Optional rotation/autoselect override for the internal local models

Each internal-model functionality can now point at a rotation or autoselect
instead of the local model, falling back to the local model when the override is
empty or fails. Per-functionality fields in internal_model (default empty):
condensation_override, autoselect_override, nsfw_classifier_override,
privacy_classifier_override.

- handlers.py: run_meta_target() runs a global rotation/autoselect and returns
  the assistant text (or None -> fallback); classification overrides prompt the
  chat model for a strict YES/NO and parse it, falling back to the local
  classifier; autoselect selection can run through an override.
- context.py: condensation prefers the override, falling back to the local model.
- settings page: per-field override inputs backed by a datalist of available
  rotations/autoselects; saved to internal_model.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

aisbf/context.py

@@ -61,7 +61,16 @@ class ContextManager:
         self._internal_tokenizer = None
         self._internal_model_lock = None
         self._use_internal_model = False
-        
+
+        # Global override: a rotation/autoselect to use for condensation instead of
+        # the local model (falls back to the local model when empty or on failure).
+        try:
+            _aisbf = config.get_aisbf_config()
+            self._condensation_override = ((_aisbf.internal_model or {}).get('condensation_override') or '').strip() if _aisbf else ''
+        except Exception:
+            self._condensation_override = ''
+
+
         # Get max_context for condensation model
         self.condensation_max_context = None
         if self.condensation_config and hasattr(self.condensation_config, 'max_context'):
@@ -329,6 +338,21 @@ class ContextManager:
 
         return head_text + summary_block + tail_text
 
+    async def _run_local_or_override_condensation(self, messages: list, max_tokens: int, temperature: float) -> str:
+        """Run condensation via the global rotation/autoselect override when set,
+        falling back to the local internal model on empty/failed override."""
+        if self._condensation_override:
+            import logging
+            logger = logging.getLogger(__name__)
+            from .handlers import run_meta_target
+            content = await run_meta_target(
+                self._condensation_override, messages, max_tokens=max_tokens, temperature=temperature
+            )
+            if content:
+                return content
+            logger.warning(f"Condensation override '{self._condensation_override}' unavailable; falling back to local model")
+        return await self._run_internal_model_condensation(messages)
+
     async def _run_internal_model_condensation(self, messages: list) -> str:
         """Run the internal model for condensation in a separate thread"""
         import logging
@@ -629,8 +653,10 @@ class ContextManager:
             summary_content = None
 
             if self._use_internal_model:
-                logger.info("Using internal model for conversational summarization")
-                summary_content = await self._run_internal_model_condensation(condensation_messages)
+                logger.info("Using internal model (or override) for conversational summarization")
+                summary_content = await self._run_local_or_override_condensation(
+                    condensation_messages, self._get_condensation_max_tokens(), 0.3
+                )
             elif self._rotation_handler and not self.condensation_model:
                 # Use rotation handler
                 condensation_request = {
@@ -733,8 +759,10 @@ class ContextManager:
             pruned_content = None
 
             if self._use_internal_model:
-                logger.info("Using internal model for semantic pruning")
-                pruned_content = await self._run_internal_model_condensation(condensation_messages)
+                logger.info("Using internal model (or override) for semantic pruning")
+                pruned_content = await self._run_local_or_override_condensation(
+                    condensation_messages, 2000, 0.2
+                )
             elif self._rotation_handler and not self.condensation_model:
                 # Use rotation handler
                 condensation_request = {

aisbf/handlers.py

@@ -2442,6 +2442,121 @@ _rotation_round_robin: Dict[str, int] = {}
 _rotation_round_robin_lock = threading.Lock()
 
 
+async def run_meta_target(target_id, messages, max_tokens=None, temperature=0.0, stop=None):
+    """Run a GLOBAL rotation or autoselect as an override for an internal/local model.
+
+    Used by the internal-model overrides (compaction, classification, autoselect
+    selection). Resolves ``target_id`` against the global rotations/autoselects,
+    forwards a non-streaming chat request, and returns the assistant message
+    content string — or ``None`` on any failure so callers can fall back to their
+    local model.
+    """
+    import logging
+    logger = logging.getLogger(__name__)
+    target_id = (target_id or '').strip()
+    if not target_id:
+        return None
+    is_rotation = bool(getattr(config, 'rotations', None)) and target_id in config.rotations
+    is_autoselect = bool(getattr(config, 'autoselect', None)) and target_id in config.autoselect
+    if not is_rotation and not is_autoselect:
+        logger.warning(f"Internal-model override target '{target_id}' is neither a rotation nor an autoselect; using local model")
+        return None
+    request_data = {
+        'model': target_id,
+        'messages': messages,
+        'stream': False,
+        'temperature': temperature,
+    }
+    if max_tokens:
+        request_data['max_tokens'] = max_tokens
+    if stop:
+        request_data['stop'] = stop
+    try:
+        if is_rotation:
+            result = await RotationHandler().handle_rotation_request(target_id, request_data)
+        else:
+            result = await AutoselectHandler().handle_autoselect_request(target_id, request_data)
+    except Exception as e:
+        logger.warning(f"Internal-model override '{target_id}' failed: {e}")
+        return None
+    if not isinstance(result, dict) or result.get('aisbf_error'):
+        logger.warning(f"Internal-model override '{target_id}' returned no usable response")
+        return None
+    try:
+        return result['choices'][0]['message']['content']
+    except Exception:
+        return None
+
+
+async def classify_with_override(target_id, text, kind):
+    """Classify ``text`` with a chat rotation/autoselect override.
+
+    ``kind`` is 'nsfw' or 'privacy'. Returns True if the content is FLAGGED
+    (unsafe), False if safe, or None when the override is unavailable/unparseable
+    so the caller can fall back to the local classifier pipeline.
+    """
+    target_id = (target_id or '').strip()
+    if not target_id:
+        return None
+    text_to_check = text[:512] if len(text) > 512 else text
+    if kind == 'nsfw':
+        question = "Does the following text contain NSFW content (sexual, explicit, or adult material)?"
+    else:
+        question = ("Does the following text contain privacy-sensitive personal information (PII) such as "
+                    "real names, addresses, emails, phone numbers, or financial/identity data?")
+    messages = [
+        {"role": "system", "content": "You are a strict binary content classifier. Reply with exactly one word: YES or NO. Do not explain."},
+        {"role": "user", "content": f"{question}\n\nTEXT:\n{text_to_check}\n\nAnswer YES or NO."},
+    ]
+    content = await run_meta_target(target_id, messages, max_tokens=5, temperature=0.0)
+    if not content:
+        return None
+    ans = content.strip().upper()
+    if ans.startswith('YES'):
+        return True
+    if ans.startswith('NO'):
+        return False
+    has_yes, has_no = ('YES' in ans), ('NO' in ans)
+    if has_yes and not has_no:
+        return True
+    if has_no and not has_yes:
+        return False
+    return None  # unparseable → fall back to local classifier
+
+
+async def classify_content_with_overrides(text, check_nsfw, check_privacy, aisbf_config):
+    """Run NSFW/privacy checks, preferring per-functionality rotation/autoselect
+    overrides and falling back to the local classifier pipelines. Returns
+    (is_safe, message), matching ContentClassifier.check_content."""
+    internal_model = (aisbf_config.internal_model or {}) if aisbf_config else {}
+    nsfw_override = internal_model.get('nsfw_classifier_override')
+    privacy_override = internal_model.get('privacy_classifier_override')
+
+    # Ensure local pipelines are available as a fallback for enabled checks.
+    if (check_nsfw or check_privacy):
+        content_classifier.initialize(internal_model.get('nsfw_classifier'), internal_model.get('privacy_classifier'))
+
+    if check_nsfw:
+        flagged = await classify_with_override(nsfw_override, text, 'nsfw') if nsfw_override else None
+        if flagged is None:
+            is_safe, message = content_classifier.check_nsfw(text)
+            if not is_safe:
+                return False, f"NSFW: {message}"
+        elif flagged:
+            return False, "NSFW: flagged by override classifier"
+
+    if check_privacy:
+        flagged = await classify_with_override(privacy_override, text, 'privacy') if privacy_override else None
+        if flagged is None:
+            is_safe, message = content_classifier.check_privacy(text)
+            if not is_safe:
+                return False, f"Privacy: {message}"
+        elif flagged:
+            return False, "Privacy: flagged by override classifier"
+
+    return True, "All content is safe"
+
+
 class RotationHandler:
     def __init__(self, user_id=None):
         self.user_id = user_id
@@ -3166,20 +3281,16 @@ class RotationHandler:
             check_privacy = aisbf_config.classify_privacy
             
             if check_nsfw or check_privacy:
-                # Initialize classifier with models from config
-                internal_model_config = aisbf_config.internal_model or {}
-                nsfw_model = internal_model_config.get('nsfw_classifier')
-                privacy_model = internal_model_config.get('privacy_classifier')
-                
-                content_classifier.initialize(nsfw_model, privacy_model)
-                
-                # Check user prompt for NSFW/privacy content
-                is_safe, message = content_classifier.check_content(
-                    user_prompt, 
-                    check_nsfw=check_nsfw, 
-                    check_privacy=check_privacy
+                # Classify, preferring per-functionality rotation/autoselect overrides
+                # (internal_model.nsfw_classifier_override / privacy_classifier_override)
+                # and falling back to the local classifier pipelines.
+                is_safe, message = await classify_content_with_overrides(
+                    user_prompt,
+                    check_nsfw=check_nsfw,
+                    check_privacy=check_privacy,
+                    aisbf_config=aisbf_config,
                 )
-                
+
                 logger.info(f"Content classification result: {message}")
                 
                 if not is_safe:
@@ -5673,6 +5784,26 @@ class AutoselectHandler:
         try:
             if selection_model == "internal":
                 aisbf_conf = self.config.get_aisbf_config()
+                # Global override: route the selection step through a rotation/autoselect
+                # instead of the local model, falling back to local on any failure.
+                autoselect_override = (
+                    (aisbf_conf.internal_model or {}).get('autoselect_override', '')
+                    if aisbf_conf else ''
+                )
+                if (autoselect_override or '').strip():
+                    logger.info(f"Autoselect selection using override target '{autoselect_override}'")
+                    override_content = await run_meta_target(
+                        autoselect_override, messages, max_tokens=100, temperature=0.0,
+                        stop=["</aisbf_model_autoselection>"]
+                    )
+                    if override_content:
+                        model_id = self._extract_model_selection(override_content)
+                        if model_id:
+                            logger.info(f"=== AUTOSELECT SUCCESS (override) === {model_id}")
+                            return model_id
+                        logger.warning("Could not extract model ID from override response; falling back to local model")
+                    else:
+                        logger.warning(f"Autoselect override '{autoselect_override}' unavailable; falling back to local model")
                 internal_model_id = (
                     (aisbf_conf.internal_model or {}).get('autoselect_model_id', '')
                     if aisbf_conf else ''

aisbf/routes/dashboard/settings.py

@@ -377,6 +377,12 @@ async def dashboard_settings(request: Request):
         }
     
     warning = request.query_params.get('warning')
+    # Available rotations/autoselects for the internal-model override pickers
+    try:
+        from aisbf.config import config as _runtime_config
+        meta_targets = sorted(list((_runtime_config.rotations or {}).keys()) + list((_runtime_config.autoselect or {}).keys()))
+    except Exception:
+        meta_targets = []
     return _templates.TemplateResponse(
         request=request,
         name="dashboard/settings.html",
@@ -385,6 +391,7 @@ async def dashboard_settings(request: Request):
         "session": request.session,
         "__version__": __version__,
         "config": aisbf_config,
+        "meta_targets": meta_targets,
         "os": os,
         "warning": warning,
     }
@@ -407,6 +414,10 @@ async def dashboard_settings_save(
    nsfw_classifier: str = Form("michelleli99/NSFW_text_classifier"),
    privacy_classifier: str = Form("iiiorg/piiranha-v1-detect-personal-information"),
    semantic_vectorization: str = Form("sentence-transformers/all-MiniLM-L6-v2"),
+   condensation_override: str = Form(""),
+   autoselect_override: str = Form(""),
+   nsfw_classifier_override: str = Form(""),
+   privacy_classifier_override: str = Form(""),
    classify_nsfw: bool = Form(False),
    classify_privacy: bool = Form(False),
    classify_semantic: bool = Form(False),
@@ -715,6 +726,11 @@ async def dashboard_settings_save(
     aisbf_config['internal_model']['nsfw_classifier'] = nsfw_classifier
     aisbf_config['internal_model']['privacy_classifier'] = privacy_classifier
     aisbf_config['internal_model']['semantic_vectorization'] = semantic_vectorization
+    # Optional rotation/autoselect overrides (empty = use the local model above)
+    aisbf_config['internal_model']['condensation_override'] = (condensation_override or '').strip()
+    aisbf_config['internal_model']['autoselect_override'] = (autoselect_override or '').strip()
+    aisbf_config['internal_model']['nsfw_classifier_override'] = (nsfw_classifier_override or '').strip()
+    aisbf_config['internal_model']['privacy_classifier_override'] = (privacy_classifier_override or '').strip()
 
     # Update batching config
     if 'batching' not in aisbf_config:

templates/dashboard/settings.html

@@ -177,6 +177,10 @@ along with this program.  If not, see <https://www.gnu.org/licenses/>.
     <div class="settings-section" id="tab-models">
     <div class="section-title"><i class="fas fa-brain"></i> <span data-i18n="settings_page.section_models">Internal Models</span></div>
 
+    <datalist id="meta-targets-dl">
+        {% for t in meta_targets or [] %}<option value="{{ t }}">{% endfor %}
+    </datalist>
+
     <div class="form-group">
         <label for="condensation_model_id" data-i18n="settings_page.lbl_condensation_model">Condensation Model ID</label>
         <div style="display:flex; gap:8px; align-items:center;">
@@ -184,6 +188,8 @@ along with this program.  If not, see <https://www.gnu.org/licenses/>.
             <button type="button" class="btn btn-secondary" style="white-space:nowrap; padding:6px 12px; font-size:.85em;" onclick="clearModelCache(document.getElementById('condensation_model_id').value, 'condensation', this)"><i class="fas fa-trash-alt"></i> Clear Cache</button>
         </div>
         <small style="color: var(--color-subtle); display: block; margin-top: 5px;">Used when condensation model is set to "internal"</small>
+        <label for="condensation_override" style="margin-top:8px;">↳ Rotation/Autoselect override <span style="color:var(--color-subtle);font-weight:normal;">(optional — overrides the local model above)</span></label>
+        <input type="text" id="condensation_override" name="condensation_override" list="meta-targets-dl" value="{{ config.internal_model.condensation_override or '' }}" placeholder="rotation or autoselect name (leave empty to use local model)" style="width:100%;">
     </div>
 
     <div class="form-group">
@@ -199,6 +205,8 @@ along with this program.  If not, see <https://www.gnu.org/licenses/>.
             <button type="button" class="btn btn-secondary" style="white-space:nowrap; padding:6px 12px; font-size:.85em;" onclick="clearModelCache(document.getElementById('autoselect_model_id').value, 'autoselect', this)"><i class="fas fa-trash-alt"></i> Clear Cache</button>
         </div>
         <small style="color: var(--color-subtle); display: block; margin-top: 5px;">Used when autoselect selection_model is set to "internal"</small>
+        <label for="autoselect_override" style="margin-top:8px;">↳ Rotation/Autoselect override <span style="color:var(--color-subtle);font-weight:normal;">(optional — overrides the local model above)</span></label>
+        <input type="text" id="autoselect_override" name="autoselect_override" list="meta-targets-dl" value="{{ config.internal_model.autoselect_override or '' }}" placeholder="rotation or autoselect name (leave empty to use local model)" style="width:100%;">
     </div>
 
     <div class="form-group">
@@ -214,6 +222,8 @@ along with this program.  If not, see <https://www.gnu.org/licenses/>.
             <button type="button" class="btn btn-secondary" style="white-space:nowrap; padding:6px 12px; font-size:.85em;" onclick="clearModelCache(document.getElementById('nsfw_classifier').value, 'nsfw', this)"><i class="fas fa-trash-alt"></i> Clear Cache</button>
         </div>
         <small style="color: var(--color-subtle); display: block; margin-top: 5px;">Model used for NSFW content detection</small>
+        <label for="nsfw_classifier_override" style="margin-top:8px;">↳ Rotation/Autoselect override <span style="color:var(--color-subtle);font-weight:normal;">(optional — prompts a chat model for YES/NO, falls back to local)</span></label>
+        <input type="text" id="nsfw_classifier_override" name="nsfw_classifier_override" list="meta-targets-dl" value="{{ config.internal_model.nsfw_classifier_override or '' }}" placeholder="rotation or autoselect name (leave empty to use local classifier)" style="width:100%;">
     </div>
 
     <div class="form-group">
@@ -223,6 +233,8 @@ along with this program.  If not, see <https://www.gnu.org/licenses/>.
             <button type="button" class="btn btn-secondary" style="white-space:nowrap; padding:6px 12px; font-size:.85em;" onclick="clearModelCache(document.getElementById('privacy_classifier').value, 'privacy', this)"><i class="fas fa-trash-alt"></i> Clear Cache</button>
         </div>
         <small style="color: var(--color-subtle); display: block; margin-top: 5px;">Model used for privacy-sensitive information detection</small>
+        <label for="privacy_classifier_override" style="margin-top:8px;">↳ Rotation/Autoselect override <span style="color:var(--color-subtle);font-weight:normal;">(optional — prompts a chat model for YES/NO, falls back to local)</span></label>
+        <input type="text" id="privacy_classifier_override" name="privacy_classifier_override" list="meta-targets-dl" value="{{ config.internal_model.privacy_classifier_override or '' }}" placeholder="rotation or autoselect name (leave empty to use local classifier)" style="width:100%;">
     </div>
 
     <div class="form-group">