feat: load glossary corrections from file when available

history.md

@@ -144,3 +144,11 @@ The project now features a high-performance, Apple Silicon-optimized pipeline th
     - **Glossary Replacements:** Added configurable `SOURCE=TARGET` term normalization (`--glossary-pair`) to consistently correct names/terms in English captions.
     - **Rolling Caption Revision Buffer:** Added a short correction window (`--caption-correction-window`, default 3s) with a 2-line rolling buffer that can merge incomplete English lines into a cleaner sentence as new context arrives.
 - **Outcome:** Captions now support lightweight post-correction behavior that improves continuity and term consistency while remaining compatible with real-time streaming.
+
+## Phase 18: File-Based Glossary Loading
+- **Goal:** Make glossary corrections persistent and easier to maintain without long CLI commands.
+- **Approach:**
+    - Added `--glossary-file` (default `glossary.txt`) to load `SOURCE=TARGET` term mappings when the file exists.
+    - Implemented comment/blank-line support and invalid-line skipping with line-level warnings.
+    - Merged file-based glossary entries with repeatable `--glossary-pair` CLI entries for runtime overrides.
+- **Outcome:** English caption correction can now use a maintained glossary file automatically, while preserving ad-hoc CLI term fixes.

transcribe.py

@@ -1,6 +1,7 @@
 import sys
 import time
 import re
+import os
 import requests
 import threading
 import json
@@ -181,6 +182,23 @@ def apply_glossary(text, glossary_pairs):
         updated = pattern.sub(target, updated)
     return updated
 
+def load_glossary_file(path):
+    """Load SOURCE=TARGET glossary pairs from a file."""
+    pairs = []
+    if not path or not os.path.exists(path):
+        return pairs
+
+    with open(path, "r", encoding="utf-8") as f:
+        for line_no, raw in enumerate(f, start=1):
+            line = raw.strip()
+            if not line or line.startswith("#"):
+                continue
+            try:
+                pairs.append(parse_glossary_pair(line))
+            except argparse.ArgumentTypeError:
+                print(f"[SYSTEM]: Skipping invalid glossary line {line_no} in {path}: {line}")
+    return pairs
+
 def normalize_english_caption(text):
     normalized = " ".join(text.split()).strip()
     if not normalized:
@@ -306,9 +324,14 @@ def main():
     parser.add_argument("--retry-logprob-threshold", type=float, default=-1.05, help="Retry transcription when mean avg_logprob is below this threshold (default: -1.05)")
     parser.add_argument("--retry-compression-threshold", type=float, default=2.4, help="Retry transcription when max compression ratio exceeds this threshold (default: 2.4)")
     parser.add_argument("--caption-correction-window", type=float, default=3.0, help="Seconds where previous English line can still be merged/corrected (default: 3.0)")
+    parser.add_argument("--glossary-file", type=str, default="glossary.txt", help="Path to glossary file with SOURCE=TARGET pairs (default: glossary.txt if present)")
     parser.add_argument("--glossary-pair", action="append", type=parse_glossary_pair, default=[], help="Term replacement pair SOURCE=TARGET (repeatable)")
     
     args = parser.parse_args()
+    file_glossary_pairs = load_glossary_file(args.glossary_file)
+    merged_glossary_pairs = file_glossary_pairs + args.glossary_pair
+    if file_glossary_pairs:
+        print(f"Loaded {len(file_glossary_pairs)} glossary terms from {args.glossary_file}")
 
     if args.quantize:
         WHISPER_MODEL = "mlx-community/whisper-small-mlx-4bit"
@@ -530,7 +553,7 @@ def main():
                                 english_for_translation = english_text
                                 if args.smart_correct and english_for_translation:
                                     english_for_translation = normalize_english_caption(english_for_translation)
-                                    english_for_translation = apply_glossary(english_for_translation, args.glossary_pair)
+                                    english_for_translation = apply_glossary(english_for_translation, merged_glossary_pairs)
 
                                 english_for_caption = english_for_translation
                                 if args.smart_correct and english_for_caption: