# Khwan **Khwan is a hosted cognition layer for AI agents.** It gives any model long-term **memory**, a **constitutional identity**, **coherence** checks, and continuous **learning** — without you running that infrastructure yourself. It is **model-agnostic (BYOM)**. Khwan never holds your provider key and never replaces your model. You keep calling the LLM you already use; Khwan wraps the thinking *around* it. ## The mental model Khwan prepares the brief and takes the notes. Your model speaks. - **Before** a turn, Khwan assembles the brief — retrieved memory, the constitution, learned lessons, and a coherence signal — into a ready-to-send system prompt. - **You** call your own model with that brief. Khwan never sees your provider key and never generates the answer — you always call your own model. - **After**, Khwan records the exchange, persists new memory, and learns — so the next brief is sharper. ```python from khwan import Khwan kw = Khwan(api_key="kwk_live_xxx", user_id="alice") turn = kw.prepare("remember I prefer short answers in Thai") # Khwan builds context, no LLM answer = my_own_llm(turn.messages) # your model + key kw.record(turn, answer) # Khwan persists + learns ``` That loop — `prepare` → *your model* → `record` — is the whole product. Khwan never generates text: there is no hosted model path, so you always call your own model. ## Isolated cores One account can hold many **cores** — fully separate brains, each with its own memory, identity, and learning. Point a client at one with `core`: ```python test = Khwan(api_key="kwk_live_xxx", user_id="alice", core="test") client1 = Khwan(api_key="kwk_live_xxx", user_id="alice", core="client1") ``` `test` and `client1` never share memory. Omit `core` for the account's default brain. Quota stays pooled at the account level. Create and manage cores in the dashboard or via the [API](/api-reference). ## What's in a turn's context `turn.messages` is a standard `[{role, content}]` array. Khwan's value is baked into the **system** message: - **Constitution** — the agent's identity and hard rules. - **Retrieved memory** — relevant facts and past exchanges from this core. - **Learned lessons** — patterns distilled from prior turns. - **Coherence** — a signal (and optional gate) on whether the turn is consistent with identity and memory. ## Why BYOM - **No lock-in.** Swap Claude for GPT for a local Ollama model without touching your memory or identity layer. - **Your key, your bill, your data path.** The generation call stays between you and your provider. Khwan never touches your model or your key — it only ever sees the input, the messages it built, and the answer you record. ## Where to go next - **[Quickstart](/quickstart)** — install the client, get an API key, run the loop. - **[Bring Your Own Model](/byom)** — `prepare`/`record` with OpenAI, Anthropic, or a local Ollama model. - **[API Reference](/api-reference)** — the raw REST endpoints and auth headers. - **[Python SDK](/sdk-python)** / **[TypeScript SDK](/sdk-ts)** — client method reference.