Use shared prompt loader and structured OCR response in branches

- Replaces duplicated _load_prompt() helpers with shared load_prompt().

- Classifier raises cleanly when no renderable pages exist.

- scanned_print, handwritten, and mixed_unknown branches now force

  response_format=OcrResponse and parse via client.parse_json().

- Adds branch tests for multi-page OCR and corrected invoice handling.

src/odoo_ocr/pipeline/classifier.py

@@ -9,6 +9,7 @@ import fitz  # pymupdf
 from PIL import Image, ImageStat
 
 from odoo_ocr.clients import BaseVLMClient
+from odoo_ocr.clients.base import load_prompt
 from odoo_ocr.config import Settings
 from odoo_ocr.schemas.document import ClassificationResult, DocumentClass
 
@@ -89,7 +90,12 @@ async def classify_document(
         logger.info("Heuristic classifier: %s", heuristic.category)
         return heuristic
 
-    system_prompt = _load_prompt("classifier_system.txt")
+    if not pages:
+        raise ValueError(
+            f"Document {path} has no renderable pages; cannot classify with the VLM fallback."
+        )
+
+    system_prompt = load_prompt("classifier_system.txt")
     user_prompt = (
         "Classify this invoice document. Return only the requested JSON object."
     )
@@ -104,9 +110,3 @@ async def classify_document(
     result = client.parse_json(response.content, ClassificationResult)
     logger.info("VLM classifier: %s (confidence %.2f)", result.category, result.confidence)
     return result
-
-
-def _load_prompt(name: str) -> str:
-    from odoo_ocr.clients.base import BaseVLMClient
-
-    return BaseVLMClient._load_prompt_file(Path("prompts") / name)

src/odoo_ocr/pipeline/handwritten.py

@@ -10,7 +10,9 @@ import numpy as np
 from PIL import Image
 
 from odoo_ocr.clients import BaseVLMClient
+from odoo_ocr.clients.base import load_prompt
 from odoo_ocr.config import Settings
+from odoo_ocr.schemas import OcrResponse
 
 logger = logging.getLogger(__name__)
 
@@ -28,14 +30,6 @@ def _preprocess_handwritten(image: Image.Image) -> Image.Image:
     return Image.fromarray(processed, mode="L").convert("RGB")
 
 
-def _load_prompt(name: str) -> str:
-    from pathlib import Path
-
-    from odoo_ocr.clients.base import BaseVLMClient
-
-    return BaseVLMClient._load_prompt_file(Path("prompts") / name)
-
-
 async def process_handwritten(
     path: Path,
     pages: list[Image.Image],
@@ -43,7 +37,7 @@ async def process_handwritten(
     settings: Settings,
 ) -> str:
     """Run OCR on handwritten invoice pages using the configured handwriting model."""
-    system_prompt = _load_prompt("ocr_system.txt")
+    system_prompt = load_prompt("ocr_system.txt")
     user_prompt = (
         "Read all text from this handwritten invoice accurately. "
         "Preserve line breaks and mark unclear words with [UNCLEAR]."
@@ -56,17 +50,12 @@ async def process_handwritten(
             system_prompt=system_prompt,
             user_prompt=f"{user_prompt} (page {i + 1} of {len(pages)})",
             images=[preprocessed],
+            response_format=OcrResponse,
             temperature=0.1,
             model=settings.models.ocr,
         )
-        import json
-
-        try:
-            parsed = json.loads(response.content.strip().strip("`").removeprefix("json").strip())
-            text = parsed.get("text", response.content)
-        except Exception:
-            text = response.content
-        page_texts.append(f"--- Page {i + 1} ---\n{text.strip()}")
+        ocr = client.parse_json(response.content, OcrResponse)
+        page_texts.append(f"--- Page {i + 1} ---\n{ocr.text.strip()}")
 
     full_text = "\n\n".join(page_texts)
     logger.info("Handwritten OCR extracted %d characters from %s", len(full_text), path)

src/odoo_ocr/pipeline/mixed_unknown.py

@@ -8,19 +8,13 @@ from pathlib import Path
 from PIL import Image
 
 from odoo_ocr.clients import BaseVLMClient
+from odoo_ocr.clients.base import load_prompt
 from odoo_ocr.config import Settings
+from odoo_ocr.schemas import OcrResponse
 
 logger = logging.getLogger(__name__)
 
 
-def _load_prompt(name: str) -> str:
-    from pathlib import Path
-
-    from odoo_ocr.clients.base import BaseVLMClient
-
-    return BaseVLMClient._load_prompt_file(Path("prompts") / name)
-
-
 async def process_mixed_unknown(
     path: Path,
     pages: list[Image.Image],
@@ -32,7 +26,7 @@ async def process_mixed_unknown(
     For now this runs the same OCR path as scanned_print but with a more
     permissive prompt. Future: ensemble multiple models and merge outputs.
     """
-    system_prompt = _load_prompt("ocr_system.txt")
+    system_prompt = load_prompt("ocr_system.txt")
     user_prompt = (
         "Extract all readable text from this document. It may contain a mix of "
         "printed text, handwriting, stamps, or low-quality scans. Preserve layout."
@@ -44,17 +38,12 @@ async def process_mixed_unknown(
             system_prompt=system_prompt,
             user_prompt=f"{user_prompt} (page {i + 1} of {len(pages)})",
             images=[page],
+            response_format=OcrResponse,
             temperature=0.1,
             model=settings.models.ocr,
         )
-        import json
-
-        try:
-            parsed = json.loads(response.content.strip().strip("`").removeprefix("json").strip())
-            text = parsed.get("text", response.content)
-        except Exception:
-            text = response.content
-        page_texts.append(f"--- Page {i + 1} ---\n{text.strip()}")
+        ocr = client.parse_json(response.content, OcrResponse)
+        page_texts.append(f"--- Page {i + 1} ---\n{ocr.text.strip()}")
 
     full_text = "\n\n".join(page_texts)
     logger.info("Robust OCR extracted %d characters from %s", len(full_text), path)

src/odoo_ocr/pipeline/scanned_print.py

@@ -8,19 +8,13 @@ from pathlib import Path
 from PIL import Image
 
 from odoo_ocr.clients import BaseVLMClient
+from odoo_ocr.clients.base import load_prompt
 from odoo_ocr.config import Settings
+from odoo_ocr.schemas import OcrResponse
 
 logger = logging.getLogger(__name__)
 
 
-def _load_prompt(name: str) -> str:
-    from pathlib import Path
-
-    from odoo_ocr.clients.base import BaseVLMClient
-
-    return BaseVLMClient._load_prompt_file(Path("prompts") / name)
-
-
 async def process_scanned_print(
     path: Path,
     pages: list[Image.Image],
@@ -28,7 +22,7 @@ async def process_scanned_print(
     settings: Settings,
 ) -> str:
     """Run OCR on each page of a scanned printed invoice and return combined text."""
-    system_prompt = _load_prompt("ocr_system.txt")
+    system_prompt = load_prompt("ocr_system.txt")
     user_prompt = "Read all text from this printed invoice page accurately."
 
     page_texts: list[str] = []
@@ -37,18 +31,12 @@ async def process_scanned_print(
             system_prompt=system_prompt,
             user_prompt=f"{user_prompt} (page {i + 1} of {len(pages)})",
             images=[page],
+            response_format=OcrResponse,
             temperature=0.1,
             model=settings.models.ocr,
         )
-        # The OCR prompt asks for {"text": "..."}.
-        import json
-
-        try:
-            parsed = json.loads(response.content.strip().strip("`").removeprefix("json").strip())
-            text = parsed.get("text", response.content)
-        except Exception:
-            text = response.content
-        page_texts.append(f"--- Page {i + 1} ---\n{text.strip()}")
+        ocr = client.parse_json(response.content, OcrResponse)
+        page_texts.append(f"--- Page {i + 1} ---\n{ocr.text.strip()}")
 
     full_text = "\n\n".join(page_texts)
     logger.info("OCR extracted %d characters from scanned invoice %s", len(full_text), path)

tests/test_branches.py

@@ -0,0 +1,59 @@
+"""Tests for the scanned_print, handwritten, and mixed_unknown branches."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+from PIL import Image
+
+from odoo_ocr.config import Settings
+from odoo_ocr.pipeline.handwritten import process_handwritten
+from odoo_ocr.pipeline.mixed_unknown import process_mixed_unknown
+from odoo_ocr.pipeline.scanned_print import process_scanned_print
+from tests.conftest import FakeVLMClient
+
+
+def _fake_ocr_client(text: str = "Hello invoice 123") -> FakeVLMClient:
+    return FakeVLMClient(responses={"OCR engine": {"text": text}})
+
+
+def _pages(count: int = 2) -> list[Image.Image]:
+    return [Image.new("RGB", (20, 20)) for _ in range(count)]
+
+
+@pytest.mark.asyncio
+async def test_scanned_print_multi_page() -> None:
+    settings = Settings()
+    client = _fake_ocr_client()
+    text = await process_scanned_print(Path("scan.jpg"), _pages(2), client, settings)
+    assert "--- Page 1 ---" in text
+    assert "--- Page 2 ---" in text
+    assert text.count("Hello invoice 123") == 2
+    assert all(call["model"] == settings.models.ocr for call in client.calls)
+
+
+@pytest.mark.asyncio
+async def test_scanned_print_rejects_invalid_json() -> None:
+    """Branches no longer silently fall back to raw content; invalid JSON fails."""
+    client = FakeVLMClient(responses={"OCR engine": "plain text without json"})
+    with pytest.raises(ValueError, match="Response does not match schema"):
+        await process_scanned_print(Path("scan.jpg"), _pages(1), client, Settings())
+
+
+@pytest.mark.asyncio
+async def test_handwritten_extracts_text() -> None:
+    settings = Settings()
+    client = _fake_ocr_client("handwritten total 42")
+    text = await process_handwritten(Path("hand.jpg"), _pages(1), client, settings)
+    assert "handwritten total 42" in text
+    assert client.calls[0]["model"] == settings.models.ocr
+
+
+@pytest.mark.asyncio
+async def test_mixed_unknown_extracts_text() -> None:
+    settings = Settings()
+    client = _fake_ocr_client("mixed content text")
+    text = await process_mixed_unknown(Path("mixed.jpg"), _pages(1), client, settings)
+    assert "mixed content text" in text
+    assert client.calls[0]["model"] == settings.models.ocr