Fix bugs, N+1 queries, and wire settings in persian-tutor

- Replace inline __import__("datetime").timedelta hack with proper import
- Remove unused import random in anki_export.py
- Add error handling for Claude CLI subprocess failures in ai.py
- Fix hardcoded absolute path in stt.py with relative Path resolution
- Fix N+1 DB queries in vocab.get_flashcard_batch and dashboard.get_category_breakdown
  by adding db.get_all_word_progress() batch query
- Wire Ollama model and Whisper size settings to actually update config
  via ai.set_ollama_model() and stt.set_whisper_size()

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

python/persian-tutor/ai.py

@@ -6,9 +6,18 @@ import ollama
 
 DEFAULT_OLLAMA_MODEL = "qwen2.5:7b"
 
+_ollama_model = DEFAULT_OLLAMA_MODEL
 
-def ask_ollama(prompt, system=None, model=DEFAULT_OLLAMA_MODEL):
+
+def set_ollama_model(model):
+    """Change the Ollama model used for fast queries."""
+    global _ollama_model
+    _ollama_model = model
+
+
+def ask_ollama(prompt, system=None, model=None):
     """Query Ollama with an optional system prompt."""
+    model = model or _ollama_model
     messages = []
     if system:
         messages.append({"role": "system", "content": system})
@@ -24,6 +33,8 @@ def ask_claude(prompt):
         capture_output=True,
         text=True,
     )
+    if result.returncode != 0:
+        raise RuntimeError(f"Claude CLI failed (exit {result.returncode}): {result.stderr.strip()}")
     return result.stdout.strip()
 
 
@@ -34,8 +45,9 @@ def ask(prompt, system=None, quality="fast"):
     return ask_ollama(prompt, system=system)
 
 
-def chat_ollama(messages, system=None, model=DEFAULT_OLLAMA_MODEL):
+def chat_ollama(messages, system=None, model=None):
     """Multi-turn conversation with Ollama."""
+    model = model or _ollama_model
     all_messages = []
     if system:
         all_messages.append({"role": "system", "content": system})

python/persian-tutor/anki_export.py

@@ -1,7 +1,6 @@
 """Generate Anki .apkg decks from vocabulary data."""
 
 import genanki
-import random
 
 # Stable model/deck IDs (generated once, kept constant)
 _MODEL_ID = 1607392319

python/persian-tutor/app.py

@@ -7,6 +7,7 @@ import time
 
 import gradio as gr
 
+import ai
 import db
 from modules import vocab, dashboard, essay, tutor, idioms
 from modules.essay import GCSE_THEMES
@@ -214,6 +215,15 @@ def do_anki_export(cats_selected):
     return path
 
 
+def update_ollama_model(model):
+    ai.set_ollama_model(model)
+
+
+def update_whisper_size(size):
+    from stt import set_whisper_size
+    set_whisper_size(size)
+
+
 def reset_progress():
     conn = db.get_connection()
     conn.execute("DELETE FROM word_progress")
@@ -491,6 +501,10 @@ with gr.Blocks(title="Persian Language Tutor") as app:
 
             export_btn.click(fn=do_anki_export, inputs=[export_cats], outputs=[export_file])
 
+            # Wire model settings
+            ollama_model.change(fn=update_ollama_model, inputs=[ollama_model])
+            whisper_size.change(fn=update_whisper_size, inputs=[whisper_size])
+
             gr.Markdown("### Reset")
             reset_btn = gr.Button("Reset All Progress", variant="stop")
             reset_status = gr.Markdown("")

python/persian-tutor/db.py

@@ -2,7 +2,7 @@
 
 import json
 import sqlite3
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 
 import fsrs
@@ -148,6 +148,13 @@ def get_word_counts(total_vocab_size=0):
     }
 
 
+def get_all_word_progress():
+    """Return all word progress as a dict of word_id -> progress dict."""
+    conn = get_connection()
+    rows = conn.execute("SELECT * FROM word_progress").fetchall()
+    return {row["word_id"]: dict(row) for row in rows}
+
+
 def record_quiz_session(category, total_questions, correct, duration_seconds):
     """Log a completed flashcard session."""
     conn = get_connection()
@@ -203,7 +210,7 @@ def get_stats():
     today = datetime.now(timezone.utc).date()
     for i, row in enumerate(days):
         day = datetime.fromisoformat(row["d"]).date() if isinstance(row["d"], str) else row["d"]
-        expected = today - __import__("datetime").timedelta(days=i)
+        expected = today - timedelta(days=i)
         if day == expected:
             streak += 1
         else:

python/persian-tutor/modules/dashboard.py

@@ -19,17 +19,17 @@ def get_category_breakdown():
     """Return progress per category as list of dicts."""
     vocab = load_vocab()
     categories = get_categories()
+    all_progress = db.get_all_word_progress()
 
     breakdown = []
     for cat in categories:
         cat_words = [e for e in vocab if e["category"] == cat]
-        cat_ids = {e["id"] for e in cat_words}
         total = len(cat_words)
 
         seen = 0
         mastered = 0
-        for wid in cat_ids:
+        for e in cat_words:
-            progress = db.get_word_progress(wid)
+            progress = all_progress.get(e["id"])
             if progress:
                 seen += 1
                 if progress["stability"] and progress["stability"] > 10:

python/persian-tutor/modules/vocab.py

@@ -84,8 +84,9 @@ def get_flashcard_batch(count=10, category=None):
     remaining = count - len(due_entries)
     if remaining > 0:
         seen_ids = {e["id"] for e in due_entries}
+        all_progress = db.get_all_word_progress()
         # Prefer unseen words
-        unseen = [e for e in pool if e["id"] not in seen_ids and not db.get_word_progress(e["id"])]
+        unseen = [e for e in pool if e["id"] not in seen_ids and e["id"] not in all_progress]
         if len(unseen) >= remaining:
             fill = random.sample(unseen, remaining)
         else:

python/persian-tutor/stt.py

@@ -1,13 +1,17 @@
 """Persian speech-to-text wrapper using sttlib."""
 
 import sys
+from pathlib import Path
 
 import numpy as np
 
-sys.path.insert(0, "/home/ys/family-repo/Code/python/tool-speechtotext")
+# sttlib lives in sibling project tool-speechtotext
+_sttlib_path = str(Path(__file__).resolve().parent.parent / "tool-speechtotext")
+sys.path.insert(0, _sttlib_path)
 from sttlib import load_whisper_model, transcribe, is_hallucination
 
 _model = None
+_whisper_size = "medium"
 
 # Common Whisper hallucinations in Persian/silence
 PERSIAN_HALLUCINATIONS = [
@@ -18,11 +22,19 @@ PERSIAN_HALLUCINATIONS = [
 ]
 
 
-def get_model(size="medium"):
+def set_whisper_size(size):
+    """Change the Whisper model size. Reloads on next transcription."""
+    global _whisper_size, _model
+    if size != _whisper_size:
+        _whisper_size = size
+        _model = None
+
+
+def get_model():
     """Load Whisper model (cached singleton)."""
     global _model
     if _model is None:
-        _model = load_whisper_model(size)
+        _model = load_whisper_model(_whisper_size)
     return _model