doc: Refactor and Refining code

src/common/utils.py

@@ -2,20 +2,20 @@ import re
 import math
 from fastapi import Request
 
-
+# Get the Real IP of the User not the infra IP (if behind proxy) for logging and abuse monitoring.
 def get_ip(request: Request) -> str:
     forwarded = request.headers.get("X-Forwarded-For")
     if forwarded:
         return forwarded.split(",")[0].strip()
     return request.client.host if request.client else "unknown"
 
-
+# Returns Boolean indicating if the provided key is the same as the default value (ignoring whitespace).
 def is_default_key(key: str, default: str) -> bool:
     if not key or not default:
         return False
     return key.strip() == default.strip()
 
-
+# Takes The Cloduinary URL and extracts the credentials from it and returns a dict with cloud_name, api_key and api_secret.
 def get_cloudinary_creds(url: str) -> dict:
     if not url or not url.startswith("cloudinary://"):
         return {}
@@ -31,13 +31,13 @@ def get_cloudinary_creds(url: str) -> dict:
     except ValueError:
         return {}
 
-
+# Replace everything except letters, numbers, _, -, . with underscores
 def sanitize_filename(filename: str) -> str:
     if not filename:
         return "unnamed_file"
     return re.sub(r'[^a-zA-Z0-9_\-\.]', '_', filename)
 
-
+# Lower Casing the File Name
 def standardize_category_name(name: str) -> str:
     if not name:
         return "uncategorized"
@@ -52,7 +52,7 @@ def to_list(vector) -> list[float]:
     except TypeError:
         return []
 
-
+# Extracting the ID from The URL
 def url_to_public_id(url: str) -> str:
     if not url:
         return ""
@@ -60,6 +60,7 @@ def url_to_public_id(url: str) -> str:
         parts = url.split("/upload/")
         if len(parts) > 1:
             path = parts[1].split("/", 1)[-1]
+            # Splits From Right and place that thing first in list
             return path.rsplit(".", 1)[0]
         return ""
     except Exception:

src/core/config.py

@@ -3,32 +3,48 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-# ──────────────────────────────────────────────────────────────
-# Credentials & core
-# ──────────────────────────────────────────────────────────────
+"""This Files have Imported and created Global Variables which are used 
+    Throughout the Project , There are in Total of 56 Variables 
+    """
+
+
+# ===============================================================
+# Credentals / Secrets (set in HF Space secrets) / KEYS / URLS
+# ===============================================================
+
+#Pinecone + Cloudinary credentials (set in HF Space secrets)
 DEFAULT_PINECONE_KEY = os.getenv("DEFAULT_PINECONE_KEY", "")
 DEFAULT_CLOUDINARY_URL = os.getenv("DEFAULT_CLOUDINARY_URL", "")
+#supbase Credentials
+SUPABASE_URL = os.getenv("SUPABASE_URL", "")
+SUPABASE_SERVICE_KEY = os.getenv("SUPABASE_SERVICE_KEY", "")
+# HF Credentials
+HF_TOKEN = os.getenv("HF_TOKEN", "")
+# Upstash_Redis credentials
+UPSTASH_REDIS_URL = os.getenv("UPSTASH_REDIS_URL", "")
+UPSTASH_REDIS_TOKEN = os.getenv("UPSTASH_REDIS_TOKEN", "")
+
+# ===============================================================
+# Variables Set in HF Spaces Can be configured
+# ===============================================================
+
 
-# Legacy index (kept for read-only backward compat during Phase 2 rollout)
+# Index Names To be used to name variable for storing embeddings genereted from DInov2 and SIGLIP models
 IDX_FACES = os.getenv("IDX_FACES", "enterprise-faces")
 IDX_OBJECTS = os.getenv("IDX_OBJECTS", "enterprise-objects")
 
-# Phase 2: split face indexes (512-d each)
+# Configure Index Names for storing Embedding Generated by ARCFACE and ADAFACE
 IDX_FACES_ARCFACE = os.getenv("IDX_FACES_ARCFACE", "faces-arcface")
 IDX_FACES_ADAFACE = os.getenv("IDX_FACES_ADAFACE", "faces-adaface")
 
 # ──────────────────────────────────────────────────────────────
-# Concurrency / limits
+# Concurrency / limits / For Speeding Up Inference 
 # ──────────────────────────────────────────────────────────────
 MAX_CONCURRENT_INFERENCES = int(os.getenv("MAX_CONCURRENT_INFERENCES", "2"))
 MAX_FILES_PER_UPLOAD = int(os.getenv("MAX_FILES_PER_UPLOAD", "50"))
 INFERENCE_CACHE_SIZE = int(os.getenv("INFERENCE_CACHE_SIZE", "128"))
 
-# ──────────────────────────────────────────────────────────────
-# Logging
-# ──────────────────────────────────────────────────────────────
-SUPABASE_URL = os.getenv("SUPABASE_URL", "")
-SUPABASE_SERVICE_KEY = os.getenv("SUPABASE_SERVICE_KEY", "")
+
 
 # ──────────────────────────────────────────────────────────────
 # Image / detection
@@ -58,7 +74,7 @@ FACE_BLUR_THRESHOLD = float(os.getenv("FACE_BLUR_THRESHOLD", "50.0"))
 # ──────────────────────────────────────────────────────────────
 FACE_DIM = 512
 ADAFACE_DIM = 512
-FUSED_FACE_DIM = 1024  # old concatenated — kept for legacy index reads
+
 
 FACE_CROP_THUMB_SIZE = int(os.getenv("FACE_CROP_THUMB_SIZE", "112"))
 FACE_CROP_QUALITY = int(os.getenv("FACE_CROP_QUALITY", "85"))
@@ -66,7 +82,7 @@ FACE_CROP_PADDING = float(os.getenv("FACE_CROP_PADDING", "0.2"))
 ADAFACE_CROP_PADDING = float(os.getenv("ADAFACE_CROP_PADDING", "0.1"))
 
 ENABLE_ADAFACE = int(os.getenv("ENABLE_ADAFACE", "1"))
-HF_TOKEN = os.getenv("HF_TOKEN", "")
+
 
 # ──────────────────────────────────────────────────────────────
 # Phase 1: Speed flags (unchanged, leaving on)
@@ -120,8 +136,7 @@ FACE_RESULTS_PER_QUERY_CAP = int(os.getenv("FACE_RESULTS_PER_QUERY_CAP", "200"))
 
 # Redis-backed inference cache + job queue (requires Upstash)
 # Set UPSTASH_REDIS_URL + UPSTASH_REDIS_TOKEN in HF Space secrets.
-UPSTASH_REDIS_URL = os.getenv("UPSTASH_REDIS_URL", "")
-UPSTASH_REDIS_TOKEN = os.getenv("UPSTASH_REDIS_TOKEN", "")
+
 
 # Master toggle: enable the persistent Redis cache (replaces in-memory dict).
 # Falls back to in-memory if UPSTASH_REDIS_URL is not set, so this is safe to

src/core/logging.py

@@ -1,10 +1,26 @@
 import asyncio
 import json
-
 from src.core.config import SUPABASE_URL, SUPABASE_SERVICE_KEY
+from loguru import logger as _loguru
+
+
+
 
 _http_session = None
 
+#Removing the Default Loging Template
+_loguru.remove()
+#Adding the Custom Loging Template
+_loguru.add(
+    lambda msg: print(msg, end=""),
+    format="<green>{time:HH:mm:ss}</green> | <level>{level:<8}</level> | {message}",
+    level="DEBUG",
+    colorize=True,
+)
+
+_log_fn = _loguru.log
+
+# A coroutine to initialize the HTTP session
 async def init_logging_session():
     global _http_session
     if SUPABASE_URL and SUPABASE_SERVICE_KEY:
@@ -17,29 +33,13 @@ async def init_logging_session():
                 "Prefer":        "return=minimal",
             }
         )
-
+# Coroutine to close the HTTP session
 async def close_logging_session():
     global _http_session
     if _http_session:
         await _http_session.close()
 
-try:
-    from loguru import logger as _loguru
-    _loguru.remove()
-    _loguru.add(
-        lambda msg: print(msg, end=""),
-        format="<green>{time:HH:mm:ss}</green> | <level>{level:<8}</level> | {message}",
-        level="DEBUG",
-        colorize=True,
-    )
-    _log_fn = _loguru.log
-except ImportError:
-    import logging as _logging
-    _logging.basicConfig(level=_logging.INFO)
-    _stdlib = _logging.getLogger("vsl")
 
-    def _log_fn(level: str, msg: str): 
-        _stdlib.log(getattr(_logging, level, 20), msg)
 
 async def _supabase_log(level: str, event: str, data: dict) -> None:
     if not _http_session:
@@ -68,6 +68,8 @@ async def _supabase_log(level: str, event: str, data: dict) -> None:
     except Exception as exc:
         _log_fn("DEBUG", f"Supabase log push skipped: {exc}")
 
+
+
 def log(level: str, event: str, **data) -> None:
     _log_fn(level.upper(), f"[{event}] {json.dumps(data, default=str)}")
     try: