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https://github.com/snapotter-hq/SnapOtter.git
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- Delete 3 dead files: use-batch-processor.ts, use-i18n.ts, smart-crop.ts (AI package) - Remove dead getJobProgress function and unused runPythonScript wrapper - Remove 6 unused imports across API and web apps - Remove unused shared types (ImageFormat, AppConfig, ApiError, HealthResponse, JobProgress) and constants (SUPPORTED_INPUT_FORMATS/OUTPUT_FORMATS, DEFAULT_OUTPUT_FORMAT) - Remove unused store method (setOriginalBlobUrl) and clean AI package re-exports - Add test infrastructure: vitest config, unit/integration/e2e tests, fixtures, screenshots - Add Docker test infrastructure: Dockerfile.test, docker-compose.test.yml - Add download_models.py for pre-baking AI model weights in Docker - Add filename sanitization utility (apps/api/src/lib/filename.ts) - Update .gitignore to exclude coverage/, *.tsbuildinfo, .superpowers/, test artifacts - Update .dockerignore to exclude test/coverage/IDE artifacts from builds - Update docs: remove smart crop from AI docs (uses Sharp directly), update bridge docs
160 lines
5.3 KiB
TypeScript
160 lines
5.3 KiB
TypeScript
import { randomUUID } from "node:crypto";
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import { writeFile } from "node:fs/promises";
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import { join } from "node:path";
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import type { FastifyInstance, FastifyRequest, FastifyReply } from "fastify";
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import { z } from "zod";
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import { createWorkspace } from "../lib/workspace.js";
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import { validateImageBuffer } from "../lib/file-validation.js";
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import { sanitizeFilename } from "../lib/filename.js";
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export interface ToolRouteConfig<T> {
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/** Unique tool identifier, used as the URL path segment. */
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toolId: string;
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/** Zod schema that validates the settings JSON from the request. */
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settingsSchema: z.ZodType<T, z.ZodTypeDef, unknown>;
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/** The processing function: takes input buffer + validated settings, returns output. */
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process: (
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inputBuffer: Buffer,
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settings: T,
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filename: string,
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) => Promise<{ buffer: Buffer; filename: string; contentType: string }>;
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}
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/**
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* In-memory registry of all tool configs, keyed by toolId.
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* Populated by createToolRoute() calls; used by batch processing.
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*/
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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const toolRegistry = new Map<string, ToolRouteConfig<any>>();
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/**
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* Retrieve a registered tool config by its ID.
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*/
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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export function getToolConfig(toolId: string): ToolRouteConfig<any> | undefined {
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return toolRegistry.get(toolId);
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}
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/**
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* Factory that registers a POST /api/v1/tools/:toolId route.
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*
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* The route accepts multipart with:
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* - A file part (the image to process)
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* - A "settings" field containing a JSON string
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*
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* The factory handles:
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* - Multipart parsing
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* - File validation
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* - Settings validation via Zod
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* - Workspace management
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* - Error handling
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* - Response formatting
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*/
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export function createToolRoute<T>(
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app: FastifyInstance,
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config: ToolRouteConfig<T>,
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): void {
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// Register in the tool registry for batch processing
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toolRegistry.set(config.toolId, config);
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app.post(
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`/api/v1/tools/${config.toolId}`,
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async (request: FastifyRequest, reply: FastifyReply) => {
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let fileBuffer: Buffer | null = null;
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let filename = "image";
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let settingsRaw: string | null = null;
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// Parse multipart parts
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try {
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const parts = request.parts();
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for await (const part of parts) {
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if (part.type === "file") {
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// Consume the file stream into a buffer
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const chunks: Buffer[] = [];
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for await (const chunk of part.file) {
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chunks.push(chunk);
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}
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fileBuffer = Buffer.concat(chunks);
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filename = sanitizeFilename(part.filename ?? "image");
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} else {
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// Field part
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if (part.fieldname === "settings") {
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settingsRaw = part.value as string;
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}
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}
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}
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} catch (err) {
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return reply.status(400).send({
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error: "Failed to parse multipart request",
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details: err instanceof Error ? err.message : String(err),
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});
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}
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// Require a file
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if (!fileBuffer || fileBuffer.length === 0) {
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return reply
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.status(400)
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.send({ error: "No image file provided" });
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}
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// Validate the uploaded image
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const validation = await validateImageBuffer(fileBuffer);
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if (!validation.valid) {
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return reply
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.status(400)
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.send({ error: `Invalid image: ${validation.reason}` });
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}
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// Parse and validate settings
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let settings: T;
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try {
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const parsed = settingsRaw ? JSON.parse(settingsRaw) : {};
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const result = config.settingsSchema.safeParse(parsed);
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if (!result.success) {
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return reply.status(400).send({
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error: "Invalid settings",
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details: result.error.issues.map((i) => ({
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path: i.path.join("."),
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message: i.message,
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})),
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});
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}
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settings = result.data;
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} catch {
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return reply.status(400).send({ error: "Settings must be valid JSON" });
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}
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// Process the image
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try {
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const result = await config.process(fileBuffer, settings, filename);
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// Create workspace and save output
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const jobId = randomUUID();
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const workspacePath = await createWorkspace(jobId);
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const outputPath = join(workspacePath, "output", result.filename);
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await writeFile(outputPath, result.buffer);
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// Also save the original input for reference/download
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const inputPath = join(workspacePath, "input", filename);
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await writeFile(inputPath, fileBuffer);
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return reply.send({
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jobId,
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downloadUrl: `/api/v1/download/${jobId}/${encodeURIComponent(result.filename)}`,
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originalSize: fileBuffer.length,
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processedSize: result.buffer.length,
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});
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} catch (err) {
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// Catch Sharp / processing errors and return a clean API error
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const message = err instanceof Error ? err.message : "Image processing failed";
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request.log.error({ err, toolId: config.toolId }, "Tool processing failed");
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return reply.status(422).send({
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error: "Processing failed",
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details: process.env.NODE_ENV === "production" ? undefined : message,
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});
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}
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},
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);
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}
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