Initial commit for fresh VoiceInvoiceAI repo

backend/core/utils.py

@@ -0,0 +1,115 @@
+# backend/core/utils.py
+
+import torch
+import gc
+import re
+import json
+from datetime import datetime, timedelta
+from typing import Dict, Any, Optional
+from backend.config import user_db, item_db # These are now mock DBs, kept for autofill logic
+from backend.models import InvoiceData, InvoiceItem, ValidationError # ValidationError for type hinting/catching
+
+def clear_gpu_memory():
+    """Clears CUDA memory cache and runs garbage collection."""
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+    gc.collect()
+
+def autofill_invoice_data(invoice_data: InvoiceData) -> InvoiceData:
+    """
+    Autofills invoice data based on simulated local databases (user_db, item_db).
+    Fills in missing client address, item prices, and calculates totals/dates.
+
+    Args:
+        invoice_data (InvoiceData): The invoice data Pydantic model to autofill.
+
+    Returns:
+        InvoiceData: The updated invoice data with autofilled information.
+    """
+    # Create a mutable copy to avoid modifying the original object in place
+    # if this function is called on an object that might be reused or
+    # that came directly from a FastAPI request body.
+    invoice_data_copy = invoice_data.model_copy(deep=True)
+
+    if invoice_data_copy.client_name:
+        normalized_client_name = invoice_data_copy.client_name.lower().strip()
+        if normalized_client_name in user_db:
+            client_info = user_db[normalized_client_name]
+            if not invoice_data_copy.client_address:
+                invoice_data_copy.client_address = client_info.get("address")
+            # Only update tax_rate if it's not explicitly set in the incoming data
+            if invoice_data_copy.tax_rate is None or invoice_data_copy.tax_rate == 0.08: # Default value
+                invoice_data_copy.tax_rate = client_info.get("default_tax_rate", 0.08)
+
+    for item in invoice_data_copy.items:
+        # If unit_price is missing but description exists, try to autofill
+        if not item.unit_price and item.description:
+            normalized_description = item.description.lower().strip()
+            for db_item, db_info in item_db.items():
+                if db_item in normalized_description: # Simple substring match
+                    item.unit_price = db_info.get("unit_price")
+                    # Break after finding the first match
+                    break
+        # Ensure item total is calculated or re-calculated after autofill of unit_price
+        if item.quantity is not None and item.unit_price is not None:
+            item.total = round(item.quantity * item.unit_price, 2)
+        elif item.total is None: # If no quantity/unit_price but total needed
+             item.total = 0.0 # Default to 0 if not enough info
+
+    # Recalculate totals after autofilling item prices and ensure they are not None
+    invoice_data_copy.subtotal = round(sum(item.total for item in invoice_data_copy.items if item.total is not None), 2)
+    effective_tax_rate = invoice_data_copy.tax_rate if invoice_data_copy.tax_rate is not None else 0.0
+    invoice_data_copy.tax_amount = round(invoice_data_copy.subtotal * effective_tax_rate, 2)
+    invoice_data_copy.grand_total = round(invoice_data_copy.subtotal + invoice_data_copy.tax_amount, 2)
+
+    # Handle dates
+    if not invoice_data_copy.invoice_date:
+        invoice_data_copy.invoice_date = datetime.now().strftime("%Y-%m-%d")
+    if not invoice_data_copy.due_date:
+        try:
+            invoice_date_dt = datetime.strptime(invoice_data_copy.invoice_date, "%Y-%m-%d")
+            invoice_data_copy.due_date = (invoice_date_dt + timedelta(days=30)).strftime("%Y-%m-%d")
+        except (ValueError, TypeError):
+            # Fallback if invoice_date is invalid or not set
+            invoice_data_copy.due_date = (datetime.now() + timedelta(days=30)).strftime("%Y-%m-%d")
+
+
+    return invoice_data_copy
+
+def check_model_devices(qwen2_audio_model: Optional[Any], device: str) -> str:
+    """
+    Checks the device placement and memory usage of the Qwen2-Audio model.
+    """
+    status_output = []
+    status_output.append("--- Checking Model Device Placement ---")
+
+    if qwen2_audio_model:
+        try:
+            if hasattr(qwen2_audio_model, 'hf_device_map') and qwen2_audio_model.hf_device_map:
+                status_output.append(f"Qwen2-Audio model device map: {qwen2_audio_model.hf_device_map}")
+            else:
+                qwen_device = next(qwen2_audio_model.parameters()).device
+                status_output.append(f"Qwen2-Audio model (first parameter) is on: {qwen_device}")
+
+            status_output.append(f"Qwen2-Audio model data type: {next(qwen2_audio_model.parameters()).dtype}")
+
+            if device == "cuda":
+                status_output.append(f"Current GPU Memory Allocated: {torch.cuda.memory_allocated() / (1024**3):.2f} GB")
+                status_output.append(f"Current GPU Memory Cached: {torch.cuda.memory_reserved() / (1024**3):.2f} GB")
+                status_output.append(f"Max GPU Memory Allocated: {torch.cuda.max_memory_allocated() / (1024**3):.2f} GB")
+                status_output.append(f"Max GPU Memory Cached: {torch.cuda.max_memory_reserved() / (1024**3):.2f} GB")
+        except Exception as e:
+            status_output.append(f"Error checking model device: {e}")
+    else:
+        status_output.append("Qwen2-Audio model is not loaded.")
+
+    status_output.append(f"System detected device: {device}")
+    if device == "cuda":
+        status_output.append(f"Number of CUDA devices: {torch.cuda.device_count()}")
+        if torch.cuda.device_count() > 0:
+            status_output.append(f"Current CUDA device: {torch.cuda.current_device()} ({torch.cuda.get_device_name(torch.cuda.current_device())})")
+            status_output.append(f"Total GPU Memory on current device: {torch.cuda.get_device_properties(torch.cuda.current_device()).total_memory / (1024**3):.2f} GB")
+        else:
+            status_output.append("No CUDA devices detected. Running on CPU.")
+
+    return "\n".join(status_output)