Add screenshot capture, OCR, Figma frame import, and prompt sharing

- Screenshot capture: pick a screen/window from the Attach menu via
  desktopCapturer and attach it as an image, reusing the existing vision
  attachment pipeline.
- OCR: extract text from any attached image via tesseract.js (runs in
  the main process, offline after the first-use model download) and
  drop it into the composer.
- Figma frame import: add a personal access token in Settings, then
  paste a "Copy link to selection" URL to fetch that frame as a PNG via
  the Figma REST API and attach it like any other image.
- Prompt library export/import: save presets to a JSON file and import
  one from a teammate - simple file-based sharing since this app has no
  server component ("Team Prompt" from the earlier feature list).

Also fixes typecheck-all.sh: its frontend step used `tsc --noEmit` on a
tsconfig that only has "files": [] and project references - without
-b/--build that's a no-op that silently checks nothing, which is how an
invalid `Figma` icon import from lucide-react slipped past typecheck
earlier and was only caught by the real `vite build`.

Author: voidstackloop

README.md

@@ -40,6 +40,10 @@ Beyond chat, Modelforge includes an **agentic mode** — the model can read/writ
 **Files & retrieval**
 - Attach files, folders, images, video, and PDFs directly into a conversation.
 - Large folders are automatically chunked, embedded (via Ollama), and retrieved by relevance instead of dumped whole into the prompt — so a big project doesn't blow out a small model's context window.
+- **Screenshot capture** — pick a screen or window from the Attach menu and it's captured and attached as an image, no separate screenshot tool needed. (macOS may require granting Screen Recording permission the first time.)
+- **OCR** — extract plain text from any attached image with one click, dropped straight into the composer. Runs fully offline via [tesseract.js](https://github.com/naptha/tesseract.js) after its first use (which needs network access once, to download the ~2MB English text-recognition model).
+- **Figma frame import** — add a personal access token in Settings → Integrations, then paste a "Copy link to selection" URL from Figma to fetch that frame as an image, attached like any other screenshot.
+- **Prompt library sharing** — export your saved prompts to a JSON file and import one a teammate sent you (Settings → Prompt Library). There's no live sync — it's just a plain file, sent however you like.
 
 **Agent mode** — see the [dedicated section](#agent-mode) below.
 

app/package-lock.json

@@ -29,7 +29,9 @@
       "package.json"
     ],
     "asarUnpack": [
-      "**/node_modules/ffmpeg-static/**"
+      "**/node_modules/ffmpeg-static/**",
+      "**/node_modules/tesseract.js/**",
+      "**/node_modules/tesseract.js-core/**"
     ],
     "extraResources": [
       {
@@ -42,13 +44,27 @@
     },
     "linux": {
       "icon": "build/icon.png",
-      "target": ["AppImage"]
+      "target": [
+        "AppImage"
+      ]
     },
     "mac": {
       "icon": "build/icon.png",
       "target": [
-        { "target": "dmg", "arch": ["x64", "arm64"] },
-        { "target": "zip", "arch": ["x64", "arm64"] }
+        {
+          "target": "dmg",
+          "arch": [
+            "x64",
+            "arm64"
+          ]
+        },
+        {
+          "target": "zip",
+          "arch": [
+            "x64",
+            "arm64"
+          ]
+        }
       ]
     },
     "publish": {
@@ -71,6 +87,7 @@
   "dependencies": {
     "electron-updater": "^6.6.2",
     "ffmpeg-static": "^5.3.0",
-    "pdf-parse": "^2.4.5"
+    "pdf-parse": "^2.4.5",
+    "tesseract.js": "^5.1.1"
   }
 }

app/package.json

@@ -3,6 +3,7 @@ import { randomUUID } from "node:crypto";
 import { app, dialog, shell, BrowserWindow } from "electron";
 import * as sessionsStore from "./sessions-store";
 import type { ChatSession } from "./sessions-store";
+import type { PromptPreset } from "./settings-store";
 
 function sanitizeFilename(name: string): string {
     return name.replace(/[/\\?%*:|"<>]/g, "-").slice(0, 80) || "chat";
@@ -75,6 +76,55 @@ export async function importSessions(win: BrowserWindow | null): Promise<{ impor
     return { imported };
 }
 
+// Presets are shared between machines/teammates as a plain JSON file rather
+// than through any live sync — this app has no server component, so "share
+// with the team" means "send them this file".
+export async function exportPromptPresets(win: BrowserWindow | null, presets: PromptPreset[]): Promise<{ success: boolean }> {
+    const date = new Date().toISOString().slice(0, 10);
+    const options = {
+        defaultPath: `modelforge-prompts-${date}.json`,
+        filters: [{ name: "JSON", extensions: ["json"] }],
+    };
+    const result = win ? await dialog.showSaveDialog(win, options) : await dialog.showSaveDialog(options);
+    if (result.canceled || !result.filePath) return { success: false };
+
+    fs.writeFileSync(result.filePath, JSON.stringify(presets, null, 2));
+    return { success: true };
+}
+
+function looksLikePreset(value: unknown): value is Partial<PromptPreset> {
+    return !!value && typeof value === "object" && typeof (value as { prompt?: unknown }).prompt === "string";
+}
+
+export async function importPromptPresets(win: BrowserWindow | null): Promise<PromptPreset[]> {
+    const options = { properties: ["openFile" as const], filters: [{ name: "JSON", extensions: ["json"] }] };
+    const result = win ? await dialog.showOpenDialog(win, options) : await dialog.showOpenDialog(options);
+    if (result.canceled || result.filePaths.length === 0) return [];
+
+    let raw: unknown;
+    try {
+        raw = JSON.parse(fs.readFileSync(result.filePaths[0], "utf-8"));
+    } catch {
+        return [];
+    }
+
+    const candidates: unknown[] = Array.isArray(raw) ? raw : [raw];
+    const now = new Date().toISOString();
+    const imported: PromptPreset[] = [];
+    for (const candidate of candidates) {
+        if (!looksLikePreset(candidate)) continue;
+        imported.push({
+            id: randomUUID(),
+            name: typeof candidate.name === "string" && candidate.name ? candidate.name : "Imported prompt",
+            prompt: candidate.prompt!,
+            versions: [],
+            createdAt: now,
+            updatedAt: now,
+        });
+    }
+    return imported;
+}
+
 export function getUserDataPath(): string {
     return app.getPath("userData");
 }

app/src/data-transfer.ts

@@ -0,0 +1,33 @@
+import { describe, it, expect } from "vitest";
+import { parseFigmaUrl } from "./figma";
+
+describe("parseFigmaUrl", () => {
+    it("parses a classic /file/ link with a node-id", () => {
+        expect(parseFigmaUrl("https://www.figma.com/file/abc123/My-Design?node-id=1-2")).toEqual({
+            fileKey: "abc123",
+            nodeId: "1:2",
+        });
+    });
+
+    it("parses a /design/ link with a node-id", () => {
+        expect(parseFigmaUrl("https://www.figma.com/design/xyz789/My-Design?node-id=45-67&t=abc")).toEqual({
+            fileKey: "xyz789",
+            nodeId: "45:67",
+        });
+    });
+
+    it("decodes a URL-encoded node-id", () => {
+        expect(parseFigmaUrl("https://www.figma.com/file/abc123/x?node-id=1%3A2")).toEqual({
+            fileKey: "abc123",
+            nodeId: "1:2",
+        });
+    });
+
+    it("returns null for a file link with no node-id (no specific frame selected)", () => {
+        expect(parseFigmaUrl("https://www.figma.com/file/abc123/My-Design")).toBeNull();
+    });
+
+    it("returns null for a non-Figma URL", () => {
+        expect(parseFigmaUrl("https://example.com/not-figma")).toBeNull();
+    });
+});