UI - LLM - Fix for settings (wtforms vs pydantic)

changedetectionio/blueprint/settings/__init__.py

@@ -99,6 +99,12 @@ def construct_blueprint(datastore: ChangeDetectionStore):
 
                 llm_form_input = dict(form.data.get('llm') or {})
 
+                # Empty IntegerField submissions come back as None from WTForms;
+                # the schema declares those fields as strict `int`, so passing
+                # them through would fail validation. Treat None like the
+                # absent-key case: keep the stored value, don't merge.
+                llm_form_input = {k: v for k, v in llm_form_input.items() if v is not None}
+
                 # PasswordField never re-renders, so a blank submitted value means
                 # "keep stored key" — drop it from the merge.
                 if not (llm_form_input.get('api_key') or '').strip():

changedetectionio/llm/evaluator.py

@@ -82,10 +82,23 @@ def _check_input_size(text: str, max_chars: int) -> None:
 
 def _thinking_extra_body(model: str, budget: int) -> dict | None:
     """Return litellm extra_body to control thinking for models that support it.
-    For Gemini 2.5+: passes thinkingConfig with the given budget (0 = disabled).
-    For all other models: returns None (no-op).
+
+    The `thinkingConfig.thinkingBudget` payload is Gemini-specific (Anthropic and
+    OpenAI reasoning models use different parameters), so we gate on the gemini/
+    provider prefix first, then defer to litellm's model registry for the actual
+    "does this model think?" decision. That picks up new Gemini variants and
+    rolling aliases (`gemini-flash-latest`, etc.) as litellm's registry tracks
+    them, without us hardcoding model names here.
     """
-    if not model.startswith('gemini/gemini-2.5'):
+    if not model.startswith('gemini/'):
+        return None
+    try:
+        import litellm
+        if not litellm.get_model_info(model).get('supports_reasoning'):
+            return None
+    except Exception:
+        # Unknown model or registry lookup failed — skip the thinking config
+        # rather than guess. Worst case: thinking stays at the provider default.
         return None
     return {'generationConfig': {'thinkingConfig': {'thinkingBudget': budget}}}
 

changedetectionio/tests/test_llm_token_budget.py

@@ -196,6 +196,81 @@ def test_settings_form_preserves_token_counters(
     delete_all_watches(client)
 
 
+def test_settings_form_blank_llm_integer_fields_preserve_stored_values(
+        client, live_server, measure_memory_usage, datastore_path):
+    """
+    Empty IntegerField submissions come back as None from WTForms. LLMSettings
+    declares token_budget_month / max_input_chars / max_tokens_per_count_period /
+    local_token_multiplier as strict `int`, so a None passed through to
+    model_validate raises ValidationError and 500s the settings save.
+
+    Regression for settings/__init__.py — the LLM merge must drop None values
+    (treat them like absent keys) so blank IntegerField submissions preserve
+    the stored value instead of crashing the form.
+    """
+    ds = client.application.config.get('DATASTORE')
+    ds.data['settings']['application']['llm'] = {
+        'model': 'gpt-4o',
+        'api_key': 'sk-existing',
+        'token_budget_month': 50000,
+        'max_input_chars': 200000,
+        'max_tokens_per_count_period': 1000,
+        'local_token_multiplier': 3,
+    }
+
+    res = client.post(
+        url_for('settings.settings_page'),
+        data={
+            'llm-model': 'gpt-4o',
+            'llm-api_key': '',
+            'llm-api_base': '',
+            # The bug-trigger: every LLM IntegerField submitted blank
+            'llm-token_budget_month': '',
+            'llm-max_input_chars': '',
+            'llm-max_tokens_per_count_period': '',
+            'llm-local_token_multiplier': '',
+            # Minimal required fields for the rest of the form to validate.
+            # 'System default' is popped from notification_format choices for the
+            # global form, so it must be one of the real codes (e.g. 'html').
+            'application-pager_size': '50',
+            'application-notification_format': 'html',
+            'application-fetch_backend': 'html_requests',
+            'application-rss_diff_length': '5',
+            'application-filter_failure_notification_threshold_attempts': '0',
+            'requests-time_between_check-days': '0',
+            'requests-time_between_check-hours': '0',
+            'requests-time_between_check-minutes': '5',
+            'requests-time_between_check-seconds': '0',
+            'requests-time_between_check-weeks': '0',
+            'requests-jitter_seconds': '0',
+            'requests-workers': '10',
+            'requests-timeout': '60',
+        },
+        follow_redirects=True,
+    )
+    assert res.status_code == 200, \
+        f"Settings save crashed on blank LLM IntegerField submission (got {res.status_code})"
+    # Sanity: the form must have actually validated and reached the LLM save path
+    # — without this the test would trivially pass because the buggy code never ran.
+    assert b'Settings updated.' in res.data, \
+        "Settings form did not validate — the bug-path was never exercised. Check fixture fields."
+    body = res.data.decode('utf-8', errors='replace')
+    assert 'ValidationError' not in body, \
+        "Pydantic ValidationError leaked into the response — blank IntegerField wasn't filtered"
+
+    llm = ds.data['settings']['application'].get('llm') or {}
+    assert llm.get('token_budget_month') == 50000, \
+        f"Blank submission must preserve stored token_budget_month (got {llm.get('token_budget_month')!r})"
+    assert llm.get('max_input_chars') == 200000, \
+        f"Blank submission must preserve stored max_input_chars (got {llm.get('max_input_chars')!r})"
+    assert llm.get('max_tokens_per_count_period') == 1000, \
+        f"Blank submission must preserve stored max_tokens_per_count_period (got {llm.get('max_tokens_per_count_period')!r})"
+    assert llm.get('local_token_multiplier') == 3, \
+        f"Blank submission must preserve stored local_token_multiplier (got {llm.get('local_token_multiplier')!r})"
+
+    delete_all_watches(client)
+
+
 def test_settings_form_cannot_inject_fake_token_counts(
         client, live_server, measure_memory_usage, datastore_path):
     """