feat: unified Docker image with GPU auto-detection (#37)

Merge CPU, CUDA, and lite Docker images into a single unified image.
One tag (latest) works on all platforms: amd64 (NVIDIA CUDA) and arm64 (CPU).
GPU auto-detected at runtime. All ML models and packages baked in.

Key changes:
- Platform-conditional Dockerfile (nvidia/cuda on amd64, node on arm64)
- tini as PID 1 for proper signal handling
- Fix FILES_STORAGE_PATH data loss bug
- Fix RealESRGAN upscaler (was broken, always fell back to Lanczos)
- Fix PaddleOCR language codes and stdout corruption
- Simplified CI/CD (single build, single tag)
- Expanded model pre-download with verification
- Shutdown timeout, improved health endpoint
- Remove unused lama-cleaner

packages/ai/python/ocr.py

@@ -33,23 +33,39 @@ def run_tesseract(input_path, language):
 def run_paddleocr(input_path, language):
     """Run PaddleOCR."""
     os.environ["PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK"] = "True"
-    from paddleocr import PaddleOCR
-    from gpu import gpu_available
 
-    emit_progress(20, "Loading")
-    ocr = PaddleOCR(lang=language, use_gpu=gpu_available())
-    emit_progress(30, "Scanning")
-    result = ocr.ocr(input_path)
-    emit_progress(70, "Extracting text")
-    text = "\n".join(
-        [
-            line[1][0]
-            for res in result
-            if res
-            for line in res
-            if line and line[1]
-        ]
-    )
+    # Redirect stdout to stderr so PaddleOCR download/init messages
+    # cannot contaminate our JSON result on stdout.
+    stdout_fd = os.dup(1)
+    os.dup2(2, 1)
+
+    try:
+        from paddleocr import PaddleOCR
+        from gpu import gpu_available
+
+        # Map API language codes to PaddleOCR codes
+        paddle_lang_map = {"en": "en", "de": "latin", "fr": "latin", "es": "latin", "zh": "ch", "ja": "japan", "ko": "korean"}
+        paddle_lang = paddle_lang_map.get(language, "en")
+
+        emit_progress(20, "Loading")
+        ocr = PaddleOCR(lang=paddle_lang, use_gpu=gpu_available(), show_log=False)
+        emit_progress(30, "Scanning")
+        result = ocr.ocr(input_path)
+        emit_progress(70, "Extracting text")
+        text = "\n".join(
+            [
+                line[1][0]
+                for res in result
+                if res
+                for line in res
+                if line and line[1]
+            ]
+        )
+    finally:
+        # Restore stdout
+        os.dup2(stdout_fd, 1)
+        os.close(stdout_fd)
+
     return text, "paddleocr"