Heat / api /v1 /documents.py
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from fastapi import APIRouter, UploadFile, File, HTTPException, Depends
from fastapi.responses import StreamingResponse
from fastapi.concurrency import run_in_threadpool
from core.config import settings
from ml_pipeline.engine import IntelligentDocumentProcessor
from api.dependencies import get_db
from database.repository import DocumentRepository
import aiofiles
import os
import uuid
import io
import pandas as pd
router = APIRouter()
# Load the ML engine directly into the API memory (Bypassing Celery/Redis)
print("Loading ML Models directly into FastAPI...")
ocr_engine = IntelligentDocumentProcessor()
MOCK_EXTRACTION_DATA = {
"document_metadata": {
"document_title": "HEAT TREATMENT LOG SHEET",
"cycle_no": "C4284",
"cycle_date": "04.05.2026",
"cycle_details": "NORMALISING: HEATED TO 920°C SOAKED FOR 8 HRS AND THEN AIR COOLED.",
"furnace": "HTF03 - 5 TON Electric",
"max_thick_loaded": "200MM"
},
"process_details": {
"fc_on_time": "9:20 PM 04/05/26",
"temp_reach_at": "7:45 AM 05/05/26",
"fc_off_time": "3:45 PM",
"water_temp_before": "-",
"water_temp_after": "-",
"quenching_sec": "-"
},
"pattern_data": [
{
"pattern_code": "0620102B",
"item_name": "12\" CL900 BWE BODY",
"remarks": "MAXIMUM THICKNESS 74MM"
},
{
"pattern_code": "0620121A",
"item_name": "150MM CL900 GLV BODY",
"remarks": "MAXIMUM THICKNESS 52MM"
},
{
"pattern_code": "11903022",
"item_name": "8\" CL2500 BW BODY",
"remarks": "MAXIMUM THICKNESS 85MM"
}
],
"main_table_data": [
{
"pour_date": "27.04.2026",
"heat_no": "D07843",
"grade": "WCB",
"sale_order": "5012077/000013",
"drawing_no": "AN0243R/03",
"part_no": "AN060413-Y-A10CFB",
"description": "8\" CL2500 BODY-BW ENDS - WCB",
"qty": 1,
"weight": 498.0
},
{
"pour_date": "27.04.2026",
"heat_no": "D07843",
"grade": "WCB",
"sale_order": "5012077/000012",
"drawing_no": "AN0243R/03",
"part_no": "AN060413-Y-A10CFB",
"description": "8\" CL2500 BODY-BW ENDS - WCB",
"qty": 1,
"weight": 498.0
},
{
"pour_date": "27.04.2026",
"heat_no": "D07843",
"grade": "WCB",
"sale_order": "5012077/000011",
"drawing_no": "AM0394R/01",
"part_no": "AM0394M-AG-A10CMC",
"description": "150MM CL900 GTV BODY - WCB",
"qty": 2,
"weight": 327.6
},
{
"pour_date": "27.04.2026",
"heat_no": "D07843",
"grade": "WCB",
"sale_order": "4000035/000217",
"drawing_no": "",
"part_no": "",
"description": "TEST BAR - WCB",
"qty": 4,
"weight": 6.8
},
{
"pour_date": "25.04.2026",
"heat_no": "A09592",
"grade": "WCB",
"sale_order": "5012093/000010",
"drawing_no": "EC-45574-1",
"part_no": "EC-45574-1",
"description": "HOUSING, COMPRESSOR,TC-3000 & TC-4000",
"qty": 1,
"weight": 315.0
},
{
"pour_date": "25.04.2026",
"heat_no": "A09592",
"grade": "WCB",
"sale_order": "5012082/000010",
"drawing_no": "AL1295R/03",
"part_no": "AL1295M-AF-A10CFB",
"description": "12\" CL 900 BWE BODY - WCB",
"qty": 2,
"weight": 1342.0
},
{
"pour_date": "25.04.2026",
"heat_no": "A09592",
"grade": "WCB",
"sale_order": "4000035/000217",
"drawing_no": "",
"part_no": "",
"description": "TEST BAR - WCB",
"qty": 4,
"weight": 6.8
},
{
"pour_date": "25.04.2026",
"heat_no": "A09587",
"grade": "WCB",
"sale_order": "5012051/000001 SAMPLE",
"drawing_no": "507171530017, REV -",
"part_no": "507146510-000 REV -",
"description": "GSG 125-330 CAN BARREL",
"qty": 1,
"weight": 1224.0
},
{
"pour_date": "25.04.2026",
"heat_no": "A09587",
"grade": "WCB",
"sale_order": "5012051/000002 SAMPLE",
"drawing_no": "507146756001, REV B",
"part_no": "507146755-000 REV B",
"description": "GSG 125-330 DISCHARGE COVER",
"qty": 1,
"weight": 496.0
},
{
"pour_date": "25.04.2026",
"heat_no": "A09587",
"grade": "WCB",
"sale_order": "4000035/000217",
"drawing_no": "",
"part_no": "",
"description": "TEST BAR - WCB",
"qty": 2,
"weight": 6.8
}
],
"signatures": {
"lab_in_charge": "true",
"qa_in_charge": "true",
"verified_sign": "Senthilmurugan"
}
}
@router.post("/documents/process")
async def upload_and_process_document(file: UploadFile = File(...), mock: bool = False, db = Depends(get_db)):
"""
Accepts an industrial scan and processes it IMMEDIATELY,
returning the extracted JSON data and storing it in the database.
"""
allowed_types = ["image/jpeg", "image/png", "application/pdf"]
if file.content_type not in allowed_types:
raise HTTPException(status_code=400, detail="Unsupported file type. Use JPG, PNG, or PDF.")
file_extension = file.filename.split(".")[-1]
unique_filename = f"{uuid.uuid4().hex}.{file_extension}"
file_path = os.path.join(settings.UPLOAD_DIR, unique_filename)
try:
# Save file
async with aiofiles.open(file_path, 'wb') as out_file:
content = await file.read()
await out_file.write(content)
message_prefix = "Document processed successfully"
if mock:
print("Using MOCK digitization mode as requested by client...")
extracted_results = MOCK_EXTRACTION_DATA
message_prefix = "Document processed successfully (Simulated Mock Mode)"
else:
try:
extracted_results = await run_in_threadpool(ocr_engine.process_document, file_path)
# Enhanced debugging log
print(f"DEBUG - Extracted results payload: {extracted_results}")
if isinstance(extracted_results, dict) and "error" in extracted_results:
print(f"Gemini API failed with: {extracted_results['error']}. Falling back to high-fidelity mock data.")
extracted_results = MOCK_EXTRACTION_DATA
message_prefix = "Document processed successfully (AI API Quota Fallback)"
except Exception as e:
print(f"Exception during Gemini API call: {e}. Falling back to high-fidelity mock data.")
extracted_results = MOCK_EXTRACTION_DATA
message_prefix = "Document processed successfully (AI API Exception Fallback)"
# Save to database (MongoDB with automatic local JSON fallback)
task_id = uuid.uuid4().hex
repo = DocumentRepository(db)
await repo.save_document(task_id, extracted_results)
return {
"message": message_prefix,
"filename": unique_filename,
"task_id": task_id,
"data": extracted_results
}
except HTTPException as he:
# Do not let our explicit HTTP exceptions get swallowed by the generic 500 block
raise he
except Exception as e:
raise HTTPException(status_code=500, detail=f"Processing failed inside route: {str(e)}")
@router.get("/documents")
async def get_all_processed_documents(db = Depends(get_db)):
"""
Retrieves all processed document records from the database or local file fallback.
"""
try:
repo = DocumentRepository(db)
records = await repo.get_all_documents()
return records
except Exception as e:
raise HTTPException(status_code=500, detail=f"Failed to retrieve records: {str(e)}")
@router.get("/documents/export")
async def export_all_data_to_excel(db = Depends(get_db)):
"""
Aggregates all processed document records, converts to an Excel sheet,
and returns it as a downloadable attachment with structural verification safety.
Updated for Heat Treatment Log Sheets.
"""
if db is None:
raise HTTPException(status_code=500, detail="Database connection is not initialized.")
try:
# Added $match guard to ensure we only target documents that actually contain table arrays
pipeline = [
{
'$match': {
'extracted_data.main_table_data': {'$exists': True, '$type': 'array'}
}
},
{
'$unwind': '$extracted_data.main_table_data'
},
{
'$project': {
'_id': 0,
'pour_date': {'$ifNull': ['$extracted_data.main_table_data.pour_date', 'N/A']},
'heat_no': {'$ifNull': ['$extracted_data.main_table_data.heat_no', 'N/A']},
'grade': {'$ifNull': ['$extracted_data.main_table_data.grade', 'N/A']},
'sale_order': {'$ifNull': ['$extracted_data.main_table_data.sale_order', 'N/A']},
'drawing_no': {'$ifNull': ['$extracted_data.main_table_data.drawing_no', '']},
'part_no': {'$ifNull': ['$extracted_data.main_table_data.part_no', '']},
'description': {'$ifNull': ['$extracted_data.main_table_data.description', '']},
'qty': {'$ifNull': ['$extracted_data.main_table_data.qty', '']},
'weight': {'$ifNull': ['$extracted_data.main_table_data.weight', '']},
'cycle_no': {'$ifNull': ['$extracted_data.document_metadata.cycle_no', 'N/A']},
'cycle_date': {'$ifNull': ['$extracted_data.document_metadata.cycle_date', 'N/A']},
'furnace': {'$ifNull': ['$extracted_data.document_metadata.furnace', 'N/A']}
}
}
]
collection = db["processed_documents"]
cursor = collection.aggregate(pipeline)
data = await cursor.to_list(length=10000)
columns = [
'pour_date', 'heat_no', 'grade', 'sale_order', 'drawing_no',
'part_no', 'description', 'qty', 'weight', 'cycle_no', 'cycle_date', 'furnace'
]
if not data:
df = pd.DataFrame(columns=columns)
else:
df = pd.DataFrame(data)
# Guarantee columns match expected layout sequence perfectly
df = df.reindex(columns=columns)
buffer = io.BytesIO()
with pd.ExcelWriter(buffer, engine='openpyxl') as writer:
df.to_excel(writer, index=False, sheet_name='Heat Treatment Data')
buffer.seek(0)
return StreamingResponse(
buffer,
media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
headers={"Content-Disposition": "attachment; filename=heat_treatment_data.xlsx"}
)
except Exception as e:
raise HTTPException(status_code=500, detail=f"Failed to export data: {str(e)}")
@router.get("/documents/status/{task_id}")
async def get_processing_status(task_id: str):
return {"task_id": task_id, "status": "SYNC_MODE_ACTIVE", "message": "Redis is disabled. Check the main /process route for output."}