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Transform isair/jarvis into a Discord-controlled voice assistant running on the Ubuntu VNC desktop, keeping the mature ~39k-line Python brain intact. - bot/ (Node + bun, discord.js): /자비스 slash commands (ephemeral), voice channel join + voice receive/playback, pluggable VNC screen broadcast (selfbot live / noVNC / screenshot) - bridge/ (Python, Flask): wraps jarvis STT + run_reply_engine + Piper TTS behind a thin localhost HTTP API - .env.example, scripts/ (start_bridge/start_bot/dev), README rewrite, docs/language-comparison.md and docs/vnc-xfce-setup.md Language decision: hybrid (Python brain + Node/bun Discord layer) because Discord blocks bot video; native screen broadcast only works via a Node selfbot library.
70 lines
2.6 KiB
Python
70 lines
2.6 KiB
Python
"""Screenshot tool implementation for OCR capture."""
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from typing import Dict, Any, Optional
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import os
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import tempfile
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import subprocess
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import shutil
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from ...debug import debug_log
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from ..base import Tool, ToolContext
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from ..types import ToolExecutionResult
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class ScreenshotTool(Tool):
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"""Tool for capturing screenshots and performing OCR."""
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@property
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def name(self) -> str:
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return "screenshot"
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@property
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def description(self) -> str:
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return "Capture a selected screen region and OCR the text. Use only if the OCR will materially help."
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@property
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def inputSchema(self) -> Dict[str, Any]:
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return {
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"type": "object",
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"properties": {},
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"required": []
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}
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def run(self, args: Optional[Dict[str, Any]], context: ToolContext) -> ToolExecutionResult:
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"""Execute the screenshot tool."""
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context.user_print("📸 Capturing a screenshot for OCR…")
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debug_log("screenshot: capturing OCR...", "screenshot")
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# Inline OCR capture logic (previously in separate helper)
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ocr_text: str = ""
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sc = shutil.which("screencapture")
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if sc:
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tmpdir = tempfile.mkdtemp(prefix="jarvis_ocr_")
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png_path = os.path.join(tmpdir, "shot.png")
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try:
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cmd = [sc, "-i", png_path]
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try:
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ret = subprocess.run(cmd)
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except Exception:
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ret = None # type: ignore
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if ret and getattr(ret, "returncode", 1) == 0 and os.path.exists(png_path):
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tess = shutil.which("tesseract")
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if tess:
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try:
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import pytesseract # type: ignore
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from PIL import Image # type: ignore
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with Image.open(png_path) as im:
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text = pytesseract.image_to_string(im)
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if text and text.strip():
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ocr_text = text.strip()
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except Exception:
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pass
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finally:
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try:
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if os.path.exists(png_path):
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os.remove(png_path)
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os.rmdir(tmpdir)
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except Exception:
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pass
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debug_log(f"screenshot: ocr_chars={len(ocr_text)}", "screenshot")
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context.user_print("✅ Screenshot processed.")
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# Return raw OCR text as tool result (no LLM processing here)
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return ToolExecutionResult(success=True, reply_text=ocr_text)
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