools are built on. See also: Chat completions · MCP
Vision: Passing an image alongside text in a chat request so the model can read, describe, or reason about it — screenshots, documents, diagrams, photos. See also: Chat completions
Embedding: A vector of numbers that captures the meaning of a piece of text, so that similar meanings sit close together. The building block of search, recommendation, and retrieval-augmented generation. AxForge returns 1024-dim vectors. See also: Embeddings · Semantic search
Vector / semantic search: Finding results by meaning rather than exact keywords: embed your documents and the query, then compare vectors. The retrieval half of RAG (retrieval- augmented generation), where you fetch relevant text and pass it to the model as context. See also: Embeddings
Reranking: A second pass that scores a shortlist of candidate documents against a query and reorders them by true relevance — sharper than vector similarity alone, and a common step between search and the model. See also: Embeddings
Image generation: Creating a picture from a text prompt via /v1/images/generations. The response carries the image as base64 PNG in data[].b64_json. See also: Image generation & editing
Image editing: Changing an existing image from an instruction — pass the source image plus a prompt to /v1/images/edits and get an edited PNG back. See also: Image generation & editing
Transcription (speech to text): Turning an uploaded audio file into text via /v1/audio/transcriptions — a multipart file upload, OpenAI Whisper shape. See also: Speech & music
Speech synthesis (text to speech): Turning text into spoken audio via /v1/audio/speech. See also: Speech & music
Music generation: Composing an audio track from a prompt (and optional lyrics) via /v1/audio/music. See also: Speech & music

Compatibility & tooling

Why your existing tools work, and the few places the ecosystem has more than one API shape. The practical guides live in Use with your stack.

OpenAI-compatible: AxForge implements the same HTTP endpoints, request bodies, and response shapes as OpenAI's API. Any client that can target a custom base URL — SDK, CLI, gateway, or app — works against AxForge by changing three things: the base URL, the key, and the model name. See also: OpenAI alternative in Europe · Use with your stack
Chat Completions API: The widely-supported /v1/chat/completions surface — messages in, a choice out. The one nearly every tool speaks; AxForge serves it (alongside the Responses and Messages surfaces). See also: Chat completions
Responses API: A newer OpenAI surface (/v1/responses) that some tools — notably OpenAI's Codex CLI and the default path of a few SDKs — now prefer. AxForge serves it natively at api.axforge.ai/v1/responses, alongside Chat Completions, so Responses-only clients point straight at us. See also: Codex & Claude Code
Messages API (Anthropic): Anthropic's /v1/messages surface, which Claude Code speaks. It is a different shape from OpenAI's, and AxForge serves it natively at api.axforge.ai/v1/messages — so a Claude-native tool points straight at us, no shim required. See also: Codex & Claude Code
SDK: A library that wraps the HTTP API for a language — the official OpenAI SDKs (Python, Node) and the Vercel AI SDK are the common ones. All of them take a base-URL option, which is where you point them at AxForge. See also: OpenAI SDK · Vercel AI SDK
Gateway: A service that sits in front of one or more model providers behind a single OpenAI-compatible endpoint — for routing, fallback, budgets, or key management. AxForge is a provider you can put behind a gateway; a gateway is not a substitute for a provider. See also: LiteLLM
MCP (Model Context Protocol): An open protocol that lets an AI app (the host, e.g. an IDE agent) connect to external tools and data through MCP servers. It is a client-side protocol, separate from how inference is served: MCP tools are driven by the model's tool calling in ordinary chat requests, so AxForge powers MCP-based agents without needing to "speak MCP" itself. See also: Use with your stack
LiteLLM: An open-source proxy that fronts an OpenAI-compatible upstream like AxForge and re-exposes it on the Chat Completions, Anthropic Messages, and Responses surfaces at once. AxForge serves all three natively, so LiteLLM is optional — reach for it when you want a gateway (budgets, fan-out, many providers). See also: LiteLLM

Regions & metering

Where inference runs, how you keep it there, and what is kept afterwards.

Region: A physical location where inference runs — e.g. eu-se-1 (Sweden) or eu-es-1 (Málaga, Spain). Responses echo the region back so you can verify where a request was served. See also: Regions & data · Data residency
Data residency: The guarantee that your requests are processed and any metadata is kept within a chosen jurisdiction — for AxForge, the EU. The basis for GDPR and sovereignty commitments. See also: Data residency · GDPR
EU-hosted / sovereign AI: Inference on infrastructure located and operated in the EU, on open-weight models, with no dependency on a non-EU cloud in the request path — so data does not leave the jurisdiction to be processed. See also: Sovereign AI cloud · EU AI API
Region pinning: Binding a key or request to one region (via the x-axforge-region header or the key's default) so inference only ever runs there. The response confirms the region that served it. See also: Regions & data
Zero retention: Prompts and completions are processed and discarded — never written to disk, logged, retained, or used for training. Only request metadata (token counts, timestamps, status) is kept, and only for billing. See also: Retention · Privacy
In-memory processing: Handling a request entirely in RAM for the moment it is served, with nothing about its content persisted afterwards — how zero retention is achieved in practice. See also: Retention
Tenant: Your isolated account boundary. Keys, usage, and any stored configuration belong to a tenant, and one tenant can never see another's data. Signing up creates your own tenant. See also: Regions & data
Workspace: A named project inside a tenant — a place to group an agent or deployment, its knowledge, and its settings in the console. Optional for raw API use. See also: Console
Deployment: A configured, addressable instance of an agent or endpoint you have published — with its own public slug and access controls — as opposed to a raw model call. See also: Console
Usage record / metering: The billing event AxForge writes after a token-priced call, recording the model and token counts against your tenant's balance. It captures counts and metadata only — never the prompt or the answer. See also: Usage · Pricing

Trust & compliance

The vocabulary that shows up in procurement, DPAs, and audits — defined as they apply to AxForge. This is orientation, not legal advice.

GDPR: The EU General Data Protection Regulation, governing how personal data is processed. EU-hosted, zero-retention inference is what makes AxForge straightforward to use under it. See also: GDPR & AI · Trust centre
DPA (Data Processing Agreement): The contract that sets out how a processor handles personal data on a controller's behalf. AxForge offers one for customers who send personal data through the API. See also: DPA
Sub-processor: A third party a processor uses to help deliver the service. AxForge's EU-hosted design keeps this list short and in-jurisdiction; it is published for transparency. See also: Trust centre · DPA
Data controller / processor: Under GDPR, the controller decides why and how personal data is processed (you), and the processor acts on the controller's instructions (AxForge, for the data you send). See also: DPA
EU AI Act: EU regulation classifying AI systems by risk and setting obligations accordingly. Your obligations depend on what you build; AxForge provides the transparency inputs (model provenance, region, retention) you need to document it. See also: EU AI API · Model transparency
Model transparency: Publishing which open-weight models serve each capability, and where, so you can record provenance for your own compliance. AxForge's models are open-weight and named per capability. See also: Model transparency · Models & pricing
No-training commitment: AxForge does not train on customer prompts or completions. Combined with zero retention, your content is used to serve your request and nothing else. See also: Retention · Privacy
PII (personal data): Information that identifies a person. You remain the controller for any PII you send; AxForge's zero-retention processing means it is not persisted, but handling it responsibly — minimising and having a lawful basis — is your call. See also: Rules & responsibilities · GDPR