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feat: add qa_build mode, tests, and region mode support

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Router Configuration:
- Add mode='qa_build' routing rule in router-config.yml
- Priority 8, uses local_qwen3_8b for Q&A generation

2-Stage Q&A Pipeline Tests:
- Create test_qa_pipeline.py with comprehensive tests
- Test prompt building, JSON parsing, router integration
- Mock DAGI Router responses for testing

Region Mode (Grounding OCR):
- Add region_bbox and region_page parameters to ParseRequest
- Support region mode in local_runtime with bbox in prompt
- Update endpoints to accept region parameters (x, y, width, height, page)
- Validate region parameters and filter pages for region mode
- Pass region_bbox through inference pipeline

Updates:
- Update local_runtime to support region_bbox in prompts
- Update inference.py to pass region_bbox to local_runtime
- Update endpoints.py to handle region mode parameters
This commit is contained in:
Apple
2025-11-16 04:26:35 -08:00
parent be22752590
commit d3c701f3ff
6 changed files with 266 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
router-config.yml
View File

@@ -95,6 +95,14 @@ routing:
use_llm: local_qwen3_8b
description: "microDAO chat → local LLM with RBAC context"
# Q&A Builder mode (for parser-service 2-stage pipeline)
- id: qa_build_mode
priority: 8
when:
mode: qa_build
use_llm: local_qwen3_8b
description: "Q&A generation from parsed documents → local LLM"
# NEW: CrewAI workflow orchestration
- id: crew_mode
priority: 3

37
services/parser-service/app/api/endpoints.py
View File

@@ -34,7 +34,12 @@ async def parse_document_endpoint(
doc_url: Optional[str] = Form(None),
output_mode: str = Form("raw_json"),
dao_id: Optional[str] = Form(None),
doc_id: Optional[str] = Form(None)
doc_id: Optional[str] = Form(None),
region_bbox_x: Optional[float] = Form(None),
region_bbox_y: Optional[float] = Form(None),
region_bbox_width: Optional[float] = Form(None),
region_bbox_height: Optional[float] = Form(None),
region_page: Optional[int] = Form(None)
):
"""
Parse document (PDF or image) using dots.ocr
@@ -81,6 +86,30 @@ async def parse_document_endpoint(
image = load_image(content)
images = [image]
# For region mode, validate and prepare region bbox
region_bbox = None
if output_mode == "region":
if not all([region_bbox_x is not None, region_bbox_y is not None,
region_bbox_width is not None, region_bbox_height is not None]):
raise HTTPException(
status_code=400,
detail="region mode requires region_bbox_x, region_bbox_y, region_bbox_width, region_bbox_height"
)
region_bbox = {
"x": float(region_bbox_x),
"y": float(region_bbox_y),
"width": float(region_bbox_width),
"height": float(region_bbox_height)
}
# If region_page specified, only process that page
if region_page is not None:
if region_page < 1 or region_page > len(images):
raise HTTPException(
status_code=400,
detail=f"region_page {region_page} out of range (1-{len(images)})"
)
images = [images[region_page - 1]]
else:
# TODO: Download from doc_url
raise HTTPException(
@@ -99,14 +128,16 @@ async def parse_document_endpoint(
images=images,
output_mode=output_mode,
doc_id=doc_id or str(uuid.uuid4()),
doc_type=doc_type
doc_type=doc_type,
region_bbox=region_bbox
)
else:
parsed_doc = parse_document_from_images(
images=images,
output_mode=output_mode,
doc_id=doc_id or str(uuid.uuid4()),
doc_type=doc_type
doc_type=doc_type,
region_bbox=region_bbox
)
# Build response based on output_mode

8
services/parser-service/app/runtime/inference.py
View File

@@ -29,7 +29,8 @@ async def parse_document_with_ollama(
images: List[Image.Image],
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"] = "raw_json",
doc_id: Optional[str] = None,
doc_type: Literal["pdf", "image"] = "image"
doc_type: Literal["pdf", "image"] = "image",
region_bbox: Optional[dict] = None
) -> ParsedDocument:
"""
Parse document using Ollama API
@@ -109,7 +110,8 @@ def parse_document_from_images(
images: List[Image.Image],
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"] = "raw_json",
doc_id: Optional[str] = None,
doc_type: Literal["pdf", "image"] = "image"
doc_type: Literal["pdf", "image"] = "image",
region_bbox: Optional[dict] = None
) -> ParsedDocument:
"""
Parse document from list of images using dots.ocr model
@@ -159,7 +161,7 @@ def parse_document_from_images(
image_bytes = buf.getvalue()
# Use local_runtime with native prompt modes
generated_text = parse_document_with_local(image_bytes, output_mode)
generated_text = parse_document_with_local(image_bytes, output_mode, region_bbox)
logger.debug(f"Model output for page {idx}: {generated_text[:100]}...")

25
services/parser-service/app/runtime/local_runtime.py
View File

@@ -6,7 +6,7 @@ Maps OutputMode to dots.ocr prompt modes using dict_promptmode_to_prompt
import os
import tempfile
import logging
from typing import Literal, Optional
from typing import Literal, Optional, Dict, Any
import torch
from transformers import AutoModelForVision2Seq, AutoProcessor
@@ -124,18 +124,29 @@ def get_model():
return _model, _processor
def _build_prompt(output_mode: str) -> str:
def _build_prompt(output_mode: str, region_bbox: Optional[Dict[str, Any]] = None) -> str:
"""
Build prompt for dots.ocr based on OutputMode
Args:
output_mode: One of "raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"
region_bbox: Optional bounding box for region mode {"x": float, "y": float, "width": float, "height": float}
Returns:
Prompt string for dots.ocr
"""
prompt_key = DOTS_PROMPT_MAP.get(output_mode, "prompt_layout_all_en")
# For region mode, add bbox information to prompt
if output_mode == "region" and region_bbox:
base_prompt = FALLBACK_PROMPTS.get("prompt_grounding_ocr", "")
region_info = (
f"\n\nExtract content from the specified region:\n"
f"Bounding box: x={region_bbox.get('x', 0)}, y={region_bbox.get('y', 0)}, "
f"width={region_bbox.get('width', 0)}, height={region_bbox.get('height', 0)}"
)
return base_prompt + region_info
# Try to use native dots.ocr prompts
if DOTS_PROMPTS_AVAILABLE and prompt_key in dict_promptmode_to_prompt:
prompt = dict_promptmode_to_prompt[prompt_key]
@@ -167,7 +178,8 @@ def _build_messages(image_path: str, prompt: str) -> list:
def _generate_from_path(
image_path: str,
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"]
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"],
region_bbox: Optional[Dict[str, Any]] = None
) -> str:
"""
Generate output from image path using dots.ocr model
@@ -180,7 +192,7 @@ def _generate_from_path(
Generated text from model
"""
model, processor = get_model()
prompt = _build_prompt(output_mode)
prompt = _build_prompt(output_mode, region_bbox)
messages = _build_messages(image_path, prompt)
# Apply chat template
@@ -236,7 +248,8 @@ def _generate_from_path(
def parse_document_with_local(
image_bytes: bytes,
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"] = "raw_json"
output_mode: Literal["raw_json", "markdown", "qa_pairs", "chunks", "layout_only", "region"] = "raw_json",
region_bbox: Optional[Dict[str, Any]] = None
) -> str:
"""
Parse document from image bytes using local dots.ocr model
@@ -264,7 +277,7 @@ def parse_document_with_local(
f.write(image_bytes)
try:
return _generate_from_path(tmp_path, output_mode)
return _generate_from_path(tmp_path, output_mode, region_bbox)
finally:
try:
os.remove(tmp_path)

3
services/parser-service/app/schemas.py
View File

@@ -120,6 +120,9 @@ class ParseRequest(BaseModel):
)
dao_id: Optional[str] = Field(None, description="DAO ID")
doc_id: Optional[str] = Field(None, description="Document ID")
# Region mode parameters (for grounding OCR)
region_bbox: Optional[BBox] = Field(None, description="Bounding box for region mode (x, y, width, height)")
region_page: Optional[int] = Field(None, description="Page number for region mode")
class ParseResponse(BaseModel):

197
services/parser-service/tests/test_qa_pipeline.py Normal file
View File

@@ -0,0 +1,197 @@
"""
Tests for 2-stage Q&A pipeline (PARSER → LLM)
"""
import pytest
from unittest.mock import AsyncMock, patch, MagicMock
from PIL import Image
import io
import json
from app.schemas import ParsedDocument, ParsedPage, ParsedBlock, BBox
from app.runtime.qa_builder import build_qa_pairs_via_router, _build_qa_prompt, _parse_qa_response
class TestQABuilder:
"""Tests for Q&A builder (2-stage pipeline)"""
def test_build_qa_prompt(self):
"""Test prompt building for Q&A generation"""
# Create mock parsed document
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[
ParsedPage(
page_num=1,
blocks=[
ParsedBlock(
type="heading",
text="Test Document",
bbox=BBox(x=0, y=0, width=800, height=50),
reading_order=1,
page_num=1
),
ParsedBlock(
type="paragraph",
text="This is a test document with some content.",
bbox=BBox(x=0, y=60, width=800, height=100),
reading_order=2,
page_num=1
)
],
width=800,
height=600
)
],
metadata={}
)
prompt = _build_qa_prompt(doc)
# Check prompt structure
assert "OCR-документу" in prompt
assert "JSON-масив" in prompt
assert "question" in prompt
assert "answer" in prompt
assert "source_page" in prompt
assert "Test Document" in prompt or "test document" in prompt.lower()
def test_parse_qa_response_valid_json(self):
"""Test parsing valid JSON response from LLM"""
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[ParsedPage(page_num=1, blocks=[], width=800, height=600)],
metadata={}
)
response_text = json.dumps([
{
"question": "Що це за документ?",
"answer": "Це тестовий документ",
"source_page": 1,
"confidence": 0.9
},
{
"question": "Який контент?",
"answer": "Тестовий контент",
"source_page": 1
}
])
qa_pairs = _parse_qa_response(response_text, doc)
assert len(qa_pairs) == 2
assert qa_pairs[0].question == "Що це за документ?"
assert qa_pairs[0].answer == "Це тестовий документ"
assert qa_pairs[0].source_page == 1
assert qa_pairs[0].confidence == 0.9
def test_parse_qa_response_markdown_code_block(self):
"""Test parsing JSON from markdown code block"""
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[ParsedPage(page_num=1, blocks=[], width=800, height=600)],
metadata={}
)
response_text = "```json\n" + json.dumps([
{
"question": "Тест?",
"answer": "Відповідь"
}
]) + "\n```"
qa_pairs = _parse_qa_response(response_text, doc)
assert len(qa_pairs) == 1
assert qa_pairs[0].question == "Тест?"
def test_parse_qa_response_invalid_json(self):
"""Test parsing invalid JSON (should return empty list)"""
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[ParsedPage(page_num=1, blocks=[], width=800, height=600)],
metadata={}
)
response_text = "This is not JSON"
qa_pairs = _parse_qa_response(response_text, doc)
assert len(qa_pairs) == 0
@pytest.mark.asyncio
async def test_build_qa_pairs_via_router_success(self):
"""Test successful Q&A generation via DAGI Router"""
# Create mock parsed document
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[
ParsedPage(
page_num=1,
blocks=[
ParsedBlock(
type="paragraph",
text="Test content",
bbox=BBox(x=0, y=0, width=800, height=100),
reading_order=1,
page_num=1
)
],
width=800,
height=600
)
],
metadata={}
)
# Mock router response
mock_response = {
"ok": True,
"data": {
"text": json.dumps([
{
"question": "Що це?",
"answer": "Тест",
"source_page": 1
}
])
}
}
with patch("app.runtime.qa_builder.httpx.AsyncClient") as mock_client:
mock_client.return_value.__aenter__.return_value.post = AsyncMock(
return_value=MagicMock(
raise_for_status=MagicMock(),
json=lambda: mock_response
)
)
qa_pairs = await build_qa_pairs_via_router(doc, dao_id="test-dao")
assert len(qa_pairs) == 1
assert qa_pairs[0].question == "Що це?"
@pytest.mark.asyncio
async def test_build_qa_pairs_via_router_failure(self):
"""Test Q&A generation failure (should raise exception)"""
doc = ParsedDocument(
doc_id="test-doc",
doc_type="pdf",
pages=[ParsedPage(page_num=1, blocks=[], width=800, height=600)],
metadata={}
)
with patch("app.runtime.qa_builder.httpx.AsyncClient") as mock_client:
mock_client.return_value.__aenter__.return_value.post = AsyncMock(
side_effect=Exception("Router error")
)
with pytest.raises(RuntimeError):
await build_qa_pairs_via_router(doc, dao_id="test-dao")