feat: custom OpenAI-compatible endpoint as a first-class provider (vision + context from /models)

This commit is contained in:
Daniel Buckner
2026-10-27 15:48:16 -07:00
parent 8f6fd7cd29
commit 07b6403d94
15 changed files with 965 additions and 41 deletions
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/**
* THE CUSTOM OPENAI-COMPATIBLE ENDPOINT (custom-endpoint wave): the deep
* module that turns the user's non-secret config (base URL + discovered model
* ids, core/settings.ts `customProvider`) into a real pi-ai provider registered
* in the process-wide `piModels()` collection — so its models fill the same
* strong/cheap/vision slots and background roles as any built-in.
*
* WHY A MODULE OWNS THIS (information hiding): the fact "a custom endpoint is
* an OpenAI-completions provider at a user URL with an optional key" would
* otherwise leak into the catalog, the keys seam, and the settings route. It
* lives here instead; those surfaces consult the pure `customProviderUsable`
* predicate (core) and call `syncCustomProvider`. The single-endpoint scope is
* special-purpose, but the builder is written general (`buildOpenAiCompatible
* Provider`) so a future multi-endpoint wave reuses it unchanged.
*
* LIFECYCLE (no restart, mirroring the keys seam): `syncCustomProvider` is
* idempotent and cheap — called at boot (stores.ts, the composition root) and
* after every connect (POST /api/custom-provider). It replaces
* or removes the provider in `piModels()` by id. The base URL is fixed at
* provider construction, so a base-URL change is a rebuild — which is exactly
* what a re-sync does.
*
* AUTH: pi-ai resolves a provider's key at request time. We read the reserved
* env var through the keys seam (`keyValue` — env-wins, file fallback, honors
* the fresh-user switch), and fall back to a placeholder when none is set so
* KEYLESS local servers (Ollama / LM Studio / llama.cpp) work. The placeholder
* is an internal detail of `resolve()` — no caller ever sees it.
*/
import { createProvider, type ApiKeyAuth, type Api, type Model, type Provider } from "@earendil-works/pi-ai";
import { openAICompletionsApi } from "@earendil-works/pi-ai/api/openai-completions.lazy";
import { piModels } from "../agent/models.ts";
import { CUSTOM_PROVIDER } from "../core/auth-keys.ts";
import {
CUSTOM_MODEL_DEFAULT_CONTEXT_WINDOW,
CUSTOM_MODEL_DEFAULT_MAX_TOKENS,
customProviderUsable,
normalizeBaseUrl,
type CustomModel,
type CustomProviderSettings,
} from "../core/settings.ts";
import { keyValue } from "./keys.ts";
/** Placeholder bearer sent to keyless endpoints. Many local OpenAI-compatible
* servers ignore the Authorization header entirely; the OpenAI client still
* requires *a* key, so we hand it this. Never shown to the user. */
const KEYLESS_PLACEHOLDER = "not-needed";
/** Narrow an unknown to a plain object (not null, not an array). */
const isRecord = (value: unknown): value is Record<string, unknown> =>
typeof value === "object" && value !== null && !Array.isArray(value);
/** The custom endpoint's auth: resolve the reserved key through the keys
* seam, else the keyless placeholder. `resolve` is the only method pi-ai
* needs to treat the provider as configured. */
const customEndpointAuth: ApiKeyAuth = {
name: `${CUSTOM_PROVIDER.label} API key`,
resolve: async () => {
const key = keyValue(CUSTOM_PROVIDER.envVar)?.trim();
// Keyless local servers ignore the header; the OpenAI client still
// needs *a* key, so hand it the placeholder.
return { auth: { apiKey: key || KEYLESS_PLACEHOLDER }, source: key ? CUSTOM_PROVIDER.envVar : "keyless" };
},
};
/** Map one discovered custom model to a pi-ai chat model entry. The endpoint's
* /models reports ids plus whatever metadata it exposes; `image` sets `input`
* so a Vision-capable model is selectable for the Vision slot (PDFs, images),
* and `context` / `maxTokens` carry the endpoint's reported token limits.
* Anything the endpoint omits falls back to the CUSTOM_MODEL_DEFAULT_* values
* (self-hosted = free, modest window). `baseUrl` is stamped per-model (pi reads
* it from the model, not the provider). */
function toPiModel(model: CustomModel, baseUrl: string): Model<Api> {
return {
id: model.id,
name: model.id,
api: "openai-completions",
provider: CUSTOM_PROVIDER.id,
baseUrl,
reasoning: false,
input: model.image ? ["text", "image"] : ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: model.context ?? CUSTOM_MODEL_DEFAULT_CONTEXT_WINDOW,
maxTokens: model.maxTokens ?? CUSTOM_MODEL_DEFAULT_MAX_TOKENS,
type: "chat",
};
}
/** Build a general OpenAI-compatible provider from parts (single-use today,
* general by design). `baseUrl` must already be normalized. */
export function buildOpenAiCompatibleProvider(input: {
baseUrl: string;
models: readonly CustomModel[];
}): Provider<Api> {
return createProvider<Api>({
id: CUSTOM_PROVIDER.id,
name: CUSTOM_PROVIDER.label,
baseUrl: input.baseUrl,
auth: { apiKey: customEndpointAuth },
models: input.models.map((m) => toPiModel(m, input.baseUrl)),
api: openAICompletionsApi(),
});
}
/**
* Re-sync the custom provider into `piModels()` from the resolved section
* (idempotent). Usable → (re)build and `setProvider` (replaces by id, so a
* base-URL/model change lands with no restart). Not usable → `deleteProvider`
* so it stops federating and any slot pinning one of its models falls back to
* the honest models_not_configured refusal. Never throws: a bad config simply
* leaves the provider absent.
*/
export function syncCustomProvider(cp: CustomProviderSettings | undefined): void {
const models = piModels();
if (!customProviderUsable(cp)) {
models.deleteProvider(CUSTOM_PROVIDER.id);
return;
}
// `customProviderUsable` narrowed cp to a defined section with a baseUrl.
models.setProvider(
buildOpenAiCompatibleProvider({ baseUrl: normalizeBaseUrl(cp.baseUrl), models: cp.models ?? [] }),
);
}
/** Outcome of a model-discovery probe. */
export type DiscoverResult = { ok: true; models: CustomModel[] } | { ok: false; error: string };
/**
* Probe an endpoint's `GET {baseUrl}/models` (the OpenAI list-models route)
* and return the model ids. The scheme is validated via normalizeBaseUrl
* (http/https only — the SSRF guard: this is a local app, but a user paste of
* `file://` or a stray string must never reach fetch). The key rides as a
* bearer when one is configured; keyless endpoints answer without it. A
* non-2xx or unparseable body is an honest error, never a silent empty list.
*/
export async function discoverModels(baseUrl: string, apiKey?: string): Promise<DiscoverResult> {
const base = normalizeBaseUrl(baseUrl);
if (!base) return { ok: false, error: "Base URL must be a valid http(s) URL" };
const key = apiKey?.trim() || keyValue(CUSTOM_PROVIDER.envVar)?.trim();
const controller = new AbortController();
const timer = setTimeout(() => controller.abort(), 15_000);
try {
const res = await fetch(`${base}/models`, {
headers: key ? { authorization: `Bearer ${key}` } : {},
signal: controller.signal,
});
if (!res.ok) return { ok: false, error: `Endpoint returned ${res.status} ${res.statusText}` };
const body = (await res.json().catch(() => null)) as unknown;
const list = extractModels(body);
if (list === null) return { ok: false, error: "Endpoint response was not a model list" };
return { ok: true, models: list };
} catch (err) {
const msg = err instanceof Error ? (err.name === "AbortError" ? "Endpoint timed out" : err.message) : "Request failed";
return { ok: false, error: msg };
} finally {
clearTimeout(timer);
}
}
/** The model rows in a list response, or null when the shape is unrecognized.
* Accepts the OpenAI `{data:[…]}`, the Ollama-style `{models:[…]}`, or a
* bare array. */
function modelRows(body: unknown): unknown[] | null {
if (Array.isArray(body)) return body;
if (isRecord(body)) {
if (Array.isArray(body.data)) return body.data;
if (Array.isArray(body.models)) return body.models;
}
return null;
}
/** Does a /models row advertise image input? Endpoints are inconsistent, so
* scan the common modality/capability fields (OpenRouter's
* `architecture.input_modalities`, plus `input_modalities` / `modalities` /
* `supported_modalities` / `capabilities`) for a value mentioning image or
* vision. Absent/unrecognized -> false (text-only); the Keys row exposes a
* manual toggle for endpoints that report nothing. */
function detectImage(row: Record<string, unknown>): boolean {
const architecture = isRecord(row.architecture) ? row.architecture : undefined;
const candidates = [
architecture?.input_modalities,
row.input_modalities,
row.modalities,
row.supported_modalities,
row.capabilities,
];
for (const c of candidates) {
if (Array.isArray(c) && c.some((v) => typeof v === "string" && /image|vision/i.test(v))) return true;
}
return false;
}
/** First positive integer among `keys` on a /models row, else undefined.
* Endpoints name the token limits inconsistently, so the caller passes an
* ordered list of candidate field names. */
function firstPositive(row: Record<string, unknown>, keys: readonly string[]): number | undefined {
for (const key of keys) {
const value = row[key];
if (typeof value === "number" && Number.isInteger(value) && value > 0) return value;
}
return undefined;
}
// Field names seen in the wild for each limit (first present wins).
const CONTEXT_KEYS = ["max_input_tokens", "context_length", "context_window", "max_context", "n_ctx", "max_seq_len", "max_position_embeddings"] as const;
const MAX_TOKEN_KEYS = ["max_output_tokens"] as const;
/** Pull models out of a list response (entries are `{id, ...}` objects or bare
* strings), each carrying its detected image capability and token limits.
* Returns null when the shape is unrecognized - the caller reports an honest
* error rather than a misleading empty "no models". */
function extractModels(body: unknown): CustomModel[] | null {
const rows = modelRows(body);
if (rows === null) return null;
const byId = new Map<string, CustomModel>();
for (const row of rows) {
if (typeof row === "string") {
if (row.trim()) byId.set(row, { id: row });
continue;
}
if (isRecord(row) && typeof row.id === "string" && row.id.trim()) {
const model: CustomModel = { id: row.id };
if (detectImage(row)) model.image = true;
const context = firstPositive(row, CONTEXT_KEYS);
if (context) model.context = context;
const maxTokens = firstPositive(row, MAX_TOKEN_KEYS);
if (maxTokens) model.maxTokens = maxTokens;
byId.set(row.id, model);
}
}
return [...byId.values()].sort((a, b) => a.id.localeCompare(b.id));
}