Merge claude/phase3-media into p3/b5-transcribe-studio

Brings in the media job RPCs, generic media tool dispatch and the image
operations; transcribe joins the operation list and the tool catalog next to
them.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
This commit is contained in:
Claude 2026-10-03 13:54:34 +00:00
commit 114103579f
No known key found for this signature in database
38 changed files with 4583 additions and 91 deletions

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@ -15,6 +15,7 @@ import type {
ComposioProvider,
ConnectorRegistry,
DestinationEmulator,
MediaOperationRegistration,
RemoteConnectorDependencies,
} from "@rakazo/adapters";
import {
@ -143,6 +144,8 @@ export async function createApp(
email?: TransactionalEmailProvider;
remoteConnectors?: RemoteConnectorDependencies;
logger?: Logger;
/** Test seam: media operations instead of the configured ones. */
mediaOperations?: MediaOperationRegistration[];
} = {},
): Promise<AppHandles> {
const {
@ -155,6 +158,7 @@ export async function createApp(
email: emailOverride,
remoteConnectors,
logger: loggerOverride,
mediaOperations,
...envOverrides
} = overrides;
const env = { ...loadEnv(process.env), ...envOverrides };
@ -384,9 +388,9 @@ export async function createApp(
events,
jobs,
artifacts,
registrations: createMediaOperations({
loadSettings: () => loadMediaSettings({ prisma, secrets }),
}),
registrations:
mediaOperations ??
createMediaOperations({ loadSettings: () => loadMediaSettings({ prisma, secrets }) }),
});
const executor = createRunExecutor({
prisma,
@ -468,6 +472,7 @@ export async function createApp(
const router = createRouter({
cloudAgent,
media,
prisma,
events,
auth,

118
apps/api/src/media-jobs.ts Normal file
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@ -0,0 +1,118 @@
import { ORPCError } from "@orpc/server";
import type { MediaRuntime } from "@rakazo/adapter-kit";
import {
type EncryptedSecretStore,
loadMediaSettings,
MediaJobRejectedError,
MediaSettingsInvalidError,
mediaSettingsView,
saveMediaSettings,
} from "@rakazo/adapters";
import type { Actor, MediaJobStartInput, MediaSettingsUpdate } from "@rakazo/contracts";
import type { PrismaClient } from "@rakazo/db";
import { resolveThreadTarget } from "./thread-target.js";
export interface MediaRouteDeps {
prisma: PrismaClient;
secrets: EncryptedSecretStore;
media?: MediaRuntime;
}
/** Media backends run on the deployment owner's own server, so only they configure them. */
function requireDeploymentOwner(actor: Actor) {
if (!actor.isDeploymentOwner) throw new ORPCError("FORBIDDEN");
}
function requireMedia(deps: MediaRouteDeps): MediaRuntime {
if (!deps.media) throw new ORPCError("NOT_IMPLEMENTED");
return deps.media;
}
export async function getMediaSettings(deps: MediaRouteDeps, actor: Actor) {
requireDeploymentOwner(actor);
return mediaSettingsView(await loadMediaSettings(deps));
}
export async function updateMediaSettings(
deps: MediaRouteDeps,
actor: Actor,
input: MediaSettingsUpdate,
) {
requireDeploymentOwner(actor);
try {
return await saveMediaSettings(deps, input);
} catch (error) {
if (error instanceof MediaSettingsInvalidError) {
throw new ORPCError("BAD_REQUEST", { message: error.message });
}
throw error;
}
}
/**
* Starts an operation a user picked on a card (export, transcribe, edit) in the same conversation.
* The thread is authorized like every thread procedure; the runtime checks that the operation's
* source artifacts belong to the actor, and the job can only ever read the actor's artifacts.
*/
export async function startMediaJob(deps: MediaRouteDeps, actor: Actor, input: MediaJobStartInput) {
const media = requireMedia(deps);
const target = await resolveThreadTarget(deps.prisma, actor, input);
const source = await deps.prisma.message.findFirst({
where: { id: input.messageId, threadId: target.threadId },
select: { botId: true },
});
if (!source) throw new ORPCError("NOT_FOUND");
const bots =
target.kind === "bot"
? [target.botId]
: [
...(target.leadBotId && target.memberBotIds.includes(target.leadBotId)
? [target.leadBotId]
: []),
...target.memberBotIds,
];
const botId = source.botId && bots.includes(source.botId) ? source.botId : bots[0];
if (!botId) throw new ORPCError("NOT_FOUND");
try {
return await media.start({
operation: input.operation,
input: input.input,
spaceId: actor.spaceId,
userId: actor.userId,
botId,
groupId: target.kind === "group" ? target.groupId : null,
threadId: target.threadId,
runId: null,
});
} catch (error) {
if (error instanceof MediaJobRejectedError) {
throw new ORPCError("BAD_REQUEST", { message: error.message });
}
throw error;
}
}
async function ownedJobId(deps: MediaRouteDeps, actor: Actor, jobId: string): Promise<string> {
const job = await deps.prisma.mediaJob.findFirst({
where: { id: jobId, spaceId: actor.spaceId, userId: actor.userId },
select: { id: true },
});
if (!job) throw new ORPCError("NOT_FOUND");
return job.id;
}
export async function getMediaJob(deps: MediaRouteDeps, actor: Actor, jobId: string) {
const media = requireMedia(deps);
const snapshot = await media.get(await ownedJobId(deps, actor, jobId));
if (!snapshot) throw new ORPCError("NOT_FOUND");
return snapshot;
}
export async function cancelMediaJob(deps: MediaRouteDeps, actor: Actor, jobId: string) {
const media = requireMedia(deps);
const id = await ownedJobId(deps, actor, jobId);
await media.cancel(id);
const snapshot = await media.get(id);
if (!snapshot) throw new ORPCError("NOT_FOUND");
return snapshot;
}

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@ -6,6 +6,7 @@ import type {
ArtifactStore,
ConnectorCatalogItem,
JobPublisher,
MediaRuntime,
MemoryStore,
SandboxProvider,
} from "@rakazo/adapter-kit";
@ -166,6 +167,13 @@ import {
renameMainConversation,
} from "./main-conversation.js";
import { buildMcpUpdateMaterial } from "./mcp-material.js";
import {
cancelMediaJob,
getMediaJob,
getMediaSettings,
startMediaJob,
updateMediaSettings,
} from "./media-jobs.js";
import {
disconnectMemoryProvider,
getMemoryProviderConfig,
@ -447,6 +455,7 @@ function mcpAssignmentDto(row: {
export interface RouterDeps {
cloudAgent?: CloudAgentConnection | null;
media?: MediaRuntime;
prisma: PrismaClient;
events: ThreadEvents;
auth: Auth;
@ -3482,6 +3491,27 @@ export function createRouter(deps: RouterDeps) {
return { ok: true as const };
}),
},
media: {
settings: {
get: authed.media.settings.get.handler(({ context }) =>
getMediaSettings(deps, context.actor),
),
update: authed.media.settings.update.handler(({ context, input }) =>
updateMediaSettings(deps, context.actor, input),
),
},
jobs: {
start: authed.media.jobs.start.handler(({ context, input }) =>
startMediaJob(deps, context.actor, input),
),
get: authed.media.jobs.get.handler(({ context, input }) =>
getMediaJob(deps, context.actor, input.jobId),
),
cancel: authed.media.jobs.cancel.handler(({ context, input }) =>
cancelMediaJob(deps, context.actor, input.jobId),
),
},
},
connections: {
catalog: authed.connections.catalog.handler(async ({ context, input }) => {
const adapterContext = connectionContext(

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@ -2,6 +2,9 @@ import type { ConnectorTool } from "@rakazo/adapter-kit";
import {
BotSecretDestination,
BotSecretName,
EditImageInputSchema,
GenerateImageInputSchema,
GenerateVideoInputSchema,
MODEL_TIERS,
SecretAskPurpose,
SecretHttpRequest,
@ -11,7 +14,14 @@ import {
import { z } from "zod";
import { mediaToolInputSchema } from "./media-tools.js";
type MediaToolSchema = Parameters<typeof mediaToolInputSchema>[0];
/** A media tool's parameters from its operation's input schema, plus `continue_after`. */
function mediaParameters(schema: z.ZodType) {
const json = z.toJSONSchema(schema, { io: "input" });
return mediaToolInputSchema({
properties: (json.properties ?? {}) as Record<string, unknown>,
required: json.required,
});
}
export const SUBAGENT_MODEL_TIER_DESCRIPTION =
"Optional model tier: fast for quick simple work, code for programming, standard otherwise. Uses the model this space maps to the tier, or your own model when it maps none. Ignored when model_provider and model_id are set.";
@ -330,11 +340,29 @@ export const builtinAgentTools: ConnectorTool[] = [
},
},
},
{
name: "generate_image",
description:
"Generate up to 4 images from a prompt on the self-hosted image server, or rework a source image (image-to-image).",
inputSchema: mediaParameters(GenerateImageInputSchema),
},
{
name: "generate_video",
description:
"Generate a short video clip from a prompt on the self-hosted image server, optionally starting from an image.",
inputSchema: mediaParameters(GenerateVideoInputSchema),
},
{
name: "edit_image",
description:
"Edit an image artifact into a new one: crop, rotate, flip, resize (crop, pad, or blur to fit a format), add borders, convert the format, or repaint it from a prompt (only when generate_image is available). Edits apply in that order.",
inputSchema: mediaParameters(EditImageInputSchema),
},
{
name: "transcribe",
description:
"Transcribe speech in an audio or video artifact into SRT and VTT subtitle files, shown on a media card. Set continue_after to get the transcript back, e.g. to burn the .srt in with edit_video.",
inputSchema: mediaToolInputSchema(z.toJSONSchema(TranscribeInputSchema) as MediaToolSchema),
inputSchema: mediaParameters(TranscribeInputSchema),
},
{
name: "add_mcp_server",

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@ -0,0 +1,227 @@
import sharp from "sharp";
import { describe, expect, it } from "vitest";
import type { ComfyUiProviderConfig } from "./comfyui-provider.js";
import {
createComfyUiProvider,
describeExecutionError,
parseGpuStatus,
} from "./comfyui-provider.js";
import { ComfyUiEmulator } from "./testing/comfyui-emulator.js";
const BASE_URL = "http://127.0.0.1:8188";
const IMAGE = { prompt: "a lighthouse", width: 512, height: 512 };
function setup(config: Partial<ComfyUiProviderConfig> = {}, emulator = new ComfyUiEmulator()) {
const provider = createComfyUiProvider({
baseUrl: BASE_URL,
fetch: emulator.fetch,
pollIntervalMs: 1,
...config,
});
return { provider, emulator };
}
function submitted(emulator: ComfyUiEmulator, index = 0) {
const graph = emulator.prompts[index]?.graph ?? {};
const byClass = (classType: string) =>
Object.values(graph).find((node) => node.class_type === classType)?.inputs ?? {};
return { graph, byClass };
}
describe("createComfyUiProvider", () => {
it("refuses metadata hosts, public hosts and keys over public http", () => {
expect(() => createComfyUiProvider({ baseUrl: "http://169.254.169.254" })).toThrow(
"blocked metadata or link-local host",
);
expect(() => createComfyUiProvider({ baseUrl: "http://comfy.example.com" })).toThrow(
"Public model endpoints are blocked",
);
expect(() => createComfyUiProvider({ baseUrl: "ftp://127.0.0.1" })).toThrow("http or https");
});
it("validates custom workflows up front", () => {
expect(() => createComfyUiProvider({ baseUrl: BASE_URL, imageWorkflow: "{" })).toThrow(
"Workflow is not valid JSON",
);
expect(() =>
createComfyUiProvider({ baseUrl: BASE_URL, videoWorkflow: '{"nodes": [], "links": []}' }),
).toThrow("API format");
});
it("keeps a reverse-proxy path prefix and sends the API key", async () => {
const emulator = new ComfyUiEmulator({ apiKey: "comfy-key", basePath: "/comfy" });
const { provider } = setup({ baseUrl: `${BASE_URL}/comfy/`, apiKey: "comfy-key" }, emulator);
await provider.generateImage(IMAGE);
expect(emulator.requests.map((request) => request.path)).toContain("prompt");
expect(emulator.requests.every((request) => request.authorization === "Bearer comfy-key")).toBe(
true,
);
const { provider: keyless } = setup({ baseUrl: `${BASE_URL}/comfy` }, emulator);
await expect(keyless.generateImage(IMAGE)).rejects.toThrow("ComfyUI returned 401");
});
it("fills the default text-to-image workflow", async () => {
const { provider, emulator } = setup();
await provider.generateImage({ ...IMAGE, width: 1001, negativePrompt: "fog", seed: 42 });
const { byClass } = submitted(emulator);
expect(byClass("CheckpointLoaderSimple").ckpt_name).toBe("sd_xl_base_1.0.safetensors");
expect(byClass("EmptyLatentImage")).toMatchObject({ width: 1000, height: 512 });
expect(byClass("KSampler")).toMatchObject({ seed: 42, denoise: 1 });
const texts = emulator.prompts[0]!.graph;
expect(Object.values(texts).map((node) => node.inputs.text)).toEqual(
expect.arrayContaining(["a lighthouse", "fog"]),
);
});
it("uses the configured model, else the first checkpoint the video workflows do not use", async () => {
const emulator = new ComfyUiEmulator();
emulator.checkpoints = ["ltx-video-2b-v0.9.5.safetensors", "v1-5-pruned.safetensors"];
emulator.checkpointListFormat = "legacy";
await setup({}, emulator).provider.generateImage(IMAGE);
expect(submitted(emulator, 0).byClass("CheckpointLoaderSimple").ckpt_name).toBe(
"v1-5-pruned.safetensors",
);
emulator.checkpoints.push("dreamshaper.safetensors");
await setup({ imageModel: "dreamshaper.safetensors" }, emulator).provider.generateImage(IMAGE);
expect(submitted(emulator, 1).byClass("CheckpointLoaderSimple").ckpt_name).toBe(
"dreamshaper.safetensors",
);
emulator.checkpoints = ["ltx-video-2b-v0.9.5.safetensors"];
await expect(setup({}, emulator).provider.generateImage(IMAGE)).rejects.toThrow(
"ComfyUI has no image checkpoint installed",
);
});
it("uploads the source image for image-to-image", async () => {
const { provider, emulator } = setup();
const bytes = new Uint8Array(Buffer.from((await sourcePng()).bytes));
await provider.generateImage({
...IMAGE,
source: { bytes, mimeType: "image/png" },
strength: 0.3,
});
const { byClass } = submitted(emulator);
const uploaded = String(byClass("LoadImage").image);
expect(uploaded).toMatch(/^evoo-.+\.png$/);
expect(Buffer.from(emulator.uploads.get(uploaded)!).equals(Buffer.from(bytes))).toBe(true);
expect(byClass("KSampler").denoise).toBe(0.3);
});
it("lets a custom workflow replace only the default it matches", async () => {
const custom = {
"1": {
class_type: "CustomTextToImage",
inputs: { text: "style: {{prompt}}", seed: "{{seed}}" },
},
"2": { class_type: "SaveImage", inputs: { images: ["1", 0], filename_prefix: "x" } },
};
const { provider, emulator } = setup({ imageWorkflow: JSON.stringify(custom) });
await provider.generateImage(IMAGE);
expect(submitted(emulator, 0).byClass("CustomTextToImage").text).toBe("style: a lighthouse");
await provider.generateImage({ ...IMAGE, source: await sourcePng() });
expect(submitted(emulator, 1).byClass("LoadImage").image).toBeDefined();
});
it("fills the LTX-Video workflow with an 8n+1 frame count and reports the clip", async () => {
const { provider, emulator } = setup();
const [clip] = await provider.generateVideo({
prompt: "a paper boat",
width: 470,
height: 836,
durationSeconds: 5,
});
const { byClass } = submitted(emulator);
expect(byClass("EmptyLTXVLatentVideo")).toMatchObject({ width: 480, height: 832, length: 121 });
expect(byClass("CreateVideo").fps).toBe(24);
expect(clip).toMatchObject({
mimeType: "video/mp4",
width: 480,
height: 832,
durationMs: 5042,
});
});
it("reads video from a custom workflow's gifs output and skips frame previews", async () => {
const custom = {
"1": { class_type: "TextToFrames", inputs: { text: "{{prompt}}" } },
"2": { class_type: "PreviewImage", inputs: { images: ["1", 0] } },
"3": { class_type: "VHS_VideoCombine", inputs: { images: ["1", 0], frame_rate: 16 } },
};
const { provider } = setup({ videoWorkflow: JSON.stringify(custom) });
const clips = await provider.generateVideo({ ...IMAGE, durationSeconds: 2 });
expect(clips.map((clip) => [clip.mimeType, clip.durationMs])).toEqual([
["video/mp4", undefined],
]);
});
it("explains rejected workflows and failed runs", async () => {
const emulator = new ComfyUiEmulator();
const { provider } = setup({ imageModel: "missing.safetensors" }, emulator);
await expect(provider.generateImage(IMAGE)).rejects.toThrow(
"ComfyUI rejected the workflow: CheckpointLoaderSimple: Value not in list: ckpt_name: 'missing.safetensors' not in list",
);
const working = setup({}, emulator).provider;
emulator.failNextExecution = "CUDA out of memory. Tried to allocate 2.00 GiB\nTraceback...";
await expect(working.generateImage(IMAGE)).rejects.toThrow(
/^ComfyUI failed in KSampler: CUDA out of memory\. Tried to allocate 2\.00 GiB$/,
);
emulator.failNextStatus = 500;
await expect(working.generateImage(IMAGE)).rejects.toThrow("ComfyUI returned 500");
});
it("reports an unreachable server", async () => {
const provider = createComfyUiProvider({
baseUrl: BASE_URL,
fetch: async () => {
throw new TypeError("fetch failed");
},
});
await expect(provider.generateImage(IMAGE)).rejects.toThrow("ComfyUI is unreachable");
await expect(provider.gpuStatus()).rejects.toThrow("ComfyUI is unreachable");
});
it("interrupts its own running prompt when the caller cancels", async () => {
const emulator = new ComfyUiEmulator();
emulator.pendingPolls = 1_000_000;
const { provider } = setup({ pollIntervalMs: 5 }, emulator);
const controller = new AbortController();
const run = provider.generateImage({ ...IMAGE, signal: controller.signal });
while (!emulator.requests.some((request) => request.path.startsWith("history/"))) {
await new Promise((resolve) => setTimeout(resolve, 1));
}
controller.abort(new Error("cancelled by user"));
await expect(run).rejects.toThrow("cancelled by user");
expect(emulator.deleted).toEqual(["prompt-1"]);
expect(emulator.interrupted).toEqual(["prompt-1"]);
});
it("reports GPU memory other processes leave to ComfyUI", async () => {
const emulator = new ComfyUiEmulator();
emulator.gpu = { totalMb: 12_288, freeMb: 3_000, torchReservedMb: 7_000, torchFreeMb: 1_000 };
await expect(setup({}, emulator).provider.gpuStatus()).resolves.toEqual({
vramFreeMb: 9_000,
vramTotalMb: 12_288,
});
emulator.gpu = null;
await expect(setup({}, emulator).provider.gpuStatus()).resolves.toBeUndefined();
expect(parseGpuStatus({ devices: [{ type: "cuda", vram_total: 0, vram_free: 0 }] })).toBe(
undefined,
);
});
it("names interrupted runs", () => {
expect(describeExecutionError([["execution_interrupted", {}]])).toBe(
"ComfyUI interrupted the run",
);
expect(describeExecutionError(undefined)).toBe("ComfyUI failed");
});
});
async function sourcePng() {
const png = await sharp({
create: { width: 32, height: 32, channels: 3, background: { r: 1, g: 2, b: 3 } },
})
.png()
.toBuffer();
return { bytes: new Uint8Array(png), mimeType: "image/png" };
}

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@ -0,0 +1,593 @@
import { randomInt, randomUUID } from "node:crypto";
import { setTimeout as sleep } from "node:timers/promises";
import type {
AdapterDescriptor,
GeneratedMedia,
GpuStatus,
ImageGenerationCapabilities,
ImageGenerationProvider,
ImageGenerationRequest,
MediaFile,
MediaProgressListener,
VideoGenerationCapabilities,
VideoGenerationProvider,
VideoGenerationRequest,
} from "@rakazo/adapter-kit";
import type { AttachmentKind } from "@rakazo/contracts";
import {
ARTIFACT_MAX_BYTES_BY_KIND,
attachmentKindOf,
MEDIA_VIDEO_MAX_SECONDS,
} from "@rakazo/contracts";
import { attachmentExtensionForMimeType, inferAttachmentMimeType } from "@rakazo/core";
import type { ComfyWorkflow, WorkflowTemplate, WorkflowValues } from "@rakazo/core/media/workflows";
import {
DEFAULT_WORKFLOWS,
fillWorkflow,
parseWorkflowTemplate,
} from "@rakazo/core/media/workflows";
import {
assertAllowedOpenAiCompatibleRequestUrl,
assertHttpsForKeyedOpenAiCompatibleUrl,
} from "./openai-compatible-url.js";
import { createOpenAiCompatibleFetch } from "./pi-openai-compatible-provider.js";
import { readBodyCapped } from "./web-ssrf.js";
export const COMFYUI_PROVIDER_ID = "comfyui";
/** Frame rate of generated video; frame counts follow LTX-Video's 8n+1 rule. */
export const COMFYUI_VIDEO_FPS = 24;
const MAX_IMAGE_SIDE = 2048;
const REQUEST_TIMEOUT_MS = 30_000;
const TRANSFER_TIMEOUT_MS = 120_000;
const CANCEL_TIMEOUT_MS = 5_000;
const IMAGE_PROMPT_TIMEOUT_MS = 10 * 60_000;
const VIDEO_PROMPT_TIMEOUT_MS = 30 * 60_000;
const POLL_INTERVAL_MS = 1_000;
const MAX_JSON_BYTES = 8 * 1024 * 1024;
const MAX_ERROR_CHARS = 400;
const MIB = 1024 * 1024;
const IMAGE_STEPS = 25;
const VIDEO_STEPS = 30;
const DEFAULT_STRENGTH = 0.6;
const DEFAULT_NEGATIVE_PROMPTS = {
image: "blurry, low quality, distorted, watermark, text",
video: "worst quality, inconsistent motion, blurry, jittery, distorted",
};
const JSON_HEADERS = { Accept: "application/json", "Content-Type": "application/json" };
export interface ComfyUiProviderConfig {
baseUrl: string;
apiKey?: string;
/** Checkpoint for `{{model}}`; the first installed image checkpoint when omitted. */
imageModel?: string;
/** API-format workflow JSON that replaces the matching default image workflow. */
imageWorkflow?: string;
/** API-format workflow JSON that replaces the matching default video workflow. */
videoWorkflow?: string;
fetch?: typeof globalThis.fetch;
/** How long to wait between checks for a finished prompt; tests shorten it. */
pollIntervalMs?: number;
}
export interface ComfyUiProvider extends ImageGenerationProvider, VideoGenerationProvider {
describe(): AdapterDescriptor<ImageGenerationCapabilities & VideoGenerationCapabilities>;
gpuStatus(signal?: AbortSignal): Promise<GpuStatus | undefined>;
}
type MediaKind = "image" | "video";
type ReadBody<T> = (response: Response, signal: AbortSignal) => Promise<T>;
interface OutputFile {
filename: string;
subfolder: string;
type: string;
mimeType: string;
kind: AttachmentKind;
}
interface GenerationJob {
kind: MediaKind;
template: WorkflowTemplate;
prompt: string;
negativePrompt?: string;
width: number;
height: number;
seed?: number;
count: number;
source?: MediaFile;
strength?: number;
frames?: number;
signal?: AbortSignal;
onProgress?: MediaProgressListener;
}
/**
* Image and video generation on a self-hosted ComfyUI server through its HTTP API: submit an
* API-format workflow, poll its history, download the outputs. Requests go through the same
* address-checked fetch as OpenAI-compatible model servers.
*/
export function createComfyUiProvider(config: ComfyUiProviderConfig): ComfyUiProvider {
return new ComfyUiClient(config);
}
class ComfyUiClient implements ComfyUiProvider {
private readonly baseUrl: URL;
private readonly apiKey: string | undefined;
private readonly imageModel: string | undefined;
private readonly imageWorkflow: WorkflowTemplate | undefined;
private readonly videoWorkflow: WorkflowTemplate | undefined;
private readonly fetch: typeof globalThis.fetch;
private readonly pollIntervalMs: number;
private readonly clientId = randomUUID();
constructor(config: ComfyUiProviderConfig) {
this.baseUrl = comfyUiBaseUrl(config.baseUrl);
this.apiKey = config.apiKey?.trim() || undefined;
assertHttpsForKeyedOpenAiCompatibleUrl(this.baseUrl, this.apiKey);
this.imageModel = config.imageModel?.trim() || undefined;
this.imageWorkflow = config.imageWorkflow?.trim()
? parseWorkflowTemplate(config.imageWorkflow)
: undefined;
this.videoWorkflow = config.videoWorkflow?.trim()
? parseWorkflowTemplate(config.videoWorkflow)
: undefined;
this.fetch = createOpenAiCompatibleFetch(config.fetch);
this.pollIntervalMs = config.pollIntervalMs ?? POLL_INTERVAL_MS;
}
describe() {
return {
id: COMFYUI_PROVIDER_ID,
contractVersion: "1",
adapterVersion: "0.1.0",
capabilities: {
textToImage: true,
imageToImage: true,
inpaint: false,
maxWidth: MAX_IMAGE_SIDE,
maxHeight: MAX_IMAGE_SIDE,
textToVideo: true,
imageToVideo: true,
maxDurationSeconds: MEDIA_VIDEO_MAX_SECONDS,
},
};
}
async gpuStatus(signal?: AbortSignal): Promise<GpuStatus | undefined> {
return parseGpuStatus(await this.getJson("system_stats", signal));
}
async generateImage(request: ImageGenerationRequest): Promise<GeneratedMedia[]> {
if (request.mask) throw new Error("ComfyUI inpainting is not supported");
return this.generate({
...request,
kind: "image",
template: pickTemplate(
this.imageWorkflow,
Boolean(request.source),
DEFAULT_WORKFLOWS.textToImage,
DEFAULT_WORKFLOWS.imageToImage,
),
width: roundSide(request.width, 8),
height: roundSide(request.height, 8),
count: request.count ?? 1,
});
}
async generateVideo(request: VideoGenerationRequest): Promise<GeneratedMedia[]> {
const seconds = Math.min(Math.max(request.durationSeconds, 1), MEDIA_VIDEO_MAX_SECONDS);
return this.generate({
...request,
kind: "video",
template: pickTemplate(
this.videoWorkflow,
Boolean(request.source),
DEFAULT_WORKFLOWS.textToVideo,
DEFAULT_WORKFLOWS.imageToVideo,
),
width: roundSide(request.width, 32),
height: roundSide(request.height, 32),
frames: 8 * Math.round((seconds * COMFYUI_VIDEO_FPS) / 8) + 1,
count: 1,
});
}
private async generate(job: GenerationJob): Promise<GeneratedMedia[]> {
const { template, signal } = job;
const values: WorkflowValues = {
prompt: job.prompt,
negative_prompt: job.negativePrompt ?? DEFAULT_NEGATIVE_PROMPTS[job.kind],
width: job.width,
height: job.height,
steps: job.kind === "image" ? IMAGE_STEPS : VIDEO_STEPS,
strength: job.strength ?? DEFAULT_STRENGTH,
frames: job.frames ?? 1,
fps: COMFYUI_VIDEO_FPS,
};
if (template.placeholders.has("model")) values.model = await this.imageCheckpoint(signal);
if (template.placeholders.has("image")) {
if (!job.source) throw new Error("ComfyUI workflow needs an input image");
values.image = await this.upload(job.source, signal);
}
const sized = template.placeholders.has("width") && template.placeholders.has("height");
const timed = template.placeholders.has("frames") && template.placeholders.has("fps");
const firstSeed = job.seed ?? randomInt(2 ** 48 - 1);
const results: GeneratedMedia[] = [];
for (let index = 0; index < job.count; index += 1) {
const graph = fillWorkflow(template, { ...values, seed: firstSeed + index });
const outputs = await this.runPrompt(graph, job.kind, signal);
const files = outputFiles(outputs, job.kind);
if (files.length === 0) throw new Error(`ComfyUI produced no ${job.kind}`);
for (const file of files) {
results.push({
bytes: await this.download(file, signal),
mimeType: file.mimeType,
name: file.filename,
...(sized && file.kind === job.kind ? { width: job.width, height: job.height } : {}),
...(timed && file.kind === "video"
? { durationMs: Math.round(((values.frames ?? 1) / COMFYUI_VIDEO_FPS) * 1000) }
: {}),
});
}
job.onProgress?.((index + 1) / job.count);
}
return results;
}
/** Submits a prompt and waits for its outputs; a cancelled or timed-out prompt is dequeued. */
private async runPrompt(
graph: ComfyWorkflow,
kind: MediaKind,
signal: AbortSignal | undefined,
): Promise<Record<string, unknown>> {
const deadline = AbortSignal.timeout(
kind === "image" ? IMAGE_PROMPT_TIMEOUT_MS : VIDEO_PROMPT_TIMEOUT_MS,
);
const runSignal = signal ? AbortSignal.any([signal, deadline]) : deadline;
const promptId = await this.submit(graph, runSignal);
try {
for (;;) {
const outputs = await this.finishedOutputs(promptId, runSignal);
if (outputs) return outputs;
await sleep(this.pollIntervalMs, undefined, { signal: runSignal });
}
} catch (error) {
if (!runSignal.aborted) throw error;
await this.cancelPrompt(promptId);
if (signal?.aborted) throw signal.reason ?? error;
throw new Error("ComfyUI timed out");
}
}
private async submit(graph: ComfyWorkflow, signal: AbortSignal): Promise<string> {
const payload = { prompt: graph, client_id: this.clientId };
return this.postJson("prompt", payload, signal, async (response, readSignal) => {
if (response.status === 400) {
const rejection = await readJson(response, readSignal).catch(() => undefined);
throw new Error(describeWorkflowRejection(rejection));
}
const result = await readOkJson(response, readSignal);
const promptId = isRecord(result) ? result.prompt_id : undefined;
if (typeof promptId !== "string" || !promptId) {
throw new Error("ComfyUI did not accept the workflow");
}
return promptId;
});
}
private async finishedOutputs(
promptId: string,
signal: AbortSignal,
): Promise<Record<string, unknown> | undefined> {
const history = await this.getJson(`history/${encodeURIComponent(promptId)}`, signal);
const entry = isRecord(history) ? history[promptId] : undefined;
if (!isRecord(entry)) return undefined;
const status = isRecord(entry.status) ? entry.status : {};
if (status.status_str === "error") throw new Error(describeExecutionError(status.messages));
if (status.completed === false) return undefined;
return isRecord(entry.outputs) ? entry.outputs : {};
}
/** Best effort: drops the prompt from the queue, or interrupts it when it is ours and running. */
private async cancelPrompt(promptId: string): Promise<void> {
try {
await this.postJson(
"queue",
{ delete: [promptId] },
undefined,
discardBody,
CANCEL_TIMEOUT_MS,
);
const queue = await this.getJson("queue", undefined, CANCEL_TIMEOUT_MS);
const running =
isRecord(queue) && Array.isArray(queue.queue_running) ? queue.queue_running : [];
if (running.some((entry) => Array.isArray(entry) && entry[1] === promptId)) {
const interrupt = { prompt_id: promptId };
await this.postJson("interrupt", interrupt, undefined, discardBody, CANCEL_TIMEOUT_MS);
}
} catch {
// The prompt then finishes on its own; nothing waits for it.
}
}
private async imageCheckpoint(signal: AbortSignal | undefined): Promise<string> {
if (this.imageModel) return this.imageModel;
const info = await this.getJson("object_info/CheckpointLoaderSimple", signal);
const videoCheckpoints = new Set(
[DEFAULT_WORKFLOWS.textToVideo, DEFAULT_WORKFLOWS.imageToVideo, this.videoWorkflow].flatMap(
(template) => (template ? checkpointNames(template.graph) : []),
),
);
const checkpoint = parseCheckpointList(info).find((name) => !videoCheckpoints.has(name));
if (!checkpoint) throw new Error("ComfyUI has no image checkpoint installed");
return checkpoint;
}
private async upload(file: MediaFile, signal: AbortSignal | undefined): Promise<string> {
const form = new FormData();
const extension = attachmentExtensionForMimeType(file.mimeType) || ".png";
form.append(
"image",
new Blob([Buffer.from(file.bytes)], { type: file.mimeType }),
`evoo-${randomUUID()}${extension}`,
);
form.append("type", "input");
form.append("overwrite", "true");
// Serialize here: the address-checked fetch runs on the undici package, whose FormData
// class differs from the global one.
const encoded = new Response(form);
const headers = {
Accept: "application/json",
"Content-Type": encoded.headers.get("content-type") ?? "",
};
const body = new Uint8Array(await encoded.arrayBuffer());
return this.send("upload/image", { method: "POST", headers, body }, signal, {
timeoutMs: TRANSFER_TIMEOUT_MS,
read: async (response, readSignal) => {
const result = await readOkJson(response, readSignal);
const name = isRecord(result) && typeof result.name === "string" ? result.name : "";
if (!name) throw new Error("ComfyUI did not accept the image");
const subfolder =
isRecord(result) && typeof result.subfolder === "string" ? result.subfolder : "";
return subfolder ? `${subfolder}/${name}` : name;
},
});
}
private download(file: OutputFile, signal: AbortSignal | undefined): Promise<Uint8Array> {
const query = new URLSearchParams({
filename: file.filename,
subfolder: file.subfolder,
type: file.type,
});
return this.send(`view?${query}`, {}, signal, {
timeoutMs: TRANSFER_TIMEOUT_MS,
read: async (response, readSignal) => {
await assertOk(response);
return readBodyCapped(response, ARTIFACT_MAX_BYTES_BY_KIND[file.kind], readSignal);
},
});
}
private getJson(path: string, signal: AbortSignal | undefined, timeoutMs?: number) {
const init = { headers: { Accept: "application/json" } };
return this.send(path, init, signal, { timeoutMs, read: readOkJson });
}
private postJson<T>(
path: string,
payload: unknown,
signal: AbortSignal | undefined,
read: ReadBody<T>,
timeoutMs?: number,
): Promise<T> {
const init = { method: "POST", headers: JSON_HEADERS, body: JSON.stringify(payload) };
return this.send(path, init, signal, { timeoutMs, read });
}
/** One request, with the timeout covering the response body too. */
private async send<T>(
path: string,
init: {
method?: string;
headers?: Record<string, string>;
body?: string | Uint8Array<ArrayBuffer>;
},
signal: AbortSignal | undefined,
options: { timeoutMs?: number; read: ReadBody<T> },
): Promise<T> {
const timeout = AbortSignal.timeout(options.timeoutMs ?? REQUEST_TIMEOUT_MS);
const requestSignal = signal ? AbortSignal.any([signal, timeout]) : timeout;
const headers: Record<string, string> = { ...init.headers };
if (this.apiKey) headers.Authorization = `Bearer ${this.apiKey}`;
try {
const response = await this.fetch(new URL(path, this.baseUrl).href, {
method: init.method ?? "GET",
headers,
body: init.body,
redirect: "error",
signal: requestSignal,
});
return await options.read(response, requestSignal);
} catch (error) {
if (signal?.aborted) throw error;
if (timeout.aborted) throw new Error("ComfyUI timed out");
// undici reports refused or reset connections as a bare "fetch failed".
if (error instanceof TypeError && error.message === "fetch failed") {
throw new Error("ComfyUI is unreachable");
}
throw error;
}
}
}
function comfyUiBaseUrl(raw: string): URL {
const url = assertAllowedOpenAiCompatibleRequestUrl(raw.trim());
url.search = "";
url.hash = "";
url.pathname = `${url.pathname.replace(/\/+$/, "")}/`;
return url;
}
function isRecord(value: unknown): value is Record<string, unknown> {
return Boolean(value) && typeof value === "object" && !Array.isArray(value);
}
function truncate(text: string): string {
return text.length > MAX_ERROR_CHARS ? `${text.slice(0, MAX_ERROR_CHARS - 1)}…` : text;
}
function roundSide(side: number, multiple: number): number {
const rounded = Math.round(side / multiple) * multiple;
return Math.min(Math.max(rounded, multiple * Math.ceil(64 / multiple)), MAX_IMAGE_SIDE);
}
/** A custom workflow replaces the default that matches whether it takes an input image. */
function pickTemplate(
custom: WorkflowTemplate | undefined,
withImage: boolean,
textDefault: WorkflowTemplate,
imageDefault: WorkflowTemplate,
): WorkflowTemplate {
if (custom && custom.placeholders.has("image") === withImage) return custom;
return withImage ? imageDefault : textDefault;
}
function checkpointNames(graph: ComfyWorkflow): string[] {
return Object.values(graph).flatMap((node) =>
typeof node.inputs.ckpt_name === "string" ? [node.inputs.ckpt_name] : [],
);
}
async function discardBody(response: Response): Promise<void> {
await response.body?.cancel().catch(() => undefined);
}
async function assertOk(response: Response): Promise<void> {
if (response.ok) return;
await discardBody(response);
throw new Error(`ComfyUI returned ${response.status}`);
}
async function readJson(response: Response, signal: AbortSignal): Promise<unknown> {
const bytes = await readBodyCapped(response, MAX_JSON_BYTES, signal);
try {
return JSON.parse(new TextDecoder().decode(bytes));
} catch {
throw new Error("ComfyUI returned invalid JSON");
}
}
async function readOkJson(response: Response, signal: AbortSignal): Promise<unknown> {
await assertOk(response);
return readJson(response, signal);
}
/**
* ComfyUI can evict its own models, so memory its PyTorch process holds counts as available;
* only memory other processes use (another model server on the same GPU) does not.
*/
export function parseGpuStatus(body: unknown): GpuStatus | undefined {
const devices = isRecord(body) && Array.isArray(body.devices) ? body.devices : [];
for (const device of devices) {
if (!isRecord(device) || device.type === "cpu") continue;
const total = finiteNumber(device.vram_total);
const free = finiteNumber(device.vram_free);
if (!total || free === undefined) continue;
const reserved = finiteNumber(device.torch_vram_total) ?? 0;
const reservedFree = finiteNumber(device.torch_vram_free) ?? 0;
const available = Math.min(total, Math.max(0, free - reservedFree + reserved));
return { vramFreeMb: Math.floor(available / MIB), vramTotalMb: Math.floor(total / MIB) };
}
return undefined;
}
function finiteNumber(value: unknown): number | undefined {
return typeof value === "number" && Number.isFinite(value) ? value : undefined;
}
/** Older ComfyUI lists combo values as `[[...names], {...}]`, newer as `["COMBO", {options}]`. */
export function parseCheckpointList(body: unknown): string[] {
const loader = isRecord(body) ? body.CheckpointLoaderSimple : undefined;
const input = isRecord(loader) ? loader.input : undefined;
const required = isRecord(input) ? input.required : undefined;
const spec = isRecord(required) ? required.ckpt_name : undefined;
if (!Array.isArray(spec)) return [];
const names = Array.isArray(spec[0])
? spec[0]
: isRecord(spec[1]) && Array.isArray(spec[1].options)
? spec[1].options
: [];
return names.filter((name): name is string => typeof name === "string" && name.length > 0);
}
/** Saved files win over previews; video runs return clips (or animations), not frames. */
function outputFiles(outputs: Record<string, unknown>, kind: MediaKind): OutputFile[] {
const files: OutputFile[] = [];
for (const node of Object.values(outputs)) {
if (!isRecord(node)) continue;
for (const key of ["images", "gifs", "videos"]) {
const entries = node[key];
if (!Array.isArray(entries)) continue;
for (const entry of entries) {
if (!isRecord(entry) || typeof entry.filename !== "string" || !entry.filename) continue;
const mimeType = inferAttachmentMimeType(entry.filename);
if (!mimeType) continue;
files.push({
filename: entry.filename,
subfolder: typeof entry.subfolder === "string" ? entry.subfolder : "",
type: typeof entry.type === "string" ? entry.type : "output",
mimeType,
kind: attachmentKindOf(mimeType),
});
}
}
}
const videos = files.filter((file) => file.kind === "video");
const wanted =
kind === "image"
? files.filter((file) => file.kind === "image")
: videos.length > 0
? videos
: files.filter((file) => file.mimeType === "image/gif" || file.mimeType === "image/webp");
const saved = wanted.filter((file) => file.type === "output");
return saved.length > 0 ? saved : wanted;
}
export function describeWorkflowRejection(body: unknown): string {
const problems: string[] = [];
const nodeErrors = isRecord(body) && isRecord(body.node_errors) ? body.node_errors : {};
for (const node of Object.values(nodeErrors)) {
if (!isRecord(node) || !Array.isArray(node.errors)) continue;
for (const error of node.errors) {
if (!isRecord(error)) continue;
const parts = [node.class_type, error.message, error.details];
problems.push(parts.filter((part) => typeof part === "string" && part).join(": "));
}
}
if (problems.length === 0 && isRecord(body) && isRecord(body.error)) {
if (typeof body.error.message === "string") problems.push(body.error.message);
}
return truncate(
problems.length > 0
? `ComfyUI rejected the workflow: ${problems.join("; ")}`
: "ComfyUI rejected the workflow",
);
}
export function describeExecutionError(messages: unknown): string {
const events = Array.isArray(messages) ? messages : [];
for (const event of events) {
if (!Array.isArray(event)) continue;
const [name, data] = event;
if (name === "execution_interrupted") return "ComfyUI interrupted the run";
if (name !== "execution_error" || !isRecord(data)) continue;
const node = typeof data.node_type === "string" ? data.node_type : "a node";
const message =
typeof data.exception_message === "string"
? data.exception_message.trim().split("\n")[0]
: "";
return truncate(`ComfyUI failed in ${node}${message ? `: ${message}` : ""}`);
}
return "ComfyUI failed";
}

View File

@ -1,6 +1,7 @@
import type { ConnectorTool } from "@rakazo/adapter-kit";
import type { ConnectorTool, MediaCapabilities } from "@rakazo/adapter-kit";
import { agentConnectionTools, builtinAgentTools } from "./builtin-tools.js";
import { selectCloudAgentTools } from "./cloud-agent-tools-select.js";
import { selectMediaTools } from "./media-tools.js";
import { selectMemoryTools } from "./memory-tools.js";
import { filterImageReturningComputerTools } from "./model-vision.js";
import {
@ -81,6 +82,8 @@ export function selectBuiltinToolsForRun(options: {
trigger: string;
semanticMemoryEnabled: boolean;
cloudAgentEnabled?: boolean;
/** Media tools appear only for operations the space can run. */
mediaCapabilities?: MediaCapabilities;
messagingChannelRun: boolean;
/** Cross-owner agent connections only exist for chat-linked bots. */
agentConnectionsEnabled?: boolean;
@ -88,21 +91,24 @@ export function selectBuiltinToolsForRun(options: {
foreignAgentRun?: boolean;
bot: BuiltinToolPolicy;
}) {
const selected = selectCloudAgentTools(
selectMemoryTools(
filterBuiltinToolsForRun(
filterBuiltinToolsForThread(
filterPageBrowserTools(
filterImageReturningComputerTools(builtinAgentTools, options.graphicalToolsAllowed),
options.pageBrowserAllowed ?? options.graphicalToolsAllowed,
const selected = selectMediaTools(
selectCloudAgentTools(
selectMemoryTools(
filterBuiltinToolsForRun(
filterBuiltinToolsForThread(
filterPageBrowserTools(
filterImageReturningComputerTools(builtinAgentTools, options.graphicalToolsAllowed),
options.pageBrowserAllowed ?? options.graphicalToolsAllowed,
),
options.groupId,
),
options.groupId,
options.trigger,
),
options.trigger,
options.semanticMemoryEnabled,
),
options.semanticMemoryEnabled,
Boolean(options.cloudAgentEnabled),
),
Boolean(options.cloudAgentEnabled),
options.mediaCapabilities,
).filter(
(tool) =>
!(options.foreignAgentRun && tool.name === "update_user_profile") &&

View File

@ -283,6 +283,7 @@ import {
needsOAuthProbe,
parseMcpServerToolArgs,
} from "./mcp-server-tool.js";
import { executeMediaTool, isMediaToolName } from "./media-tools.js";
import { loadAgentMemoryContext } from "./memory-context.js";
import type { MemoryProviderResolver } from "./memory-provider-factory.js";
import { selectMemoryTools } from "./memory-tools.js";
@ -1478,6 +1479,7 @@ export function createRunExecutor(deps: ExecutorDeps) {
trigger: run.trigger,
semanticMemoryEnabled,
cloudAgentEnabled: cloudAgentsEnabled(cloudAgent, run.spaceId),
mediaCapabilities: await deps.media?.capabilities(run.spaceId).catch(() => undefined),
messagingChannelRun,
agentConnectionsEnabled: hasMessagingIdentity,
foreignAgentRun,
@ -2599,6 +2601,24 @@ export function createRunExecutor(deps: ExecutorDeps) {
return computerScreenToolResult(() => tool(browser, computer, context, args), finish);
}
if (isMediaToolName(name)) {
return finish(
await executeMediaTool(
deps.media,
{
spaceId: run.spaceId,
userId: run.userId,
botId: bot.id,
groupId: thread.groupId,
threadId: run.threadId,
runId: run.id,
operationKey: effectKey,
},
name,
args,
),
);
}
if (name.startsWith("cloud_agent_")) {
return finish(
await executeCloudAgentTool(

View File

@ -0,0 +1,111 @@
import type {
ImageGenerationProvider,
MediaFile,
VideoGenerationProvider,
} from "@rakazo/adapter-kit";
import { attachmentKindOf } from "@rakazo/contracts";
import sharp from "sharp";
import { describe, expect, it } from "vitest";
import { createComfyUiProvider } from "./comfyui-provider.js";
import { ComfyUiEmulator } from "./testing/comfyui-emulator.js";
type MediaGenerationProvider = ImageGenerationProvider & VideoGenerationProvider;
const factories: Record<string, () => MediaGenerationProvider> = {
comfyui: () =>
createComfyUiProvider({
baseUrl: "http://127.0.0.1:8188",
fetch: new ComfyUiEmulator().fetch,
pollIntervalMs: 1,
}),
};
async function sourceImage(): Promise<MediaFile> {
const png = await sharp({
create: { width: 96, height: 64, channels: 3, background: { r: 10, g: 20, b: 30 } },
})
.png()
.toBuffer();
return { bytes: new Uint8Array(png), mimeType: "image/png", name: "source.png" };
}
/**
* Offline conformance: every image/video generation provider describes its limits, returns
* the requested number of decodable images, is reproducible by seed, takes a source image,
* reports progress, returns video, and honors cancellation.
*/
for (const [name, create] of Object.entries(factories)) {
describe(`${name} media generation conformance (offline)`, () => {
it("describes the contract and its limits", () => {
const image: ImageGenerationProvider = create();
const video: VideoGenerationProvider = create();
expect(image.describe().contractVersion).toBe("1");
expect(image.describe().capabilities.maxWidth).toBeGreaterThanOrEqual(1024);
expect(image.describe().capabilities.maxHeight).toBeGreaterThanOrEqual(1024);
expect(video.describe().contractVersion).toBe("1");
expect(video.describe().capabilities.maxDurationSeconds).toBeGreaterThan(0);
});
it("returns the requested number of images, reproducible by seed", async () => {
const provider = create();
const progress: number[] = [];
const request = { prompt: "a red kite", width: 256, height: 192, count: 2, seed: 7 };
const images = await provider.generateImage({
...request,
onProgress: (fraction) => progress.push(fraction),
});
expect(images).toHaveLength(2);
for (const image of images) {
expect(attachmentKindOf(image.mimeType)).toBe("image");
const metadata = await sharp(image.bytes).metadata();
expect([metadata.width, metadata.height]).toEqual([256, 192]);
}
expect(Buffer.from(images[0]!.bytes).equals(Buffer.from(images[1]!.bytes))).toBe(false);
expect(progress.at(-1)).toBe(1);
const again = await provider.generateImage({ ...request, count: 1 });
expect(Buffer.from(again[0]!.bytes).equals(Buffer.from(images[0]!.bytes))).toBe(true);
});
it("generates from a source image", async () => {
const images = await create().generateImage({
prompt: "the same scene at night",
width: 96,
height: 64,
source: await sourceImage(),
strength: 0.5,
});
expect(images).toHaveLength(1);
expect(attachmentKindOf(images[0]!.mimeType)).toBe("image");
});
it("returns video from text and from a start frame", async () => {
const provider = create();
for (const source of [undefined, await sourceImage()]) {
const [clip, ...rest] = await provider.generateVideo({
prompt: "waves rolling onto a beach",
width: 768,
height: 512,
durationSeconds: 2,
source,
});
expect(rest).toHaveLength(0);
expect(attachmentKindOf(clip!.mimeType)).toBe("video");
expect(clip!.bytes.byteLength).toBeGreaterThan(0);
}
});
it("reports GPU memory with free not above total", async () => {
const status = await create().gpuStatus?.();
if (!status) return;
expect(status.vramTotalMb).toBeGreaterThan(0);
expect(status.vramFreeMb).toBeGreaterThanOrEqual(0);
expect(status.vramFreeMb).toBeLessThanOrEqual(status.vramTotalMb);
});
it("rejects when the caller cancels", async () => {
const request = { prompt: "x", width: 64, height: 64, signal: AbortSignal.abort() };
await expect(create().generateImage(request)).rejects.toThrow();
await expect(create().generateVideo({ ...request, durationSeconds: 1 })).rejects.toThrow();
});
});
}

View File

@ -24,6 +24,7 @@ export * from "./cloud-agent-provider-env.js";
export * from "./cloud-agent-service.js";
export * from "./cloud-agent-tools.js";
export * from "./cloud-agent-tools-select.js";
export * from "./comfyui-provider.js";
export * from "./composio-catalog-cache.js";
export * from "./composio-connector.js";
export * from "./composio-emulator.js";

View File

@ -1,4 +1,5 @@
import type { MediaSettings } from "@rakazo/contracts";
import { createImageOperations } from "./media/image-operations.js";
import { createTranscriptionOperations } from "./media/transcription.js";
import type { MediaOperationRegistration } from "./media-runtime.js";
@ -12,5 +13,8 @@ export interface MediaOperationDeps {
* from this one list, so both processes run the same operations.
*/
export function createMediaOperations(deps: MediaOperationDeps): MediaOperationRegistration[] {
return [...createTranscriptionOperations({ loadSettings: deps.loadSettings })];
return [
...createImageOperations(deps),
...createTranscriptionOperations({ loadSettings: deps.loadSettings }),
];
}

View File

@ -0,0 +1,615 @@
import { randomUUID } from "node:crypto";
import { existsSync } from "node:fs";
import { mkdtemp, readdir, rm, writeFile } from "node:fs/promises";
import { tmpdir } from "node:os";
import path from "node:path";
import type {
BackgroundJob,
JobPublisher,
MediaJobContext,
MediaOperationResult,
} from "@rakazo/adapter-kit";
import { MediaJobDeferredError, mediaRunJobKey } from "@rakazo/adapter-kit";
import type { MediaJobBlock, MessageBlock } from "@rakazo/contracts";
import { clearThread, createDb, type PrismaClient } from "@rakazo/db";
import { afterAll, beforeAll, describe, expect, it, vi } from "vitest";
import { z } from "zod";
import { storeArtifactFromFile } from "./artifact-files.js";
import { LocalArtifactStore } from "./artifacts.js";
import {
createMediaRuntime,
MEDIA_WAKE_TRIGGER,
MediaJobRejectedError,
type MediaOperationRegistration,
type MediaRuntimeOptions,
} from "./media-runtime.js";
const describePostgres =
process.env.VERIFY_DATABASE && process.env.DATABASE_URL ? describe.sequential : describe.skip;
const PNG = new Uint8Array([0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a, 1, 2, 3, 4]);
type FakeInput = { prompt: string; source?: string };
type Run = (context: MediaJobContext) => Promise<MediaOperationResult>;
function deferred<T = void>() {
let resolve!: (value: T) => void;
const promise = new Promise<T>((done) => {
resolve = done;
});
return { promise, resolve };
}
describePostgres("media job runtime (PostgreSQL, fake operations)", () => {
let prisma: PrismaClient;
let db: ReturnType<typeof createDb>;
let root: string;
const users: string[] = [];
beforeAll(async () => {
db = createDb(process.env.DATABASE_URL!);
prisma = db.prisma;
root = await mkdtemp(path.join(tmpdir(), "media-runtime-test-"));
});
afterAll(async () => {
if (!db) return;
await prisma.organization.deleteMany({ where: { id: { in: users } } });
await prisma.user.deleteMany({ where: { id: { in: users } } });
await prisma.$disconnect();
await db.pool.end();
await rm(root, { recursive: true, force: true });
});
async function setup(
options: {
run?: Run;
available?: () => Promise<boolean>;
gpu?: MediaOperationRegistration["gpu"];
runtime?: MediaRuntimeOptions;
} = {},
) {
const id = randomUUID();
users.push(id);
await prisma.user.create({
data: { id, name: "Media test", email: `${id}@example.test`, emailVerified: true },
});
await prisma.organization.create({
data: { id, name: "Media test", slug: id, createdAt: new Date() },
});
await prisma.space.create({
data: { id, organizationId: id, name: "Media test", isDefault: true },
});
await prisma.member.create({
data: { id, organizationId: id, userId: id, role: "owner", createdAt: new Date() },
});
const bot = await prisma.bot.create({
data: { spaceId: id, userId: id, name: "Studio", color: "test-color" },
});
const thread = await prisma.thread.create({ data: { spaceId: id, userId: id, botId: bot.id } });
const task = await prisma.task.create({
data: {
spaceId: id,
userId: id,
botId: bot.id,
threadId: thread.id,
prompt: "Make a picture",
status: "running",
},
});
const run = await prisma.run.create({
data: {
spaceId: id,
userId: id,
botId: bot.id,
threadId: thread.id,
taskId: task.id,
status: "running",
trigger: "user",
},
});
const artifacts = new LocalArtifactStore(path.join(root, id));
const enqueued: BackgroundJob[] = [];
const cancelled: string[] = [];
const jobs: JobPublisher = {
enqueue: async (job) => {
enqueued.push(job);
},
cancel: async (key) => {
cancelled.push(key);
},
close: async () => undefined,
};
const notify = vi.fn(async () => undefined);
const handlerCalls: string[] = [];
const defaultRun: Run = async (context) => {
const input = context.input as FakeInput;
if (input.source) await context.fetchArtifact(input.source);
await context.progress(0.5);
const file = path.join(context.tempDir, "out.png");
const poster = path.join(context.tempDir, "poster.jpg");
await writeFile(file, PNG);
await writeFile(poster, PNG);
await context.addOutput({
path: file,
name: "picture.png",
mimeType: "image/png",
width: 64,
height: 32,
posterPath: poster,
parentArtifactId: input.source,
});
return { summary: `Drew ${input.prompt}.` };
};
const registration: MediaOperationRegistration<FakeInput> = {
operation: "generate_image",
inputSchema: z.object({ prompt: z.string().min(1), source: z.string().optional() }),
title: (input) => input.prompt,
available: options.available ?? (async () => true),
artifactIds: (input) => (input.source ? [input.source] : []),
handler: {
operation: "generate_image",
run: async (context) => {
handlerCalls.push(context.jobId);
return (options.run ?? defaultRun)(context);
},
},
...(options.gpu ? { gpu: options.gpu } : {}),
};
const tempRoot = path.join(root, id, "tmp");
const runtimeDeps = {
prisma,
events: { notify },
jobs,
artifacts,
registrations: [registration as MediaOperationRegistration],
};
const runtimeOptions: MediaRuntimeOptions = {
tempRoot,
heartbeatMs: 50,
progressIntervalMs: 0,
...options.runtime,
};
const runtime = createMediaRuntime(runtimeDeps, runtimeOptions);
const start = (input: Record<string, unknown>, extra: Record<string, unknown> = {}) =>
runtime.start({
operation: "generate_image",
input,
spaceId: id,
userId: id,
botId: bot.id,
groupId: null,
threadId: thread.id,
runId: run.id,
...extra,
});
const job = (jobId: string) => prisma.mediaJob.findUniqueOrThrow({ where: { id: jobId } });
const card = async (jobId: string): Promise<MediaJobBlock> => {
const row = await job(jobId);
const message = await prisma.message.findUniqueOrThrow({ where: { id: row.messageId! } });
const block = (message.blocks as MessageBlock[]).find(
(entry): entry is MediaJobBlock => entry.kind === "media",
);
if (!block) throw new Error("media card missing");
return block;
};
const sourceArtifact = async () => {
const file = path.join(root, `${randomUUID()}.png`);
await writeFile(file, PNG);
return storeArtifactFromFile(
{ prisma, artifacts },
{
path: file,
name: "source.png",
mimeType: "image/png",
spaceId: id,
userId: id,
botId: bot.id,
groupId: null,
runId: null,
},
);
};
return {
id,
bot,
thread,
run,
runtime,
runtimeDeps,
runtimeOptions,
enqueued,
cancelled,
notify,
handlerCalls,
tempRoot,
start,
job,
card,
sourceArtifact,
};
}
it("runs a job to done, stores outputs with posters and versions, and cleans its temp dir", async () => {
const ctx = await setup();
const source = await ctx.sourceArtifact();
const started = await ctx.start({ prompt: "a red fox", source: source.id });
const queued = await ctx.card(started.jobId);
expect(queued).toMatchObject({ status: "queued", title: "a red fox", outputs: [] });
expect(ctx.enqueued.map((job) => job.name)).toEqual(["media.run"]);
expect(ctx.enqueued[0]).toMatchObject({ payload: { jobId: started.jobId }, queue: "media" });
const message = await prisma.message.findUniqueOrThrow({ where: { id: started.messageId } });
expect(message).toMatchObject({ role: "bot", botId: ctx.bot.id, runId: ctx.run.id });
await ctx.runtime.runJob(started.jobId);
const done = await ctx.job(started.jobId);
expect(done).toMatchObject({ status: "done", progress: 1, attempts: 1, leaseToken: null });
expect(done.finishedAt).toBeInstanceOf(Date);
const block = await ctx.card(started.jobId);
expect(block.status).toBe("done");
expect(block.outputs).toHaveLength(1);
const [output] = block.outputs;
expect(output).toMatchObject({
kind: "image",
mimeType: "image/png",
name: "picture.png",
size: PNG.byteLength,
width: 64,
height: 32,
parentArtifactId: source.id,
});
expect(done.outputArtifactIds).toEqual([output!.posterArtifactId, output!.artifactId]);
const stored = await prisma.artifact.findUniqueOrThrow({ where: { id: output!.artifactId } });
expect(stored).toMatchObject({
spaceId: ctx.id,
userId: ctx.id,
botId: ctx.bot.id,
runId: ctx.run.id,
parentArtifactId: source.id,
width: 64,
height: 32,
});
const events = await prisma.event.findMany({
where: { threadId: ctx.thread.id, type: "thread.message.updated" },
orderBy: { seq: "asc" },
});
const statuses = events.map(
(event) => ((event.payload as { blocks: MessageBlock[] }).blocks[0] as MediaJobBlock).status,
);
expect(statuses[0]).toBe("running");
expect(statuses.at(-1)).toBe("done");
expect(ctx.notify).toHaveBeenCalled();
expect(existsSync(path.join(ctx.tempRoot, started.jobId))).toBe(false);
// No wake without continue_after.
expect(
await prisma.run.count({ where: { trigger: MEDIA_WAKE_TRIGGER, spaceId: ctx.id } }),
).toBe(0);
expect(await ctx.runtime.get(started.jobId)).toMatchObject({
id: started.jobId,
status: "done",
outputs: block.outputs,
});
});
it("validates input, availability and readable artifacts before creating a job", async () => {
const ctx = await setup();
await expect(ctx.start({ prompt: "" })).rejects.toBeInstanceOf(MediaJobRejectedError);
await expect(ctx.start({ prompt: "x", source: "not-an-artifact" })).rejects.toThrow(
"Unknown artifact.",
);
const other = await setup();
const foreign = await other.sourceArtifact();
await expect(ctx.start({ prompt: "x", source: foreign.id })).rejects.toThrow(
"Unknown artifact.",
);
await expect(ctx.start({ prompt: "x" }, { threadId: other.thread.id })).rejects.toThrow(
"This conversation is no longer available.",
);
const unavailable = await setup({ available: async () => false });
await expect(unavailable.start({ prompt: "x" })).rejects.toThrow("not available");
expect(
await prisma.mediaJob.count({ where: { spaceId: { in: [ctx.id, unavailable.id] } } }),
).toBe(0);
});
it("returns the first job for a replayed tool call", async () => {
const ctx = await setup();
const first = await ctx.start({ prompt: "fox" }, { operationKey: `effect:${ctx.id}` });
const replay = await ctx.start({ prompt: "fox" }, { operationKey: `effect:${ctx.id}` });
expect(replay).toEqual(first);
expect(await prisma.mediaJob.count({ where: { spaceId: ctx.id } })).toBe(1);
});
it("fails a job with the operation's error and still cleans up", async () => {
let tempDir = "";
const ctx = await setup({
run: async (context) => {
tempDir = context.tempDir;
await writeFile(path.join(context.tempDir, "partial.bin"), PNG);
throw new Error(`ComfyUI rejected the workflow (${context.tempDir}/x)`);
},
});
const { jobId } = await ctx.start({ prompt: "fox" });
await ctx.runtime.runJob(jobId);
const failed = await ctx.job(jobId);
expect(failed.status).toBe("failed");
expect(failed.error).toBe("ComfyUI rejected the workflow (/x)");
expect((await ctx.card(jobId)).error).toBe(failed.error);
expect(existsSync(tempDir)).toBe(false);
});
it("refuses outputs outside the temp dir and sources of another user", async () => {
const other = await setup();
const foreign = await other.sourceArtifact();
const ctx = await setup({
run: async (context) => {
await context.fetchArtifact(foreign.id);
return { summary: "" };
},
});
const { jobId } = await ctx.start({ prompt: "fox" });
await ctx.runtime.runJob(jobId);
expect(await ctx.job(jobId)).toMatchObject({
status: "failed",
error: "A source file is no longer available.",
});
const outside = await setup({
run: async (context) => {
await context.addOutput({ path: "/etc/hostname", name: "x.png", mimeType: "image/png" });
return { summary: "" };
},
});
const escaped = await outside.start({ prompt: "fox" });
await outside.runtime.runJob(escaped.jobId);
expect((await outside.job(escaped.jobId)).status).toBe("failed");
expect(await prisma.artifact.count({ where: { spaceId: outside.id } })).toBe(0);
});
it("defers with backoff, then fails once the deferral budget is spent", async () => {
const ctx = await setup({
run: async () => {
throw new MediaJobDeferredError("ComfyUI queue is full", 2_000);
},
runtime: { maxDeferrals: 2 },
});
const { jobId } = await ctx.start({ prompt: "fox" });
const before = Date.now();
await ctx.runtime.runJob(jobId);
const waiting = await ctx.job(jobId);
expect(waiting).toMatchObject({ status: "waiting", deferrals: 1, leaseToken: null });
expect(waiting.nextAttemptAt!.getTime()).toBeGreaterThanOrEqual(before + 2_000);
expect((await ctx.card(jobId)).status).toBe("waiting");
const retry = ctx.enqueued.at(-1)!;
expect(retry).toMatchObject({ name: "media.run", payload: { jobId }, queue: "media" });
expect(retry.availableAt?.getTime()).toBe(waiting.nextAttemptAt!.getTime());
// Too early: the delayed job owns the next attempt.
await ctx.runtime.runJob(jobId);
expect(ctx.handlerCalls).toHaveLength(1);
await prisma.mediaJob.update({ where: { id: jobId }, data: { nextAttemptAt: new Date() } });
await ctx.runtime.runJob(jobId);
const second = await ctx.job(jobId);
expect(second).toMatchObject({ status: "waiting", deferrals: 2 });
// Backoff doubles.
expect(second.nextAttemptAt!.getTime() - Date.now()).toBeGreaterThan(3_000);
await prisma.mediaJob.update({ where: { id: jobId }, data: { nextAttemptAt: new Date() } });
await ctx.runtime.runJob(jobId);
expect(await ctx.job(jobId)).toMatchObject({
status: "failed",
error: "The media server stayed busy. Try again later.",
});
});
it("waits for free GPU memory before running the handler", async () => {
let free = 1_000;
const ctx = await setup({
gpu: {
minVramMb: 6_000,
status: async () => ({ vramFreeMb: free, vramTotalMb: 24_000 }),
},
});
const { jobId } = await ctx.start({ prompt: "fox" });
await ctx.runtime.runJob(jobId);
expect(ctx.handlerCalls).toHaveLength(0);
expect(await ctx.job(jobId)).toMatchObject({ status: "waiting", deferrals: 1 });
free = 20_000;
await prisma.mediaJob.update({ where: { id: jobId }, data: { nextAttemptAt: new Date() } });
await ctx.runtime.runJob(jobId);
expect(ctx.handlerCalls).toHaveLength(1);
expect((await ctx.job(jobId)).status).toBe("done");
});
it("cancels a queued job at once and a running job through the lease heartbeat", async () => {
const ctx = await setup({
run: async (context) => {
await new Promise<void>((resolve) => {
context.signal.addEventListener("abort", () => resolve(), { once: true });
});
context.signal.throwIfAborted();
return { summary: "" };
},
});
const queued = await ctx.start({ prompt: "queued" });
await ctx.runtime.cancel(queued.jobId);
expect(await ctx.job(queued.jobId)).toMatchObject({ status: "cancelled" });
expect((await ctx.card(queued.jobId)).status).toBe("cancelled");
expect(ctx.cancelled).toEqual([mediaRunJobKey(queued.jobId)]);
await ctx.runtime.runJob(queued.jobId);
expect(ctx.handlerCalls).toHaveLength(0);
// Another process (a second runtime) asks to cancel a job this one runs.
const running = await ctx.start({ prompt: "running" });
const runningJob = ctx.runtime.runJob(running.jobId);
await vi.waitFor(() => expect(ctx.handlerCalls).toEqual([running.jobId]));
const otherProcess = createMediaRuntime(ctx.runtimeDeps, ctx.runtimeOptions);
await otherProcess.cancel(running.jobId);
expect((await ctx.job(running.jobId)).status).toBe("running");
await runningJob;
expect(await ctx.job(running.jobId)).toMatchObject({ status: "cancelled", leaseToken: null });
expect((await ctx.card(running.jobId)).status).toBe("cancelled");
});
it("never runs one job twice and keeps one job on the GPU at a time", async () => {
const release = deferred();
const entered = deferred();
const ctx = await setup({
run: async () => {
entered.resolve();
await release.promise;
return { summary: "ok" };
},
});
const otherProcess = createMediaRuntime(ctx.runtimeDeps, ctx.runtimeOptions);
const first = await ctx.start({ prompt: "one" });
const second = await ctx.start({ prompt: "two" });
const a = ctx.runtime.runJob(first.jobId);
await entered.promise;
await otherProcess.runJob(first.jobId);
await otherProcess.runJob(second.jobId);
expect(ctx.handlerCalls).toEqual([first.jobId]);
expect(await ctx.job(second.jobId)).toMatchObject({ status: "waiting", attempts: 0 });
release.resolve();
await a;
await prisma.mediaJob.update({
where: { id: second.jobId },
data: { nextAttemptAt: new Date() },
});
await otherProcess.runJob(second.jobId);
expect(ctx.handlerCalls).toEqual([first.jobId, second.jobId]);
expect((await ctx.job(second.jobId)).status).toBe("done");
});
it("recovers a job whose runner died and fails it after too many restarts", async () => {
const ctx = await setup();
const { jobId } = await ctx.start({ prompt: "fox" });
const crashedAt = new Date(Date.now() - 1_000);
await prisma.mediaJob.update({
where: { id: jobId },
data: {
status: "running",
attempts: 1,
leaseToken: "dead-runner",
leaseExpiresAt: crashedAt,
updatedAt: crashedAt,
},
});
ctx.enqueued.length = 0;
await ctx.runtime.reconcile();
expect(ctx.enqueued).toEqual([
expect.objectContaining({ name: "media.run", payload: { jobId } }),
]);
await ctx.runtime.runJob(jobId);
expect(await ctx.job(jobId)).toMatchObject({ status: "done", attempts: 2 });
const doomed = await ctx.start({ prompt: "crashes" });
await prisma.mediaJob.update({
where: { id: doomed.jobId },
data: {
status: "running",
attempts: 3,
leaseToken: "dead-runner",
leaseExpiresAt: crashedAt,
},
});
await ctx.runtime.runJob(doomed.jobId);
expect(await ctx.job(doomed.jobId)).toMatchObject({
status: "failed",
error: "The job was interrupted. Try again.",
});
expect(ctx.handlerCalls).toEqual([jobId]);
});
it("re-enqueues lost and overdue jobs, outside the queue once they look stuck", async () => {
const ctx = await setup();
const fresh = await ctx.start({ prompt: "fresh" });
const lost = await ctx.start({ prompt: "lost" });
const stuck = await ctx.start({ prompt: "stuck" });
const minuteAgo = new Date(Date.now() - 60_000);
const hourAgo = new Date(Date.now() - 3_600_000);
await prisma.mediaJob.update({
where: { id: lost.jobId },
data: { updatedAt: minuteAgo, createdAt: minuteAgo },
});
await prisma.mediaJob.update({
where: { id: stuck.jobId },
data: { updatedAt: hourAgo, createdAt: hourAgo },
});
ctx.enqueued.length = 0;
await ctx.runtime.reconcile();
const byJob = new Map(
ctx.enqueued.map((job) => [(job.payload as { jobId: string }).jobId, job]),
);
expect(byJob.has(fresh.jobId)).toBe(false);
expect(byJob.get(lost.jobId)).toMatchObject({ queue: "media", availableAt: minuteAgo });
expect(byJob.get(stuck.jobId)?.queue).toBeUndefined();
});
it("wakes the starting bot with the result when continue_after is set", async () => {
const ctx = await setup();
const { jobId } = await ctx.start({ prompt: "fox" }, { continueAfter: true });
ctx.enqueued.length = 0;
await ctx.runtime.runJob(jobId);
const wake = await prisma.run.findFirstOrThrow({
where: { spaceId: ctx.id, trigger: MEDIA_WAKE_TRIGGER },
include: { task: true },
});
expect(wake).toMatchObject({ botId: ctx.bot.id, threadId: ctx.thread.id, status: "queued" });
expect(wake.task.prompt).toContain(`Media job ${jobId}`);
expect(wake.task.prompt).toContain("Drew fox.");
expect(wake.task.prompt).toContain("picture.png");
expect(ctx.enqueued).toEqual([
expect.objectContaining({ name: "run.continue", payload: { runId: wake.id } }),
]);
});
it("cancels a job whose conversation was cleared without running it", async () => {
const ctx = await setup();
const { jobId } = await ctx.start({ prompt: "fox" }, { continueAfter: true });
await prisma.run.update({ where: { id: ctx.run.id }, data: { status: "completed" } });
await clearThread(prisma, { spaceId: ctx.id, botId: ctx.bot.id, threadId: ctx.thread.id });
await ctx.runtime.runJob(jobId);
expect(ctx.handlerCalls).toHaveLength(0);
expect(await ctx.job(jobId)).toMatchObject({ status: "cancelled" });
expect(
await prisma.run.count({ where: { spaceId: ctx.id, trigger: MEDIA_WAKE_TRIGGER } }),
).toBe(0);
});
it("fails a job that outlives its run limit", async () => {
const ctx = await setup({
run: async (context) => {
await new Promise((resolve) => setTimeout(resolve, 5_000));
context.signal.throwIfAborted();
return { summary: "" };
},
runtime: { maxRunMs: 50, abortGraceMs: 20 },
});
const { jobId } = await ctx.start({ prompt: "slow" });
await ctx.runtime.runJob(jobId);
expect(await ctx.job(jobId)).toMatchObject({
status: "failed",
error: "The job took too long.",
});
expect(await readdir(ctx.tempRoot)).toEqual([]);
});
it("reports which operations a space can run", async () => {
const ctx = await setup();
const capabilities = await ctx.runtime.capabilities(ctx.id);
expect(capabilities.generate_image).toBe(true);
expect(capabilities.transcribe).toBe(false);
const broken = await setup({
available: async () => {
throw new Error("probe failed");
},
});
expect((await broken.runtime.capabilities(broken.id)).generate_image).toBe(false);
});
});

View File

@ -1,7 +1,11 @@
import { createHash, randomUUID } from "node:crypto";
import { mkdir, readFile, rm, stat, writeFile } from "node:fs/promises";
import { randomUUID } from "node:crypto";
import { constants, createWriteStream } from "node:fs";
import { copyFile, mkdir, rm } from "node:fs/promises";
import { tmpdir } from "node:os";
import path from "node:path";
import { Readable } from "node:stream";
import { pipeline } from "node:stream/promises";
import type { ReadableStream as NodeReadableStream } from "node:stream/web";
import type {
AdapterContext,
ArtifactStore,
@ -17,13 +21,13 @@ import type {
StartMediaJobInput,
} from "@rakazo/adapter-kit";
import {
ArtifactTooLargeError,
MediaJobDeferredError,
mediaRunJob,
mediaRunJobKey,
runContinueJob,
} from "@rakazo/adapter-kit";
import {
ARTIFACT_MAX_BYTES_BY_KIND,
attachmentKindOf,
MEDIA_JOB_ACTIVE_STATUSES,
type MediaJobBlock,
@ -33,11 +37,7 @@ import {
type MediaOutput,
type MessageBlock,
} from "@rakazo/contracts";
import {
attachmentExtensionForMimeType,
inferAttachmentMimeType,
validateAttachmentMimeType,
} from "@rakazo/core";
import { attachmentExtensionForMimeType, inferAttachmentMimeType } from "@rakazo/core";
import {
appendEventInTransaction,
createThreadMessageInTransaction,
@ -49,6 +49,7 @@ import {
} from "@rakazo/db";
import { getLogger } from "@rakazo/logging";
import type { z } from "zod";
import { storeArtifactFromFile } from "./artifact-files.js";
/** Run trigger of the turn that wakes a bot when its media job ends (`continue_after`). */
export const MEDIA_WAKE_TRIGGER = "media";
@ -505,6 +506,7 @@ export function createMediaRuntime(
const storeArtifactFile = async (
job: MediaJob,
signal: AbortSignal,
file: {
path: string;
name: string;
@ -515,38 +517,37 @@ export function createMediaRuntime(
parentArtifactId?: string;
},
) => {
// Swap point for the streaming artifact store: until it lands, files go through put().
const bytes = new Uint8Array(await readFile(file.path));
const context = artifactContext(job, `media-output:${job.id}`);
const stored = await deps.artifacts.put(
{ name: file.name, mimeType: file.mimeType, bytes },
context,
);
try {
return await deps.prisma.artifact.create({
data: {
spaceId: job.spaceId,
userId: job.userId,
botId: job.botId,
groupId: job.groupId,
runId: job.runId,
name: file.name,
mimeType: file.mimeType,
size: bytes.byteLength,
hash: createHash("sha256").update(bytes).digest("hex"),
storageKey: stored.id,
width: file.width,
height: file.height,
durationMs: file.durationMs,
parentArtifactId: file.parentArtifactId,
},
return await storeArtifactFromFile(deps, {
...file,
spaceId: job.spaceId,
userId: job.userId,
botId: job.botId,
groupId: job.groupId,
runId: job.runId,
signal,
});
} catch (error) {
await deps.artifacts.remove(stored.id, context).catch(() => undefined);
if (error instanceof ArtifactTooLargeError) throw new MediaJobRejectedError(TOO_LARGE_ERROR);
throw error;
}
};
/** Copies a stored artifact to `file`: a clone of the local file when possible, else a stream. */
const copyArtifact = async (job: MediaJob, storageKey: string, file: string) => {
const context = artifactContext(job, `media-input:${job.id}`);
const local = await deps.artifacts.localPath?.(storageKey, context).catch(() => undefined);
if (local) {
await copyFile(local, file, constants.COPYFILE_EXCL | constants.COPYFILE_FICLONE);
return;
}
const stream = await deps.artifacts.createReadStream(storageKey, context);
await pipeline(
Readable.fromWeb(stream as NodeReadableStream<Uint8Array>),
createWriteStream(file, { flags: "wx", mode: 0o600 }),
);
};
const removeArtifacts = async (job: MediaJob, ids: string[]) => {
const rows = await deps.prisma.artifact.findMany({
where: { id: { in: ids }, spaceId: job.spaceId },
@ -657,12 +658,7 @@ export function createMediaRuntime(
attachmentExtensionForMimeType(row.mimeType) ||
(/^\.[a-z0-9]{1,8}$/i.test(path.extname(row.name)) ? path.extname(row.name) : "");
const file = path.join(tempDir, `input-${row.id}${extension.toLowerCase()}`);
// Swap point for the streaming artifact store (localPath / createReadStream).
const bytes = await deps.artifacts.get(
row.storageKey,
artifactContext(job, `media-input:${job.id}`),
);
await writeFile(file, bytes, { mode: 0o600, flag: "wx" });
await copyArtifact(job, row.storageKey, file);
const input: MediaJobInputFile = {
artifactId: row.id,
path: file,
@ -679,12 +675,8 @@ export function createMediaRuntime(
},
addOutput: async (file: MediaJobOutputFile) => {
signal.throwIfAborted();
validateAttachmentMimeType(file.mimeType);
const kind = attachmentKindOf(file.mimeType);
const filePath = insideDir(tempDir, file.path);
const size = (await stat(filePath)).size;
if (size > ARTIFACT_MAX_BYTES_BY_KIND[kind])
throw new MediaJobRejectedError(TOO_LARGE_ERROR);
const parent = file.parentArtifactId
? await deps.prisma.artifact.findFirst({
where: { id: file.parentArtifactId, spaceId: job.spaceId, userId: job.userId },
@ -702,7 +694,7 @@ export function createMediaRuntime(
const posterName = `${path.parse(name).name}-poster${path.extname(posterPath).toLowerCase()}`;
const posterMime = inferAttachmentMimeType(posterName);
if (posterMime && attachmentKindOf(posterMime) === "image") {
const poster = await storeArtifactFile(job, {
const poster = await storeArtifactFile(job, signal, {
path: posterPath,
name: posterName,
mimeType: posterMime,
@ -716,7 +708,7 @@ export function createMediaRuntime(
const width = positiveInt(file.width);
const height = positiveInt(file.height);
const durationMs = nonNegativeInt(file.durationMs);
const artifact = await storeArtifactFile(job, {
const artifact = await storeArtifactFile(job, signal, {
path: filePath,
name,
mimeType: file.mimeType,

View File

@ -1,10 +1,6 @@
import {
type MediaSettings,
MediaSettingsSchema,
type MediaSettingsUpdate,
MediaSettingsUpdateSchema,
type MediaSettingsView,
} from "@rakazo/contracts";
import type { MediaSettings, MediaSettingsUpdate, MediaSettingsView } from "@rakazo/contracts";
import { MediaSettingsSchema, MediaSettingsUpdateSchema } from "@rakazo/contracts";
import { parseWorkflowTemplate } from "@rakazo/core/media/workflows";
import type { PrismaClient } from "@rakazo/db";
import {
assertAllowedOpenAiCompatibleRequestUrl,
@ -82,31 +78,59 @@ function keptKey(
return new URL(previous.baseUrl).origin === new URL(baseUrl).origin ? previous.apiKey : undefined;
}
/** A media setting the deployment owner has to correct; the message says what is wrong. */
export class MediaSettingsInvalidError extends Error {
constructor(message: string) {
super(message);
this.name = "MediaSettingsInvalidError";
}
}
function assertValidWorkflow(label: string, workflow: string | undefined): void {
if (!workflow) return;
try {
parseWorkflowTemplate(workflow);
} catch (error) {
throw new Error(`${label}: ${error instanceof Error ? error.message : String(error)}`);
}
}
function resolveSettings(previous: MediaSettings, update: MediaSettingsUpdate): MediaSettings {
const parsed = MediaSettingsUpdateSchema.parse(update);
try {
assertValidWorkflow("Image workflow", parsed.comfyui?.imageWorkflow);
assertValidWorkflow("Video workflow", parsed.comfyui?.videoWorkflow);
let comfyui: MediaSettings["comfyui"] = null;
if (parsed.comfyui) {
const baseUrl = normalizeComfyUiBaseUrl(parsed.comfyui.baseUrl);
const apiKey = keptKey(parsed.comfyui.apiKey, previous.comfyui, baseUrl);
assertHttpsForKeyedOpenAiCompatibleUrl(new URL(baseUrl), apiKey);
comfyui = { ...parsed.comfyui, baseUrl, apiKey };
}
let transcription: MediaSettings["transcription"] = null;
if (parsed.transcription) {
const baseUrl = normalizeTranscriptionBaseUrl(parsed.transcription.baseUrl);
const apiKey = keptKey(parsed.transcription.apiKey, previous.transcription, baseUrl);
assertHttpsForKeyedOpenAiCompatibleUrl(new URL(baseUrl), apiKey);
transcription = { ...parsed.transcription, baseUrl, apiKey };
}
return MediaSettingsSchema.parse({ comfyui, transcription });
} catch (error) {
throw new MediaSettingsInvalidError(
error instanceof Error ? error.message : "These media settings are not valid",
);
}
}
/**
* Validates and stores the media backends (deployment owner only; the caller authorizes).
* Throws an Error with a user-facing message when a URL is not allowed.
* Throws MediaSettingsInvalidError when a URL is not allowed.
*/
export async function saveMediaSettings(
deps: MediaSettingsDeps,
update: MediaSettingsUpdate,
): Promise<MediaSettingsView> {
const parsed = MediaSettingsUpdateSchema.parse(update);
const previous = await loadMediaSettings(deps);
let comfyui: MediaSettings["comfyui"] = null;
if (parsed.comfyui) {
const baseUrl = normalizeComfyUiBaseUrl(parsed.comfyui.baseUrl);
const apiKey = keptKey(parsed.comfyui.apiKey, previous.comfyui, baseUrl);
assertHttpsForKeyedOpenAiCompatibleUrl(new URL(baseUrl), apiKey);
comfyui = { ...parsed.comfyui, baseUrl, apiKey };
}
let transcription: MediaSettings["transcription"] = null;
if (parsed.transcription) {
const baseUrl = normalizeTranscriptionBaseUrl(parsed.transcription.baseUrl);
const apiKey = keptKey(parsed.transcription.apiKey, previous.transcription, baseUrl);
assertHttpsForKeyedOpenAiCompatibleUrl(new URL(baseUrl), apiKey);
transcription = { ...parsed.transcription, baseUrl, apiKey };
}
const settings = MediaSettingsSchema.parse({ comfyui, transcription });
const settings = resolveSettings(await loadMediaSettings(deps), update);
if (!settings.comfyui && !settings.transcription) {
await deps.prisma.integrationProviderConfig.deleteMany({ where: { id: MEDIA_SETTINGS_ID } });
return mediaSettingsView(settings);

View File

@ -0,0 +1,125 @@
import type { MediaCapabilities, MediaRuntime, StartMediaJobInput } from "@rakazo/adapter-kit";
import { describe, expect, it, vi } from "vitest";
import { selectBuiltinToolsForRun } from "./executor-tools.js";
import { MediaJobRejectedError } from "./media-runtime.js";
import {
executeMediaTool,
isMediaToolName,
MEDIA_CONTINUE_AFTER_PROPERTY,
mediaToolInputSchema,
selectMediaTools,
} from "./media-tools.js";
const none: MediaCapabilities = {
generate_image: false,
generate_video: false,
edit_image: false,
edit_video: false,
export_video: false,
transcribe: false,
};
const scope = {
spaceId: "space-1",
userId: "user-1",
botId: "bot-1",
groupId: null,
threadId: "thread-1",
runId: "run-1",
operationKey: "effect-1",
};
function runtime(start: MediaRuntime["start"]): MediaRuntime {
return {
capabilities: async () => none,
start,
get: async () => null,
cancel: async () => undefined,
};
}
describe("media tools", () => {
it("names tools after their operations", () => {
expect(isMediaToolName("generate_image")).toBe(true);
expect(isMediaToolName("transcribe")).toBe(true);
expect(isMediaToolName("render_plot")).toBe(false);
});
it("shows a media tool only when the space can run its operation", () => {
const tools = [{ name: "generate_image" }, { name: "transcribe" }, { name: "web_search" }];
expect(selectMediaTools(tools, undefined).map((tool) => tool.name)).toEqual(["web_search"]);
expect(selectMediaTools(tools, { ...none, transcribe: true }).map((tool) => tool.name)).toEqual(
["transcribe", "web_search"],
);
});
it("leaves non-media tools of a run untouched", () => {
const base = {
graphicalToolsAllowed: true,
groupId: null,
trigger: "user",
semanticMemoryEnabled: false,
messagingChannelRun: false,
bot: { kind: "specialist", restrictBuiltinTools: false, allowedBuiltinTools: [] },
};
const names = (mediaCapabilities?: MediaCapabilities) =>
selectBuiltinToolsForRun({ ...base, mediaCapabilities })
.map((tool) => tool.name)
.filter((name) => !isMediaToolName(name));
expect(names({ ...none, generate_image: true, transcribe: true })).toEqual(names(undefined));
expect(selectBuiltinToolsForRun(base).some((tool) => isMediaToolName(tool.name))).toBe(false);
});
it("adds continue_after to every media tool schema", () => {
expect(
mediaToolInputSchema({
properties: { prompt: { type: "string" } },
required: ["prompt"],
}),
).toEqual({
type: "object",
properties: { prompt: { type: "string" }, ...MEDIA_CONTINUE_AFTER_PROPERTY },
required: ["prompt"],
});
});
it("starts the job with the tool scope and returns at once", async () => {
const start = vi.fn(async (_input: StartMediaJobInput) => ({
jobId: "job-1",
messageId: "message-1",
}));
const result = await executeMediaTool(runtime(start), scope, "generate_image", {
prompt: "a fox",
continue_after: true,
});
expect(start).toHaveBeenCalledWith({
operation: "generate_image",
input: { prompt: "a fox" },
...scope,
continueAfter: true,
});
expect(result).toMatchObject({ jobId: "job-1", status: "queued" });
expect((result as { note: string }).note).toContain("woken");
await executeMediaTool(runtime(start), scope, "generate_image", { prompt: "a fox" });
expect(start.mock.calls[1]?.[0]).toMatchObject({ continueAfter: false });
});
it("returns refusals to the model and rethrows other failures", async () => {
const refused = runtime(async () => {
throw new MediaJobRejectedError("Invalid generate_image input: prompt: Required");
});
expect(await executeMediaTool(refused, scope, "generate_image", {})).toEqual({
error: "Invalid generate_image input: prompt: Required",
});
expect(await executeMediaTool(undefined, scope, "transcribe", {})).toEqual({
error: "transcribe is not available.",
});
const broken = runtime(async () => {
throw new Error("database down");
});
await expect(executeMediaTool(broken, scope, "transcribe", {})).rejects.toThrow(
"database down",
);
});
});

View File

@ -0,0 +1,28 @@
import { describe, expect, it } from "vitest";
import { saveMediaSettings } from "../media-settings.js";
const comfyui = (workflows: { imageWorkflow?: string; videoWorkflow?: string }) => ({
comfyui: { baseUrl: "http://127.0.0.1:8188", ...workflows },
transcription: null,
});
describe("ComfyUI settings", () => {
it("refuses custom workflows the provider could not fill", async () => {
const deps = {} as Parameters<typeof saveMediaSettings>[0];
await expect(
saveMediaSettings(
deps,
comfyui({ imageWorkflow: '{"1": {"class_type": "X", "inputs": {}}}' }),
),
).rejects.toThrow("Image workflow: Workflow needs a {{prompt}} placeholder");
await expect(
saveMediaSettings(
deps,
comfyui({
videoWorkflow:
'{"1": {"class_type": "X", "inputs": {"t": "{{prompt}}", "c": "{{cfg}}"}}}',
}),
),
).rejects.toThrow("Video workflow: Unknown workflow placeholders: {{cfg}}");
});
});

View File

@ -0,0 +1,110 @@
import sharp from "sharp";
import { describe, expect, it } from "vitest";
import { editImageGeometry, encodeImage, imageSize } from "./image-edit.js";
/** Left half red, right half blue. */
async function halves(width = 40, height = 20): Promise<Buffer> {
const half = Math.floor(width / 2);
const blue = await sharp({
create: { width: width - half, height, channels: 3, background: { r: 0, g: 0, b: 255 } },
})
.png()
.toBuffer();
return sharp({ create: { width, height, channels: 3, background: { r: 255, g: 0, b: 0 } } })
.composite([{ input: blue, left: half, top: 0 }])
.png()
.toBuffer();
}
async function pixel(image: Uint8Array, x: number, y: number) {
const { data, info } = await sharp(image).raw().toBuffer({ resolveWithObject: true });
const offset = (y * info.width + x) * info.channels;
return [...data.subarray(offset, offset + info.channels)];
}
async function size(image: Uint8Array) {
const { width, height } = await sharp(image).metadata();
return [width, height];
}
describe("editImageGeometry", () => {
it("applies crop before rotate, in source coordinates", async () => {
const result = await editImageGeometry(await halves(), {
crop: { left: 20, top: 0, width: 20, height: 10 },
rotate: 90,
});
expect(await size(result)).toEqual([10, 20]);
expect((await pixel(result, 5, 5)).slice(0, 3)).toEqual([0, 0, 255]);
});
it("flips horizontally and vertically", async () => {
const flopped = await editImageGeometry(await halves(), { flip: "horizontal" });
expect((await pixel(flopped, 0, 0)).slice(0, 3)).toEqual([0, 0, 255]);
const flipped = await editImageGeometry(await halves(), { flip: "vertical" });
expect((await pixel(flipped, 0, 0)).slice(0, 3)).toEqual([255, 0, 0]);
});
it("resizes to a preset with crop, pad or blur, and keeps the aspect for one side", async () => {
const source = await halves(160, 90);
for (const fit of ["crop", "pad", "blur"] as const) {
const result = await editImageGeometry(source, { resize: { aspect: "square", fit } });
expect(await size(result)).toEqual([1080, 1080]);
}
const padded = await editImageGeometry(source, { resize: { aspect: "vertical", fit: "pad" } });
expect((await pixel(padded, 0, 0)).at(-1)).toBe(0);
const scaled = await editImageGeometry(source, { resize: { width: 80, fit: "crop" } });
expect(await size(scaled)).toEqual([80, 45]);
});
it("extends with a color or transparency", async () => {
const colored = await editImageGeometry(await halves(), {
extend: { top: 5, right: 0, bottom: 0, left: 3, color: "#00ff00" },
});
expect(await size(colored)).toEqual([43, 25]);
expect((await pixel(colored, 0, 0)).slice(0, 3)).toEqual([0, 255, 0]);
const clear = await editImageGeometry(await halves(), {
extend: { top: 2, right: 2, bottom: 2, left: 2 },
});
expect((await pixel(clear, 0, 0)).at(-1)).toBe(0);
});
it("applies EXIF orientation first", async () => {
const rotatedJpeg = await sharp(await halves())
.jpeg()
.withMetadata({ orientation: 6 })
.toBuffer();
expect(await imageSize(rotatedJpeg)).toEqual({ width: 20, height: 40 });
expect(await size(await editImageGeometry(rotatedJpeg, { flip: "vertical" }))).toEqual([
20, 40,
]);
});
it("refuses crops outside the image and oversized results", async () => {
await expect(
editImageGeometry(await halves(), { crop: { left: 30, top: 0, width: 20, height: 10 } }),
).rejects.toThrow("The crop area is outside the 40×20 image");
await expect(
editImageGeometry(await halves(), {
extend: { top: 9000, right: 0, bottom: 0, left: 9000 },
}),
).rejects.toThrow("The edited image would be too large");
await expect(
editImageGeometry(await halves(), { resize: { width: 8192, height: 8193, fit: "crop" } }),
).rejects.toThrow("The edited image would be too large");
});
});
describe("encodeImage", () => {
it("encodes each format and flattens transparency for JPEG", async () => {
const clear = await editImageGeometry(await halves(), {
extend: { top: 2, right: 0, bottom: 0, left: 0 },
});
for (const format of ["png", "jpeg", "webp"] as const) {
const encoded = await encodeImage(clear, format);
expect((await sharp(encoded.bytes).metadata()).format).toBe(format);
expect([encoded.width, encoded.height]).toEqual([40, 22]);
}
const jpeg = await encodeImage(clear, "jpeg");
expect((await pixel(jpeg.bytes, 0, 0)).every((channel) => channel < 16)).toBe(true);
});
});

View File

@ -0,0 +1,156 @@
import type { EditImageInput, ImageFormat } from "@rakazo/contracts";
import { MEDIA_PRESETS } from "@rakazo/contracts";
import type sharpFactory from "sharp";
import type { Sharp } from "sharp";
type SharpFactory = typeof sharpFactory;
export type ImageGeometryEdits = Pick<
EditImageInput,
"crop" | "rotate" | "flip" | "resize" | "extend"
>;
/** Edited images stay below this many pixels (8192²). */
const MAX_EDIT_PIXELS = 8192 * 8192;
const TRANSPARENT = { r: 0, g: 0, b: 0, alpha: 0 };
const BLACK = { r: 0, g: 0, b: 0 };
let sharpModule: Promise<SharpFactory> | undefined;
/** sharp is a native module; load it on first use so a platform without it only loses edits. */
export function loadSharp(): Promise<SharpFactory> {
sharpModule ??= import("sharp").then((module) => module.default);
return sharpModule;
}
export async function sharpAvailable(): Promise<boolean> {
return loadSharp().then(
() => true,
() => false,
);
}
/** Displayed size, with EXIF orientation applied. */
export async function imageSize(
input: string | Uint8Array,
): Promise<{ width: number; height: number }> {
const sharp = await loadSharp();
const { autoOrient } = await sharp(input).metadata();
return { width: autoOrient.width, height: autoOrient.height };
}
/** Covers exactly width×height (center crop) as PNG: generation inputs at the size asked for. */
export async function coverImage(
input: string | Uint8Array,
width: number,
height: number,
): Promise<Uint8Array> {
const sharp = await loadSharp();
const png = await sharp(input, { autoOrient: true })
.resize(width, height, { fit: "cover" })
.png()
.toBuffer();
return new Uint8Array(png);
}
function parseColor(hex: string | undefined) {
if (!hex) return TRANSPARENT;
const value = Number.parseInt(hex.slice(1), 16);
return { r: (value >> 16) & 255, g: (value >> 8) & 255, b: value & 255, alpha: 1 };
}
function assertSize(width: number, height: number): void {
if (width * height > MAX_EDIT_PIXELS) throw new Error("The edited image would be too large");
}
/** Runs each step on decoded pixels, so steps apply in the order given, not sharp's own order. */
async function materialize(sharp: SharpFactory, image: Sharp) {
const { data, info } = await image.raw().toBuffer({ resolveWithObject: true });
const { width, height, channels } = info;
return { image: sharp(data, { raw: { width, height, channels } }), width, height };
}
async function resizeTo(
sharp: SharpFactory,
image: Sharp,
width: number,
height: number,
fit: "crop" | "pad" | "blur",
): Promise<Sharp> {
if (fit === "crop") return image.resize(width, height, { fit: "cover" });
if (fit === "pad")
return image.resize(width, height, { fit: "contain", background: TRANSPARENT });
const source = await image.png().toBuffer();
const background = await sharp(source)
.resize(width, height, { fit: "cover" })
.blur(Math.max(width, height) / 40)
.toBuffer();
const foreground = await sharp(source).resize(width, height, { fit: "inside" }).toBuffer();
return sharp(background).composite([{ input: foreground, gravity: "centre" }]);
}
/**
* Applies crop, rotate, flip, resize and extend in that order and returns a lossless PNG.
* EXIF orientation is applied first, so coordinates match what viewers show.
*/
export async function editImageGeometry(
input: string | Uint8Array,
edits: ImageGeometryEdits,
): Promise<Buffer> {
const sharp = await loadSharp();
let current = await materialize(sharp, sharp(input, { autoOrient: true }));
const step = async (apply: (image: Sharp) => Sharp | Promise<Sharp>) => {
current = await materialize(sharp, await apply(current.image));
};
const { crop, rotate, flip, resize, extend } = edits;
if (crop) {
if (crop.left + crop.width > current.width || crop.top + crop.height > current.height) {
throw new Error(`The crop area is outside the ${current.width}×${current.height} image`);
}
await step((image) => image.extract(crop));
}
if (rotate) await step((image) => image.rotate(rotate));
if (flip) await step((image) => (flip === "vertical" ? image.flip() : image.flop()));
if (resize) {
const preset = resize.aspect ? MEDIA_PRESETS[resize.aspect] : undefined;
const width = preset?.width ?? resize.width;
const height = preset?.height ?? resize.height;
const scale = width ? width / current.width : height! / current.height;
assertSize(width ?? current.width * scale, height ?? current.height * scale);
await step((image) =>
width && height
? resizeTo(sharp, image, width, height, resize.fit)
: image.resize(width ?? null, height ?? null),
);
}
if (extend) {
const { top, right, bottom, left, color } = extend;
assertSize(current.width + left + right, current.height + top + bottom);
await step((image) =>
image.extend({ top, right, bottom, left, background: parseColor(color) }),
);
}
return current.image.png().toBuffer();
}
export const IMAGE_FORMAT_MIME_TYPES: Record<ImageFormat, string> = {
png: "image/png",
jpeg: "image/jpeg",
webp: "image/webp",
};
/** Encodes the final image; JPEG has no transparency, so transparent areas turn black. */
export async function encodeImage(
input: Uint8Array,
format: ImageFormat,
): Promise<{ bytes: Buffer; width: number; height: number }> {
const sharp = await loadSharp();
const image = sharp(input);
const encoded =
format === "jpeg"
? image.flatten({ background: BLACK }).jpeg({ quality: 90, mozjpeg: true })
: format === "webp"
? image.webp({ quality: 90 })
: image.png();
const { data, info } = await encoded.toBuffer({ resolveWithObject: true });
return { bytes: data, width: info.width, height: info.height };
}

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@ -0,0 +1,172 @@
import { randomUUID } from "node:crypto";
import { mkdtemp, rm } from "node:fs/promises";
import { tmpdir } from "node:os";
import { join } from "node:path";
import type { JobPublisher } from "@rakazo/adapter-kit";
import type { MediaJobBlock, MessageBlock } from "@rakazo/contracts";
import { ComfyUiSettingsSchema } from "@rakazo/contracts";
import type { PrismaClient } from "@rakazo/db";
import { createDb } from "@rakazo/db";
import { afterAll, beforeAll, describe, expect, it } from "vitest";
import { LocalArtifactStore } from "../artifacts.js";
import { createMediaRuntime, MediaJobRejectedError } from "../media-runtime.js";
import { ComfyUiEmulator } from "../testing/comfyui-emulator.js";
import { createImageOperations } from "./image-operations.js";
const describePostgres =
process.env.VERIFY_DATABASE && process.env.DATABASE_URL ? describe.sequential : describe.skip;
describePostgres("ComfyUI operations in the media runtime (PostgreSQL + ComfyUI emulator)", () => {
let db: ReturnType<typeof createDb>;
let prisma: PrismaClient;
let root: string;
const users: string[] = [];
beforeAll(async () => {
db = createDb(process.env.DATABASE_URL!);
prisma = db.prisma;
root = await mkdtemp(join(tmpdir(), "image-operations-pg-"));
});
afterAll(async () => {
if (!db) return;
await prisma.mediaJob.deleteMany({ where: { userId: { in: users } } });
await prisma.artifact.deleteMany({ where: { userId: { in: users } } });
await prisma.organization.deleteMany({ where: { id: { in: users } } });
await prisma.user.deleteMany({ where: { id: { in: users } } });
await prisma.$disconnect();
await db.pool.end();
await rm(root, { recursive: true, force: true });
});
async function setup() {
const id = randomUUID();
users.push(id);
await prisma.user.create({
data: { id, name: "Media test", email: `${id}@example.test`, emailVerified: true },
});
await prisma.organization.create({
data: { id, name: "Media test", slug: id, createdAt: new Date() },
});
await prisma.space.create({ data: { id, organizationId: id, name: "Media", isDefault: true } });
await prisma.member.create({
data: { id, organizationId: id, userId: id, role: "owner", createdAt: new Date() },
});
const bot = await prisma.bot.create({
data: { spaceId: id, userId: id, name: "Studio", color: "test-color" },
});
const thread = await prisma.thread.create({ data: { spaceId: id, userId: id, botId: bot.id } });
const emulator = new ComfyUiEmulator();
emulator.pendingPolls = 0;
const jobs: JobPublisher = {
enqueue: async () => undefined,
cancel: async () => undefined,
close: async () => undefined,
};
const runtime = createMediaRuntime(
{
prisma,
events: { notify: async () => undefined },
jobs,
artifacts: new LocalArtifactStore(join(root, id, "artifacts")),
registrations: createImageOperations({
loadSettings: async () => ({
comfyui: ComfyUiSettingsSchema.parse({ baseUrl: "http://127.0.0.1:8188" }),
transcription: null,
}),
fetch: emulator.fetch,
}),
},
{ tempRoot: join(root, id, "jobs") },
);
const scope = {
spaceId: id,
userId: id,
botId: bot.id,
groupId: null,
threadId: thread.id,
runId: null,
};
return { emulator, runtime, scope };
}
async function card(messageId: string, jobId: string): Promise<MediaJobBlock | undefined> {
const message = await prisma.message.findUniqueOrThrow({ where: { id: messageId } });
return (message.blocks as MessageBlock[]).find(
(block): block is MediaJobBlock => block.kind === "media" && block.jobId === jobId,
);
}
it("generates images onto the card and edits one into a linked version", async () => {
const { runtime, scope } = await setup();
const generated = await runtime.start({
...scope,
operation: "generate_image",
input: { prompt: "a lighthouse at dusk", aspect: "landscape", count: 2, seed: 3 },
});
await runtime.runJob(generated.jobId);
const job = await runtime.get(generated.jobId);
expect(job).toMatchObject({ status: "done", title: "a lighthouse at dusk" });
expect(job?.outputs.map((output) => [output.mimeType, output.width, output.height])).toEqual([
["image/png", 1344, 768],
["image/png", 1344, 768],
]);
expect(await card(generated.messageId, generated.jobId)).toMatchObject({
status: "done",
outputs: job?.outputs,
});
const source = job!.outputs[0]!.artifactId;
const edited = await runtime.start({
...scope,
operation: "edit_image",
input: { artifactId: source, resize: { aspect: "vertical", fit: "blur" }, format: "jpeg" },
});
await runtime.runJob(edited.jobId);
const edit = await runtime.get(edited.jobId);
expect(edit).toMatchObject({ status: "done", title: "9:16 · JPEG" });
const [output] = edit!.outputs;
expect(output).toMatchObject({ mimeType: "image/jpeg", width: 1080, height: 1920 });
const artifact = await prisma.artifact.findUniqueOrThrow({ where: { id: output!.artifactId } });
expect(artifact).toMatchObject({ parentArtifactId: source, width: 1080, height: 1920 });
});
it("refuses source artifacts the user cannot read", async () => {
const { runtime, scope } = await setup();
const other = await setup();
const generated = await other.runtime.start({
...other.scope,
operation: "generate_image",
input: { prompt: "private" },
});
await other.runtime.runJob(generated.jobId);
const foreign = (await other.runtime.get(generated.jobId))!.outputs[0]!.artifactId;
await expect(
runtime.start({
...scope,
operation: "generate_video",
input: { prompt: "animate it", sourceArtifactId: foreign },
}),
).rejects.toThrow(MediaJobRejectedError);
await expect(
runtime.start({
...scope,
operation: "edit_image",
input: { artifactId: foreign, rotate: 90 },
}),
).rejects.toThrow(MediaJobRejectedError);
});
it("waits while the GPU lacks free memory", async () => {
const { emulator, runtime, scope } = await setup();
emulator.gpu = { totalMb: 24_576, freeMb: 4_000, torchReservedMb: 0, torchFreeMb: 0 };
const video = await runtime.start({
...scope,
operation: "generate_video",
input: { prompt: "rain on a window" },
});
await runtime.runJob(video.jobId);
expect(await runtime.get(video.jobId)).toMatchObject({ status: "waiting", outputs: [] });
expect(emulator.prompts).toHaveLength(0);
});
});

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import { copyFile, mkdtemp, rm, stat, writeFile } from "node:fs/promises";
import { tmpdir } from "node:os";
import { join } from "node:path";
import type { MediaJobContext, MediaJobOutputFile } from "@rakazo/adapter-kit";
import { MediaJobDeferredError } from "@rakazo/adapter-kit";
import type { ComfyUiSettings, MediaOutput } from "@rakazo/contracts";
import { attachmentKindOf, ComfyUiSettingsSchema } from "@rakazo/contracts";
import sharp from "sharp";
import { afterEach, describe, expect, it } from "vitest";
import { ComfyUiEmulator } from "../testing/comfyui-emulator.js";
import {
createImageOperations,
editImageTitle,
fileStem,
generationSize,
IMAGE_GENERATION_MIN_VRAM_MB,
VIDEO_GENERATION_MIN_VRAM_MB,
} from "./image-operations.js";
const dirs: string[] = [];
afterEach(async () => {
await Promise.all(dirs.splice(0).map((dir) => rm(dir, { recursive: true, force: true })));
});
async function tempDir(): Promise<string> {
const dir = await mkdtemp(join(tmpdir(), "image-operations-"));
dirs.push(dir);
return dir;
}
async function fixture(name: string, width: number, height: number): Promise<string> {
const path = join(await tempDir(), name);
const image = sharp({
create: { width, height, channels: 3, background: { r: 200, g: 120, b: 40 } },
});
await writeFile(path, await (name.endsWith(".jpg") ? image.jpeg() : image.png()).toBuffer());
return path;
}
function setup(
settings: ComfyUiSettings | null = ComfyUiSettingsSchema.parse({
baseUrl: "http://127.0.0.1:8188",
}),
) {
const emulator = new ComfyUiEmulator();
emulator.pendingPolls = 0;
const operations = createImageOperations({
loadSettings: async () => ({ comfyui: settings, transcription: null }),
fetch: emulator.fetch,
});
const operation = (name: string) => operations.find((entry) => entry.operation === name)!;
return { emulator, operations, operation };
}
async function run(
operation: ReturnType<typeof setup>["operation"],
name: string,
input: unknown,
artifacts: Record<string, string> = {},
) {
const dir = await tempDir();
const outputs: MediaJobOutputFile[] = [];
const progress: number[] = [];
const context: MediaJobContext = {
jobId: "job-1",
spaceId: "space-1",
userId: "user-1",
botId: null,
input,
tempDir: dir,
signal: new AbortController().signal,
progress: async (fraction) => {
progress.push(fraction);
},
fetchArtifact: async (artifactId) => {
const source = artifacts[artifactId];
if (!source) throw new Error("Artifact not found");
const name = source.split("/").at(-1)!;
const path = join(dir, `input-${name}`);
await copyFile(source, path);
const mimeType = name.endsWith(".jpg")
? "image/jpeg"
: name.endsWith(".mp4")
? "video/mp4"
: "image/png";
return {
artifactId,
path,
name,
mimeType,
kind: attachmentKindOf(mimeType),
size: (await stat(path)).size,
};
},
addOutput: async (file) => {
outputs.push(file);
const output: MediaOutput = {
artifactId: `output-${outputs.length}`,
kind: attachmentKindOf(file.mimeType),
mimeType: file.mimeType,
name: file.name,
size: (await stat(file.path)).size,
};
return output;
},
};
const result = await operation(name).handler.run(context);
return { result, outputs, progress };
}
describe("image operations", () => {
it("are available by configuration and guard the GPU", async () => {
const configured = setup();
expect(configured.operations.map((entry) => entry.operation)).toEqual([
"generate_image",
"generate_video",
"edit_image",
]);
for (const entry of configured.operations) {
await expect(entry.available({ spaceId: "space-1" })).resolves.toBe(true);
}
const generateImage = configured.operation("generate_image");
expect(generateImage.gpu?.minVramMb).toBe(IMAGE_GENERATION_MIN_VRAM_MB);
expect(configured.operation("generate_video").gpu?.minVramMb).toBe(
VIDEO_GENERATION_MIN_VRAM_MB,
);
await expect(generateImage.gpu?.status()).resolves.toEqual({
vramFreeMb: 20_000,
vramTotalMb: 24_576,
});
const unconfigured = setup(null);
await expect(
unconfigured.operation("generate_image").available({ spaceId: "s" }),
).resolves.toBe(false);
await expect(unconfigured.operation("edit_image").available({ spaceId: "s" })).resolves.toBe(
true,
);
await expect(run(unconfigured.operation, "generate_image", { prompt: "x" })).rejects.toThrow(
"ComfyUI is not configured",
);
});
it("generates images at the aspect asked for", async () => {
const { operation } = setup();
const { result, outputs, progress } = await run(operation, "generate_image", {
prompt: "A red kite, über the sea!",
aspect: "vertical",
count: 2,
seed: 11,
continue_after: true,
});
expect(
outputs.map(({ name, mimeType, width, height }) => [name, mimeType, width, height]),
).toEqual([
["a-red-kite-uber-the-sea-1.png", "image/png", 768, 1344],
["a-red-kite-uber-the-sea-2.png", "image/png", 768, 1344],
]);
expect(progress.at(-1)).toBe(1);
expect(result.summary).toBe("Generated 2 images with seed 11.");
});
it("starts from a source image at the source's aspect and links the result to it", async () => {
const { operation, emulator } = setup();
const photo = await fixture("photo.jpg", 300, 200);
const { outputs } = await run(
operation,
"generate_image",
{ prompt: "night", sourceArtifactId: "photo-1" },
{ "photo-1": photo },
);
const [upload] = emulator.uploads.values();
expect((await sharp(upload!).metadata()).width).toBe(1280);
expect(outputs[0]).toMatchObject({ width: 1280, height: 832, parentArtifactId: "photo-1" });
const clip = await fixture("clip.mp4", 8, 8);
await expect(
run(operation, "generate_image", { prompt: "x", sourceArtifactId: "c" }, { c: clip }),
).rejects.toThrow("The source must be an image");
});
it("generates video in the preset's aspect", async () => {
const { operation, emulator } = setup();
const { outputs, result } = await run(operation, "generate_video", {
prompt: "paper boat on a river",
aspect: "vertical",
});
expect(outputs).toEqual([
expect.objectContaining({
name: "paper-boat-on-a-river.mp4",
mimeType: "video/mp4",
width: 480,
height: 832,
durationMs: 5042,
}),
]);
expect(emulator.prompts[0]?.graph["6"]?.inputs).toMatchObject({ width: 480, height: 832 });
expect(result.summary).toMatch(/^Generated a 5 s video with seed \d+\.$/);
});
it("edits locally in order and keeps the source as parent", async () => {
const { operation, emulator } = setup(null);
const photo = await fixture("photo.jpg", 400, 300);
const { outputs, result } = await run(
operation,
"edit_image",
{
artifactId: "photo-1",
crop: { left: 0, top: 0, width: 300, height: 300 },
rotate: 90,
resize: { aspect: "vertical", fit: "blur" },
format: "webp",
},
{ "photo-1": photo },
);
expect(outputs).toEqual([
expect.objectContaining({
name: "photo-edit.webp",
mimeType: "image/webp",
width: 1080,
height: 1920,
parentArtifactId: "photo-1",
}),
]);
expect((await sharp(outputs[0]!.path).metadata()).format).toBe("webp");
expect(result.summary).toBe("Edited photo.jpg into photo-edit.webp (1080×1920).");
expect(emulator.requests).toHaveLength(0);
await expect(
run(operation, "edit_image", { artifactId: "photo-1", prompt: "snow" }, { "photo-1": photo }),
).rejects.toThrow("ComfyUI is not configured");
});
it("repaints an edit on ComfyUI at the edited size, deferring while the GPU is busy", async () => {
const { operation, emulator } = setup();
const photo = await fixture("photo.png", 300, 200);
const input = {
artifactId: "photo-1",
crop: { left: 0, top: 0, width: 250, height: 200 },
prompt: "snow",
};
const { outputs } = await run(operation, "edit_image", input, { "photo-1": photo });
expect(outputs[0]).toMatchObject({ name: "photo-edit.png", width: 250, height: 200 });
const [upload] = emulator.uploads.values();
expect(await sharp(upload!).metadata()).toMatchObject({ width: 1152, height: 896 });
emulator.gpu = { totalMb: 24_576, freeMb: 2_000, torchReservedMb: 0, torchFreeMb: 0 };
await expect(run(operation, "edit_image", input, { "photo-1": photo })).rejects.toBeInstanceOf(
MediaJobDeferredError,
);
});
});
describe("helpers", () => {
it("sizes generations near the pixel budget", () => {
expect(generationSize(1, 1024 * 1024, 64)).toEqual({ width: 1024, height: 1024 });
expect(generationSize(16 / 9, 768 * 512, 32)).toEqual({ width: 832, height: 480 });
expect(generationSize(21 / 9, 1024 * 1024, 64)).toEqual({ width: 1536, height: 640 });
});
it("names files and titles edits briefly", () => {
expect(fileStem(" Ünïcode — Straße 42 at night, very long prompt here ", "image")).toBe(
"unicode-strasse-42-at-night-very",
);
expect(fileStem("夜の海", "video")).toBe("video");
expect(
editImageTitle({
artifactId: "a",
crop: { left: 0, top: 0, width: 1, height: 1 },
rotate: 90,
resize: { aspect: "vertical", fit: "crop" },
format: "png",
}),
).toBe("crop · 90° · 9:16 · PNG");
expect(editImageTitle({ artifactId: "a", resize: { width: 800, fit: "crop" } })).toBe("800×…");
expect(editImageTitle({ artifactId: "a", prompt: "make it snow" })).toBe("make it snow");
});
});

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import { randomInt } from "node:crypto";
import { writeFile } from "node:fs/promises";
import { join } from "node:path";
import type {
GeneratedMedia,
GpuStatus,
MediaJobContext,
MediaJobInputFile,
MediaOperationResult,
} from "@rakazo/adapter-kit";
import { MediaJobDeferredError } from "@rakazo/adapter-kit";
import type {
EditImageInput,
GenerateImageInput,
GenerateVideoInput,
ImageFormat,
MediaPresetId,
} from "@rakazo/contracts";
import {
attachmentKindOf,
EditImageInputSchema,
GenerateImageInputSchema,
GenerateVideoInputSchema,
MEDIA_PRESETS,
} from "@rakazo/contracts";
import { attachmentExtensionForMimeType } from "@rakazo/core";
import type { ComfyUiProvider } from "../comfyui-provider.js";
import { createComfyUiProvider } from "../comfyui-provider.js";
import type { MediaOperationDeps } from "../media-operations.js";
import type { MediaOperationRegistration } from "../media-runtime.js";
import {
coverImage,
editImageGeometry,
encodeImage,
IMAGE_FORMAT_MIME_TYPES,
imageSize,
sharpAvailable,
} from "./image-edit.js";
/** Free GPU memory a generation needs before it starts; fixed, so a custom workflow cannot lower it. */
export const IMAGE_GENERATION_MIN_VRAM_MB = 6_000;
export const VIDEO_GENERATION_MIN_VRAM_MB = 12_000;
/** Pixel budgets the default workflows are tuned for (SDXL-class images, LTX-Video clips). */
const IMAGE_PIXELS = 1024 * 1024;
const VIDEO_PIXELS = 768 * 512;
const GPU_RETRY_MS = 60_000;
export interface ImageOperationsDeps extends MediaOperationDeps {
/** Tests point the provider at an emulator. */
fetch?: typeof globalThis.fetch;
}
type ProviderSource = () => Promise<ComfyUiProvider | null>;
/** A size close to `pixels` with this aspect ratio, in multiples of `multiple`. */
export function generationSize(aspect: number, pixels: number, multiple: number) {
return {
width: Math.max(multiple, Math.round(Math.sqrt(pixels * aspect) / multiple) * multiple),
height: Math.max(multiple, Math.round(Math.sqrt(pixels / aspect) / multiple) * multiple),
};
}
function presetAspect(preset: MediaPresetId): number {
return MEDIA_PRESETS[preset].width / MEDIA_PRESETS[preset].height;
}
/** File name stem from a prompt: its first words in lowercase ASCII. */
export function fileStem(text: string, fallback: string): string {
const words = text
.normalize("NFKD")
.replace(/\p{M}/gu, "")
.toLowerCase()
.replace(/ß/g, "ss")
.match(/[a-z0-9]+/g);
return words?.slice(0, 6).join("-").slice(0, 48).replace(/-+$/, "") || fallback;
}
/** Short card title for an edit without a prompt, such as "crop · 9:16 · PNG". */
export function editImageTitle(input: EditImageInput): string {
if (input.prompt) return input.prompt;
const { resize } = input;
const parts = [
input.crop && "crop",
input.rotate && `${input.rotate}°`,
input.flip && "flip",
resize &&
(resize.aspect
? MEDIA_PRESETS[resize.aspect].aspect
: `${resize.width ?? "…"}×${resize.height ?? "…"}`),
input.extend && "extend",
input.format?.toUpperCase(),
];
return parts.filter(Boolean).join(" · ");
}
function reportProgress(context: MediaJobContext) {
return (fraction: number) => {
context.progress(fraction).catch(() => undefined);
};
}
async function requireProvider(source: ProviderSource): Promise<ComfyUiProvider> {
const provider = await source();
if (!provider) throw new Error("ComfyUI is not configured");
return provider;
}
/** Defers instead of starting a generation the GPU has no room for right now. */
async function assertGpuReady(
provider: ComfyUiProvider,
minVramMb: number,
signal: AbortSignal,
): Promise<void> {
const status: GpuStatus | undefined = await provider.gpuStatus(signal);
if (status && status.vramFreeMb < Math.min(minVramMb, status.vramTotalMb)) {
throw new MediaJobDeferredError("Waiting for free GPU memory", GPU_RETRY_MS);
}
}
async function fetchImage(
context: MediaJobContext,
artifactId: string,
): Promise<MediaJobInputFile & { width: number; height: number }> {
const file = await context.fetchArtifact(artifactId);
if (file.kind !== "image") throw new Error("The source must be an image");
return { ...file, ...(await imageSize(file.path)) };
}
async function addGeneratedOutputs(
context: MediaJobContext,
results: GeneratedMedia[],
stem: string,
parentArtifactId: string | undefined,
): Promise<void> {
for (const [index, result] of results.entries()) {
const extension = attachmentExtensionForMimeType(result.mimeType);
const name = `${stem}${results.length > 1 ? `-${index + 1}` : ""}${extension}`;
const path = join(context.tempDir, name);
await writeFile(path, result.bytes);
const size =
attachmentKindOf(result.mimeType) === "image"
? await imageSize(path)
: { width: result.width, height: result.height };
await context.addOutput({
path,
name,
mimeType: result.mimeType,
...size,
...(result.durationMs !== undefined ? { durationMs: result.durationMs } : {}),
...(parentArtifactId ? { parentArtifactId } : {}),
});
}
}
async function generateImage(
context: MediaJobContext,
providers: ProviderSource,
): Promise<MediaOperationResult> {
const input = GenerateImageInputSchema.parse(context.input);
const provider = await requireProvider(providers);
const source = input.sourceArtifactId
? await fetchImage(context, input.sourceArtifactId)
: undefined;
const aspect = input.aspect
? presetAspect(input.aspect)
: source
? source.width / source.height
: 1;
const size =
input.width && input.height
? { width: input.width, height: input.height }
: generationSize(aspect, IMAGE_PIXELS, 64);
const seed = input.seed ?? randomInt(2 ** 48 - 1);
const images = await provider.generateImage({
prompt: input.prompt,
negativePrompt: input.negativePrompt,
...size,
count: input.count,
seed,
source: source && {
bytes: await coverImage(source.path, size.width, size.height),
mimeType: "image/png",
},
strength: input.strength,
signal: context.signal,
onProgress: reportProgress(context),
});
await addGeneratedOutputs(context, images, fileStem(input.prompt, "image"), source?.artifactId);
const count = images.length === 1 ? "1 image" : `${images.length} images`;
return { summary: `Generated ${count} with seed ${seed}.` };
}
async function generateVideo(
context: MediaJobContext,
providers: ProviderSource,
): Promise<MediaOperationResult> {
const input = GenerateVideoInputSchema.parse(context.input);
const provider = await requireProvider(providers);
const source = input.sourceArtifactId
? await fetchImage(context, input.sourceArtifactId)
: undefined;
const aspect = input.aspect
? presetAspect(input.aspect)
: source
? source.width / source.height
: presetAspect("landscape");
const size = generationSize(aspect, VIDEO_PIXELS, 32);
const seed = input.seed ?? randomInt(2 ** 48 - 1);
const clips = await provider.generateVideo({
prompt: input.prompt,
negativePrompt: input.negativePrompt,
...size,
durationSeconds: input.durationSeconds,
seed,
source: source && {
bytes: await coverImage(source.path, size.width, size.height),
mimeType: "image/png",
},
signal: context.signal,
onProgress: reportProgress(context),
});
await addGeneratedOutputs(context, clips, fileStem(input.prompt, "video"), source?.artifactId);
return { summary: `Generated a ${input.durationSeconds} s video with seed ${seed}.` };
}
function defaultFormat(mimeType: string): ImageFormat {
if (mimeType === "image/jpeg") return "jpeg";
if (mimeType === "image/webp") return "webp";
return "png";
}
async function editImage(
context: MediaJobContext,
providers: ProviderSource,
): Promise<MediaOperationResult> {
const input = EditImageInputSchema.parse(context.input);
const source = await fetchImage(context, input.artifactId);
let png: Uint8Array = await editImageGeometry(source.path, input);
if (input.prompt) {
const provider = await requireProvider(providers);
await assertGpuReady(provider, IMAGE_GENERATION_MIN_VRAM_MB, context.signal);
const { width, height } = await imageSize(png);
// Repaint near the model's native size, then return to the edited size.
const size = generationSize(width / height, IMAGE_PIXELS, 64);
const [repainted] = await provider.generateImage({
prompt: input.prompt,
...size,
source: { bytes: await coverImage(png, size.width, size.height), mimeType: "image/png" },
strength: input.strength,
signal: context.signal,
onProgress: reportProgress(context),
});
if (!repainted) throw new Error("ComfyUI produced no image");
png = await coverImage(repainted.bytes, width, height);
}
const format = input.format ?? defaultFormat(source.mimeType);
const encoded = await encodeImage(png, format);
const mimeType = IMAGE_FORMAT_MIME_TYPES[format];
const stem = source.name.replace(/\.[^.]+$/, "") || "image";
const name = `${stem}-edit${attachmentExtensionForMimeType(mimeType)}`;
const path = join(context.tempDir, name);
await writeFile(path, encoded.bytes);
await context.addOutput({
path,
name,
mimeType,
width: encoded.width,
height: encoded.height,
parentArtifactId: source.artifactId,
});
return { summary: `Edited ${source.name} into ${name} (${encoded.width}×${encoded.height}).` };
}
/**
* Media operations for image and video generation on ComfyUI and for image edits with sharp.
* Generation is available when ComfyUI is configured; edits whenever sharp loads (repainting
* an edit also needs ComfyUI).
*/
export function createImageOperations(deps: ImageOperationsDeps): MediaOperationRegistration[] {
const providers: ProviderSource = async () => {
const { comfyui } = await deps.loadSettings();
return comfyui ? createComfyUiProvider({ ...comfyui, fetch: deps.fetch }) : null;
};
const comfyUiConfigured = async () => Boolean((await deps.loadSettings()).comfyui);
const status = async (signal?: AbortSignal) => (await providers())?.gpuStatus(signal);
const sourceIds = (input: { sourceArtifactId?: string }) =>
input.sourceArtifactId ? [input.sourceArtifactId] : [];
const image: MediaOperationRegistration<GenerateImageInput> = {
operation: "generate_image",
inputSchema: GenerateImageInputSchema,
title: (input) => input.prompt,
available: comfyUiConfigured,
handler: { operation: "generate_image", run: (context) => generateImage(context, providers) },
gpu: { minVramMb: IMAGE_GENERATION_MIN_VRAM_MB, status },
artifactIds: sourceIds,
};
const video: MediaOperationRegistration<GenerateVideoInput> = {
operation: "generate_video",
inputSchema: GenerateVideoInputSchema,
title: (input) => input.prompt,
available: comfyUiConfigured,
handler: { operation: "generate_video", run: (context) => generateVideo(context, providers) },
gpu: { minVramMb: VIDEO_GENERATION_MIN_VRAM_MB, status },
artifactIds: sourceIds,
};
const edit: MediaOperationRegistration<EditImageInput> = {
operation: "edit_image",
inputSchema: EditImageInputSchema,
title: editImageTitle,
available: sharpAvailable,
handler: { operation: "edit_image", run: (context) => editImage(context, providers) },
artifactIds: (input) => [input.artifactId],
};
return [image, video, edit] as MediaOperationRegistration[];
}

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import { createHash } from "node:crypto";
/** A 1 s, 32×32 H.264 MP4 (ffmpeg testsrc), small enough to inline. */
const TINY_MP4_BASE64 = [
"AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAM+bW9vdgAAAGxtdmhkAAAAAAAAAAAAAAAAAAAD6AAAA+gAAQAAAQAA",
"AAAAAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgAA",
"Ao10cmFrAAAAXHRraGQAAAADAAAAAAAAAAAAAAABAAAAAAAAA+gAAAAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAABAAAA",
"AAAAAAAAAAAAAABAAAAAACAAAAAgAAAAAAAkZWR0cwAAABxlbHN0AAAAAAAAAAEAAAPoAAAQAAABAAAAAAIFbWRpYQAAACBtZGhk",
"AAAAAAAAAAAAAAAAAABAAAAAQABVxAAAAAAALWhkbHIAAAAAAAAAAHZpZGUAAAAAAAAAAAAAAABWaWRlb0hhbmRsZXIAAAABsG1p",
"bmYAAAAUdm1oZAAAAAEAAAAAAAAAAAAAACRkaW5mAAAAHGRyZWYAAAAAAAAAAQAAAAx1cmwgAAAAAQAAAXBzdGJsAAAAwHN0c2QA",
"AAAAAAAAAQAAALBhdmMxAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAACAAIABIAAAASAAAAAAAAAABDExhdmMgbGlieDI2NAAAAAAA",
"AAAAAAAAAAAAAAAAAAAAGP//AAAANmF2Y0MBZAAK/+EAGGdkAAqscgRJbARAAAADAEAAAAQDxIlhGAEAB2joQ4OSyLD9+PgAAAAA",
"EHBhc3AAAAABAAAAAQAAABRidHJ0AAAAAAAADAgAAAwIAAAAGHN0dHMAAAAAAAAAAQAAAAgAAAgAAAAAFHN0c3MAAAAAAAAAAQAA",
"AAEAAAAYY3R0cwAAAAAAAAABAAAACAAAEAAAAAAcc3RzYwAAAAAAAAABAAAAAQAAAAgAAAABAAAANHN0c3oAAAAAAAAAAAAAAAgA",
"AADTAAAADAAAABgAAAAdAAAAGgAAAB0AAAAfAAAAFwAAABRzdGNvAAAAAAAAAAEAAANuAAAAPXVkdGEAAAA1bWV0YQAAAAAAAAAh",
"aGRscgAAAAAAAAAAbWRpcmFwcGwAAAAAAAAAAAAAAAAIaWxzdAAAAAhmcmVlAAABiW1kYXQAAADPZYiBABP/115QL0x5O3/uan23",
"okcn80QwiyZelIq0iY0T1naTwGHVgXgsN7YBwlEikXvo+AyEjKk/afikvNFJbO7NjVpKr2f7e+xmO5rxkaelhrWKVT83gKOM5wKs",
"QoFpCKDo56fFf6IYs3U1LAHAxZY3IIAUCFca5RyJ/ibKbmkxBCXXiBuUCCuL9FhMjcqhW2misGdpwuLgknHPr/37MowWA2zcOn9B",
"OHR5mfgyt4/0x3o95hpnI+2axZFkXHhYwK55h134UUvr+r3B9b/xAAAACEGaCC2JP6KAAAAAFEGaEEvwIGTKYTe7qicJ6jU1YvCB",
"AAAAGUGaGGk8CB5MpgTfu1UOB2sZPRDVFTCp+IAAAAAWQZogiXwIH5MpgER/wf8hVV5nVt8U2QAAABlBmiipvAgf5MpgBFfFjke1",
"iXbU9gFuIojBAAAAG0GaMMn8CB/5MpgARn/KNfso3F7XaeLq3d3VjQAAABNBmjjojwIH/5MpgAEIf9P6j9Ph",
].join("");
export const COMFYUI_EMULATOR_MP4 = new Uint8Array(Buffer.from(TINY_MP4_BASE64, "base64"));
const MIB = 1024 * 1024;
type EmulatedNode = { class_type: string; inputs: Record<string, unknown> };
type EmulatedGraph = Record<string, EmulatedNode>;
type FileRef = { filename: string; subfolder: string; type: string };
interface EmulatedPrompt {
id: string;
graph: EmulatedGraph;
polls: number;
failure?: string;
interrupted?: boolean;
/** Dropped from the queue before it ran. */
removed?: boolean;
/** Reported as finished by the history. */
done?: boolean;
outputs?: Record<string, Record<string, unknown>>;
}
export interface EmulatedComfyUiRequest {
method: string;
path: string;
authorization: string | null;
body?: unknown;
}
function isRecord(value: unknown): value is Record<string, unknown> {
return Boolean(value) && typeof value === "object" && !Array.isArray(value);
}
function json(body: unknown, status = 200): Response {
return Response.json(body, { status });
}
/**
* In-process substitute for a ComfyUI server's HTTP API, so the real provider runs in offline
* tests: it validates submitted workflows like ComfyUI does, "runs" them after a few history
* polls, and returns small generated PNGs or an MP4 fixture.
*/
export class ComfyUiEmulator {
readonly requests: EmulatedComfyUiRequest[] = [];
readonly prompts: EmulatedPrompt[] = [];
readonly uploads = new Map<string, Uint8Array>();
readonly deleted: string[] = [];
readonly interrupted: string[] = [];
checkpoints = ["sd_xl_base_1.0.safetensors", "ltx-video-2b-v0.9.5.safetensors"];
/** `options` answers like current ComfyUI (`["COMBO", {options}]`), `legacy` like older ones. */
checkpointListFormat: "options" | "legacy" = "options";
/** null reports a CPU-only server. */
gpu: { totalMb: number; freeMb: number; torchReservedMb: number; torchFreeMb: number } | null = {
totalMb: 24_576,
freeMb: 20_000,
torchReservedMb: 0,
torchFreeMb: 0,
};
/** History polls that still report a submitted prompt as running. */
pendingPolls = 1;
/** Answer the next request with this HTTP status. */
failNextStatus: number | undefined;
/** Fail the next submitted prompt while it runs, with this exception message. */
failNextExecution: string | undefined;
private readonly files = new Map<string, Uint8Array>();
private nextPrompt = 1;
/** `basePath` serves the API under a prefix, like ComfyUI behind a reverse proxy. */
constructor(private readonly options: { apiKey?: string; basePath?: string } = {}) {}
readonly fetch: typeof fetch = async (input, init) => {
init?.signal?.throwIfAborted();
const url = new URL(input instanceof Request ? input.url : String(input));
const method = init?.method ?? "GET";
const headers = new Headers(init?.headers);
const authorization = headers.get("authorization");
const prefix = `/${(this.options.basePath ?? "").replace(/^\/+|\/+$/g, "")}/`.replace(
"//",
"/",
);
if (!url.pathname.startsWith(prefix)) return json({ error: "Not found" }, 404);
const path = url.pathname.slice(prefix.length);
const body =
typeof init?.body === "string" && headers.get("content-type")?.includes("json")
? JSON.parse(init.body)
: undefined;
this.requests.push({ method, path, authorization, body });
if (this.failNextStatus) {
const status = this.failNextStatus;
this.failNextStatus = undefined;
return new Response("Upstream failure", { status });
}
if (this.options.apiKey && authorization !== `Bearer ${this.options.apiKey}`) {
return json({ error: "Unauthorized" }, 401);
}
const route = `${method} ${path.split("/")[0]}`;
if (route === "GET system_stats") return this.systemStats();
if (route === "GET object_info" && path === "object_info/CheckpointLoaderSimple") {
return this.checkpointInfo();
}
if (route === "POST prompt") return this.submit(body);
if (route === "GET history") return this.history(decodeURIComponent(path.slice(8)));
if (route === "GET view") return this.view(url.searchParams);
if (route === "POST upload") return this.upload(input, init);
if (route === "GET queue") return this.queue();
if (route === "POST queue") {
for (const id of Array.isArray(body?.delete) ? body.delete : []) {
this.deleted.push(id);
// Like ComfyUI, deleting only drops pending prompts; a running one needs an interrupt.
const prompt = this.prompts.find((entry) => entry.id === id);
if (prompt && prompt !== this.unfinished()[0]) prompt.removed = true;
}
return json({});
}
if (route === "POST interrupt") {
const id = String(body?.prompt_id ?? "");
this.interrupted.push(id);
const running = this.unfinished()[0];
if (running && (!id || running.id === id)) running.interrupted = true;
return json({});
}
return json({ error: "Not found" }, 404);
};
private systemStats(): Response {
const gpu = this.gpu;
return json({
system: { os: "posix", comfyui_version: "0.3.60", embedded_python: false },
devices: [
gpu
? {
name: "cuda:0 Emulated GPU",
type: "cuda",
index: 0,
vram_total: gpu.totalMb * MIB,
vram_free: gpu.freeMb * MIB,
torch_vram_total: gpu.torchReservedMb * MIB,
torch_vram_free: gpu.torchFreeMb * MIB,
}
: { name: "cpu", type: "cpu", index: null, vram_total: 64 * 1024 * MIB, vram_free: 0 },
],
});
}
private checkpointInfo(): Response {
const spec =
this.checkpointListFormat === "legacy"
? [this.checkpoints, { tooltip: "Checkpoint" }]
: ["COMBO", { options: this.checkpoints, tooltip: "Checkpoint" }];
return json({
CheckpointLoaderSimple: {
input: { required: { ckpt_name: spec } },
output: ["MODEL", "CLIP", "VAE"],
name: "CheckpointLoaderSimple",
},
});
}
private submit(body: unknown): Response {
const graph = isRecord(body) ? body.prompt : undefined;
if (!isRecord(graph) || typeof (body as { client_id?: unknown }).client_id !== "string") {
return json(
{ error: { type: "invalid_prompt", message: "Cannot execute because prompt is invalid" } },
400,
);
}
const nodeErrors: Record<string, unknown> = {};
const reject = (id: string, node: unknown, message: string, details: string) => {
nodeErrors[id] = {
errors: [{ type: "invalid", message, details, extra_info: {} }],
dependent_outputs: [],
class_type: isRecord(node) ? node.class_type : undefined,
};
};
for (const [id, node] of Object.entries(graph)) {
if (!isRecord(node) || typeof node.class_type !== "string" || !isRecord(node.inputs)) {
reject(id, node, "Invalid node", "class_type and inputs are required");
continue;
}
for (const [name, value] of Object.entries(node.inputs)) {
if (typeof value === "string" && value.includes("{{")) {
reject(id, node, "Unfilled placeholder", `${name}: ${value}`);
}
if (Array.isArray(value) && !isRecord(graph[String(value[0])])) {
reject(id, node, "Missing linked node", `${name}: ${String(value[0])}`);
}
}
const checkpoint = node.inputs.ckpt_name;
if (typeof checkpoint === "string" && !this.checkpoints.includes(checkpoint)) {
reject(id, node, "Value not in list", `ckpt_name: '${checkpoint}' not in list`);
}
if (node.class_type === "LoadImage" && !this.uploads.has(String(node.inputs.image))) {
reject(id, node, "Invalid image file", `image - ${String(node.inputs.image)}`);
}
}
if (Object.keys(nodeErrors).length > 0) {
return json(
{
error: {
type: "prompt_outputs_failed_validation",
message: "Prompt outputs failed validation",
},
node_errors: nodeErrors,
},
400,
);
}
const id = `prompt-${this.nextPrompt++}`;
this.prompts.push({
id,
graph: graph as EmulatedGraph,
polls: 0,
failure: this.failNextExecution,
});
this.failNextExecution = undefined;
return json({ prompt_id: id, number: this.nextPrompt, node_errors: {} });
}
private async history(id: string): Promise<Response> {
const prompt = this.prompts.find((entry) => entry.id === id);
if (!prompt || prompt.removed) return json({});
if (!prompt.done && !prompt.interrupted && prompt.polls < this.pendingPolls) {
prompt.polls += 1;
return json({});
}
prompt.done = true;
if (prompt.interrupted) {
return json({
[id]: {
prompt: [0, id, prompt.graph, {}, []],
outputs: {},
status: {
status_str: "error",
completed: false,
messages: [["execution_interrupted", { prompt_id: id, node_id: "5" }]],
},
},
});
}
if (prompt.failure) {
return json({
[id]: {
prompt: [0, id, prompt.graph, {}, []],
outputs: {},
status: {
status_str: "error",
completed: false,
messages: [
["execution_start", { prompt_id: id }],
[
"execution_error",
{
prompt_id: id,
node_id: "5",
node_type: "KSampler",
exception_message: prompt.failure,
exception_type: "RuntimeError",
traceback: ["..."],
},
],
],
},
},
});
}
prompt.outputs ??= await this.execute(prompt);
return json({
[id]: {
prompt: [0, id, prompt.graph, {}, Object.keys(prompt.outputs)],
outputs: prompt.outputs,
status: { status_str: "success", completed: true, messages: [] },
},
});
}
private async execute(prompt: EmulatedPrompt): Promise<Record<string, Record<string, unknown>>> {
const outputs: Record<string, Record<string, unknown>> = {};
let counter = 0;
const save = (bytes: Uint8Array, extension: string, type: string): FileRef => {
counter += 1;
const ref = {
filename: `${prompt.id}_${String(counter).padStart(5, "0")}_.${extension}`,
subfolder: type === "output" ? "evoo" : "",
type,
};
this.files.set(fileKey(ref), bytes);
return ref;
};
for (const [id, node] of Object.entries(prompt.graph)) {
if (node.class_type === "SaveImage" || node.class_type === "PreviewImage") {
const type = node.class_type === "SaveImage" ? "output" : "temp";
outputs[id] = { images: [save(await this.renderImage(prompt.graph), "png", type)] };
} else if (node.class_type === "SaveVideo") {
outputs[id] = { images: [save(COMFYUI_EMULATOR_MP4, "mp4", "output")], animated: [true] };
} else if (node.class_type === "VHS_VideoCombine") {
outputs[id] = { gifs: [save(COMFYUI_EMULATOR_MP4, "mp4", "output")] };
}
}
return outputs;
}
/** A flat color derived from the seed, at the workflow's size (or its input image's). */
private async renderImage(graph: EmulatedGraph): Promise<Uint8Array> {
const { default: sharp } = await import("sharp");
const nodes = Object.values(graph);
const input = (name: string) =>
nodes.map((node) => node.inputs[name]).find((value) => typeof value === "number");
let width = Number(input("width") ?? 0);
let height = Number(input("height") ?? 0);
const loaded = nodes.find((node) => node.class_type === "LoadImage");
if (loaded && !(width && height)) {
const metadata = await sharp(this.uploads.get(String(loaded.inputs.image))).metadata();
width = metadata.width ?? 64;
height = metadata.height ?? 64;
}
const seed = String(input("seed") ?? input("noise_seed") ?? 0);
const [r = 0, g = 0, b = 0] = createHash("sha256").update(seed).digest();
const png = await sharp({
create: { width: width || 64, height: height || 64, channels: 3, background: { r, g, b } },
})
.png()
.toBuffer();
return new Uint8Array(png);
}
private view(params: URLSearchParams): Response {
const bytes = this.files.get(
fileKey({
filename: params.get("filename") ?? "",
subfolder: params.get("subfolder") ?? "",
type: params.get("type") ?? "",
}),
);
if (!bytes) return new Response("Not found", { status: 404 });
return new Response(Buffer.from(bytes), {
headers: { "Content-Type": "application/octet-stream" },
});
}
private async upload(input: RequestInfo | URL, init?: RequestInit): Promise<Response> {
const form = await new Request(String(input), {
method: "POST",
headers: init?.headers,
body: init?.body,
}).formData();
const image = form.get("image");
if (!(image instanceof File) || form.get("type") !== "input") {
return json({ error: "Invalid upload" }, 400);
}
this.uploads.set(image.name, new Uint8Array(await image.arrayBuffer()));
return json({ name: image.name, subfolder: "", type: "input" });
}
private unfinished(): EmulatedPrompt[] {
return this.prompts.filter((prompt) => !prompt.done && !prompt.removed);
}
private queue(): Response {
const running = this.unfinished();
return json({
queue_running: running.slice(0, 1).map((prompt) => [0, prompt.id, prompt.graph, {}, []]),
queue_pending: running
.slice(1)
.map((prompt, index) => [index + 1, prompt.id, prompt.graph, {}, []]),
});
}
}
function fileKey(ref: FileRef): string {
return `${ref.type}/${ref.subfolder}/${ref.filename}`;
}

View File

@ -10,6 +10,8 @@ export * from "./integration-settings.js";
export * from "./local-settings.js";
export * from "./mcp.js";
export * from "./media.js";
export * from "./media-generation.js";
export * from "./media-jobs.js";
export * from "./media-settings.js";
export * from "./media-transcription.js";
export * from "./model-tiers.js";

View File

@ -0,0 +1,42 @@
import { describe, expect, it } from "vitest";
import {
EditImageInputSchema,
GenerateImageInputSchema,
GenerateVideoInputSchema,
} from "./media-generation.js";
describe("media generation inputs", () => {
it("fills defaults and drops unknown fields such as continue_after", () => {
expect(GenerateImageInputSchema.parse({ prompt: " a fox ", continue_after: true })).toEqual({
prompt: "a fox",
count: 1,
});
expect(GenerateVideoInputSchema.parse({ prompt: "waves" })).toEqual({
prompt: "waves",
durationSeconds: 5,
});
});
it("bounds image count, size and video duration", () => {
expect(GenerateImageInputSchema.safeParse({ prompt: "x", count: 5 }).success).toBe(false);
expect(GenerateImageInputSchema.safeParse({ prompt: "x", width: 512 }).success).toBe(false);
expect(
GenerateImageInputSchema.safeParse({ prompt: "x", width: 512, height: 4096 }).success,
).toBe(false);
expect(GenerateVideoInputSchema.safeParse({ prompt: "x", durationSeconds: 11 }).success).toBe(
false,
);
});
it("needs at least one edit and valid edit values", () => {
expect(EditImageInputSchema.safeParse({ artifactId: "a" }).success).toBe(false);
expect(EditImageInputSchema.safeParse({ artifactId: "a", rotate: 45 }).success).toBe(false);
expect(EditImageInputSchema.safeParse({ artifactId: "a", resize: {} }).success).toBe(false);
expect(
EditImageInputSchema.safeParse({ artifactId: "a", extend: { top: 4, color: "red" } }).success,
).toBe(false);
expect(
EditImageInputSchema.parse({ artifactId: "a", resize: { aspect: "vertical" }, rotate: 90 }),
).toEqual({ artifactId: "a", resize: { aspect: "vertical", fit: "crop" }, rotate: 90 });
});
});

View File

@ -0,0 +1,107 @@
import * as z from "zod";
import { Id } from "./ids.js";
import { MediaFitSchema, MediaPresetIdSchema } from "./media.js";
export const MEDIA_IMAGE_MAX_COUNT = 4;
export const MEDIA_VIDEO_MAX_SECONDS = 10;
const Prompt = z.string().trim().min(1).max(4000);
const NegativePrompt = z.string().trim().max(4000).optional().describe("What to avoid.");
const Seed = z
.number()
.int()
.min(0)
.max(Number.MAX_SAFE_INTEGER)
.optional()
.describe("Reuse a seed to reproduce a result.");
const Strength = z.number().min(0).max(1).optional();
const ASPECTS = "vertical 9:16, landscape 16:9, square 1:1, portrait 4:5, classic 4:3, cinema 21:9";
const aspect = (fallback: string) => MediaPresetIdSchema.describe(`${ASPECTS}. ${fallback}`);
const Side = z.number().int().min(64).max(2048);
const Pixels = z.number().int().min(0).max(16_384);
export const GenerateImageInputSchema = z
.object({
prompt: Prompt.describe("What the image shows."),
negativePrompt: NegativePrompt,
aspect: aspect("Default square, or the source image's aspect ratio.").optional(),
width: Side.optional().describe("Exact width in pixels, with height; overrides aspect."),
height: Side.optional(),
count: z.number().int().min(1).max(MEDIA_IMAGE_MAX_COUNT).default(1),
seed: Seed,
sourceArtifactId: Id.optional().describe("Image artifact to start from (image-to-image)."),
strength: Strength.describe("With a source: how far to move away from it (default 0.6)."),
})
.refine((input) => (input.width === undefined) === (input.height === undefined), {
message: "Set width and height together",
path: ["width"],
});
export type GenerateImageInput = z.infer<typeof GenerateImageInputSchema>;
export const GenerateVideoInputSchema = z.object({
prompt: Prompt.describe("What happens in the clip: subject, motion, camera."),
negativePrompt: NegativePrompt,
aspect: aspect("Default landscape, or the start frame's aspect ratio.").optional(),
durationSeconds: z.number().min(1).max(MEDIA_VIDEO_MAX_SECONDS).default(5),
seed: Seed,
sourceArtifactId: Id.optional().describe("Image artifact to use as the first frame."),
});
export type GenerateVideoInput = z.infer<typeof GenerateVideoInputSchema>;
export const ImageFormatSchema = z.enum(["png", "jpeg", "webp"]);
export type ImageFormat = z.infer<typeof ImageFormatSchema>;
/** Edits apply in this order: crop, rotate, flip, resize, extend, repaint, format. */
export const EditImageInputSchema = z
.object({
artifactId: Id.describe("Image artifact to edit."),
crop: z
.object({ left: Pixels, top: Pixels, width: Pixels.min(1), height: Pixels.min(1) })
.optional()
.describe("Area to keep, in source pixels."),
rotate: z.literal([90, 180, 270]).optional().describe("Clockwise, in degrees."),
flip: z.enum(["horizontal", "vertical"]).optional(),
resize: z
.object({
aspect: aspect("Resizes to the format's exact size.").optional(),
width: z.number().int().min(1).max(8192).optional(),
height: z.number().int().min(1).max(8192).optional(),
fit: MediaFitSchema.default("crop").describe(
"How a different aspect ratio fills the size: crop, pad, or blur (blurred background).",
),
})
.refine((resize) => resize.aspect || resize.width || resize.height, {
message: "Set aspect, width or height",
})
.optional()
.describe("Width or height alone keeps the aspect ratio."),
extend: z
.object({
top: Pixels.default(0),
right: Pixels.default(0),
bottom: Pixels.default(0),
left: Pixels.default(0),
color: z
.string()
.regex(/^#[0-9a-fA-F]{6}$/)
.optional()
.describe("#RRGGBB; transparent when omitted and the format allows it."),
})
.optional()
.describe("Borders to add, in pixels."),
prompt: Prompt.optional().describe("Repaint the image with this prompt."),
strength: Strength.describe("How far the repaint moves away from the image (default 0.6)."),
format: ImageFormatSchema.optional().describe("Default keeps the source format."),
})
.refine(
(input) =>
input.crop ||
input.rotate ||
input.flip ||
input.resize ||
input.extend ||
input.prompt ||
input.format,
{ message: "Nothing to edit" },
);
export type EditImageInput = z.infer<typeof EditImageInputSchema>;

View File

@ -0,0 +1,36 @@
import * as z from "zod";
import { Id } from "./ids.js";
import { MediaJobStatusSchema, MediaOperationSchema, MediaOutputSchema } from "./media.js";
/** Operations a user starts from a media card (export, transcribe, edit); generation goes through a bot. */
export const MediaCardOperationSchema = z.enum(["edit_image", "export_video", "transcribe"]);
export type MediaCardOperation = z.infer<typeof MediaCardOperationSchema>;
export const MediaJobStartInputSchema = z
.object({
/** The conversation, like other thread procedures: a bot chat or a group. */
botId: Id.optional(),
groupId: Id.optional(),
/** The message the action came from; its bot posts the new card. */
messageId: Id,
operation: MediaCardOperationSchema,
/** The operation's input; validated by the operation. */
input: z.record(z.string(), z.unknown()),
})
.refine((input) => Boolean(input.botId) !== Boolean(input.groupId), {
message: "Pass botId or groupId",
});
export type MediaJobStartInput = z.infer<typeof MediaJobStartInputSchema>;
export const MediaJobSnapshotSchema = z.object({
id: Id,
operation: MediaOperationSchema,
status: MediaJobStatusSchema,
title: z.string(),
progress: z.number().min(0).max(1).nullable(),
error: z.string().nullable(),
outputs: z.array(MediaOutputSchema),
});
export type MediaJobSnapshotDto = z.infer<typeof MediaJobSnapshotSchema>;
export const MediaJobStartOutputSchema = z.object({ jobId: Id, messageId: Id });

View File

@ -82,6 +82,12 @@ import {
IntegrationProviderConfigSchema,
IntegrationSetupStateSchema,
} from "./integration-settings.js";
import {
MediaJobSnapshotSchema,
MediaJobStartInputSchema,
MediaJobStartOutputSchema,
} from "./media-jobs.js";
import { MediaSettingsUpdateSchema, MediaSettingsViewSchema } from "./media-settings.js";
import { ModelTierMappingSchema, SetModelTierInput } from "./model-tiers.js";
import {
CreateProjectGoalInput,
@ -690,6 +696,18 @@ export const appContract = {
get: oc.output(IntegrationSetupStateSchema),
save: oc.input(IntegrationProviderConfigSchema).output(z.object({ ok: z.literal(true) })),
},
media: {
/** Deployment-wide media backends; deployment owner only. */
settings: {
get: oc.output(MediaSettingsViewSchema),
update: oc.input(MediaSettingsUpdateSchema).output(MediaSettingsViewSchema),
},
jobs: {
start: oc.input(MediaJobStartInputSchema).output(MediaJobStartOutputSchema),
get: oc.input(z.object({ jobId: Id })).output(MediaJobSnapshotSchema),
cancel: oc.input(z.object({ jobId: Id })).output(MediaJobSnapshotSchema),
},
},
connections: {
catalog: oc
.input(z.object({ query: z.string().optional(), connectorId: z.string().optional() }))

View File

@ -34,6 +34,11 @@
"development": "./src/plot/plot-spec.ts",
"default": "./src/plot/plot-spec.ts"
},
"./media/workflows": {
"types": "./src/media/workflow-template.ts",
"development": "./src/media/workflow-template.ts",
"default": "./src/media/workflow-template.ts"
},
"./node/desktop-runtime": {
"types": "./src/node/desktop-runtime.ts",
"development": "./src/node/desktop-runtime.ts",

View File

@ -1,12 +1,10 @@
import type { AttachmentKind, AttachmentMimeType, MessageBlock } from "@rakazo/contracts";
import {
ATTACHMENT_MAX_BASE64_LENGTH,
ATTACHMENT_MAX_BYTES,
type AttachmentKind,
type AttachmentMimeType,
attachmentKindOf,
isAllowedAttachmentMimeType,
isAttachmentImageMimeType,
type MessageBlock,
} from "@rakazo/contracts";
export class AttachmentValidationError extends Error {

View File

@ -0,0 +1,113 @@
import { describe, expect, it } from "vitest";
import {
DEFAULT_WORKFLOWS,
fillWorkflow,
parseWorkflowTemplate,
WorkflowTemplateError,
} from "./workflow-template.js";
const minimal = {
"1": { class_type: "CLIPTextEncode", inputs: { text: "{{prompt}}", clip: ["2", 1] } },
"2": { class_type: "EmptyLatentImage", inputs: { width: "{{width}}", height: 512 } },
"3": { class_type: "SaveImage", inputs: { filename_prefix: "run/{{seed}}-{{prompt}}" } },
};
describe("parseWorkflowTemplate", () => {
it("accepts JSON text or parsed graphs and lists the placeholders", () => {
for (const source of [minimal, JSON.stringify(minimal)]) {
const template = parseWorkflowTemplate(source);
expect([...template.placeholders].sort()).toEqual(["prompt", "seed", "width"]);
}
});
it.each([
["not json", "Workflow is not valid JSON"],
["[]", "Workflow must be a JSON object"],
["{}", "Workflow must have 1 to 1000 nodes"],
[JSON.stringify({ nodes: [], links: [] }), "Workflow must be exported in ComfyUI's API format"],
[JSON.stringify({ "1": { inputs: {} } }), "Workflow node 1 needs a class_type and inputs"],
[
JSON.stringify({ "1": { class_type: "SaveImage", inputs: { text: "plain" } } }),
"Workflow needs a {{prompt}} placeholder",
],
[
JSON.stringify({
"1": { class_type: "X", inputs: { a: "{{prompt}}", b: "{{cfg}}" } },
}),
"Unknown workflow placeholders: {{cfg}}",
],
])("rejects %s", (source, message) => {
expect(() => parseWorkflowTemplate(source)).toThrow(new WorkflowTemplateError(message));
});
it("rejects placeholder names that only exist on Object.prototype", () => {
const source = {
"1": {
class_type: "X",
inputs: { a: "{{prompt}}", b: "{{constructor}}", c: "{{__proto__}}" },
},
};
expect(() => parseWorkflowTemplate(source)).toThrow(
"Unknown workflow placeholders: {{constructor}}, {{__proto__}}",
);
});
it("rejects oversized workflow text", () => {
expect(() => parseWorkflowTemplate(" ".repeat(1_000_001))).toThrow("Workflow is too large");
});
});
describe("fillWorkflow", () => {
it("replaces whole values with typed values and embedded ones with text, without mutating", () => {
const template = parseWorkflowTemplate(minimal);
const graph = fillWorkflow(template, { prompt: "a $& cat", width: 768, seed: 7 });
expect(graph["1"]?.inputs).toEqual({ text: "a $& cat", clip: ["2", 1] });
expect(graph["2"]?.inputs).toEqual({ width: 768, height: 512 });
expect(graph["3"]?.inputs.filename_prefix).toBe("run/7-a $& cat");
expect(minimal["2"].inputs.width).toBe("{{width}}");
});
it("refuses missing or mistyped values", () => {
const template = parseWorkflowTemplate(minimal);
expect(() => fillWorkflow(template, { prompt: "cat", seed: 1 })).toThrow(
"Workflow value for {{width}} is missing",
);
expect(() => fillWorkflow(template, { prompt: "cat", width: 1.5, seed: 1 })).toThrow(
"{{width}}",
);
});
});
describe("DEFAULT_WORKFLOWS", () => {
it("only image-to-* defaults need an input image", () => {
expect(DEFAULT_WORKFLOWS.textToImage.placeholders.has("image")).toBe(false);
expect(DEFAULT_WORKFLOWS.textToVideo.placeholders.has("image")).toBe(false);
expect(DEFAULT_WORKFLOWS.imageToImage.placeholders.has("image")).toBe(true);
expect(DEFAULT_WORKFLOWS.imageToVideo.placeholders.has("image")).toBe(true);
});
it("fill into graphs whose links point at existing nodes", () => {
const values = {
prompt: "a lighthouse",
negative_prompt: "",
model: "model.safetensors",
image: "input.png",
width: 512,
height: 512,
seed: 1,
steps: 20,
strength: 0.6,
frames: 25,
fps: 24,
};
for (const template of Object.values(DEFAULT_WORKFLOWS)) {
const graph = fillWorkflow(template, values);
expect(JSON.stringify(graph)).not.toContain("{{");
for (const node of Object.values(graph)) {
for (const input of Object.values(node.inputs)) {
if (Array.isArray(input)) expect(graph[String(input[0])]).toBeDefined();
}
}
}
});
});

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@ -0,0 +1,159 @@
import imageToImage from "./workflows/image-to-image.json" with { type: "json" };
import imageToVideo from "./workflows/image-to-video.json" with { type: "json" };
import textToImage from "./workflows/text-to-image.json" with { type: "json" };
import textToVideo from "./workflows/text-to-video.json" with { type: "json" };
/**
* Values a ComfyUI workflow template can ask for. A string value that is exactly `{{name}}`
* becomes the typed value (so `"{{width}}"` turns into the number 1024); `{{name}}` inside a
* longer string is replaced by its text. Templates are data: nothing is ever evaluated.
*/
export const WORKFLOW_PLACEHOLDERS = {
prompt: "string",
negative_prompt: "string",
/** Checkpoint file name: the configured image model or the first installed checkpoint. */
model: "string",
/** Uploaded input image (image-to-image, image-to-video). */
image: "string",
width: "integer",
height: "integer",
seed: "integer",
steps: "integer",
/** 0–1 denoise for image-to-image. */
strength: "number",
frames: "integer",
fps: "number",
} as const satisfies Record<string, "string" | "integer" | "number">;
export type WorkflowPlaceholder = keyof typeof WORKFLOW_PLACEHOLDERS;
export type WorkflowValues = {
[Name in WorkflowPlaceholder]?: (typeof WORKFLOW_PLACEHOLDERS)[Name] extends "string"
? string
: number;
};
/** One node of a workflow in ComfyUI's API format ("Export (API)" in ComfyUI). */
export interface ComfyWorkflowNode {
class_type: string;
inputs: Record<string, unknown>;
}
export type ComfyWorkflow = Record<string, ComfyWorkflowNode>;
export interface WorkflowTemplate {
readonly graph: ComfyWorkflow;
/** The placeholders the graph uses; `image` marks a template that needs an input image. */
readonly placeholders: ReadonlySet<WorkflowPlaceholder>;
}
export class WorkflowTemplateError extends Error {
constructor(message: string) {
super(message);
this.name = "WorkflowTemplateError";
}
}
const PLACEHOLDER_PATTERN = /\{\{([a-z_]+)\}\}/g;
const WHOLE_PLACEHOLDER = /^\{\{([a-z_]+)\}\}$/;
const MAX_WORKFLOW_CHARS = 1_000_000;
const MAX_WORKFLOW_NODES = 1_000;
function isRecord(value: unknown): value is Record<string, unknown> {
return Boolean(value) && typeof value === "object" && !Array.isArray(value);
}
function isPlaceholder(name: string): name is WorkflowPlaceholder {
return Object.hasOwn(WORKFLOW_PLACEHOLDERS, name);
}
function visitStrings(value: unknown, visit: (text: string) => void): void {
if (typeof value === "string") visit(value);
else if (Array.isArray(value)) for (const entry of value) visitStrings(entry, visit);
else if (isRecord(value)) for (const entry of Object.values(value)) visitStrings(entry, visit);
}
/** Validates an API-format workflow (JSON text or parsed) and lists its placeholders. */
export function parseWorkflowTemplate(source: unknown): WorkflowTemplate {
let value = source;
if (typeof source === "string") {
if (source.length > MAX_WORKFLOW_CHARS) {
throw new WorkflowTemplateError("Workflow is too large");
}
try {
value = JSON.parse(source);
} catch {
throw new WorkflowTemplateError("Workflow is not valid JSON");
}
}
if (!isRecord(value)) throw new WorkflowTemplateError("Workflow must be a JSON object");
if (Array.isArray(value.nodes)) {
throw new WorkflowTemplateError("Workflow must be exported in ComfyUI's API format");
}
const nodes = Object.entries(value);
if (nodes.length === 0 || nodes.length > MAX_WORKFLOW_NODES) {
throw new WorkflowTemplateError(`Workflow must have 1 to ${MAX_WORKFLOW_NODES} nodes`);
}
for (const [id, node] of nodes) {
if (!isRecord(node) || typeof node.class_type !== "string" || !isRecord(node.inputs)) {
throw new WorkflowTemplateError(`Workflow node ${id} needs a class_type and inputs`);
}
}
const placeholders = new Set<WorkflowPlaceholder>();
const unknown = new Set<string>();
visitStrings(value, (text) => {
for (const [, name = ""] of text.matchAll(PLACEHOLDER_PATTERN)) {
if (isPlaceholder(name)) placeholders.add(name);
else unknown.add(`{{${name}}}`);
}
});
if (unknown.size > 0) {
throw new WorkflowTemplateError(`Unknown workflow placeholders: ${[...unknown].join(", ")}`);
}
if (!placeholders.has("prompt")) {
throw new WorkflowTemplateError("Workflow needs a {{prompt}} placeholder");
}
return { graph: value as unknown as ComfyWorkflow, placeholders };
}
function replacePlaceholders(value: unknown, values: WorkflowValues): unknown {
if (typeof value === "string") {
const whole = WHOLE_PLACEHOLDER.exec(value)?.[1];
if (whole) return values[whole as WorkflowPlaceholder];
return value.replace(PLACEHOLDER_PATTERN, (_, name: string) =>
String(values[name as WorkflowPlaceholder]),
);
}
if (Array.isArray(value)) return value.map((entry) => replacePlaceholders(entry, values));
if (isRecord(value)) {
return Object.fromEntries(
Object.entries(value).map(([key, entry]) => [key, replacePlaceholders(entry, values)]),
);
}
return value;
}
/** Returns a copy of the template's graph with every placeholder replaced by its typed value. */
export function fillWorkflow(template: WorkflowTemplate, values: WorkflowValues): ComfyWorkflow {
for (const name of template.placeholders) {
const value = values[name];
const type = WORKFLOW_PLACEHOLDERS[name];
const valid =
type === "string"
? typeof value === "string"
: typeof value === "number" &&
Number.isFinite(value) &&
(type === "number" || Number.isInteger(value));
if (!valid) throw new WorkflowTemplateError(`Workflow value for {{${name}}} is missing`);
}
return replacePlaceholders(template.graph, values) as ComfyWorkflow;
}
/**
* Built-in workflows. Images use core nodes only and run on any SD-family checkpoint; video
* uses ComfyUI's core LTX-Video nodes (model files in workflows/README.md).
*/
export const DEFAULT_WORKFLOWS = {
textToImage: parseWorkflowTemplate(textToImage),
imageToImage: parseWorkflowTemplate(imageToImage),
textToVideo: parseWorkflowTemplate(textToVideo),
imageToVideo: parseWorkflowTemplate(imageToVideo),
} as const;

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@ -0,0 +1,35 @@
# ComfyUI workflows
Default workflows for `generate_image`, `generate_video` and repainting in `edit_image`, in
ComfyUI's API format. A custom workflow in the Media settings replaces the matching default:
one that uses `{{image}}` replaces the image-to-image (or image-to-video) default, one without
it replaces the text-to-image (or text-to-video) default.
## Placeholders
A string value that is exactly `{{name}}` becomes the typed value; `{{name}}` inside a longer
string is replaced by its text. Every workflow needs `{{prompt}}`; other names are optional.
| Placeholder | Value |
|---|---|
| `{{prompt}}`, `{{negative_prompt}}` | text |
| `{{model}}` | the configured image model, or the first installed checkpoint |
| `{{image}}` | the uploaded input image (for `LoadImage`) |
| `{{width}}`, `{{height}}` | output size in pixels |
| `{{seed}}`, `{{steps}}` | integers |
| `{{strength}}` | 0–1, image-to-image denoise |
| `{{frames}}`, `{{fps}}` | video length in frames (8n+1) and frame rate |
To write your own, build it in ComfyUI, replace the values above with placeholders and export it
with **Export (API)**.
## Model files
- Images: any SD 1.5 or SDXL checkpoint in `models/checkpoints/`.
- Video (LTX-Video, core nodes, about 12 GB of VRAM):
- `models/checkpoints/ltx-video-2b-v0.9.5.safetensors` from
[Lightricks/LTX-Video](https://huggingface.co/Lightricks/LTX-Video)
- `models/text_encoders/t5xxl_fp16.safetensors` from
[comfyanonymous/flux_text_encoders](https://huggingface.co/comfyanonymous/flux_text_encoders)
The video workflows need a ComfyUI release with the `CreateVideo` and `SaveVideo` nodes.

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@ -0,0 +1,45 @@
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "{{model}}" }
},
"2": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{prompt}}", "clip": ["1", 1] }
},
"3": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{negative_prompt}}", "clip": ["1", 1] }
},
"4": {
"class_type": "LoadImage",
"inputs": { "image": "{{image}}" }
},
"5": {
"class_type": "VAEEncode",
"inputs": { "pixels": ["4", 0], "vae": ["1", 2] }
},
"6": {
"class_type": "KSampler",
"inputs": {
"model": ["1", 0],
"positive": ["2", 0],
"negative": ["3", 0],
"latent_image": ["5", 0],
"seed": "{{seed}}",
"steps": "{{steps}}",
"cfg": 7,
"sampler_name": "dpmpp_2m",
"scheduler": "karras",
"denoise": "{{strength}}"
}
},
"7": {
"class_type": "VAEDecode",
"inputs": { "samples": ["6", 0], "vae": ["1", 2] }
},
"8": {
"class_type": "SaveImage",
"inputs": { "images": ["7", 0], "filename_prefix": "evoo/image" }
}
}

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@ -0,0 +1,86 @@
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "ltx-video-2b-v0.9.5.safetensors" }
},
"2": {
"class_type": "CLIPLoader",
"inputs": { "clip_name": "t5xxl_fp16.safetensors", "type": "ltxv" }
},
"3": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{prompt}}", "clip": ["2", 0] }
},
"4": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{negative_prompt}}", "clip": ["2", 0] }
},
"5": {
"class_type": "LoadImage",
"inputs": { "image": "{{image}}" }
},
"6": {
"class_type": "LTXVImgToVideo",
"inputs": {
"positive": ["3", 0],
"negative": ["4", 0],
"vae": ["1", 2],
"image": ["5", 0],
"width": "{{width}}",
"height": "{{height}}",
"length": "{{frames}}",
"batch_size": 1,
"strength": 1
}
},
"7": {
"class_type": "LTXVConditioning",
"inputs": { "positive": ["6", 0], "negative": ["6", 1], "frame_rate": "{{fps}}" }
},
"8": {
"class_type": "LTXVScheduler",
"inputs": {
"steps": "{{steps}}",
"max_shift": 2.05,
"base_shift": 0.95,
"stretch": true,
"terminal": 0.1,
"latent": ["6", 2]
}
},
"9": {
"class_type": "KSamplerSelect",
"inputs": { "sampler_name": "euler" }
},
"10": {
"class_type": "SamplerCustom",
"inputs": {
"model": ["1", 0],
"add_noise": true,
"noise_seed": "{{seed}}",
"cfg": 3,
"positive": ["7", 0],
"negative": ["7", 1],
"sampler": ["9", 0],
"sigmas": ["8", 0],
"latent_image": ["6", 2]
}
},
"11": {
"class_type": "VAEDecode",
"inputs": { "samples": ["10", 0], "vae": ["1", 2] }
},
"12": {
"class_type": "CreateVideo",
"inputs": { "images": ["11", 0], "fps": "{{fps}}" }
},
"13": {
"class_type": "SaveVideo",
"inputs": {
"video": ["12", 0],
"filename_prefix": "evoo/video",
"format": "mp4",
"codec": "h264"
}
}
}

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@ -0,0 +1,41 @@
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "{{model}}" }
},
"2": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{prompt}}", "clip": ["1", 1] }
},
"3": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{negative_prompt}}", "clip": ["1", 1] }
},
"4": {
"class_type": "EmptyLatentImage",
"inputs": { "width": "{{width}}", "height": "{{height}}", "batch_size": 1 }
},
"5": {
"class_type": "KSampler",
"inputs": {
"model": ["1", 0],
"positive": ["2", 0],
"negative": ["3", 0],
"latent_image": ["4", 0],
"seed": "{{seed}}",
"steps": "{{steps}}",
"cfg": 7,
"sampler_name": "dpmpp_2m",
"scheduler": "karras",
"denoise": 1
}
},
"6": {
"class_type": "VAEDecode",
"inputs": { "samples": ["5", 0], "vae": ["1", 2] }
},
"7": {
"class_type": "SaveImage",
"inputs": { "images": ["6", 0], "filename_prefix": "evoo/image" }
}
}

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@ -0,0 +1,77 @@
{
"1": {
"class_type": "CheckpointLoaderSimple",
"inputs": { "ckpt_name": "ltx-video-2b-v0.9.5.safetensors" }
},
"2": {
"class_type": "CLIPLoader",
"inputs": { "clip_name": "t5xxl_fp16.safetensors", "type": "ltxv" }
},
"3": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{prompt}}", "clip": ["2", 0] }
},
"4": {
"class_type": "CLIPTextEncode",
"inputs": { "text": "{{negative_prompt}}", "clip": ["2", 0] }
},
"5": {
"class_type": "LTXVConditioning",
"inputs": { "positive": ["3", 0], "negative": ["4", 0], "frame_rate": "{{fps}}" }
},
"6": {
"class_type": "EmptyLTXVLatentVideo",
"inputs": {
"width": "{{width}}",
"height": "{{height}}",
"length": "{{frames}}",
"batch_size": 1
}
},
"7": {
"class_type": "LTXVScheduler",
"inputs": {
"steps": "{{steps}}",
"max_shift": 2.05,
"base_shift": 0.95,
"stretch": true,
"terminal": 0.1,
"latent": ["6", 0]
}
},
"8": {
"class_type": "KSamplerSelect",
"inputs": { "sampler_name": "euler" }
},
"9": {
"class_type": "SamplerCustom",
"inputs": {
"model": ["1", 0],
"add_noise": true,
"noise_seed": "{{seed}}",
"cfg": 3,
"positive": ["5", 0],
"negative": ["5", 1],
"sampler": ["8", 0],
"sigmas": ["7", 0],
"latent_image": ["6", 0]
}
},
"10": {
"class_type": "VAEDecode",
"inputs": { "samples": ["9", 0], "vae": ["1", 2] }
},
"11": {
"class_type": "CreateVideo",
"inputs": { "images": ["10", 0], "fps": "{{fps}}" }
},
"12": {
"class_type": "SaveVideo",
"inputs": {
"video": ["11", 0],
"filename_prefix": "evoo/video",
"format": "mp4",
"codec": "h264"
}
}
}

View File

@ -106,6 +106,7 @@ async function main() {
"packages/testkit/src/connections.test.ts",
"packages/testkit/src/bot-secrets.test.ts",
"packages/testkit/src/delegation.postgres.test.ts",
"packages/testkit/src/media.postgres.test.ts",
"packages/testkit/src/user-profile.postgres.test.ts",
"packages/db/src/space-membership.postgres.test.ts",
"packages/db/src/main-agent.postgres.test.ts",
@ -117,7 +118,9 @@ async function main() {
"packages/adapters/src/realtime.postgres.test.ts",
"packages/adapters/src/job-reconciler.postgres.test.ts",
"packages/adapters/src/cloud-agent.postgres.test.ts",
"packages/adapters/src/media/image-operations.postgres.test.ts",
"packages/adapters/src/media/transcription.postgres.test.ts",
"packages/adapters/src/media-runtime.postgres.test.ts",
"packages/adapters/src/builtin-memory-provider.postgres.test.ts",
"packages/adapters/src/profile-consolidation.postgres.test.ts",
];

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@ -0,0 +1,378 @@
import { mkdtempSync, rmSync } from "node:fs";
import { writeFile } from "node:fs/promises";
import { tmpdir } from "node:os";
import path from "node:path";
import { ComposioEmulator, type MediaOperationRegistration } from "@rakazo/adapters";
import {
type MediaJobBlock,
MediaOutputSchema,
type MediaSettingsView,
type MessageBlock,
} from "@rakazo/contracts";
import { createThreadMessage } from "@rakazo/db";
import { afterAll, beforeAll, describe, expect, it } from "vitest";
import type { createApp } from "../../../apps/api/src/app.ts";
import { sessionCookieHeader } from "./index.js";
type App = { request: (input: string, init?: RequestInit) => Response | Promise<Response> };
type AppHandles = Awaited<ReturnType<typeof createApp>>;
process.env.WAKEUP_DRIVER = "memory";
process.env.SANDBOX_PROVIDER = "fake";
process.env.AGENT_RUNTIME = "scripted";
const hasDb = process.env.VERIFY_DATABASE === "1" && Boolean(process.env.DATABASE_URL);
const describeWithDatabase = hasDb ? describe.sequential : describe.skip;
const PNG_BASE64 = Buffer.from([0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a, 1, 2, 3]).toString(
"base64",
);
// testkit has no zod of its own; the contracts' schemas carry it.
const SourceInputSchema = MediaOutputSchema.pick({ artifactId: true });
/** Fake card operations: an export that copies its source, and a transcription that waits. */
function fakeOperations(): MediaOperationRegistration[] {
const exportVideo: MediaOperationRegistration<{ artifactId: string }> = {
operation: "export_video",
inputSchema: SourceInputSchema,
title: () => "Export",
available: async () => true,
artifactIds: (input) => [input.artifactId],
handler: {
operation: "export_video",
run: async (context) => {
const { artifactId } = context.input as { artifactId: string };
const source = await context.fetchArtifact(artifactId);
const out = path.join(context.tempDir, "export.png");
await writeFile(out, Buffer.from(PNG_BASE64, "base64"));
await context.addOutput({
path: out,
name: "export.png",
mimeType: "image/png",
parentArtifactId: source.artifactId,
preset: "square",
});
return { summary: "Exported." };
},
},
};
const transcribe: MediaOperationRegistration<{ artifactId: string }> = {
operation: "transcribe",
inputSchema: SourceInputSchema,
title: () => "Transcript",
available: async () => true,
artifactIds: (input) => [input.artifactId],
handler: {
operation: "transcribe",
run: async (context) => {
await new Promise<void>((resolve) => {
context.signal.addEventListener("abort", () => resolve(), { once: true });
});
context.signal.throwIfAborted();
return { summary: "" };
},
},
};
return [exportVideo, transcribe] as MediaOperationRegistration[];
}
describeWithDatabase("media RPCs (PostgreSQL)", () => {
let handles: AppHandles;
let app: App;
const stamp = `${Date.now()}-${Math.random().toString(36).slice(2)}`;
const dataDir = mkdtempSync(path.join(tmpdir(), "rakazo-media-"));
beforeAll(async () => {
const { createApp } = await import("../../../apps/api/src/app.ts");
handles = await createApp({
databaseUrl: process.env.DATABASE_URL!,
dataDir,
sandboxProvider: "fake",
agentRuntime: "scripted",
wakeupDriver: "memory",
signupsEnabled: "true",
composio: new ComposioEmulator(),
mediaOperations: fakeOperations(),
});
app = handles.app;
});
afterAll(async () => {
await handles?.prisma.integrationProviderConfig.deleteMany({ where: { id: "media" } });
await handles?.stop();
rmSync(dataDir, { recursive: true, force: true });
});
async function user(label: string) {
const cookie = await signup(app, `${label}-${stamp}@rakazo.test`, label);
const me = await rpc<{ userId: string; spaceId: string }>(app, cookie, "me");
const bot = await rpc<{ id: string }>(app, cookie, "bots/create", {
name: `${label} bot`,
title: "",
description: "",
instructions: "",
notifyOnFinish: false,
});
const thread = await handles.prisma.thread.findUniqueOrThrow({ where: { botId: bot.id } });
const card = await createThreadMessage(handles.prisma, {
threadId: thread.id,
role: "bot",
botId: bot.id,
blocks: [{ kind: "text", text: "Here is your clip." }],
});
const artifact = await rpc<{ id: string }>(app, cookie, "artifacts/create", {
botId: bot.id,
name: "clip.png",
mimeType: "image/png",
contentBase64: PNG_BASE64,
});
return { cookie, me, bot, thread, card, artifact };
}
async function waitForStatus(jobId: string, status: string) {
const start = Date.now();
while (Date.now() - start < 20_000) {
const job = await handles.prisma.mediaJob.findUnique({ where: { id: jobId } });
if (job?.status === status) return job;
await new Promise((resolve) => setTimeout(resolve, 50));
}
throw new Error(`media job ${jobId} never reached ${status}`);
}
it("lets only the deployment owner read and change media settings, and never returns keys", async () => {
const owner = await user("media-owner");
const other = await user("media-other");
await handles.prisma.deploymentSettings.upsert({
where: { id: "default" },
create: { id: "default", ownerUserId: owner.me.userId },
update: { ownerUserId: owner.me.userId },
});
const update = {
comfyui: {
baseUrl: "http://127.0.0.1:8188/",
apiKey: "comfy-test-key",
imageModel: "sd_xl_base_1.0.safetensors",
imageWorkflow: '{"3":{"class_type":"KSampler","inputs":{}}}',
videoWorkflow: "",
},
transcription: { baseUrl: "http://127.0.0.1:8080", model: "whisper-1", apiKey: "" },
};
expect((await raw(app, other.cookie, "media/settings/get", {})).status).toBe(403);
expect((await raw(app, other.cookie, "media/settings/update", update)).status).toBe(403);
expect(await handles.prisma.integrationProviderConfig.count({ where: { id: "media" } })).toBe(
0,
);
const saved = await rpc<MediaSettingsView>(app, owner.cookie, "media/settings/update", update);
expect(saved).toEqual({
comfyui: {
baseUrl: "http://127.0.0.1:8188",
hasApiKey: true,
imageModel: "sd_xl_base_1.0.safetensors",
imageWorkflow: update.comfyui.imageWorkflow,
},
transcription: { baseUrl: "http://127.0.0.1:8080/v1", model: "whisper-1", hasApiKey: false },
});
expect(JSON.stringify(saved)).not.toContain("comfy-test-key");
expect(await rpc(app, owner.cookie, "media/settings/get")).toEqual(saved);
const row = await handles.prisma.integrationProviderConfig.findUniqueOrThrow({
where: { id: "media" },
});
expect(row.ciphertext).not.toContain("comfy-test-key");
expect(row.ciphertext).not.toContain("127.0.0.1");
// An omitted key stays with the same server, never follows the settings elsewhere.
const { apiKey: _key, ...withoutKey } = update.comfyui;
const kept = await rpc<MediaSettingsView>(app, owner.cookie, "media/settings/update", {
...update,
comfyui: withoutKey,
});
expect(kept.comfyui?.hasApiKey).toBe(true);
const moved = await rpc<MediaSettingsView>(app, owner.cookie, "media/settings/update", {
...update,
comfyui: { ...withoutKey, baseUrl: "http://127.0.0.1:8189" },
});
expect(moved.comfyui?.hasApiKey).toBe(false);
for (const baseUrl of ["http://169.254.169.254", "http://user:pass@127.0.0.1:8188"]) {
const refused = await raw(app, owner.cookie, "media/settings/update", {
...update,
comfyui: { ...update.comfyui, baseUrl },
});
expect(refused.status, baseUrl).toBe(400);
}
const badWorkflow = await raw(app, owner.cookie, "media/settings/update", {
...update,
comfyui: { ...update.comfyui, imageWorkflow: "[1, 2" },
});
expect(badWorkflow.status).toBe(400);
const previous = process.env.RAKAZO_OPENAI_COMPAT_ALLOW_PUBLIC;
try {
delete process.env.RAKAZO_OPENAI_COMPAT_ALLOW_PUBLIC;
expect(
(
await raw(app, owner.cookie, "media/settings/update", {
comfyui: null,
transcription: { baseUrl: "http://transcribe.example.com" },
})
).status,
).toBe(400);
process.env.RAKAZO_OPENAI_COMPAT_ALLOW_PUBLIC = "1";
// A key is never sent in cleartext to a public host.
expect(
(
await raw(app, owner.cookie, "media/settings/update", {
comfyui: null,
transcription: { baseUrl: "http://transcribe.example.com", apiKey: "secret" },
})
).status,
).toBe(400);
const https = await rpc<MediaSettingsView>(app, owner.cookie, "media/settings/update", {
comfyui: null,
transcription: { baseUrl: "https://transcribe.example.com", apiKey: "secret" },
});
expect(https.transcription).toMatchObject({
baseUrl: "https://transcribe.example.com/v1",
hasApiKey: true,
});
} finally {
if (previous === undefined) delete process.env.RAKAZO_OPENAI_COMPAT_ALLOW_PUBLIC;
else process.env.RAKAZO_OPENAI_COMPAT_ALLOW_PUBLIC = previous;
}
expect(
await rpc(app, owner.cookie, "media/settings/update", { comfyui: null, transcription: null }),
).toEqual({ comfyui: null, transcription: null });
expect(await handles.prisma.integrationProviderConfig.count({ where: { id: "media" } })).toBe(
0,
);
});
it("starts, reads and cancels card jobs only for the actor's own threads and files", async () => {
const alice = await user("media-alice");
const mallory = await user("media-mallory");
const started = await rpc<{ jobId: string; messageId: string }>(
app,
alice.cookie,
"media/jobs/start",
{
botId: alice.bot.id,
messageId: alice.card.id,
operation: "export_video",
input: { artifactId: alice.artifact.id },
},
);
const job = await waitForStatus(started.jobId, "done");
expect(job).toMatchObject({
spaceId: alice.me.spaceId,
userId: alice.me.userId,
botId: alice.bot.id,
threadId: alice.thread.id,
runId: null,
continueAfter: false,
});
const snapshot = await rpc<{ status: string; outputs: MediaJobBlock["outputs"] }>(
app,
alice.cookie,
"media/jobs/get",
{ jobId: started.jobId },
);
expect(snapshot.status).toBe("done");
expect(snapshot.outputs).toEqual([
expect.objectContaining({
name: "export.png",
parentArtifactId: alice.artifact.id,
preset: "square",
}),
]);
const card = await handles.prisma.message.findUniqueOrThrow({
where: { id: started.messageId },
});
expect(card).toMatchObject({ threadId: alice.thread.id, botId: alice.bot.id, role: "bot" });
expect((card.blocks as MessageBlock[])[0]).toMatchObject({ kind: "media", status: "done" });
// Another user can neither read nor cancel the job, nor start one in Alice's conversation
// or on her files.
expect(
(await raw(app, mallory.cookie, "media/jobs/get", { jobId: started.jobId })).status,
).toBe(404);
expect(
(await raw(app, mallory.cookie, "media/jobs/cancel", { jobId: started.jobId })).status,
).toBe(404);
for (const body of [
{
botId: alice.bot.id,
messageId: alice.card.id,
operation: "export_video",
input: { artifactId: mallory.artifact.id },
},
{
botId: mallory.bot.id,
messageId: alice.card.id,
operation: "export_video",
input: { artifactId: mallory.artifact.id },
},
{
botId: mallory.bot.id,
messageId: mallory.card.id,
operation: "export_video",
input: { artifactId: alice.artifact.id },
},
{
botId: mallory.bot.id,
messageId: mallory.card.id,
operation: "generate_image",
input: { prompt: "anything" },
},
]) {
const response = await raw(app, mallory.cookie, "media/jobs/start", body);
expect(response.status, JSON.stringify(body)).toBeGreaterThanOrEqual(400);
}
expect(await handles.prisma.mediaJob.count({ where: { userId: mallory.me.userId } })).toBe(0);
const slow = await rpc<{ jobId: string }>(app, alice.cookie, "media/jobs/start", {
botId: alice.bot.id,
messageId: alice.card.id,
operation: "transcribe",
input: { artifactId: alice.artifact.id },
});
await waitForStatus(slow.jobId, "running");
const cancelled = await rpc<{ status: string }>(app, alice.cookie, "media/jobs/cancel", {
jobId: slow.jobId,
});
expect(["running", "cancelled"]).toContain(cancelled.status);
await waitForStatus(slow.jobId, "cancelled");
});
});
async function signup(app: App, email: string, name: string) {
const res = await app.request("/api/auth/sign-up/email", {
method: "POST",
headers: { "content-type": "application/json", origin: "http://127.0.0.1:5173" },
body: JSON.stringify({ email, password: "password12", name }),
});
if (res.status >= 400) throw new Error(`signup failed ${res.status}: ${await res.text()}`);
return sessionCookieHeader(res);
}
function raw(app: App, cookie: string, proc: string, body: unknown = {}) {
return app.request(`/rpc/${proc}`, {
method: "POST",
headers: { "content-type": "application/json", cookie, origin: "http://127.0.0.1:5173" },
body: JSON.stringify({ json: body }),
});
}
async function rpc<T>(app: App, cookie: string, proc: string, body: unknown = {}): Promise<T> {
const res = await raw(app, cookie, proc, body);
const text = await res.text();
const parsed = JSON.parse(text) as { json?: T; error?: { message?: string } };
if (res.status >= 400 || parsed.error) {
throw new Error(`${proc} ${res.status}: ${parsed.error?.message ?? text}`);
}
return parsed.json as T;
}