diff --git a/app.py b/app.py
index 900d13f..53edae0 100644
--- a/app.py
+++ b/app.py
@@ -27,6 +27,18 @@ file_handler.setFormatter(logging.Formatter(
     "%(asctime)s - %(levelname)s - %(name)s - %(message)s"
 ))
 
+import pyodbc
+
+def get_db_connection():
+    return pyodbc.connect(
+        "DRIVER={ODBC Driver 18 for SQL Server};"
+        "SERVER=VPS88.DATACENTER.CSTI;"
+        "DATABASE=Faircot-Test;"
+        "UID=SINGA_META;"
+        "PWD=Start.123;"
+        "TrustServerCertificate=yes;"
+    )
+
 class AHKParser:
     lab = "AHK"    
     
@@ -484,48 +496,126 @@ predictor = ocr_predictor(pretrained=True)
 
 logger.info("Models loaded successfully.")
 
-# =============================
-# 🧠 Smart OCR
-# =============================
-# @app.post("/ocr")
-# async def ocr(file: UploadFile):
-#     logger.info(f"Received OCR request: {file.filename}")
-#     try:
-#         file_data = await file.read()
-#         ext = file.filename.lower()
+@app.post("/weight-report")
+def create_weight_report(payload: dict = Body(...)):
+    logger.info("Create weight report called")
 
-#         # --------- PDF with native text ---------
-#         if ext.endswith(".pdf"):
-#             logger.info("PDF detected → Extracting native text first")
-#             reader = PdfReader(io.BytesIO(file_data))
-#             direct_text = "".join(
-#                 page.extract_text() or "" for page in reader.pages
-#             )
+    # -------- Validation minimale --------
+    required_fields = [
+        "chunk_key",
+        "gross_weight",
+        "net_weight",
+        "tare_total",
+        "bags",
+        "surveyor_code",
+        "place_key",
+        "report_date"
+    ]
 
-#             if direct_text.strip():
-#                 logger.info("Native PDF text found → No OCR needed")
-#                 return {"ocr_text": direct_text}
+    missing = [f for f in required_fields if f not in payload]
+    if missing:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Missing fields: {', '.join(missing)}"
+        )
 
-#             # -------- Fallback: scanned PDF OCR --------
-#             logger.info("No native text → PDF treated as scanned → OCR")
-#             from pdf2image import convert_from_bytes
-#             images = convert_from_bytes(file_data)
-#             text = ""
-#             for i, img in enumerate(images):
-#                 logger.info(f"OCR page {i+1}/{len(images)}")
-#                 text += pytesseract.image_to_string(img) + "\n"
+    try:
+        chunk_key     = int(payload["chunk_key"])
+        gross_weight  = float(payload["gross_weight"])
+        net_weight    = float(payload["net_weight"])
+        tare_total    = float(payload["tare_total"])
+        bags          = int(payload["bags"])
+        surveyor_code = int(payload["surveyor_code"])
+        place_key     = int(payload["place_key"])
+        report_date   = int(payload["report_date"])
+    except Exception as e:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Invalid payload types: {e}"
+        )
 
-#             return {"ocr_text": text}
+    try:
+        conn = get_db_connection()
+        cursor = conn.cursor()
 
-#         # --------- Image file OCR ---------
-#         logger.info("Image detected → Running OCR")
-#         img = Image.open(io.BytesIO(file_data))
-#         text = pytesseract.image_to_string(img)
-#         return {"ocr_text": text}
+        cursor.execute("""
+        EXEC dbo.sp_Singa_Automation_InsertWeightReport
+            @CHUNK_KEY = ?,
+            @BAGS_SOUND_AND_FULL = ?,
+            @BAGS_SOUND_AND_SLACK = 0,
+            @BAGS_DAMAGED_AND_FULL = 0,
+            @BAGS_DAMAGED_AND_SLACK = 0,
+            @BAGS_SHORT_LANDED = 0,
+            @GROSS_SOUND_AND_FULL = ?,
+            @GROSS_SOUND_AND_SLACK = 0,
+            @GROSS_DAMAGED_AND_FULL = 0,
+            @GROSS_DAMAGED_AND_SLACK = 0,
+            @GROSS_SAMPLES = 0,
+            @WEIGHING_DATE = ?,
+            @REPORT_DATE = ?,
+            @DATE_RECEIVED = ?,
+            @NET_WEIGHT = ?,
+            @TARE_TOTAL = ?,
+            @TARE_FOR_TEN_BAGS = 0,
+            @SURVEYOR_CODE = ?,
+            @PLACE_KEY = ?,
+            @SAMPLE_AFTER_WEIGHING = 'N',
+            @MODIFIED_BY = 'FAIRCOTBOT',
+            @MODIFY_DATE = ?,
+            @VERSION_NB = 1,
+            @FORWARDER_REF = 'API-TRYTON',
+            @INSURED_VALUE = '0',
+            @CREATED_BY = 1424,
+            @UPDATED_BY = 1424,
+            @BUY_INVOICE_AMOUNT = 0,
+            @BUY_CURR_KEY = 0,
+            @SEL_INVOICE_AMOUNT = 0,
+            @SEL_CURR_KEY = 0,
+            @CONSISTENCY = 'N',
+            @FINALIZED = 'N',
+            @MOISTURE_VALUE = NULL,
+            @REPORT_TYPE = 0,
+            @WET_WEIGHT = NULL,
+            @WSMD_LOCATION = 0
+        """,
+        chunk_key,
+        bags,
+        gross_weight,
+        report_date,
+        report_date,
+        report_date,
+        net_weight,
+        tare_total,
+        surveyor_code,
+        place_key,
+        report_date
+        )
+
+        # 🟢 On récupère le SELECT final de la SP
+        row = cursor.fetchone()
+        conn.commit()
+
+        if not row:
+            raise HTTPException(
+                status_code=500,
+                detail="Stored procedure returned no data"
+            )
+
+        return {
+            "success": True,
+            "weight_report_key": row.WEIGHT_REPORT_KEY
+        }
+
+    except Exception as e:
+        logger.exception("Weight report creation failed")
+        raise HTTPException(status_code=500, detail=str(e))
+
+    finally:
+        try:
+            conn.close()
+        except:
+            pass
 
-#     except Exception as e:
-#         logger.error(f"OCR failed: {e}", exc_info=True)
-#         raise HTTPException(status_code=500, detail=str(e))
 @app.post("/ocr")
 async def ocr(file: UploadFile):
     """
@@ -849,7 +939,6 @@ def call_extractor(text: str, lab: str = "AHK"):
 
     return response.json()
 
-
 @app.post("/parse")
 async def parse_endpoint(text: str = Body(..., embed=True)):
     lab = parse_report(text)