fix: Restore all files lost during destructive rebase
A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.
This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).
Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
214
backend/klausur/services/trocr_client.py
Normal file
214
backend/klausur/services/trocr_client.py
Normal file
@@ -0,0 +1,214 @@
|
||||
"""
|
||||
TrOCR Client - Connects to external TrOCR service (Mac Mini).
|
||||
|
||||
This client forwards OCR requests to the TrOCR service running on
|
||||
the Mac Mini, enabling handwriting recognition without requiring
|
||||
local GPU/ML dependencies.
|
||||
|
||||
Privacy: Images are sent over the local network only - no cloud.
|
||||
"""
|
||||
import os
|
||||
import httpx
|
||||
import logging
|
||||
from typing import Optional, List, Dict
|
||||
from dataclasses import dataclass
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Mac Mini TrOCR Service URL
|
||||
TROCR_SERVICE_URL = os.environ.get(
|
||||
"TROCR_SERVICE_URL",
|
||||
"http://192.168.178.163:8084"
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class OCRResult:
|
||||
"""Result from TrOCR extraction."""
|
||||
text: str
|
||||
confidence: float
|
||||
processing_time_ms: int
|
||||
device: str = "remote"
|
||||
|
||||
|
||||
class TrOCRClient:
|
||||
"""
|
||||
Client for external TrOCR service.
|
||||
|
||||
Usage:
|
||||
client = TrOCRClient()
|
||||
|
||||
# Check if service is available
|
||||
if await client.is_available():
|
||||
result = await client.extract_text(image_bytes)
|
||||
print(result.text)
|
||||
"""
|
||||
|
||||
def __init__(self, base_url: Optional[str] = None):
|
||||
self.base_url = base_url or TROCR_SERVICE_URL
|
||||
self._client: Optional[httpx.AsyncClient] = None
|
||||
|
||||
async def _get_client(self) -> httpx.AsyncClient:
|
||||
"""Get or create HTTP client."""
|
||||
if self._client is None or self._client.is_closed:
|
||||
self._client = httpx.AsyncClient(
|
||||
base_url=self.base_url,
|
||||
timeout=300.0 # 5 min timeout for model loading
|
||||
)
|
||||
return self._client
|
||||
|
||||
async def close(self):
|
||||
"""Close the HTTP client."""
|
||||
if self._client and not self._client.is_closed:
|
||||
await self._client.aclose()
|
||||
|
||||
async def is_available(self) -> bool:
|
||||
"""Check if TrOCR service is available."""
|
||||
try:
|
||||
client = await self._get_client()
|
||||
response = await client.get("/health", timeout=5.0)
|
||||
return response.status_code == 200
|
||||
except Exception as e:
|
||||
logger.warning(f"TrOCR service not available: {e}")
|
||||
return False
|
||||
|
||||
async def get_status(self) -> Dict:
|
||||
"""Get TrOCR service status."""
|
||||
try:
|
||||
client = await self._get_client()
|
||||
response = await client.get("/api/v1/status")
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get TrOCR status: {e}")
|
||||
return {
|
||||
"status": "unavailable",
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
async def extract_text(
|
||||
self,
|
||||
image_data: bytes,
|
||||
filename: str = "image.png",
|
||||
detect_lines: bool = True
|
||||
) -> OCRResult:
|
||||
"""
|
||||
Extract text from an image using TrOCR.
|
||||
|
||||
Args:
|
||||
image_data: Raw image bytes
|
||||
filename: Original filename
|
||||
detect_lines: Whether to detect individual lines
|
||||
|
||||
Returns:
|
||||
OCRResult with extracted text
|
||||
"""
|
||||
try:
|
||||
client = await self._get_client()
|
||||
|
||||
files = {"file": (filename, image_data, "image/png")}
|
||||
params = {"detect_lines": str(detect_lines).lower()}
|
||||
|
||||
response = await client.post(
|
||||
"/api/v1/extract",
|
||||
files=files,
|
||||
params=params
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
data = response.json()
|
||||
|
||||
return OCRResult(
|
||||
text=data.get("text", ""),
|
||||
confidence=data.get("confidence", 0.0),
|
||||
processing_time_ms=data.get("processing_time_ms", 0),
|
||||
device=data.get("device", "remote")
|
||||
)
|
||||
|
||||
except httpx.TimeoutException:
|
||||
logger.error("TrOCR request timed out (model may be loading)")
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"TrOCR extraction failed: {e}")
|
||||
raise
|
||||
|
||||
async def batch_extract(
|
||||
self,
|
||||
images: List[bytes],
|
||||
filenames: Optional[List[str]] = None,
|
||||
detect_lines: bool = True
|
||||
) -> List[OCRResult]:
|
||||
"""
|
||||
Extract text from multiple images.
|
||||
|
||||
Args:
|
||||
images: List of image bytes
|
||||
filenames: Optional list of filenames
|
||||
detect_lines: Whether to detect individual lines
|
||||
|
||||
Returns:
|
||||
List of OCRResult
|
||||
"""
|
||||
if filenames is None:
|
||||
filenames = [f"image_{i}.png" for i in range(len(images))]
|
||||
|
||||
try:
|
||||
client = await self._get_client()
|
||||
|
||||
files = [
|
||||
("files", (fn, img, "image/png"))
|
||||
for fn, img in zip(filenames, images)
|
||||
]
|
||||
|
||||
response = await client.post(
|
||||
"/api/v1/batch-extract",
|
||||
files=files
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
data = response.json()
|
||||
results = []
|
||||
|
||||
for item in data.get("results", []):
|
||||
results.append(OCRResult(
|
||||
text=item.get("text", ""),
|
||||
confidence=item.get("confidence", 0.85),
|
||||
processing_time_ms=0,
|
||||
device="remote"
|
||||
))
|
||||
|
||||
return results
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"TrOCR batch extraction failed: {e}")
|
||||
raise
|
||||
|
||||
|
||||
# Singleton instance
|
||||
_trocr_client: Optional[TrOCRClient] = None
|
||||
|
||||
|
||||
def get_trocr_client() -> TrOCRClient:
|
||||
"""Get the TrOCR client singleton."""
|
||||
global _trocr_client
|
||||
if _trocr_client is None:
|
||||
_trocr_client = TrOCRClient()
|
||||
return _trocr_client
|
||||
|
||||
|
||||
async def extract_text_from_image(
|
||||
image_data: bytes,
|
||||
filename: str = "image.png"
|
||||
) -> OCRResult:
|
||||
"""
|
||||
Convenience function to extract text from an image.
|
||||
|
||||
Args:
|
||||
image_data: Raw image bytes
|
||||
filename: Original filename
|
||||
|
||||
Returns:
|
||||
OCRResult with extracted text
|
||||
"""
|
||||
client = get_trocr_client()
|
||||
return await client.extract_text(image_data, filename)
|
||||
Reference in New Issue
Block a user