Improve LLM model default selection and admin actions

Backend logic for selecting the default LLM model now prioritizes the recommended model, with improved fallbacks and error handling if no models are enabled. The migration enforces a single recommended model at the database level. Frontend admin actions for LLM models and providers now correctly interpret form values for boolean fields and fix the return type for the delete action.

autogpt_platform/backend/backend/api/conn_manager.py

@@ -122,6 +122,24 @@ class ConnectionManager:
 
         return len(connections)
 
+    async def broadcast_to_all(self, *, method: WSMethod, data: dict) -> int:
+        """Broadcast a message to all active websocket connections."""
+        message = WSMessage(
+            method=method,
+            data=data,
+        ).model_dump_json()
+
+        connections = tuple(self.active_connections)
+        if not connections:
+            return 0
+
+        await asyncio.gather(
+            *(connection.send_text(message) for connection in connections),
+            return_exceptions=True,
+        )
+
+        return len(connections)
+
     async def _subscribe(self, channel_key: str, websocket: WebSocket) -> str:
         if channel_key not in self.subscriptions:
             self.subscriptions[channel_key] = set()

autogpt_platform/backend/backend/api/features/admin/execution_analytics_routes.py

@@ -173,30 +173,64 @@ async def get_execution_analytics_config(
         # Return with provider prefix for clarity
         return f"{provider_name}: {model_name}"
 
-    # Include all LlmModel values (no more filtering by hardcoded list)
-    recommended_model = LlmModel.GPT4O_MINI.value
-    for model in LlmModel:
-        label = generate_model_label(model)
+    # Get all models from the registry (dynamic, not hardcoded enum)
+    from backend.data import llm_registry
+    from backend.server.v2.llm import db as llm_db
+
+    # Get the recommended model from the database (configurable via admin UI)
+    recommended_model_slug = await llm_db.get_recommended_model_slug()
+
+    # Build the available models list
+    first_enabled_slug = None
+    for registry_model in llm_registry.iter_dynamic_models():
+        # Only include enabled models in the list
+        if not registry_model.is_enabled:
+            continue
+
+        # Track first enabled model as fallback
+        if first_enabled_slug is None:
+            first_enabled_slug = registry_model.slug
+
+        model_enum = LlmModel(registry_model.slug)  # Create enum instance from slug
+        label = generate_model_label(model_enum)
         # Add "(Recommended)" suffix to the recommended model
-        if model.value == recommended_model:
+        if registry_model.slug == recommended_model_slug:
             label += " (Recommended)"
 
         available_models.append(
             ModelInfo(
-                value=model.value,
+                value=registry_model.slug,
                 label=label,
-                provider=model.provider,
+                provider=registry_model.metadata.provider,
             )
         )
 
     # Sort models by provider and name for better UX
     available_models.sort(key=lambda x: (x.provider, x.label))
 
+    # Handle case where no models are available
+    if not available_models:
+        logger.warning(
+            "No enabled LLM models found in registry. "
+            "Ensure models are configured and enabled in the LLM Registry."
+        )
+        # Provide a placeholder entry so admins see meaningful feedback
+        available_models.append(
+            ModelInfo(
+                value="",
+                label="No models available - configure in LLM Registry",
+                provider="none",
+            )
+        )
+
+    # Use the DB recommended model, or fallback to first enabled model
+    final_recommended = recommended_model_slug or first_enabled_slug or ""
+
     return ExecutionAnalyticsConfig(
         available_models=available_models,
         default_system_prompt=DEFAULT_SYSTEM_PROMPT,
         default_user_prompt=DEFAULT_USER_PROMPT,
-        recommended_model=recommended_model,
+        recommended_model=final_recommended,
     )
 
 

autogpt_platform/backend/backend/api/features/admin/llm_routes.py

@@ -0,0 +1,554 @@
+import logging
+
+import autogpt_libs.auth
+import fastapi
+
+from backend.data import llm_registry
+from backend.data.block_cost_config import refresh_llm_costs
+from backend.server.v2.llm import db as llm_db
+from backend.server.v2.llm import model as llm_model
+
+logger = logging.getLogger(__name__)
+
+router = fastapi.APIRouter(
+    prefix="/admin/llm",
+    tags=["llm", "admin"],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_admin_user)],
+)
+
+
+async def _refresh_runtime_state() -> None:
+    """Refresh the LLM registry and clear all related caches to ensure real-time updates."""
+    logger.info("Refreshing LLM registry runtime state...")
+
+    # Refresh registry from database
+    await llm_registry.refresh_llm_registry()
+    refresh_llm_costs()
+
+    # Clear block schema caches so they're regenerated with updated model options
+    from backend.data.block import BlockSchema
+
+    BlockSchema.clear_all_schema_caches()
+    logger.info("Cleared all block schema caches")
+
+    # Clear the /blocks endpoint cache so frontend gets updated schemas
+    try:
+        from backend.api.features.v1 import _get_cached_blocks
+
+        _get_cached_blocks.cache_clear()
+        logger.info("Cleared /blocks endpoint cache")
+    except Exception as e:
+        logger.warning("Failed to clear /blocks cache: %s", e)
+
+    # Clear the v2 builder providers cache (if it exists)
+    try:
+        from backend.api.features.builder import db as builder_db
+
+        if hasattr(builder_db, "_get_all_providers"):
+            builder_db._get_all_providers.cache_clear()
+            logger.info("Cleared v2 builder providers cache")
+    except Exception as e:
+        logger.debug("Could not clear v2 builder cache: %s", e)
+
+    # Notify all executor services to refresh their registry cache
+    from backend.data.llm_registry import publish_registry_refresh_notification
+
+    publish_registry_refresh_notification()
+    logger.info("Published registry refresh notification")
+
+
+@router.get(
+    "/providers",
+    summary="List LLM providers",
+    response_model=llm_model.LlmProvidersResponse,
+)
+async def list_llm_providers(include_models: bool = True):
+    providers = await llm_db.list_providers(include_models=include_models)
+    return llm_model.LlmProvidersResponse(providers=providers)
+
+
+@router.post(
+    "/providers",
+    summary="Create LLM provider",
+    response_model=llm_model.LlmProvider,
+)
+async def create_llm_provider(request: llm_model.UpsertLlmProviderRequest):
+    provider = await llm_db.upsert_provider(request=request)
+    await _refresh_runtime_state()
+    return provider
+
+
+@router.patch(
+    "/providers/{provider_id}",
+    summary="Update LLM provider",
+    response_model=llm_model.LlmProvider,
+)
+async def update_llm_provider(
+    provider_id: str,
+    request: llm_model.UpsertLlmProviderRequest,
+):
+    provider = await llm_db.upsert_provider(request=request, provider_id=provider_id)
+    await _refresh_runtime_state()
+    return provider
+
+
+@router.get(
+    "/models",
+    summary="List LLM models",
+    response_model=llm_model.LlmModelsResponse,
+)
+async def list_llm_models(provider_id: str | None = fastapi.Query(default=None)):
+    models = await llm_db.list_models(provider_id=provider_id)
+    return llm_model.LlmModelsResponse(models=models)
+
+
+@router.post(
+    "/models",
+    summary="Create LLM model",
+    response_model=llm_model.LlmModel,
+)
+async def create_llm_model(request: llm_model.CreateLlmModelRequest):
+    model = await llm_db.create_model(request=request)
+    await _refresh_runtime_state()
+    return model
+
+
+@router.patch(
+    "/models/{model_id}",
+    summary="Update LLM model",
+    response_model=llm_model.LlmModel,
+)
+async def update_llm_model(
+    model_id: str,
+    request: llm_model.UpdateLlmModelRequest,
+):
+    model = await llm_db.update_model(model_id=model_id, request=request)
+    await _refresh_runtime_state()
+    return model
+
+
+@router.patch(
+    "/models/{model_id}/toggle",
+    summary="Toggle LLM model availability",
+    response_model=llm_model.ToggleLlmModelResponse,
+)
+async def toggle_llm_model(
+    model_id: str,
+    request: llm_model.ToggleLlmModelRequest,
+):
+    """
+    Toggle a model's enabled status, optionally migrating workflows when disabling.
+
+    If disabling a model and `migrate_to_slug` is provided, all workflows using
+    this model will be migrated to the specified replacement model before disabling.
+    A migration record is created which can be reverted later using the revert endpoint.
+
+    Optional fields:
+    - `migration_reason`: Reason for the migration (e.g., "Provider outage")
+    - `custom_credit_cost`: Custom pricing during the migration period
+    """
+    try:
+        result = await llm_db.toggle_model(
+            model_id=model_id,
+            is_enabled=request.is_enabled,
+            migrate_to_slug=request.migrate_to_slug,
+            migration_reason=request.migration_reason,
+            custom_credit_cost=request.custom_credit_cost,
+        )
+        await _refresh_runtime_state()
+        if result.nodes_migrated > 0:
+            logger.info(
+                "Toggled model '%s' to %s and migrated %d nodes to '%s' (migration_id=%s)",
+                result.model.slug,
+                "enabled" if request.is_enabled else "disabled",
+                result.nodes_migrated,
+                result.migrated_to_slug,
+                result.migration_id,
+            )
+        return result
+    except ValueError as exc:
+        logger.warning("Model toggle validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to toggle LLM model %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to toggle model availability",
+        ) from exc
+
+
+@router.get(
+    "/models/{model_id}/usage",
+    summary="Get model usage count",
+    response_model=llm_model.LlmModelUsageResponse,
+)
+async def get_llm_model_usage(model_id: str):
+    """Get the number of workflow nodes using this model."""
+    try:
+        return await llm_db.get_model_usage(model_id=model_id)
+    except ValueError as exc:
+        raise fastapi.HTTPException(status_code=404, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to get model usage %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get model usage",
+        ) from exc
+
+
+@router.delete(
+    "/models/{model_id}",
+    summary="Delete LLM model and migrate workflows",
+    response_model=llm_model.DeleteLlmModelResponse,
+)
+async def delete_llm_model(
+    model_id: str,
+    replacement_model_slug: str = fastapi.Query(
+        ..., description="Slug of the model to migrate existing workflows to"
+    ),
+):
+    """
+    Delete a model and automatically migrate all workflows using it to a replacement model.
+
+    This endpoint:
+    1. Validates the replacement model exists and is enabled
+    2. Counts how many workflow nodes use the model being deleted
+    3. Updates all AgentNode.constantInput->model fields to the replacement
+    4. Deletes the model record
+    5. Refreshes all caches and notifies executors
+
+    Example: DELETE /admin/llm/models/{id}?replacement_model_slug=gpt-4o
+    """
+    try:
+        result = await llm_db.delete_model(
+            model_id=model_id, replacement_model_slug=replacement_model_slug
+        )
+        await _refresh_runtime_state()
+        logger.info(
+            "Deleted model '%s' and migrated %d nodes to '%s'",
+            result.deleted_model_slug,
+            result.nodes_migrated,
+            result.replacement_model_slug,
+        )
+        return result
+    except ValueError as exc:
+        # Validation errors (model not found, replacement invalid, etc.)
+        logger.warning("Model deletion validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to delete LLM model %s: %s", model_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to delete model and migrate workflows",
+        ) from exc
+
+
+# ============================================================================
+# Migration Management Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/migrations",
+    summary="List model migrations",
+    response_model=llm_model.LlmMigrationsResponse,
+)
+async def list_llm_migrations(
+    include_reverted: bool = fastapi.Query(
+        default=False, description="Include reverted migrations in the list"
+    ),
+):
+    """
+    List all model migrations.
+
+    Migrations are created when disabling a model with the migrate_to_slug option.
+    They can be reverted to restore the original model configuration.
+    """
+    try:
+        migrations = await llm_db.list_migrations(include_reverted=include_reverted)
+        return llm_model.LlmMigrationsResponse(migrations=migrations)
+    except Exception as exc:
+        logger.exception("Failed to list migrations: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to list migrations",
+        ) from exc
+
+
+@router.get(
+    "/migrations/{migration_id}",
+    summary="Get migration details",
+    response_model=llm_model.LlmModelMigration,
+)
+async def get_llm_migration(migration_id: str):
+    """Get details of a specific migration."""
+    try:
+        migration = await llm_db.get_migration(migration_id)
+        if not migration:
+            raise fastapi.HTTPException(
+                status_code=404, detail=f"Migration '{migration_id}' not found"
+            )
+        return migration
+    except fastapi.HTTPException:
+        raise
+    except Exception as exc:
+        logger.exception("Failed to get migration %s: %s", migration_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get migration",
+        ) from exc
+
+
+@router.post(
+    "/migrations/{migration_id}/revert",
+    summary="Revert a model migration",
+    response_model=llm_model.RevertMigrationResponse,
+)
+async def revert_llm_migration(
+    migration_id: str,
+    request: llm_model.RevertMigrationRequest | None = None,
+):
+    """
+    Revert a model migration, restoring affected workflows to their original model.
+
+    This only reverts the specific nodes that were part of the migration.
+    The source model must exist for the revert to succeed.
+
+    Options:
+    - `re_enable_source_model`: Whether to re-enable the source model if disabled (default: True)
+
+    Response includes:
+    - `nodes_reverted`: Number of nodes successfully reverted
+    - `nodes_already_changed`: Number of nodes that were modified since migration (not reverted)
+    - `source_model_re_enabled`: Whether the source model was re-enabled
+
+    Requirements:
+    - Migration must not already be reverted
+    - Source model must exist
+    """
+    try:
+        re_enable = request.re_enable_source_model if request else True
+        result = await llm_db.revert_migration(
+            migration_id,
+            re_enable_source_model=re_enable,
+        )
+        await _refresh_runtime_state()
+        logger.info(
+            "Reverted migration '%s': %d nodes restored from '%s' to '%s' "
+            "(%d already changed, source re-enabled=%s)",
+            migration_id,
+            result.nodes_reverted,
+            result.target_model_slug,
+            result.source_model_slug,
+            result.nodes_already_changed,
+            result.source_model_re_enabled,
+        )
+        return result
+    except ValueError as exc:
+        logger.warning("Migration revert validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to revert migration %s: %s", migration_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to revert migration",
+        ) from exc
+
+
+# ============================================================================
+# Creator Management Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/creators",
+    summary="List model creators",
+    response_model=llm_model.LlmCreatorsResponse,
+)
+async def list_llm_creators():
+    """
+    List all model creators.
+
+    Creators are organizations that create/train models (e.g., OpenAI, Meta, Anthropic).
+    This is distinct from providers who host/serve the models (e.g., OpenRouter).
+    """
+    try:
+        creators = await llm_db.list_creators()
+        return llm_model.LlmCreatorsResponse(creators=creators)
+    except Exception as exc:
+        logger.exception("Failed to list creators: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to list creators",
+        ) from exc
+
+
+@router.get(
+    "/creators/{creator_id}",
+    summary="Get creator details",
+    operation_id="getV2GetLlmCreatorDetails",
+    response_model=llm_model.LlmModelCreator,
+)
+async def get_llm_creator(creator_id: str):
+    """Get details of a specific model creator."""
+    try:
+        creator = await llm_db.get_creator(creator_id)
+        if not creator:
+            raise fastapi.HTTPException(
+                status_code=404, detail=f"Creator '{creator_id}' not found"
+            )
+        return creator
+    except fastapi.HTTPException:
+        raise
+    except Exception as exc:
+        logger.exception("Failed to get creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get creator",
+        ) from exc
+
+
+@router.post(
+    "/creators",
+    summary="Create model creator",
+    response_model=llm_model.LlmModelCreator,
+)
+async def create_llm_creator(request: llm_model.UpsertLlmCreatorRequest):
+    """
+    Create a new model creator.
+
+    A creator represents an organization that creates/trains AI models,
+    such as OpenAI, Anthropic, Meta, or Google.
+    """
+    try:
+        creator = await llm_db.upsert_creator(request=request)
+        await _refresh_runtime_state()
+        logger.info("Created model creator '%s' (%s)", creator.display_name, creator.id)
+        return creator
+    except Exception as exc:
+        logger.exception("Failed to create creator: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to create creator",
+        ) from exc
+
+
+@router.patch(
+    "/creators/{creator_id}",
+    summary="Update model creator",
+    response_model=llm_model.LlmModelCreator,
+)
+async def update_llm_creator(
+    creator_id: str,
+    request: llm_model.UpsertLlmCreatorRequest,
+):
+    """Update an existing model creator."""
+    try:
+        creator = await llm_db.upsert_creator(request=request, creator_id=creator_id)
+        await _refresh_runtime_state()
+        logger.info("Updated model creator '%s' (%s)", creator.display_name, creator_id)
+        return creator
+    except Exception as exc:
+        logger.exception("Failed to update creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to update creator",
+        ) from exc
+
+
+@router.delete(
+    "/creators/{creator_id}",
+    summary="Delete model creator",
+    response_model=dict,
+)
+async def delete_llm_creator(creator_id: str):
+    """
+    Delete a model creator.
+
+    This will remove the creator association from all models that reference it
+    (sets creatorId to NULL), but will not delete the models themselves.
+    """
+    try:
+        await llm_db.delete_creator(creator_id)
+        await _refresh_runtime_state()
+        logger.info("Deleted model creator '%s'", creator_id)
+        return {"success": True, "message": f"Creator '{creator_id}' deleted"}
+    except ValueError as exc:
+        logger.warning("Creator deletion validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=404, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to delete creator %s: %s", creator_id, exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to delete creator",
+        ) from exc
+
+
+# ============================================================================
+# Recommended Model Endpoints
+# ============================================================================
+
+
+@router.get(
+    "/recommended-model",
+    summary="Get recommended model",
+    response_model=llm_model.RecommendedModelResponse,
+)
+async def get_recommended_model():
+    """
+    Get the currently recommended LLM model.
+
+    The recommended model is shown to users as the default/suggested option
+    in model selection dropdowns.
+    """
+    try:
+        model = await llm_db.get_recommended_model()
+        return llm_model.RecommendedModelResponse(
+            model=model,
+            slug=model.slug if model else None,
+        )
+    except Exception as exc:
+        logger.exception("Failed to get recommended model: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to get recommended model",
+        ) from exc
+
+
+@router.post(
+    "/recommended-model",
+    summary="Set recommended model",
+    response_model=llm_model.SetRecommendedModelResponse,
+)
+async def set_recommended_model(request: llm_model.SetRecommendedModelRequest):
+    """
+    Set a model as the recommended model.
+
+    This clears the recommended flag from any other model and sets it on
+    the specified model. The model must be enabled to be set as recommended.
+
+    The recommended model is displayed to users as the default/suggested
+    option in model selection dropdowns throughout the platform.
+    """
+    try:
+        model, previous_slug = await llm_db.set_recommended_model(request.model_id)
+        await _refresh_runtime_state()
+        logger.info(
+            "Set recommended model to '%s' (previous: %s)",
+            model.slug,
+            previous_slug or "none",
+        )
+        return llm_model.SetRecommendedModelResponse(
+            model=model,
+            previous_recommended_slug=previous_slug,
+            message=f"Model '{model.display_name}' is now the recommended model",
+        )
+    except ValueError as exc:
+        logger.warning("Set recommended model validation failed: %s", exc)
+        raise fastapi.HTTPException(status_code=400, detail=str(exc)) from exc
+    except Exception as exc:
+        logger.exception("Failed to set recommended model: %s", exc)
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Failed to set recommended model",
+        ) from exc

autogpt_platform/backend/backend/api/features/admin/llm_routes_test.py

@@ -0,0 +1,405 @@
+from unittest.mock import AsyncMock
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+from autogpt_libs.auth.jwt_utils import get_jwt_payload
+from pytest_snapshot.plugin import Snapshot
+
+import backend.api.features.admin.llm_routes as llm_routes
+
+app = fastapi.FastAPI()
+app.include_router(llm_routes.router)
+
+client = fastapi.testclient.TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_admin_auth(mock_jwt_admin):
+    """Setup admin auth overrides for all tests in this module"""
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def test_list_llm_providers_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful listing of LLM providers"""
+    # Mock the database function
+    mock_providers = [
+        {
+            "id": "provider-1",
+            "name": "openai",
+            "display_name": "OpenAI",
+            "description": "OpenAI LLM provider",
+            "supports_tools": True,
+            "supports_json_output": True,
+            "supports_reasoning": False,
+            "supports_parallel_tool": True,
+            "metadata": {},
+            "models": [],
+        },
+        {
+            "id": "provider-2",
+            "name": "anthropic",
+            "display_name": "Anthropic",
+            "description": "Anthropic LLM provider",
+            "supports_tools": True,
+            "supports_json_output": True,
+            "supports_reasoning": False,
+            "supports_parallel_tool": True,
+            "metadata": {},
+            "models": [],
+        },
+    ]
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.list_providers",
+        new=AsyncMock(return_value=mock_providers),
+    )
+
+    response = client.get("/admin/llm/providers")
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert len(response_data["providers"]) == 2
+    assert response_data["providers"][0]["name"] == "openai"
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "list_llm_providers_success.json")
+
+
+def test_list_llm_models_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful listing of LLM models"""
+    # Mock the database function
+    mock_models = [
+        {
+            "id": "model-1",
+            "slug": "gpt-4o",
+            "display_name": "GPT-4o",
+            "description": "GPT-4 Optimized",
+            "provider_id": "provider-1",
+            "context_window": 128000,
+            "max_output_tokens": 16384,
+            "is_enabled": True,
+            "capabilities": {},
+            "metadata": {},
+            "costs": [
+                {
+                    "id": "cost-1",
+                    "credit_cost": 10,
+                    "credential_provider": "openai",
+                    "metadata": {},
+                }
+            ],
+        }
+    ]
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.list_models",
+        new=AsyncMock(return_value=mock_models),
+    )
+
+    response = client.get("/admin/llm/models")
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert len(response_data["models"]) == 1
+    assert response_data["models"][0]["slug"] == "gpt-4o"
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "list_llm_models_success.json")
+
+
+def test_create_llm_provider_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful creation of LLM provider"""
+    mock_provider = {
+        "id": "new-provider-id",
+        "name": "groq",
+        "display_name": "Groq",
+        "description": "Groq LLM provider",
+        "supports_tools": True,
+        "supports_json_output": True,
+        "supports_reasoning": False,
+        "supports_parallel_tool": False,
+        "metadata": {},
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.upsert_provider",
+        new=AsyncMock(return_value=mock_provider),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "name": "groq",
+        "display_name": "Groq",
+        "description": "Groq LLM provider",
+        "supports_tools": True,
+        "supports_json_output": True,
+        "supports_reasoning": False,
+        "supports_parallel_tool": False,
+        "metadata": {},
+    }
+
+    response = client.post("/admin/llm/providers", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["name"] == "groq"
+    assert response_data["display_name"] == "Groq"
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "create_llm_provider_success.json")
+
+
+def test_create_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful creation of LLM model"""
+    mock_model = {
+        "id": "new-model-id",
+        "slug": "gpt-4.1-mini",
+        "display_name": "GPT-4.1 Mini",
+        "description": "Latest GPT-4.1 Mini model",
+        "provider_id": "provider-1",
+        "context_window": 128000,
+        "max_output_tokens": 16384,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "id": "cost-id",
+                "credit_cost": 5,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.create_model",
+        new=AsyncMock(return_value=mock_model),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "slug": "gpt-4.1-mini",
+        "display_name": "GPT-4.1 Mini",
+        "description": "Latest GPT-4.1 Mini model",
+        "provider_id": "provider-1",
+        "context_window": 128000,
+        "max_output_tokens": 16384,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "credit_cost": 5,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    response = client.post("/admin/llm/models", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["slug"] == "gpt-4.1-mini"
+    assert response_data["is_enabled"] is True
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "create_llm_model_success.json")
+
+
+def test_update_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful update of LLM model"""
+    mock_model = {
+        "id": "model-1",
+        "slug": "gpt-4o",
+        "display_name": "GPT-4o Updated",
+        "description": "Updated description",
+        "provider_id": "provider-1",
+        "context_window": 256000,
+        "max_output_tokens": 32768,
+        "is_enabled": True,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [
+            {
+                "id": "cost-1",
+                "credit_cost": 15,
+                "credential_provider": "openai",
+                "metadata": {},
+            }
+        ],
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.update_model",
+        new=AsyncMock(return_value=mock_model),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {
+        "display_name": "GPT-4o Updated",
+        "description": "Updated description",
+        "context_window": 256000,
+        "max_output_tokens": 32768,
+    }
+
+    response = client.patch("/admin/llm/models/model-1", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["display_name"] == "GPT-4o Updated"
+    assert response_data["context_window"] == 256000
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "update_llm_model_success.json")
+
+
+def test_toggle_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful toggling of LLM model enabled status"""
+    mock_model = {
+        "id": "model-1",
+        "slug": "gpt-4o",
+        "display_name": "GPT-4o",
+        "description": "GPT-4 Optimized",
+        "provider_id": "provider-1",
+        "context_window": 128000,
+        "max_output_tokens": 16384,
+        "is_enabled": False,
+        "capabilities": {},
+        "metadata": {},
+        "costs": [],
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.toggle_model",
+        new=AsyncMock(return_value=mock_model),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    request_data = {"is_enabled": False}
+
+    response = client.patch("/admin/llm/models/model-1/toggle", json=request_data)
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["is_enabled"] is False
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "toggle_llm_model_success.json")
+
+
+def test_delete_llm_model_success(
+    mocker: pytest_mock.MockFixture,
+    configured_snapshot: Snapshot,
+) -> None:
+    """Test successful deletion of LLM model with migration"""
+    mock_response = {
+        "deleted_model_slug": "gpt-3.5-turbo",
+        "deleted_model_display_name": "GPT-3.5 Turbo",
+        "replacement_model_slug": "gpt-4o-mini",
+        "nodes_migrated": 42,
+        "message": "Successfully deleted model 'GPT-3.5 Turbo' (gpt-3.5-turbo) "
+        "and migrated 42 workflow node(s) to 'gpt-4o-mini'.",
+    }
+
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(return_value=type("obj", (object,), mock_response)()),
+    )
+
+    mock_refresh = mocker.patch(
+        "backend.api.features.admin.llm_routes._refresh_runtime_state",
+        new=AsyncMock(),
+    )
+
+    response = client.delete(
+        "/admin/llm/models/model-1?replacement_model_slug=gpt-4o-mini"
+    )
+
+    assert response.status_code == 200
+    response_data = response.json()
+    assert response_data["deleted_model_slug"] == "gpt-3.5-turbo"
+    assert response_data["nodes_migrated"] == 42
+    assert response_data["replacement_model_slug"] == "gpt-4o-mini"
+
+    # Verify refresh was called
+    mock_refresh.assert_called_once()
+
+    # Snapshot test the response
+    configured_snapshot.assert_match(response_data, "delete_llm_model_success.json")
+
+
+def test_delete_llm_model_validation_error(
+    mocker: pytest_mock.MockFixture,
+) -> None:
+    """Test deletion fails with proper error when validation fails"""
+    mocker.patch(
+        "backend.api.features.admin.llm_routes.llm_db.delete_model",
+        new=AsyncMock(side_effect=ValueError("Replacement model 'invalid' not found")),
+    )
+
+    response = client.delete("/admin/llm/models/model-1?replacement_model_slug=invalid")
+
+    assert response.status_code == 400
+    assert "Replacement model 'invalid' not found" in response.json()["detail"]
+
+
+def test_delete_llm_model_missing_replacement(
+    mocker: pytest_mock.MockFixture,
+) -> None:
+    """Test deletion fails when replacement_model_slug is not provided"""
+    response = client.delete("/admin/llm/models/model-1")
+
+    # FastAPI will return 422 for missing required query params
+    assert response.status_code == 422

autogpt_platform/backend/backend/api/features/builder/db.py

@@ -15,6 +15,7 @@ from backend.blocks import load_all_blocks
 from backend.blocks.llm import LlmModel
 from backend.data.block import AnyBlockSchema, BlockCategory, BlockInfo, BlockSchema
 from backend.data.db import query_raw_with_schema
+from backend.data.llm_registry import get_all_model_slugs_for_validation
 from backend.integrations.providers import ProviderName
 from backend.util.cache import cached
 from backend.util.models import Pagination
@@ -31,7 +32,14 @@ from .model import (
 )
 
 logger = logging.getLogger(__name__)
-llm_models = [name.name.lower().replace("_", " ") for name in LlmModel]
+
+
+def _get_llm_models() -> list[str]:
+    """Get LLM model names for search matching from the registry."""
+    return [
+        slug.lower().replace("-", " ") for slug in get_all_model_slugs_for_validation()
+    ]
+
 
 MAX_LIBRARY_AGENT_RESULTS = 100
 MAX_MARKETPLACE_AGENT_RESULTS = 100
@@ -496,8 +504,8 @@ async def _get_static_counts():
 def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
     for field in schema_cls.model_fields.values():
         if field.annotation == LlmModel:
-            # Check if query matches any value in llm_models
-            if any(query in name for name in llm_models):
+            # Check if query matches any value in llm_models from registry
+            if any(query in name for name in _get_llm_models()):
                 return True
     return False
 

autogpt_platform/backend/backend/api/features/store/routes.py

@@ -294,6 +294,7 @@ async def get_creators(
 @router.get(
     "/creator/{username}",
     summary="Get creator details",
+    operation_id="getV2GetCreatorDetails",
     tags=["store", "public"],
     response_model=store_model.CreatorDetails,
 )

autogpt_platform/backend/backend/api/rest_api.py

@@ -18,6 +18,7 @@ from prisma.errors import PrismaError
 
 import backend.api.features.admin.credit_admin_routes
 import backend.api.features.admin.execution_analytics_routes
+import backend.api.features.admin.llm_routes
 import backend.api.features.admin.store_admin_routes
 import backend.api.features.builder
 import backend.api.features.builder.routes
@@ -37,9 +38,11 @@ import backend.data.db
 import backend.data.graph
 import backend.data.user
 import backend.integrations.webhooks.utils
+import backend.server.v2.llm.routes as public_llm_routes
 import backend.util.service
 import backend.util.settings
-from backend.blocks.llm import DEFAULT_LLM_MODEL
+from backend.data import llm_registry
+from backend.data.block_cost_config import refresh_llm_costs
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
 from backend.monitoring.instrumentation import instrument_fastapi
@@ -109,11 +112,27 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     AutoRegistry.patch_integrations()
 
+    # Refresh LLM registry before initializing blocks so blocks can use registry data
+    await llm_registry.refresh_llm_registry()
+    refresh_llm_costs()
+
+    # Clear block schema caches so they're regenerated with updated discriminator_mapping
+    from backend.data.block import BlockSchema
+
+    BlockSchema.clear_all_schema_caches()
+
     await backend.data.block.initialize_blocks()
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
     await backend.data.graph.fix_llm_provider_credentials()
-    await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
+    # migrate_llm_models uses registry default model
+    from backend.blocks.llm import LlmModel
+
+    default_model_slug = llm_registry.get_default_model_slug()
+    if default_model_slug:
+        await backend.data.graph.migrate_llm_models(LlmModel(default_model_slug))
+    else:
+        logger.warning("Skipping LLM model migration: no default model available")
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
     with launch_darkly_context():
@@ -298,6 +317,16 @@ app.include_router(
     tags=["v2", "executions", "review"],
     prefix="/api/review",
 )
+app.include_router(
+    backend.api.features.admin.llm_routes.router,
+    tags=["v2", "admin", "llm"],
+    prefix="/api/llm/admin",
+)
+app.include_router(
+    public_llm_routes.router,
+    tags=["v2", "llm"],
+    prefix="/api",
+)
 app.include_router(
     backend.api.features.library.routes.router, tags=["v2"], prefix="/api/library"
 )

autogpt_platform/backend/backend/api/ws_api.py

@@ -77,7 +77,39 @@ async def event_broadcaster(manager: ConnectionManager):
                 payload=notification.payload,
             )
 
-    await asyncio.gather(execution_worker(), notification_worker())
+    async def registry_refresh_worker():
+        """Listen for LLM registry refresh notifications and broadcast to all clients."""
+        from backend.data.llm_registry import REGISTRY_REFRESH_CHANNEL
+        from backend.data.redis_client import connect_async
+
+        redis = await connect_async()
+        pubsub = redis.pubsub()
+        await pubsub.subscribe(REGISTRY_REFRESH_CHANNEL)
+        logger.info(
+            "Subscribed to LLM registry refresh notifications for WebSocket broadcast"
+        )
+
+        async for message in pubsub.listen():
+            if (
+                message["type"] == "message"
+                and message["channel"] == REGISTRY_REFRESH_CHANNEL
+            ):
+                logger.info(
+                    "Broadcasting LLM registry refresh to all WebSocket clients"
+                )
+                await manager.broadcast_to_all(
+                    method=WSMethod.NOTIFICATION,
+                    data={
+                        "type": "LLM_REGISTRY_REFRESH",
+                        "event": "registry_updated",
+                    },
+                )
+
+    await asyncio.gather(
+        execution_worker(),
+        notification_worker(),
+        registry_refresh_worker(),
+    )
 
 
 async def authenticate_websocket(websocket: WebSocket) -> str:

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -1,7 +1,6 @@
 from typing import Any
 
 from backend.blocks.llm import (
-    DEFAULT_LLM_MODEL,
     TEST_CREDENTIALS,
     TEST_CREDENTIALS_INPUT,
     AIBlockBase,
@@ -10,6 +9,7 @@ from backend.blocks.llm import (
     LlmModel,
     LLMResponse,
     llm_call,
+    llm_model_schema_extra,
 )
 from backend.data.block import (
     BlockCategory,
@@ -50,9 +50,10 @@ class AIConditionBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for evaluating the condition.",
             advanced=False,
+            json_schema_extra=llm_model_schema_extra(),
         )
         credentials: AICredentials = AICredentialsField()
 
@@ -82,7 +83,7 @@ class AIConditionBlock(AIBlockBase):
                 "condition": "the input is an email address",
                 "yes_value": "Valid email",
                 "no_value": "Not an email",
-                "model": DEFAULT_LLM_MODEL,
+                "model": "gpt-4o",  # Using string value - enum accepts any model slug dynamically
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,

autogpt_platform/backend/backend/blocks/llm.py

@@ -4,17 +4,19 @@ import logging
 import re
 import secrets
 from abc import ABC
-from enum import Enum, EnumMeta
+from enum import Enum
 from json import JSONDecodeError
-from typing import Any, Iterable, List, Literal, NamedTuple, Optional
+from typing import Any, Iterable, List, Literal, Optional
 
 import anthropic
 import ollama
 import openai
 from anthropic.types import ToolParam
 from groq import AsyncGroq
-from pydantic import BaseModel, SecretStr
+from pydantic import BaseModel, GetCoreSchemaHandler, SecretStr
+from pydantic_core import CoreSchema, core_schema
 
+from backend.data import llm_registry
 from backend.data.block import (
     Block,
     BlockCategory,
@@ -22,6 +24,7 @@ from backend.data.block import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.llm_registry import ModelMetadata
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -66,114 +69,117 @@ TEST_CREDENTIALS_INPUT = {
 
 
 def AICredentialsField() -> AICredentials:
+    """
+    Returns a CredentialsField for LLM providers.
+    The discriminator_mapping will be refreshed when the schema is generated
+    if it's empty, ensuring the LLM registry is loaded.
+    """
+    # Get the mapping now - it may be empty initially, but will be refreshed
+    # when the schema is generated via CredentialsMetaInput._add_json_schema_extra
+    mapping = llm_registry.get_llm_discriminator_mapping()
+
     return CredentialsField(
         description="API key for the LLM provider.",
         discriminator="model",
-        discriminator_mapping={
-            model.value: model.metadata.provider for model in LlmModel
-        },
+        discriminator_mapping=mapping,  # May be empty initially, refreshed later
     )
 
 
-class ModelMetadata(NamedTuple):
-    provider: str
-    context_window: int
-    max_output_tokens: int | None
+def llm_model_schema_extra() -> dict[str, Any]:
+    return {"options": llm_registry.get_llm_model_schema_options()}
 
 
-class LlmModelMeta(EnumMeta):
-    pass
+class LlmModelMeta(type):
+    """
+    Metaclass for LlmModel that enables attribute-style access to dynamic models.
+
+    This allows code like `LlmModel.GPT4O` to work by converting the attribute
+    name to a slug format:
+    - GPT4O -> gpt-4o
+    - GPT4O_MINI -> gpt-4o-mini
+    - CLAUDE_3_5_SONNET -> claude-3-5-sonnet
+    """
+
+    def __getattr__(cls, name: str):
+        # Don't intercept private/dunder attributes
+        if name.startswith("_"):
+            raise AttributeError(f"type object 'LlmModel' has no attribute '{name}'")
+
+        # Convert attribute name to slug format:
+        # 1. Lowercase: GPT4O -> gpt4o
+        # 2. Underscores to hyphens: GPT4O_MINI -> gpt4o-mini
+        # 3. Insert hyphen between letter and digit: gpt4o -> gpt-4o
+        slug = name.lower().replace("_", "-")
+        slug = re.sub(r"([a-z])(\d)", r"\1-\2", slug)
+
+        return cls(slug)
 
 
-class LlmModel(str, Enum, metaclass=LlmModelMeta):
-    # OpenAI models
-    O3_MINI = "o3-mini"
-    O3 = "o3-2025-04-16"
-    O1 = "o1"
-    O1_MINI = "o1-mini"
-    # GPT-5 models
-    GPT5_2 = "gpt-5.2-2025-12-11"
-    GPT5_1 = "gpt-5.1-2025-11-13"
-    GPT5 = "gpt-5-2025-08-07"
-    GPT5_MINI = "gpt-5-mini-2025-08-07"
-    GPT5_NANO = "gpt-5-nano-2025-08-07"
-    GPT5_CHAT = "gpt-5-chat-latest"
-    GPT41 = "gpt-4.1-2025-04-14"
-    GPT41_MINI = "gpt-4.1-mini-2025-04-14"
-    GPT4O_MINI = "gpt-4o-mini"
-    GPT4O = "gpt-4o"
-    GPT4_TURBO = "gpt-4-turbo"
-    GPT3_5_TURBO = "gpt-3.5-turbo"
-    # Anthropic models
-    CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
-    CLAUDE_4_OPUS = "claude-opus-4-20250514"
-    CLAUDE_4_SONNET = "claude-sonnet-4-20250514"
-    CLAUDE_4_5_OPUS = "claude-opus-4-5-20251101"
-    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
-    CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
-    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
-    CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
-    # AI/ML API models
-    AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
-    AIML_API_LLAMA3_1_70B = "nvidia/llama-3.1-nemotron-70b-instruct"
-    AIML_API_LLAMA3_3_70B = "meta-llama/Llama-3.3-70B-Instruct-Turbo"
-    AIML_API_META_LLAMA_3_1_70B = "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo"
-    AIML_API_LLAMA_3_2_3B = "meta-llama/Llama-3.2-3B-Instruct-Turbo"
-    # Groq models
-    LLAMA3_3_70B = "llama-3.3-70b-versatile"
-    LLAMA3_1_8B = "llama-3.1-8b-instant"
-    # Ollama models
-    OLLAMA_LLAMA3_3 = "llama3.3"
-    OLLAMA_LLAMA3_2 = "llama3.2"
-    OLLAMA_LLAMA3_8B = "llama3"
-    OLLAMA_LLAMA3_405B = "llama3.1:405b"
-    OLLAMA_DOLPHIN = "dolphin-mistral:latest"
-    # OpenRouter models
-    OPENAI_GPT_OSS_120B = "openai/gpt-oss-120b"
-    OPENAI_GPT_OSS_20B = "openai/gpt-oss-20b"
-    GEMINI_2_5_PRO = "google/gemini-2.5-pro-preview-03-25"
-    GEMINI_3_PRO_PREVIEW = "google/gemini-3-pro-preview"
-    GEMINI_2_5_FLASH = "google/gemini-2.5-flash"
-    GEMINI_2_0_FLASH = "google/gemini-2.0-flash-001"
-    GEMINI_2_5_FLASH_LITE_PREVIEW = "google/gemini-2.5-flash-lite-preview-06-17"
-    GEMINI_2_0_FLASH_LITE = "google/gemini-2.0-flash-lite-001"
-    MISTRAL_NEMO = "mistralai/mistral-nemo"
-    COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024"
-    COHERE_COMMAND_R_PLUS_08_2024 = "cohere/command-r-plus-08-2024"
-    DEEPSEEK_CHAT = "deepseek/deepseek-chat"  # Actually: DeepSeek V3
-    DEEPSEEK_R1_0528 = "deepseek/deepseek-r1-0528"
-    PERPLEXITY_SONAR = "perplexity/sonar"
-    PERPLEXITY_SONAR_PRO = "perplexity/sonar-pro"
-    PERPLEXITY_SONAR_DEEP_RESEARCH = "perplexity/sonar-deep-research"
-    NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B = "nousresearch/hermes-3-llama-3.1-405b"
-    NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B = "nousresearch/hermes-3-llama-3.1-70b"
-    AMAZON_NOVA_LITE_V1 = "amazon/nova-lite-v1"
-    AMAZON_NOVA_MICRO_V1 = "amazon/nova-micro-v1"
-    AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1"
-    MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b"
-    GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b"
-    META_LLAMA_4_SCOUT = "meta-llama/llama-4-scout"
-    META_LLAMA_4_MAVERICK = "meta-llama/llama-4-maverick"
-    GROK_4 = "x-ai/grok-4"
-    GROK_4_FAST = "x-ai/grok-4-fast"
-    GROK_4_1_FAST = "x-ai/grok-4.1-fast"
-    GROK_CODE_FAST_1 = "x-ai/grok-code-fast-1"
-    KIMI_K2 = "moonshotai/kimi-k2"
-    QWEN3_235B_A22B_THINKING = "qwen/qwen3-235b-a22b-thinking-2507"
-    QWEN3_CODER = "qwen/qwen3-coder"
-    # Llama API models
-    LLAMA_API_LLAMA_4_SCOUT = "Llama-4-Scout-17B-16E-Instruct-FP8"
-    LLAMA_API_LLAMA4_MAVERICK = "Llama-4-Maverick-17B-128E-Instruct-FP8"
-    LLAMA_API_LLAMA3_3_8B = "Llama-3.3-8B-Instruct"
-    LLAMA_API_LLAMA3_3_70B = "Llama-3.3-70B-Instruct"
-    # v0 by Vercel models
-    V0_1_5_MD = "v0-1.5-md"
-    V0_1_5_LG = "v0-1.5-lg"
-    V0_1_0_MD = "v0-1.0-md"
+class LlmModel(str, metaclass=LlmModelMeta):
+    """
+    Dynamic LLM model type that accepts any model slug from the registry.
+
+    This is a string subclass (not an Enum) that allows any model slug value.
+    All models are managed via the LLM Registry in the database.
+
+    Usage:
+        model = LlmModel("gpt-4o")  # Direct construction
+        model = LlmModel.GPT4O      # Attribute access (converted to "gpt-4o")
+        model.value                  # Returns the slug string
+        model.provider               # Returns the provider from registry
+    """
+
+    def __new__(cls, value: str):
+        if isinstance(value, LlmModel):
+            return value
+        return str.__new__(cls, value)
+
+    @classmethod
+    def __get_pydantic_core_schema__(
+        cls, source_type: Any, handler: GetCoreSchemaHandler
+    ) -> CoreSchema:
+        """
+        Tell Pydantic how to validate LlmModel.
+
+        Accepts strings and converts them to LlmModel instances.
+        """
+        return core_schema.no_info_after_validator_function(
+            cls,  # The validator function (LlmModel constructor)
+            core_schema.str_schema(),  # Accept string input
+            serialization=core_schema.to_string_ser_schema(),  # Serialize as string
+        )
+
+    @property
+    def value(self) -> str:
+        """Return the model slug (for compatibility with enum-style access)."""
+        return str(self)
+
+    @classmethod
+    def default(cls) -> "LlmModel":
+        """
+        Get the default model from the registry.
+
+        Returns the recommended model if set, otherwise gpt-4o if available
+        and enabled, otherwise the first enabled model from the registry.
+        Falls back to "gpt-4o" if registry is empty (e.g., at module import time).
+        """
+        from backend.data.llm_registry import get_default_model_slug
+
+        slug = get_default_model_slug()
+        if slug is None:
+            # Registry is empty (e.g., at module import time before DB connection).
+            # Fall back to gpt-4o for backward compatibility.
+            slug = "gpt-4o"
+        return cls(slug)
 
     @property
     def metadata(self) -> ModelMetadata:
-        return MODEL_METADATA[self]
+        metadata = llm_registry.get_llm_model_metadata(self.value)
+        if metadata:
+            return metadata
+        raise ValueError(
+            f"Missing metadata for model: {self.value}. Model not found in LLM registry."
+        )
 
     @property
     def provider(self) -> str:
@@ -188,128 +194,11 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
         return self.metadata.max_output_tokens
 
 
-MODEL_METADATA = {
-    # https://platform.openai.com/docs/models
-    LlmModel.O3: ModelMetadata("openai", 200000, 100000),
-    LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000),  # o3-mini-2025-01-31
-    LlmModel.O1: ModelMetadata("openai", 200000, 100000),  # o1-2024-12-17
-    LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536),  # o1-mini-2024-09-12
-    # GPT-5 models
-    LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
-    LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
-    LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
-    LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
-    LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
-    LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
-    LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
-    LlmModel.GPT41_MINI: ModelMetadata("openai", 1047576, 32768),
-    LlmModel.GPT4O_MINI: ModelMetadata(
-        "openai", 128000, 16384
-    ),  # gpt-4o-mini-2024-07-18
-    LlmModel.GPT4O: ModelMetadata("openai", 128000, 16384),  # gpt-4o-2024-08-06
-    LlmModel.GPT4_TURBO: ModelMetadata(
-        "openai", 128000, 4096
-    ),  # gpt-4-turbo-2024-04-09
-    LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096),  # gpt-3.5-turbo-0125
-    # https://docs.anthropic.com/en/docs/about-claude/models
-    LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000
-    ),  # claude-opus-4-1-20250805
-    LlmModel.CLAUDE_4_OPUS: ModelMetadata(
-        "anthropic", 200000, 32000
-    ),  # claude-4-opus-20250514
-    LlmModel.CLAUDE_4_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
-    ),  # claude-4-sonnet-20250514
-    LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
-        "anthropic", 200000, 64000
-    ),  # claude-opus-4-5-20251101
-    LlmModel.CLAUDE_4_5_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
-    ),  # claude-sonnet-4-5-20250929
-    LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
-        "anthropic", 200000, 64000
-    ),  # claude-haiku-4-5-20251001
-    LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000
-    ),  # claude-3-7-sonnet-20250219
-    LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
-        "anthropic", 200000, 4096
-    ),  # claude-3-haiku-20240307
-    # https://docs.aimlapi.com/api-overview/model-database/text-models
-    LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000),
-    LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000),
-    LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None),
-    LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000),
-    LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None),
-    # https://console.groq.com/docs/models
-    LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768),
-    LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 128000, 8192),
-    # https://ollama.com/library
-    LlmModel.OLLAMA_LLAMA3_3: ModelMetadata("ollama", 8192, None),
-    LlmModel.OLLAMA_LLAMA3_2: ModelMetadata("ollama", 8192, None),
-    LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192, None),
-    LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192, None),
-    LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
-    # https://openrouter.ai/models
-    LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
-    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata("open_router", 1048576, 65535),
-    LlmModel.GEMINI_2_5_FLASH: ModelMetadata("open_router", 1048576, 65535),
-    LlmModel.GEMINI_2_0_FLASH: ModelMetadata("open_router", 1048576, 8192),
-    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
-        "open_router", 1048576, 65535
-    ),
-    LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata("open_router", 1048576, 8192),
-    LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata("open_router", 128000, 4096),
-    LlmModel.DEEPSEEK_CHAT: ModelMetadata("open_router", 64000, 2048),
-    LlmModel.DEEPSEEK_R1_0528: ModelMetadata("open_router", 163840, 163840),
-    LlmModel.PERPLEXITY_SONAR: ModelMetadata("open_router", 127000, 8000),
-    LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata("open_router", 200000, 8000),
-    LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata(
-        "open_router",
-        128000,
-        16000,
-    ),
-    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata(
-        "open_router", 131000, 4096
-    ),
-    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata(
-        "open_router", 12288, 12288
-    ),
-    LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata("open_router", 131072, 131072),
-    LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata("open_router", 131072, 32768),
-    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 300000, 5120),
-    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 128000, 5120),
-    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
-    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
-    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
-    LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
-    LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
-    LlmModel.GROK_4: ModelMetadata("open_router", 256000, 256000),
-    LlmModel.GROK_4_FAST: ModelMetadata("open_router", 2000000, 30000),
-    LlmModel.GROK_4_1_FAST: ModelMetadata("open_router", 2000000, 30000),
-    LlmModel.GROK_CODE_FAST_1: ModelMetadata("open_router", 256000, 10000),
-    LlmModel.KIMI_K2: ModelMetadata("open_router", 131000, 131000),
-    LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata("open_router", 262144, 262144),
-    LlmModel.QWEN3_CODER: ModelMetadata("open_router", 262144, 262144),
-    # Llama API models
-    LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
-    LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
-    LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
-    LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
-    # v0 by Vercel models
-    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
-    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
-    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
-}
+# MODEL_METADATA removed - all models now come from the database via llm_registry
 
-DEFAULT_LLM_MODEL = LlmModel.GPT5_2
-
-for model in LlmModel:
-    if model not in MODEL_METADATA:
-        raise ValueError(f"Missing MODEL_METADATA metadata for model: {model}")
+# Default model constant for backward compatibility
+# Uses the dynamic registry to get the default model
+DEFAULT_LLM_MODEL = LlmModel.default()
 
 
 class ToolCall(BaseModel):
@@ -438,19 +327,94 @@ async def llm_call(
             - prompt_tokens: The number of tokens used in the prompt.
             - completion_tokens: The number of tokens used in the completion.
     """
-    provider = llm_model.metadata.provider
-    context_window = llm_model.context_window
+    # Get model metadata and check if enabled - with fallback support
+    # The model we'll actually use (may differ if original is disabled)
+    model_to_use = llm_model.value
+
+    # Check if model is in registry and if it's enabled
+    from backend.data.llm_registry import (
+        get_fallback_model_for_disabled,
+        get_model_info,
+    )
+
+    model_info = get_model_info(llm_model.value)
+
+    if model_info and not model_info.is_enabled:
+        # Model is disabled - try to find a fallback from the same provider
+        fallback = get_fallback_model_for_disabled(llm_model.value)
+        if fallback:
+            logger.warning(
+                f"Model '{llm_model.value}' is disabled. Using fallback model '{fallback.slug}' from the same provider ({fallback.metadata.provider})."
+            )
+            model_to_use = fallback.slug
+            # Use fallback model's metadata
+            provider = fallback.metadata.provider
+            context_window = fallback.metadata.context_window
+            model_max_output = fallback.metadata.max_output_tokens or int(2**15)
+        else:
+            # No fallback available - raise error
+            raise ValueError(
+                f"LLM model '{llm_model.value}' is disabled and no fallback model "
+                f"from the same provider is available. Please enable the model or "
+                f"select a different model in the block configuration."
+            )
+    else:
+        # Model is enabled or not in registry (legacy/static model)
+        try:
+            provider = llm_model.metadata.provider
+            context_window = llm_model.context_window
+            model_max_output = llm_model.max_output_tokens or int(2**15)
+        except ValueError:
+            # Model not in cache - try refreshing the registry once if we have DB access
+            logger.warning(f"Model {llm_model.value} not found in registry cache")
+
+            # Try refreshing the registry if we have database access
+            from backend.data.db import is_connected
+
+            if is_connected():
+                try:
+                    logger.info(
+                        f"Refreshing LLM registry and retrying lookup for {llm_model.value}"
+                    )
+                    await llm_registry.refresh_llm_registry()
+                    # Try again after refresh
+                    try:
+                        provider = llm_model.metadata.provider
+                        context_window = llm_model.context_window
+                        model_max_output = llm_model.max_output_tokens or int(2**15)
+                        logger.info(
+                            f"Successfully loaded model {llm_model.value} metadata after registry refresh"
+                        )
+                    except ValueError:
+                        # Still not found after refresh
+                        raise ValueError(
+                            f"LLM model '{llm_model.value}' not found in registry after refresh. "
+                            "Please ensure the model is added and enabled in the LLM registry via the admin UI."
+                        )
+                except Exception as refresh_exc:
+                    logger.error(f"Failed to refresh LLM registry: {refresh_exc}")
+                    raise ValueError(
+                        f"LLM model '{llm_model.value}' not found in registry and failed to refresh. "
+                        "Please ensure the model is added to the LLM registry via the admin UI."
+                    ) from refresh_exc
+            else:
+                # No DB access (e.g., in executor without direct DB connection)
+                # The registry should have been loaded on startup
+                raise ValueError(
+                    f"LLM model '{llm_model.value}' not found in registry cache. "
+                    "The registry may need to be refreshed. Please contact support or try again later."
+                )
 
     if compress_prompt_to_fit:
         prompt = compress_prompt(
             messages=prompt,
-            target_tokens=llm_model.context_window // 2,
+            target_tokens=context_window // 2,
             lossy_ok=True,
         )
 
     # Calculate available tokens based on context window and input length
     estimated_input_tokens = estimate_token_count(prompt)
-    model_max_output = llm_model.max_output_tokens or int(2**15)
+    # model_max_output already set above
     user_max = max_tokens or model_max_output
     available_tokens = max(context_window - estimated_input_tokens, 0)
     max_tokens = max(min(available_tokens, model_max_output, user_max), 1)
@@ -468,7 +432,7 @@ async def llm_call(
             response_format = {"type": "json_object"}
 
         response = await oai_client.chat.completions.create(
-            model=llm_model.value,
+            model=model_to_use,
             messages=prompt,  # type: ignore
             response_format=response_format,  # type: ignore
             max_completion_tokens=max_tokens,
@@ -515,7 +479,7 @@ async def llm_call(
         )
         try:
             resp = await client.messages.create(
-                model=llm_model.value,
+                model=model_to_use,
                 system=sysprompt,
                 messages=messages,
                 max_tokens=max_tokens,
@@ -579,7 +543,7 @@ async def llm_call(
         client = AsyncGroq(api_key=credentials.api_key.get_secret_value())
         response_format = {"type": "json_object"} if force_json_output else None
         response = await client.chat.completions.create(
-            model=llm_model.value,
+            model=model_to_use,
             messages=prompt,  # type: ignore
             response_format=response_format,  # type: ignore
             max_tokens=max_tokens,
@@ -601,7 +565,7 @@ async def llm_call(
         sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
         usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
         response = await client.generate(
-            model=llm_model.value,
+            model=model_to_use,
             prompt=f"{sys_messages}\n\n{usr_messages}",
             stream=False,
             options={"num_ctx": max_tokens},
@@ -631,7 +595,7 @@ async def llm_call(
                 "HTTP-Referer": "https://agpt.co",
                 "X-Title": "AutoGPT",
             },
-            model=llm_model.value,
+            model=model_to_use,
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
             tools=tools_param,  # type: ignore
@@ -673,7 +637,7 @@ async def llm_call(
                 "HTTP-Referer": "https://agpt.co",
                 "X-Title": "AutoGPT",
             },
-            model=llm_model.value,
+            model=model_to_use,
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
             tools=tools_param,  # type: ignore
@@ -700,7 +664,7 @@ async def llm_call(
             reasoning=reasoning,
         )
     elif provider == "aiml_api":
-        client = openai.OpenAI(
+        client = openai.AsyncOpenAI(
             base_url="https://api.aimlapi.com/v2",
             api_key=credentials.api_key.get_secret_value(),
             default_headers={
@@ -710,8 +674,8 @@ async def llm_call(
             },
         )
 
-        completion = client.chat.completions.create(
-            model=llm_model.value,
+        completion = await client.chat.completions.create(
+            model=model_to_use,
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
         )
@@ -743,7 +707,7 @@ async def llm_call(
         )
 
         response = await client.chat.completions.create(
-            model=llm_model.value,
+            model=model_to_use,
             messages=prompt,  # type: ignore
             response_format=response_format,  # type: ignore
             max_tokens=max_tokens,
@@ -794,9 +758,10 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for answering the prompt.",
             advanced=False,
+            json_schema_extra=llm_model_schema_extra(),
         )
         force_json_output: bool = SchemaField(
             title="Restrict LLM to pure JSON output",
@@ -859,7 +824,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
             input_schema=AIStructuredResponseGeneratorBlock.Input,
             output_schema=AIStructuredResponseGeneratorBlock.Output,
             test_input={
-                "model": DEFAULT_LLM_MODEL,
+                "model": "gpt-4o",  # Using string value - enum accepts any model slug dynamically
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "expected_format": {
                     "key1": "value1",
@@ -1225,9 +1190,10 @@ class AITextGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for answering the prompt.",
             advanced=False,
+            json_schema_extra=llm_model_schema_extra(),
         )
         credentials: AICredentials = AICredentialsField()
         sys_prompt: str = SchemaField(
@@ -1321,8 +1287,9 @@ class AITextSummarizerBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for summarizing the text.",
+            json_schema_extra=llm_model_schema_extra(),
         )
         focus: str = SchemaField(
             title="Focus",
@@ -1538,8 +1505,9 @@ class AIConversationBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for the conversation.",
+            json_schema_extra=llm_model_schema_extra(),
         )
         credentials: AICredentials = AICredentialsField()
         max_tokens: int | None = SchemaField(
@@ -1576,7 +1544,7 @@ class AIConversationBlock(AIBlockBase):
                     },
                     {"role": "user", "content": "Where was it played?"},
                 ],
-                "model": DEFAULT_LLM_MODEL,
+                "model": "gpt-4o",  # Using string value - enum accepts any model slug dynamically
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_credentials=TEST_CREDENTIALS,
@@ -1639,9 +1607,10 @@ class AIListGeneratorBlock(AIBlockBase):
         )
         model: LlmModel = SchemaField(
             title="LLM Model",
-            default=DEFAULT_LLM_MODEL,
+            default_factory=LlmModel.default,
             description="The language model to use for generating the list.",
             advanced=True,
+            json_schema_extra=llm_model_schema_extra(),
         )
         credentials: AICredentials = AICredentialsField()
         max_retries: int = SchemaField(
@@ -1696,7 +1665,7 @@ class AIListGeneratorBlock(AIBlockBase):
                     "drawing explorers to uncover its mysteries. Each planet showcases the limitless possibilities of "
                     "fictional worlds."
                 ),
-                "model": DEFAULT_LLM_MODEL,
+                "model": "gpt-4o",  # Using string value - enum accepts any model slug dynamically
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "max_retries": 3,
                 "force_json_output": False,

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -226,9 +226,10 @@ class SmartDecisionMakerBlock(Block):
         )
         model: llm.LlmModel = SchemaField(
             title="LLM Model",
-            default=llm.DEFAULT_LLM_MODEL,
+            default_factory=llm.LlmModel.default,
             description="The language model to use for answering the prompt.",
             advanced=False,
+            json_schema_extra=llm.llm_model_schema_extra(),
         )
         credentials: llm.AICredentials = llm.AICredentialsField()
         multiple_tool_calls: bool = SchemaField(

autogpt_platform/backend/backend/blocks/stagehand/blocks.py

@@ -10,13 +10,13 @@ import stagehand.main
 from stagehand import Stagehand
 
 from backend.blocks.llm import (
-    MODEL_METADATA,
     AICredentials,
     AICredentialsField,
     LlmModel,
     ModelMetadata,
 )
 from backend.blocks.stagehand._config import stagehand as stagehand_provider
+from backend.data import llm_registry
 from backend.sdk import (
     APIKeyCredentials,
     Block,
@@ -91,7 +91,7 @@ class StagehandRecommendedLlmModel(str, Enum):
         Returns the provider name for the model in the required format for Stagehand:
         provider/model_name
         """
-        model_metadata = MODEL_METADATA[LlmModel(self.value)]
+        model_metadata = self.metadata
         model_name = self.value
 
         if len(model_name.split("/")) == 1 and not self.value.startswith(
@@ -107,19 +107,23 @@ class StagehandRecommendedLlmModel(str, Enum):
 
     @property
     def provider(self) -> str:
-        return MODEL_METADATA[LlmModel(self.value)].provider
+        return self.metadata.provider
 
     @property
     def metadata(self) -> ModelMetadata:
-        return MODEL_METADATA[LlmModel(self.value)]
+        metadata = llm_registry.get_llm_model_metadata(self.value)
+        if metadata:
+            return metadata
+        # Fallback to LlmModel enum if registry lookup fails
+        return LlmModel(self.value).metadata
 
     @property
     def context_window(self) -> int:
-        return MODEL_METADATA[LlmModel(self.value)].context_window
+        return self.metadata.context_window
 
     @property
     def max_output_tokens(self) -> int | None:
-        return MODEL_METADATA[LlmModel(self.value)].max_output_tokens
+        return self.metadata.max_output_tokens
 
 
 class StagehandObserveBlock(Block):

autogpt_platform/backend/backend/data/block.py

@@ -25,6 +25,7 @@ from prisma.models import AgentBlock
 from prisma.types import AgentBlockCreateInput
 from pydantic import BaseModel
 
+from backend.data.llm_registry import update_schema_with_llm_registry
 from backend.data.model import NodeExecutionStats
 from backend.integrations.providers import ProviderName
 from backend.util import json
@@ -141,35 +142,59 @@ class BlockInfo(BaseModel):
 
 
 class BlockSchema(BaseModel):
-    cached_jsonschema: ClassVar[dict[str, Any]]
+    cached_jsonschema: ClassVar[dict[str, Any] | None] = None
+
+    @classmethod
+    def clear_schema_cache(cls) -> None:
+        """Clear the cached JSON schema for this class."""
+        # Use None instead of {} because {} is truthy and would prevent regeneration
+        cls.cached_jsonschema = None  # type: ignore
+
+    @staticmethod
+    def clear_all_schema_caches() -> None:
+        """Clear cached JSON schemas for all BlockSchema subclasses."""
+
+        def clear_recursive(cls: type) -> None:
+            """Recursively clear cache for class and all subclasses."""
+            if hasattr(cls, "clear_schema_cache"):
+                cls.clear_schema_cache()
+            for subclass in cls.__subclasses__():
+                clear_recursive(subclass)
+
+        clear_recursive(BlockSchema)
 
     @classmethod
     def jsonschema(cls) -> dict[str, Any]:
-        if cls.cached_jsonschema:
-            return cls.cached_jsonschema
+        # Generate schema if not cached
+        if not cls.cached_jsonschema:
+            model = jsonref.replace_refs(cls.model_json_schema(), merge_props=True)
 
-        model = jsonref.replace_refs(cls.model_json_schema(), merge_props=True)
+            def ref_to_dict(obj):
+                if isinstance(obj, dict):
+                    # OpenAPI <3.1 does not support sibling fields that has a $ref key
+                    # So sometimes, the schema has an "allOf"/"anyOf"/"oneOf" with 1 item.
+                    keys = {"allOf", "anyOf", "oneOf"}
+                    one_key = next(
+                        (k for k in keys if k in obj and len(obj[k]) == 1), None
+                    )
+                    if one_key:
+                        obj.update(obj[one_key][0])
 
-        def ref_to_dict(obj):
-            if isinstance(obj, dict):
-                # OpenAPI <3.1 does not support sibling fields that has a $ref key
-                # So sometimes, the schema has an "allOf"/"anyOf"/"oneOf" with 1 item.
-                keys = {"allOf", "anyOf", "oneOf"}
-                one_key = next((k for k in keys if k in obj and len(obj[k]) == 1), None)
-                if one_key:
-                    obj.update(obj[one_key][0])
+                    return {
+                        key: ref_to_dict(value)
+                        for key, value in obj.items()
+                        if not key.startswith("$") and key != one_key
+                    }
+                elif isinstance(obj, list):
+                    return [ref_to_dict(item) for item in obj]
 
-                return {
-                    key: ref_to_dict(value)
-                    for key, value in obj.items()
-                    if not key.startswith("$") and key != one_key
-                }
-            elif isinstance(obj, list):
-                return [ref_to_dict(item) for item in obj]
+                return obj
 
-            return obj
+            cls.cached_jsonschema = cast(dict[str, Any], ref_to_dict(model))
 
-        cls.cached_jsonschema = cast(dict[str, Any], ref_to_dict(model))
+        # Always post-process to ensure LLM registry data is up-to-date
+        # This refreshes model options and discriminator mappings even if schema was cached
+        update_schema_with_llm_registry(cls.cached_jsonschema, cls)
 
         return cls.cached_jsonschema
 
@@ -785,6 +810,28 @@ def is_block_auth_configured(
 
 
 async def initialize_blocks() -> None:
+    # Refresh LLM registry before initializing blocks so blocks can use registry data
+    # This ensures the registry cache is populated even in executor context
+    try:
+        from backend.data import llm_registry
+        from backend.data.block_cost_config import refresh_llm_costs
+
+        # Only refresh if we have DB access (check if Prisma is connected)
+        from backend.data.db import is_connected
+
+        if is_connected():
+            await llm_registry.refresh_llm_registry()
+            refresh_llm_costs()
+            logger.info("LLM registry refreshed during block initialization")
+        else:
+            logger.warning(
+                "Prisma not connected, skipping LLM registry refresh during block initialization"
+            )
+    except Exception as exc:
+        logger.warning(
+            "Failed to refresh LLM registry during block initialization: %s", exc
+        )
+
     # First, sync all provider costs to blocks
     # Imported here to avoid circular import
     from backend.sdk.cost_integration import sync_all_provider_costs

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -1,3 +1,4 @@
+import logging
 from typing import Type
 
 from backend.blocks.ai_image_customizer import AIImageCustomizerBlock, GeminiImageModel
@@ -23,19 +24,18 @@ from backend.blocks.ideogram import IdeogramModelBlock
 from backend.blocks.jina.embeddings import JinaEmbeddingBlock
 from backend.blocks.jina.search import ExtractWebsiteContentBlock, SearchTheWebBlock
 from backend.blocks.llm import (
-    MODEL_METADATA,
     AIConversationBlock,
     AIListGeneratorBlock,
     AIStructuredResponseGeneratorBlock,
     AITextGeneratorBlock,
     AITextSummarizerBlock,
-    LlmModel,
 )
 from backend.blocks.replicate.flux_advanced import ReplicateFluxAdvancedModelBlock
 from backend.blocks.replicate.replicate_block import ReplicateModelBlock
 from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 from backend.blocks.talking_head import CreateTalkingAvatarVideoBlock
 from backend.blocks.text_to_speech_block import UnrealTextToSpeechBlock
+from backend.data import llm_registry
 from backend.data.block import Block, BlockCost, BlockCostType
 from backend.integrations.credentials_store import (
     aiml_api_credentials,
@@ -55,210 +55,63 @@ from backend.integrations.credentials_store import (
     v0_credentials,
 )
 
-# =============== Configure the cost for each LLM Model call =============== #
+logger = logging.getLogger(__name__)
 
-MODEL_COST: dict[LlmModel, int] = {
-    LlmModel.O3: 4,
-    LlmModel.O3_MINI: 2,
-    LlmModel.O1: 16,
-    LlmModel.O1_MINI: 4,
-    # GPT-5 models
-    LlmModel.GPT5_2: 6,
-    LlmModel.GPT5_1: 5,
-    LlmModel.GPT5: 2,
-    LlmModel.GPT5_MINI: 1,
-    LlmModel.GPT5_NANO: 1,
-    LlmModel.GPT5_CHAT: 5,
-    LlmModel.GPT41: 2,
-    LlmModel.GPT41_MINI: 1,
-    LlmModel.GPT4O_MINI: 1,
-    LlmModel.GPT4O: 3,
-    LlmModel.GPT4_TURBO: 10,
-    LlmModel.GPT3_5_TURBO: 1,
-    LlmModel.CLAUDE_4_1_OPUS: 21,
-    LlmModel.CLAUDE_4_OPUS: 21,
-    LlmModel.CLAUDE_4_SONNET: 5,
-    LlmModel.CLAUDE_4_5_HAIKU: 4,
-    LlmModel.CLAUDE_4_5_OPUS: 14,
-    LlmModel.CLAUDE_4_5_SONNET: 9,
-    LlmModel.CLAUDE_3_7_SONNET: 5,
-    LlmModel.CLAUDE_3_HAIKU: 1,
-    LlmModel.AIML_API_QWEN2_5_72B: 1,
-    LlmModel.AIML_API_LLAMA3_1_70B: 1,
-    LlmModel.AIML_API_LLAMA3_3_70B: 1,
-    LlmModel.AIML_API_META_LLAMA_3_1_70B: 1,
-    LlmModel.AIML_API_LLAMA_3_2_3B: 1,
-    LlmModel.LLAMA3_3_70B: 1,
-    LlmModel.LLAMA3_1_8B: 1,
-    LlmModel.OLLAMA_LLAMA3_3: 1,
-    LlmModel.OLLAMA_LLAMA3_2: 1,
-    LlmModel.OLLAMA_LLAMA3_8B: 1,
-    LlmModel.OLLAMA_LLAMA3_405B: 1,
-    LlmModel.OLLAMA_DOLPHIN: 1,
-    LlmModel.OPENAI_GPT_OSS_120B: 1,
-    LlmModel.OPENAI_GPT_OSS_20B: 1,
-    LlmModel.GEMINI_2_5_PRO: 4,
-    LlmModel.GEMINI_3_PRO_PREVIEW: 5,
-    LlmModel.MISTRAL_NEMO: 1,
-    LlmModel.COHERE_COMMAND_R_08_2024: 1,
-    LlmModel.COHERE_COMMAND_R_PLUS_08_2024: 3,
-    LlmModel.DEEPSEEK_CHAT: 2,
-    LlmModel.PERPLEXITY_SONAR: 1,
-    LlmModel.PERPLEXITY_SONAR_PRO: 5,
-    LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: 10,
-    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: 1,
-    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: 1,
-    LlmModel.AMAZON_NOVA_LITE_V1: 1,
-    LlmModel.AMAZON_NOVA_MICRO_V1: 1,
-    LlmModel.AMAZON_NOVA_PRO_V1: 1,
-    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: 1,
-    LlmModel.GRYPHE_MYTHOMAX_L2_13B: 1,
-    LlmModel.META_LLAMA_4_SCOUT: 1,
-    LlmModel.META_LLAMA_4_MAVERICK: 1,
-    LlmModel.LLAMA_API_LLAMA_4_SCOUT: 1,
-    LlmModel.LLAMA_API_LLAMA4_MAVERICK: 1,
-    LlmModel.LLAMA_API_LLAMA3_3_8B: 1,
-    LlmModel.LLAMA_API_LLAMA3_3_70B: 1,
-    LlmModel.GROK_4: 9,
-    LlmModel.GROK_4_FAST: 1,
-    LlmModel.GROK_4_1_FAST: 1,
-    LlmModel.GROK_CODE_FAST_1: 1,
-    LlmModel.KIMI_K2: 1,
-    LlmModel.QWEN3_235B_A22B_THINKING: 1,
-    LlmModel.QWEN3_CODER: 9,
-    LlmModel.GEMINI_2_5_FLASH: 1,
-    LlmModel.GEMINI_2_0_FLASH: 1,
-    LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
-    LlmModel.GEMINI_2_0_FLASH_LITE: 1,
-    LlmModel.DEEPSEEK_R1_0528: 1,
-    # v0 by Vercel models
-    LlmModel.V0_1_5_MD: 1,
-    LlmModel.V0_1_5_LG: 2,
-    LlmModel.V0_1_0_MD: 1,
+PROVIDER_CREDENTIALS = {
+    "openai": openai_credentials,
+    "anthropic": anthropic_credentials,
+    "groq": groq_credentials,
+    "open_router": open_router_credentials,
+    "llama_api": llama_api_credentials,
+    "aiml_api": aiml_api_credentials,
+    "v0": v0_credentials,
 }
 
-for model in LlmModel:
-    if model not in MODEL_COST:
-        raise ValueError(f"Missing MODEL_COST for model: {model}")
+# =============== Configure the cost for each LLM Model call =============== #
+# All LLM costs now come from the database via llm_registry
+
+LLM_COST: list[BlockCost] = []
 
 
-LLM_COST = (
-    # Anthropic Models
-    [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
+def _build_llm_costs_from_registry() -> list[BlockCost]:
+    """Build BlockCost list from all models in the LLM registry."""
+    costs: list[BlockCost] = []
+    for model in llm_registry.iter_dynamic_models():
+        for cost in model.costs:
+            credentials = PROVIDER_CREDENTIALS.get(cost.credential_provider)
+            if not credentials:
+                logger.warning(
+                    "Skipping cost entry for %s due to unknown credentials provider %s",
+                    model.slug,
+                    cost.credential_provider,
+                )
+                continue
+            cost_filter = {
+                "model": model.slug,
                 "credentials": {
-                    "id": anthropic_credentials.id,
-                    "provider": anthropic_credentials.provider,
-                    "type": anthropic_credentials.type,
+                    "id": credentials.id,
+                    "provider": credentials.provider,
+                    "type": credentials.type,
                 },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "anthropic"
-    ]
-    # OpenAI Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {
-                    "id": openai_credentials.id,
-                    "provider": openai_credentials.provider,
-                    "type": openai_credentials.type,
-                },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "openai"
-    ]
-    # Groq Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {"id": groq_credentials.id},
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "groq"
-    ]
-    # Open Router Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {
-                    "id": open_router_credentials.id,
-                    "provider": open_router_credentials.provider,
-                    "type": open_router_credentials.type,
-                },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "open_router"
-    ]
-    # Llama API Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {
-                    "id": llama_api_credentials.id,
-                    "provider": llama_api_credentials.provider,
-                    "type": llama_api_credentials.type,
-                },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "llama_api"
-    ]
-    # v0 by Vercel Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {
-                    "id": v0_credentials.id,
-                    "provider": v0_credentials.provider,
-                    "type": v0_credentials.type,
-                },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "v0"
-    ]
-    # AI/ML Api Models
-    + [
-        BlockCost(
-            cost_type=BlockCostType.RUN,
-            cost_filter={
-                "model": model,
-                "credentials": {
-                    "id": aiml_api_credentials.id,
-                    "provider": aiml_api_credentials.provider,
-                    "type": aiml_api_credentials.type,
-                },
-            },
-            cost_amount=cost,
-        )
-        for model, cost in MODEL_COST.items()
-        if MODEL_METADATA[model].provider == "aiml_api"
-    ]
-)
+            }
+            costs.append(
+                BlockCost(
+                    cost_type=BlockCostType.RUN,
+                    cost_filter=cost_filter,
+                    cost_amount=cost.credit_cost,
+                )
+            )
+    return costs
+
+
+def refresh_llm_costs() -> None:
+    """Refresh LLM costs from the registry. All costs now come from the database."""
+    LLM_COST.clear()
+    LLM_COST.extend(_build_llm_costs_from_registry())
+
+
+# Initial load will happen after registry is refreshed at startup
+# Don't call refresh_llm_costs() here - it will be called after registry refresh
 
 # =============== This is the exhaustive list of cost for each Block =============== #
 

autogpt_platform/backend/backend/data/graph.py

@@ -1443,8 +1443,10 @@ async def migrate_llm_models(migrate_to: LlmModel):
             if field.annotation == LlmModel:
                 llm_model_fields[block.id] = field_name
 
-    # Convert enum values to a list of strings for the SQL query
-    enum_values = [v.value for v in LlmModel]
+    # Get all model slugs from the registry (dynamic, not hardcoded enum)
+    from backend.data import llm_registry
+
+    enum_values = list(llm_registry.get_all_model_slugs_for_validation())
     escaped_enum_values = repr(tuple(enum_values))  # hack but works
 
     # Update each block

autogpt_platform/backend/backend/data/llm_registry/__init__.py

@@ -0,0 +1,72 @@
+"""
+LLM Registry module for managing LLM models, providers, and costs dynamically.
+
+This module provides a database-driven registry system for LLM models,
+replacing hardcoded model configurations with a flexible admin-managed system.
+"""
+
+from backend.data.llm_registry.model_types import ModelMetadata
+
+# Re-export for backwards compatibility
+from backend.data.llm_registry.notifications import (
+    REGISTRY_REFRESH_CHANNEL,
+    publish_registry_refresh_notification,
+    subscribe_to_registry_refresh,
+)
+from backend.data.llm_registry.registry import (
+    RegistryModel,
+    RegistryModelCost,
+    RegistryModelCreator,
+    get_all_model_slugs_for_validation,
+    get_default_model_slug,
+    get_dynamic_model_slugs,
+    get_fallback_model_for_disabled,
+    get_llm_discriminator_mapping,
+    get_llm_model_cost,
+    get_llm_model_metadata,
+    get_llm_model_schema_options,
+    get_model_info,
+    is_model_enabled,
+    iter_dynamic_models,
+    refresh_llm_registry,
+    register_static_costs,
+    register_static_metadata,
+)
+from backend.data.llm_registry.schema_utils import (
+    is_llm_model_field,
+    refresh_llm_discriminator_mapping,
+    refresh_llm_model_options,
+    update_schema_with_llm_registry,
+)
+
+__all__ = [
+    # Types
+    "ModelMetadata",
+    "RegistryModel",
+    "RegistryModelCost",
+    "RegistryModelCreator",
+    # Registry functions
+    "get_all_model_slugs_for_validation",
+    "get_default_model_slug",
+    "get_dynamic_model_slugs",
+    "get_fallback_model_for_disabled",
+    "get_llm_discriminator_mapping",
+    "get_llm_model_cost",
+    "get_llm_model_metadata",
+    "get_llm_model_schema_options",
+    "get_model_info",
+    "is_model_enabled",
+    "iter_dynamic_models",
+    "refresh_llm_registry",
+    "register_static_costs",
+    "register_static_metadata",
+    # Notifications
+    "REGISTRY_REFRESH_CHANNEL",
+    "publish_registry_refresh_notification",
+    "subscribe_to_registry_refresh",
+    # Schema utilities
+    "is_llm_model_field",
+    "refresh_llm_discriminator_mapping",
+    "refresh_llm_model_options",
+    "update_schema_with_llm_registry",
+]

autogpt_platform/backend/backend/data/llm_registry/model_types.py

@@ -0,0 +1,11 @@
+"""Type definitions for LLM model metadata."""
+
+from typing import NamedTuple
+
+
+class ModelMetadata(NamedTuple):
+    """Metadata for an LLM model."""
+
+    provider: str
+    context_window: int
+    max_output_tokens: int | None

autogpt_platform/backend/backend/data/llm_registry/notifications.py

@@ -0,0 +1,91 @@
+"""
+Redis pub/sub notifications for LLM registry updates.
+
+When models are added/updated/removed via the admin UI, this module
+publishes notifications to Redis that all executor services subscribe to,
+ensuring they refresh their registry cache in real-time.
+"""
+
+import asyncio
+import logging
+from typing import Any
+
+from backend.data.redis_client import get_redis
+
+logger = logging.getLogger(__name__)
+
+# Redis channel name for LLM registry refresh notifications
+REGISTRY_REFRESH_CHANNEL = "llm_registry:refresh"
+
+
+def publish_registry_refresh_notification() -> None:
+    """
+    Publish a notification to Redis that the LLM registry has been updated.
+    All executor services subscribed to this channel will refresh their registry.
+    """
+    try:
+        redis = get_redis()
+        redis.publish(REGISTRY_REFRESH_CHANNEL, "refresh")
+        logger.info("Published LLM registry refresh notification to Redis")
+    except Exception as exc:
+        logger.warning(
+            "Failed to publish LLM registry refresh notification: %s",
+            exc,
+            exc_info=True,
+        )
+
+
+async def subscribe_to_registry_refresh(
+    on_refresh: Any,  # Async callable that takes no args
+) -> None:
+    """
+    Subscribe to Redis notifications for LLM registry updates.
+    This runs in a loop and processes messages as they arrive.
+
+    Args:
+        on_refresh: Async callable to execute when a refresh notification is received
+    """
+    from backend.data.redis_client import connect_async
+
+    try:
+        redis = await connect_async()
+        pubsub = redis.pubsub()
+        await pubsub.subscribe(REGISTRY_REFRESH_CHANNEL)
+        logger.info(
+            "Subscribed to LLM registry refresh notifications on channel: %s",
+            REGISTRY_REFRESH_CHANNEL,
+        )
+
+        # Process messages in a loop
+        while True:
+            try:
+                message = await pubsub.get_message(
+                    ignore_subscribe_messages=True, timeout=1.0
+                )
+                if (
+                    message
+                    and message["type"] == "message"
+                    and message["channel"] == REGISTRY_REFRESH_CHANNEL
+                ):
+                    logger.info("Received LLM registry refresh notification")
+                    try:
+                        await on_refresh()
+                    except Exception as exc:
+                        logger.error(
+                            "Error refreshing LLM registry from notification: %s",
+                            exc,
+                            exc_info=True,
+                        )
+            except Exception as exc:
+                logger.warning(
+                    "Error processing registry refresh message: %s", exc, exc_info=True
+                )
+                # Continue listening even if one message fails
+                await asyncio.sleep(1)
+    except Exception as exc:
+        logger.error(
+            "Failed to subscribe to LLM registry refresh notifications: %s",
+            exc,
+            exc_info=True,
+        )
+        raise

autogpt_platform/backend/backend/data/llm_registry/registry.py

@@ -0,0 +1,371 @@
+"""Core LLM registry implementation for managing models dynamically."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from dataclasses import dataclass, field
+from typing import Any, Iterable
+
+import prisma.models
+
+from backend.data.llm_registry.model_types import ModelMetadata
+
+logger = logging.getLogger(__name__)
+
+
+def _json_to_dict(value: Any) -> dict[str, Any]:
+    """Convert Prisma Json type to dict, with fallback to empty dict."""
+    if value is None:
+        return {}
+    if isinstance(value, dict):
+        return value
+    # Prisma Json type should always be a dict at runtime
+    return dict(value) if value else {}
+
+
+@dataclass(frozen=True)
+class RegistryModelCost:
+    """Cost configuration for an LLM model."""
+
+    credit_cost: int
+    credential_provider: str
+    credential_id: str | None
+    credential_type: str | None
+    currency: str | None
+    metadata: dict[str, Any]
+
+
+@dataclass(frozen=True)
+class RegistryModelCreator:
+    """Creator information for an LLM model."""
+
+    id: str
+    name: str
+    display_name: str
+    description: str | None
+    website_url: str | None
+    logo_url: str | None
+
+
+@dataclass(frozen=True)
+class RegistryModel:
+    """Represents a model in the LLM registry."""
+
+    slug: str
+    display_name: str
+    description: str | None
+    metadata: ModelMetadata
+    capabilities: dict[str, Any]
+    extra_metadata: dict[str, Any]
+    provider_display_name: str
+    is_enabled: bool
+    is_recommended: bool = False
+    costs: tuple[RegistryModelCost, ...] = field(default_factory=tuple)
+    creator: RegistryModelCreator | None = None
+
+
+_static_metadata: dict[str, ModelMetadata] = {}
+_static_costs: dict[str, int] = {}
+_dynamic_models: dict[str, RegistryModel] = {}
+_schema_options: list[dict[str, str]] = []
+_discriminator_mapping: dict[str, str] = {}
+_lock = asyncio.Lock()
+
+
+def register_static_metadata(metadata: dict[Any, ModelMetadata]) -> None:
+    """Register static metadata for legacy models (deprecated)."""
+    _static_metadata.update({str(key): value for key, value in metadata.items()})
+    _refresh_cached_schema()
+
+
+def register_static_costs(costs: dict[Any, int]) -> None:
+    """Register static costs for legacy models (deprecated)."""
+    _static_costs.update({str(key): value for key, value in costs.items()})
+
+
+def _build_schema_options() -> list[dict[str, str]]:
+    """Build schema options for model selection dropdown. Only includes enabled models."""
+    options: list[dict[str, str]] = []
+    # Only include enabled models in the dropdown options
+    for model in sorted(_dynamic_models.values(), key=lambda m: m.display_name.lower()):
+        if model.is_enabled:
+            options.append(
+                {
+                    "label": model.display_name,
+                    "value": model.slug,
+                    "group": model.metadata.provider,
+                    "description": model.description or "",
+                }
+            )
+
+    for slug, metadata in _static_metadata.items():
+        if slug in _dynamic_models:
+            continue
+        options.append(
+            {
+                "label": slug,
+                "value": slug,
+                "group": metadata.provider,
+                "description": "",
+            }
+        )
+    return options
+
+
+async def refresh_llm_registry() -> None:
+    """Refresh the LLM registry from the database. Loads all models (enabled and disabled)."""
+    async with _lock:
+        try:
+            records = await prisma.models.LlmModel.prisma().find_many(
+                include={
+                    "Provider": True,
+                    "Costs": True,
+                    "Creator": True,
+                }
+            )
+            logger.debug("Found %d LLM model records in database", len(records))
+        except Exception as exc:
+            logger.error(
+                "Failed to refresh LLM registry from DB: %s", exc, exc_info=True
+            )
+            return
+
+        dynamic: dict[str, RegistryModel] = {}
+        for record in records:
+            provider_name = (
+                record.Provider.name if record.Provider else record.providerId
+            )
+            metadata = ModelMetadata(
+                provider=provider_name,
+                context_window=record.contextWindow,
+                max_output_tokens=record.maxOutputTokens,
+            )
+            costs = tuple(
+                RegistryModelCost(
+                    credit_cost=cost.creditCost,
+                    credential_provider=cost.credentialProvider,
+                    credential_id=cost.credentialId,
+                    credential_type=cost.credentialType,
+                    currency=cost.currency,
+                    metadata=_json_to_dict(cost.metadata),
+                )
+                for cost in (record.Costs or [])
+            )
+
+            # Map creator if present
+            creator = None
+            if record.Creator:
+                creator = RegistryModelCreator(
+                    id=record.Creator.id,
+                    name=record.Creator.name,
+                    display_name=record.Creator.displayName,
+                    description=record.Creator.description,
+                    website_url=record.Creator.websiteUrl,
+                    logo_url=record.Creator.logoUrl,
+                )
+
+            dynamic[record.slug] = RegistryModel(
+                slug=record.slug,
+                display_name=record.displayName,
+                description=record.description,
+                metadata=metadata,
+                capabilities=_json_to_dict(record.capabilities),
+                extra_metadata=_json_to_dict(record.metadata),
+                provider_display_name=(
+                    record.Provider.displayName
+                    if record.Provider
+                    else record.providerId
+                ),
+                is_enabled=record.isEnabled,
+                is_recommended=record.isRecommended,
+                costs=costs,
+                creator=creator,
+            )
+
+        _dynamic_models.clear()
+        _dynamic_models.update(dynamic)
+        _refresh_cached_schema()
+        logger.info(
+            "LLM registry refreshed with %s dynamic models (enabled: %s, disabled: %s)",
+            len(dynamic),
+            sum(1 for m in dynamic.values() if m.is_enabled),
+            sum(1 for m in dynamic.values() if not m.is_enabled),
+        )
+
+
+def _refresh_cached_schema() -> None:
+    """Refresh cached schema options and discriminator mapping."""
+    new_options = _build_schema_options()
+    _schema_options.clear()
+    _schema_options.extend(new_options)
+    _discriminator_mapping.clear()
+    _discriminator_mapping.update(
+        {slug: entry.metadata.provider for slug, entry in _dynamic_models.items()}
+    )
+    for slug, metadata in _static_metadata.items():
+        _discriminator_mapping.setdefault(slug, metadata.provider)
+
+
+def get_llm_model_metadata(slug: str) -> ModelMetadata | None:
+    """Get model metadata by slug. Checks dynamic models first, then static metadata."""
+    if slug in _dynamic_models:
+        return _dynamic_models[slug].metadata
+    return _static_metadata.get(slug)
+
+
+def get_llm_model_cost(slug: str) -> tuple[RegistryModelCost, ...]:
+    """Get model cost configuration by slug."""
+    if slug in _dynamic_models:
+        return _dynamic_models[slug].costs
+    cost_value = _static_costs.get(slug)
+    if cost_value is None:
+        return tuple()
+    return (
+        RegistryModelCost(
+            credit_cost=cost_value,
+            credential_provider="static",
+            credential_id=None,
+            credential_type=None,
+            currency=None,
+            metadata={},
+        ),
+    )
+
+
+def get_llm_model_schema_options() -> list[dict[str, str]]:
+    """
+    Get schema options for LLM model selection dropdown.
+
+    Returns cached schema options that are refreshed when the registry is updated
+    via refresh_llm_registry() (called on startup and via Redis pub/sub notifications).
+    """
+    return _schema_options
+
+
+def get_llm_discriminator_mapping() -> dict[str, str]:
+    """
+    Get discriminator mapping for LLM models.
+
+    Returns cached discriminator mapping that is refreshed when the registry is updated
+    via refresh_llm_registry() (called on startup and via Redis pub/sub notifications).
+    """
+    return _discriminator_mapping
+
+
+def get_dynamic_model_slugs() -> set[str]:
+    """Get all dynamic model slugs from the registry."""
+    return set(_dynamic_models.keys())
+
+
+def get_all_model_slugs_for_validation() -> set[str]:
+    """
+    Get ALL model slugs (both enabled and disabled) for validation purposes.
+
+    This is used for JSON schema enum validation - we need to accept any known
+    model value (even disabled ones) so that existing graphs don't fail validation.
+    The actual fallback/enforcement happens at runtime in llm_call().
+    """
+    all_slugs = set(_dynamic_models.keys())
+    all_slugs.update(_static_metadata.keys())
+    return all_slugs
+
+
+def iter_dynamic_models() -> Iterable[RegistryModel]:
+    """Iterate over all dynamic models in the registry."""
+    return tuple(_dynamic_models.values())
+
+
+def get_fallback_model_for_disabled(disabled_model_slug: str) -> RegistryModel | None:
+    """
+    Find a fallback model when the requested model is disabled.
+
+    Looks for an enabled model from the same provider. Prefers models with
+    similar names or capabilities if possible.
+
+    Args:
+        disabled_model_slug: The slug of the disabled model
+
+    Returns:
+        An enabled RegistryModel from the same provider, or None if no fallback found
+    """
+    disabled_model = _dynamic_models.get(disabled_model_slug)
+    if not disabled_model:
+        return None
+
+    provider = disabled_model.metadata.provider
+
+    # Find all enabled models from the same provider
+    candidates = [
+        model
+        for model in _dynamic_models.values()
+        if model.is_enabled and model.metadata.provider == provider
+    ]
+
+    if not candidates:
+        return None
+
+    # Sort by: prefer models with similar context window, then by name
+    candidates.sort(
+        key=lambda m: (
+            abs(m.metadata.context_window - disabled_model.metadata.context_window),
+            m.display_name.lower(),
+        )
+    )
+
+    return candidates[0]
+
+
+def is_model_enabled(model_slug: str) -> bool:
+    """Check if a model is enabled in the registry."""
+    model = _dynamic_models.get(model_slug)
+    if not model:
+        # Model not in registry - assume it's a static/legacy model and allow it
+        return True
+    return model.is_enabled
+
+
+def get_model_info(model_slug: str) -> RegistryModel | None:
+    """Get model info from the registry."""
+    return _dynamic_models.get(model_slug)
+
+
+def get_default_model_slug() -> str | None:
+    """
+    Get the default model slug to use for block defaults.
+
+    Returns the recommended model if set, otherwise falls back to "gpt-4o"
+    if available and enabled, then first enabled model alphabetically.
+    Returns None if no models are available or enabled.
+    """
+    # First, check for recommended model
+    for model in _dynamic_models.values():
+        if model.is_recommended and model.is_enabled:
+            return model.slug
+
+    # Fallback to gpt-4o if available and enabled
+    fallback_slug = "gpt-4o"
+    fallback_model = _dynamic_models.get(fallback_slug)
+    if fallback_model and fallback_model.is_enabled:
+        return fallback_slug
+
+    # Find first enabled model alphabetically
+    for model in sorted(_dynamic_models.values(), key=lambda m: m.display_name.lower()):
+        if model.is_enabled:
+            logger.warning(
+                "Preferred model '%s' not available, using '%s' as default",
+                fallback_slug,
+                model.slug,
+            )
+            return model.slug
+
+    # No enabled models available
+    if _dynamic_models:
+        logger.error(
+            "No enabled models found in registry (%d models registered but all disabled)",
+            len(_dynamic_models),
+        )
+    else:
+        logger.error("No models registered in LLM registry")
+
+    return None

autogpt_platform/backend/backend/data/llm_registry/schema_utils.py

@@ -0,0 +1,130 @@
+"""
+Helper utilities for LLM registry integration with block schemas.
+
+This module handles the dynamic injection of discriminator mappings
+and model options from the LLM registry into block schemas.
+"""
+
+import logging
+from typing import Any
+
+from backend.data.llm_registry.registry import (
+    get_all_model_slugs_for_validation,
+    get_default_model_slug,
+    get_llm_discriminator_mapping,
+    get_llm_model_schema_options,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def is_llm_model_field(field_name: str, field_info: Any) -> bool:
+    """
+    Check if a field is an LLM model selection field.
+
+    Returns True if the field has 'options' in json_schema_extra
+    (set by llm_model_schema_extra() in blocks/llm.py).
+    """
+    if not hasattr(field_info, "json_schema_extra"):
+        return False
+
+    extra = field_info.json_schema_extra
+    if isinstance(extra, dict):
+        return "options" in extra
+
+    return False
+
+
+def refresh_llm_model_options(field_schema: dict[str, Any]) -> None:
+    """
+    Refresh LLM model options from the registry.
+
+    Updates 'options' (for frontend dropdown) to show only enabled models,
+    but keeps the 'enum' (for validation) inclusive of ALL known models.
+
+    This is important because:
+    - Options: What users see in the dropdown (enabled models only)
+    - Enum: What values pass validation (all known models, including disabled)
+
+    Existing graphs may have disabled models selected - they should pass validation
+    and the fallback logic in llm_call() will handle using an alternative model.
+    """
+    fresh_options = get_llm_model_schema_options()
+    if not fresh_options:
+        return
+
+    # Update options array (UI dropdown) - only enabled models
+    if "options" in field_schema:
+        field_schema["options"] = fresh_options
+
+    all_known_slugs = get_all_model_slugs_for_validation()
+    if all_known_slugs and "enum" in field_schema:
+        existing_enum = set(field_schema.get("enum", []))
+        combined_enum = existing_enum | all_known_slugs
+        field_schema["enum"] = sorted(combined_enum)
+
+    # Set the default value from the registry (gpt-4o if available, else first enabled)
+    # This ensures new blocks have a sensible default pre-selected
+    default_slug = get_default_model_slug()
+    if default_slug:
+        field_schema["default"] = default_slug
+
+
+def refresh_llm_discriminator_mapping(field_schema: dict[str, Any]) -> None:
+    """
+    Refresh discriminator_mapping for fields that use model-based discrimination.
+
+    The discriminator is already set when AICredentialsField() creates the field.
+    We only need to refresh the mapping when models are added/removed.
+    """
+    if field_schema.get("discriminator") != "model":
+        return
+
+    # Always refresh the mapping to get latest models
+    fresh_mapping = get_llm_discriminator_mapping()
+    if fresh_mapping:
+        field_schema["discriminator_mapping"] = fresh_mapping
+
+
+def update_schema_with_llm_registry(
+    schema: dict[str, Any], model_class: type | None = None
+) -> None:
+    """
+    Update a JSON schema with current LLM registry data.
+
+    Refreshes:
+    1. Model options for LLM model selection fields (dropdown choices)
+    2. Discriminator mappings for credentials fields (model → provider)
+
+    Args:
+        schema: The JSON schema to update (mutated in-place)
+        model_class: The Pydantic model class (optional, for field introspection)
+    """
+    properties = schema.get("properties", {})
+
+    for field_name, field_schema in properties.items():
+        if not isinstance(field_schema, dict):
+            continue
+
+        # Refresh model options for LLM model fields
+        if model_class and hasattr(model_class, "model_fields"):
+            field_info = model_class.model_fields.get(field_name)
+            if field_info and is_llm_model_field(field_name, field_info):
+                try:
+                    refresh_llm_model_options(field_schema)
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to refresh LLM options for field %s: %s",
+                        field_name,
+                        exc,
+                    )
+
+        # Refresh discriminator mapping for fields that use model discrimination
+        try:
+            refresh_llm_discriminator_mapping(field_schema)
+        except Exception as exc:
+            logger.warning(
+                "Failed to refresh discriminator mapping for field %s: %s",
+                field_name,
+                exc,
+            )

autogpt_platform/backend/backend/data/model.py

@@ -40,6 +40,7 @@ from pydantic_core import (
 )
 from typing_extensions import TypedDict
 
+from backend.data.llm_registry import update_schema_with_llm_registry
 from backend.integrations.providers import ProviderName
 from backend.util.json import loads as json_loads
 from backend.util.settings import Secrets
@@ -544,7 +545,9 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
             else:
                 schema["credentials_provider"] = allowed_providers
             schema["credentials_types"] = model_class.allowed_cred_types()
-        # Do not return anything, just mutate schema in place
+
+        # Ensure LLM discriminators are populated (delegates to shared helper)
+        update_schema_with_llm_registry(schema, model_class)
 
     model_config = ConfigDict(
         json_schema_extra=_add_json_schema_extra,  # type: ignore
@@ -693,16 +696,20 @@ def CredentialsField(
     This is enforced by the `BlockSchema` base class.
     """
 
-    field_schema_extra = {
-        k: v
-        for k, v in {
-            "credentials_scopes": list(required_scopes) or None,
-            "discriminator": discriminator,
-            "discriminator_mapping": discriminator_mapping,
-            "discriminator_values": discriminator_values,
-        }.items()
-        if v is not None
-    }
+    # Build field_schema_extra - always include discriminator and mapping if discriminator is set
+    field_schema_extra: dict[str, Any] = {}
+
+    # Always include discriminator if provided
+    if discriminator is not None:
+        field_schema_extra["discriminator"] = discriminator
+        # Always include discriminator_mapping when discriminator is set (even if empty initially)
+        field_schema_extra["discriminator_mapping"] = discriminator_mapping or {}
+
+    # Include other optional fields (only if not None)
+    if required_scopes:
+        field_schema_extra["credentials_scopes"] = list(required_scopes)
+    if discriminator_values:
+        field_schema_extra["discriminator_values"] = discriminator_values
 
     # Merge any json_schema_extra passed in kwargs
     if "json_schema_extra" in kwargs:

autogpt_platform/backend/backend/executor/llm_registry_init.py

@@ -0,0 +1,66 @@
+"""
+Helper functions for LLM registry initialization in executor context.
+
+These functions handle refreshing the LLM registry when the executor starts
+and subscribing to real-time updates via Redis pub/sub.
+"""
+
+import logging
+
+from backend.data import db, llm_registry
+from backend.data.block import BlockSchema, initialize_blocks
+from backend.data.block_cost_config import refresh_llm_costs
+from backend.data.llm_registry import subscribe_to_registry_refresh
+
+logger = logging.getLogger(__name__)
+
+
+async def initialize_registry_for_executor() -> None:
+    """
+    Initialize blocks and refresh LLM registry in the executor context.
+
+    This must run in the executor's event loop to have access to the database.
+    """
+    try:
+        # Connect to database if not already connected
+        if not db.is_connected():
+            await db.connect()
+            logger.info("[GraphExecutor] Connected to database for registry refresh")
+
+        # Initialize blocks (internally refreshes LLM registry and costs)
+        await initialize_blocks()
+        logger.info("[GraphExecutor] Blocks initialized")
+    except Exception as exc:
+        logger.warning(
+            "[GraphExecutor] Failed to refresh LLM registry on startup: %s",
+            exc,
+            exc_info=True,
+        )
+
+
+async def refresh_registry_on_notification() -> None:
+    """Refresh LLM registry when notified via Redis pub/sub."""
+    try:
+        # Ensure DB is connected
+        if not db.is_connected():
+            await db.connect()
+
+        # Refresh registry and costs
+        await llm_registry.refresh_llm_registry()
+        refresh_llm_costs()
+
+        # Clear block schema caches so they regenerate with new model options
+        BlockSchema.clear_all_schema_caches()
+
+        logger.info("[GraphExecutor] LLM registry refreshed from notification")
+    except Exception as exc:
+        logger.error(
+            "[GraphExecutor] Failed to refresh LLM registry from notification: %s",
+            exc,
+            exc_info=True,
+        )
+
+
+async def subscribe_to_registry_updates() -> None:
+    """Subscribe to Redis pub/sub for LLM registry refresh notifications."""
+    await subscribe_to_registry_refresh(refresh_registry_on_notification)

autogpt_platform/backend/backend/executor/manager.py

@@ -696,6 +696,20 @@ class ExecutionProcessor:
         )
         self.node_execution_thread.start()
         self.node_evaluation_thread.start()
+
+        # Initialize LLM registry and subscribe to updates
+        from backend.executor.llm_registry_init import (
+            initialize_registry_for_executor,
+            subscribe_to_registry_updates,
+        )
+
+        asyncio.run_coroutine_threadsafe(
+            initialize_registry_for_executor(), self.node_execution_loop
+        )
+        asyncio.run_coroutine_threadsafe(
+            subscribe_to_registry_updates(), self.node_execution_loop
+        )
+
         logger.info(f"[GraphExecutor] {self.tid} started")
 
     @error_logged(swallow=False)

autogpt_platform/backend/backend/server/v2/llm/db.py

@@ -0,0 +1,847 @@
+from __future__ import annotations
+
+from typing import Any, Iterable, Sequence, cast
+
+import prisma
+import prisma.models
+
+from backend.data.db import transaction
+from backend.server.v2.llm import model as llm_model
+
+
+def _json_dict(value: Any | None) -> dict[str, Any]:
+    if not value:
+        return {}
+    if isinstance(value, dict):
+        return value
+    return {}
+
+
+def _map_cost(record: prisma.models.LlmModelCost) -> llm_model.LlmModelCost:
+    return llm_model.LlmModelCost(
+        id=record.id,
+        unit=record.unit,
+        credit_cost=record.creditCost,
+        credential_provider=record.credentialProvider,
+        credential_id=record.credentialId,
+        credential_type=record.credentialType,
+        currency=record.currency,
+        metadata=_json_dict(record.metadata),
+    )
+
+
+def _map_creator(
+    record: prisma.models.LlmModelCreator,
+) -> llm_model.LlmModelCreator:
+    return llm_model.LlmModelCreator(
+        id=record.id,
+        name=record.name,
+        display_name=record.displayName,
+        description=record.description,
+        website_url=record.websiteUrl,
+        logo_url=record.logoUrl,
+        metadata=_json_dict(record.metadata),
+    )
+
+
+def _map_model(record: prisma.models.LlmModel) -> llm_model.LlmModel:
+    costs = []
+    if record.Costs:
+        costs = [_map_cost(cost) for cost in record.Costs]
+
+    creator = None
+    if hasattr(record, "Creator") and record.Creator:
+        creator = _map_creator(record.Creator)
+
+    return llm_model.LlmModel(
+        id=record.id,
+        slug=record.slug,
+        display_name=record.displayName,
+        description=record.description,
+        provider_id=record.providerId,
+        creator_id=record.creatorId,
+        creator=creator,
+        context_window=record.contextWindow,
+        max_output_tokens=record.maxOutputTokens,
+        is_enabled=record.isEnabled,
+        is_recommended=record.isRecommended,
+        capabilities=_json_dict(record.capabilities),
+        metadata=_json_dict(record.metadata),
+        costs=costs,
+    )
+
+
+def _map_provider(record: prisma.models.LlmProvider) -> llm_model.LlmProvider:
+    models: list[llm_model.LlmModel] = []
+    if record.Models:
+        models = [_map_model(model) for model in record.Models]
+
+    return llm_model.LlmProvider(
+        id=record.id,
+        name=record.name,
+        display_name=record.displayName,
+        description=record.description,
+        default_credential_provider=record.defaultCredentialProvider,
+        default_credential_id=record.defaultCredentialId,
+        default_credential_type=record.defaultCredentialType,
+        supports_tools=record.supportsTools,
+        supports_json_output=record.supportsJsonOutput,
+        supports_reasoning=record.supportsReasoning,
+        supports_parallel_tool=record.supportsParallelTool,
+        metadata=_json_dict(record.metadata),
+        models=models,
+    )
+
+
+async def list_providers(
+    include_models: bool = True, enabled_only: bool = False
+) -> list[llm_model.LlmProvider]:
+    """
+    List all LLM providers.
+
+    Args:
+        include_models: Whether to include models for each provider
+        enabled_only: If True, only include enabled models (for public routes)
+    """
+    include: Any = None
+    if include_models:
+        model_where = {"isEnabled": True} if enabled_only else None
+        include = {
+            "Models": {
+                "include": {"Costs": True, "Creator": True},
+                "where": model_where,
+            }
+        }
+    records = await prisma.models.LlmProvider.prisma().find_many(include=include)
+    return [_map_provider(record) for record in records]
+
+
+async def upsert_provider(
+    request: llm_model.UpsertLlmProviderRequest,
+    provider_id: str | None = None,
+) -> llm_model.LlmProvider:
+    data: Any = {
+        "name": request.name,
+        "displayName": request.display_name,
+        "description": request.description,
+        "defaultCredentialProvider": request.default_credential_provider,
+        "defaultCredentialId": request.default_credential_id,
+        "defaultCredentialType": request.default_credential_type,
+        "supportsTools": request.supports_tools,
+        "supportsJsonOutput": request.supports_json_output,
+        "supportsReasoning": request.supports_reasoning,
+        "supportsParallelTool": request.supports_parallel_tool,
+        "metadata": request.metadata,
+    }
+    include: Any = {"Models": {"include": {"Costs": True, "Creator": True}}}
+    if provider_id:
+        record = await prisma.models.LlmProvider.prisma().update(
+            where={"id": provider_id},
+            data=data,
+            include=include,
+        )
+    else:
+        record = await prisma.models.LlmProvider.prisma().create(
+            data=data,
+            include=include,
+        )
+    if record is None:
+        raise ValueError("Failed to create/update provider")
+    return _map_provider(record)
+
+
+async def list_models(
+    provider_id: str | None = None, enabled_only: bool = False
+) -> list[llm_model.LlmModel]:
+    """
+    List LLM models.
+
+    Args:
+        provider_id: Optional filter by provider ID
+        enabled_only: If True, only return enabled models (for public routes)
+    """
+    where: Any = {}
+    if provider_id:
+        where["providerId"] = provider_id
+    if enabled_only:
+        where["isEnabled"] = True
+
+    records = await prisma.models.LlmModel.prisma().find_many(
+        where=where if where else None,
+        include={"Costs": True, "Creator": True},
+    )
+    return [_map_model(record) for record in records]
+
+
+def _cost_create_payload(
+    costs: Sequence[llm_model.LlmModelCostInput],
+) -> dict[str, Iterable[dict[str, Any]]]:
+
+    create_items = []
+    for cost in costs:
+        item: dict[str, Any] = {
+            "unit": cost.unit,
+            "creditCost": cost.credit_cost,
+            "credentialProvider": cost.credential_provider,
+        }
+        # Only include optional fields if they have values
+        if cost.credential_id:
+            item["credentialId"] = cost.credential_id
+        if cost.credential_type:
+            item["credentialType"] = cost.credential_type
+        if cost.currency:
+            item["currency"] = cost.currency
+        # Handle metadata - use Prisma Json type
+        if cost.metadata is not None and cost.metadata != {}:
+            item["metadata"] = prisma.Json(cost.metadata)
+        create_items.append(item)
+    return {"create": create_items}
+
+
+async def create_model(
+    request: llm_model.CreateLlmModelRequest,
+) -> llm_model.LlmModel:
+    data: Any = {
+        "slug": request.slug,
+        "displayName": request.display_name,
+        "description": request.description,
+        "providerId": request.provider_id,
+        "contextWindow": request.context_window,
+        "maxOutputTokens": request.max_output_tokens,
+        "isEnabled": request.is_enabled,
+        "capabilities": request.capabilities,
+        "metadata": request.metadata,
+        "Costs": _cost_create_payload(request.costs),
+    }
+    if request.creator_id:
+        data["creatorId"] = request.creator_id
+
+    record = await prisma.models.LlmModel.prisma().create(
+        data=data,
+        include={"Costs": True, "Creator": True},
+    )
+    return _map_model(record)
+
+
+async def update_model(
+    model_id: str,
+    request: llm_model.UpdateLlmModelRequest,
+) -> llm_model.LlmModel:
+    # Build scalar field updates (non-relation fields)
+    scalar_data: Any = {}
+    if request.display_name is not None:
+        scalar_data["displayName"] = request.display_name
+    if request.description is not None:
+        scalar_data["description"] = request.description
+    if request.context_window is not None:
+        scalar_data["contextWindow"] = request.context_window
+    if request.max_output_tokens is not None:
+        scalar_data["maxOutputTokens"] = request.max_output_tokens
+    if request.is_enabled is not None:
+        scalar_data["isEnabled"] = request.is_enabled
+    if request.capabilities is not None:
+        scalar_data["capabilities"] = request.capabilities
+    if request.metadata is not None:
+        scalar_data["metadata"] = request.metadata
+    # Foreign keys can be updated directly as scalar fields
+    if request.provider_id is not None:
+        scalar_data["providerId"] = request.provider_id
+    if request.creator_id is not None:
+        # Empty string means remove the creator
+        scalar_data["creatorId"] = request.creator_id if request.creator_id else None
+
+    # If we have costs to update, we need to handle them separately
+    # because nested writes have different constraints
+    if request.costs is not None:
+        # Wrap cost replacement in a transaction for atomicity
+        async with transaction() as tx:
+            # First update scalar fields
+            if scalar_data:
+                await tx.llmmodel.update(
+                    where={"id": model_id},
+                    data=scalar_data,
+                )
+            # Then handle costs: delete existing and create new
+            await tx.llmmodelcost.delete_many(where={"llmModelId": model_id})
+            if request.costs:
+                cost_payload = _cost_create_payload(request.costs)
+                for cost_item in cost_payload["create"]:
+                    cost_item["llmModelId"] = model_id
+                    await tx.llmmodelcost.create(data=cast(Any, cost_item))
+        # Fetch the updated record (outside transaction)
+        record = await prisma.models.LlmModel.prisma().find_unique(
+            where={"id": model_id},
+            include={"Costs": True, "Creator": True},
+        )
+    else:
+        # No costs update - simple update
+        record = await prisma.models.LlmModel.prisma().update(
+            where={"id": model_id},
+            data=scalar_data,
+            include={"Costs": True, "Creator": True},
+        )
+
+    if not record:
+        raise ValueError(f"Model with id '{model_id}' not found")
+    return _map_model(record)
+
+
+async def toggle_model(
+    model_id: str,
+    is_enabled: bool,
+    migrate_to_slug: str | None = None,
+    migration_reason: str | None = None,
+    custom_credit_cost: int | None = None,
+) -> llm_model.ToggleLlmModelResponse:
+    """
+    Toggle a model's enabled status, optionally migrating workflows when disabling.
+
+    Args:
+        model_id: UUID of the model to toggle
+        is_enabled: New enabled status
+        migrate_to_slug: If disabling and this is provided, migrate all workflows
+                         using this model to the specified replacement model
+        migration_reason: Optional reason for the migration (e.g., "Provider outage")
+        custom_credit_cost: Optional custom pricing during the migration period
+
+    Returns:
+        ToggleLlmModelResponse with the updated model and optional migration stats
+    """
+    import json
+
+    # Get the model being toggled
+    model = await prisma.models.LlmModel.prisma().find_unique(
+        where={"id": model_id}, include={"Costs": True}
+    )
+    if not model:
+        raise ValueError(f"Model with id '{model_id}' not found")
+
+    nodes_migrated = 0
+    migration_id: str | None = None
+
+    # If disabling with migration, perform migration first
+    if not is_enabled and migrate_to_slug:
+        # Validate replacement model exists and is enabled
+        replacement = await prisma.models.LlmModel.prisma().find_unique(
+            where={"slug": migrate_to_slug}
+        )
+        if not replacement:
+            raise ValueError(f"Replacement model '{migrate_to_slug}' not found")
+        if not replacement.isEnabled:
+            raise ValueError(
+                f"Replacement model '{migrate_to_slug}' is disabled. "
+                f"Please enable it before using it as a replacement."
+            )
+
+        # Perform all operations atomically within a single transaction
+        # This ensures no nodes are missed between query and update
+        async with transaction() as tx:
+            # Get the IDs of nodes that will be migrated (inside transaction for consistency)
+            node_ids_result = await tx.query_raw(
+                """
+                SELECT id
+                FROM "AgentNode"
+                WHERE "constantInput"::jsonb->>'model' = $1
+                FOR UPDATE
+                """,
+                model.slug,
+            )
+            migrated_node_ids = (
+                [row["id"] for row in node_ids_result] if node_ids_result else []
+            )
+            nodes_migrated = len(migrated_node_ids)
+
+            if nodes_migrated > 0:
+                # Update by IDs to ensure we only update the exact nodes we queried
+                node_ids_pg_array = "{" + ",".join(migrated_node_ids) + "}"
+                await tx.execute_raw(
+                    """
+                    UPDATE "AgentNode"
+                    SET "constantInput" = JSONB_SET(
+                        "constantInput"::jsonb,
+                        '{model}',
+                        to_jsonb($1::text)
+                    )
+                    WHERE id::text = ANY($2::text[])
+                    """,
+                    migrate_to_slug,
+                    node_ids_pg_array,
+                )
+
+            record = await tx.llmmodel.update(
+                where={"id": model_id},
+                data={"isEnabled": is_enabled},
+                include={"Costs": True},
+            )
+
+            # Create migration record for revert capability
+            if nodes_migrated > 0:
+                migration_data: Any = {
+                    "sourceModelSlug": model.slug,
+                    "targetModelSlug": migrate_to_slug,
+                    "reason": migration_reason,
+                    "migratedNodeIds": json.dumps(migrated_node_ids),
+                    "nodeCount": nodes_migrated,
+                    "customCreditCost": custom_credit_cost,
+                }
+                migration_record = await tx.llmmodelmigration.create(
+                    data=migration_data
+                )
+                migration_id = migration_record.id
+    else:
+        # Simple toggle without migration
+        record = await prisma.models.LlmModel.prisma().update(
+            where={"id": model_id},
+            data={"isEnabled": is_enabled},
+            include={"Costs": True},
+        )
+
+    if record is None:
+        raise ValueError(f"Model with id '{model_id}' not found")
+    return llm_model.ToggleLlmModelResponse(
+        model=_map_model(record),
+        nodes_migrated=nodes_migrated,
+        migrated_to_slug=migrate_to_slug if nodes_migrated > 0 else None,
+        migration_id=migration_id,
+    )
+
+
+async def get_model_usage(model_id: str) -> llm_model.LlmModelUsageResponse:
+    """Get usage count for a model."""
+    import prisma as prisma_module
+
+    model = await prisma.models.LlmModel.prisma().find_unique(where={"id": model_id})
+    if not model:
+        raise ValueError(f"Model with id '{model_id}' not found")
+
+    count_result = await prisma_module.get_client().query_raw(
+        """
+        SELECT COUNT(*) as count
+        FROM "AgentNode"
+        WHERE "constantInput"::jsonb->>'model' = $1
+        """,
+        model.slug,
+    )
+    node_count = int(count_result[0]["count"]) if count_result else 0
+
+    return llm_model.LlmModelUsageResponse(model_slug=model.slug, node_count=node_count)
+
+
+async def delete_model(
+    model_id: str, replacement_model_slug: str
+) -> llm_model.DeleteLlmModelResponse:
+    """
+    Delete a model and migrate all AgentNodes using it to a replacement model.
+
+    This performs an atomic operation within a database transaction:
+    1. Validates the model exists
+    2. Validates the replacement model exists and is enabled
+    3. Counts affected nodes
+    4. Migrates all AgentNode.constantInput->model to replacement (in transaction)
+    5. Deletes the LlmModel record (CASCADE deletes costs) (in transaction)
+
+    Args:
+        model_id: UUID of the model to delete
+        replacement_model_slug: Slug of the model to migrate to
+
+    Returns:
+        DeleteLlmModelResponse with migration stats
+
+    Raises:
+        ValueError: If model not found, replacement not found, or replacement is disabled
+    """
+    # 1. Get the model being deleted (validation - outside transaction)
+    model = await prisma.models.LlmModel.prisma().find_unique(
+        where={"id": model_id}, include={"Costs": True}
+    )
+    if not model:
+        raise ValueError(f"Model with id '{model_id}' not found")
+
+    deleted_slug = model.slug
+    deleted_display_name = model.displayName
+
+    # 2. Validate replacement model exists and is enabled (validation - outside transaction)
+    replacement = await prisma.models.LlmModel.prisma().find_unique(
+        where={"slug": replacement_model_slug}
+    )
+    if not replacement:
+        raise ValueError(f"Replacement model '{replacement_model_slug}' not found")
+    if not replacement.isEnabled:
+        raise ValueError(
+            f"Replacement model '{replacement_model_slug}' is disabled. "
+            f"Please enable it before using it as a replacement."
+        )
+
+    # 3 & 4. Perform count, migration and deletion atomically within a transaction
+    nodes_affected = 0
+    async with transaction() as tx:
+        # Count affected nodes (inside transaction for consistency)
+        count_result = await tx.query_raw(
+            """
+            SELECT COUNT(*) as count
+            FROM "AgentNode"
+            WHERE "constantInput"::jsonb->>'model' = $1
+            """,
+            deleted_slug,
+        )
+        nodes_affected = int(count_result[0]["count"]) if count_result else 0
+
+        # Migrate all AgentNode.constantInput->model to replacement
+        if nodes_affected > 0:
+            await tx.execute_raw(
+                """
+                UPDATE "AgentNode"
+                SET "constantInput" = JSONB_SET(
+                    "constantInput"::jsonb,
+                    '{model}',
+                    to_jsonb($1::text)
+                )
+                WHERE "constantInput"::jsonb->>'model' = $2
+                """,
+                replacement_model_slug,
+                deleted_slug,
+            )
+
+        # Delete the model (CASCADE will delete costs automatically)
+        await tx.llmmodel.delete(where={"id": model_id})
+
+    return llm_model.DeleteLlmModelResponse(
+        deleted_model_slug=deleted_slug,
+        deleted_model_display_name=deleted_display_name,
+        replacement_model_slug=replacement_model_slug,
+        nodes_migrated=nodes_affected,
+        message=(
+            f"Successfully deleted model '{deleted_display_name}' ({deleted_slug}) "
+            f"and migrated {nodes_affected} workflow node(s) to '{replacement_model_slug}'."
+        ),
+    )
+
+
+def _map_migration(
+    record: prisma.models.LlmModelMigration,
+) -> llm_model.LlmModelMigration:
+    return llm_model.LlmModelMigration(
+        id=record.id,
+        source_model_slug=record.sourceModelSlug,
+        target_model_slug=record.targetModelSlug,
+        reason=record.reason,
+        node_count=record.nodeCount,
+        custom_credit_cost=record.customCreditCost,
+        is_reverted=record.isReverted,
+        created_at=record.createdAt.isoformat(),
+        reverted_at=record.revertedAt.isoformat() if record.revertedAt else None,
+    )
+
+
+async def list_migrations(
+    include_reverted: bool = False,
+) -> list[llm_model.LlmModelMigration]:
+    """
+    List model migrations, optionally including reverted ones.
+
+    Args:
+        include_reverted: If True, include reverted migrations. Default is False.
+
+    Returns:
+        List of LlmModelMigration records
+    """
+    where: Any = None if include_reverted else {"isReverted": False}
+    records = await prisma.models.LlmModelMigration.prisma().find_many(
+        where=where,
+        order={"createdAt": "desc"},
+    )
+    return [_map_migration(record) for record in records]
+
+
+async def get_migration(migration_id: str) -> llm_model.LlmModelMigration | None:
+    """Get a specific migration by ID."""
+    record = await prisma.models.LlmModelMigration.prisma().find_unique(
+        where={"id": migration_id}
+    )
+    return _map_migration(record) if record else None
+
+
+async def revert_migration(
+    migration_id: str,
+    re_enable_source_model: bool = True,
+) -> llm_model.RevertMigrationResponse:
+    """
+    Revert a model migration, restoring affected nodes to their original model.
+
+    This only reverts the specific nodes that were migrated, not all nodes
+    currently using the target model.
+
+    Args:
+        migration_id: UUID of the migration to revert
+        re_enable_source_model: Whether to re-enable the source model if it's disabled
+
+    Returns:
+        RevertMigrationResponse with revert stats
+
+    Raises:
+        ValueError: If migration not found, already reverted, or source model not available
+    """
+    import json
+    from datetime import datetime, timezone
+
+    # Get the migration record
+    migration = await prisma.models.LlmModelMigration.prisma().find_unique(
+        where={"id": migration_id}
+    )
+    if not migration:
+        raise ValueError(f"Migration with id '{migration_id}' not found")
+
+    if migration.isReverted:
+        raise ValueError(
+            f"Migration '{migration_id}' has already been reverted "
+            f"on {migration.revertedAt.isoformat() if migration.revertedAt else 'unknown date'}"
+        )
+
+    # Check if source model exists
+    source_model = await prisma.models.LlmModel.prisma().find_unique(
+        where={"slug": migration.sourceModelSlug}
+    )
+    if not source_model:
+        raise ValueError(
+            f"Source model '{migration.sourceModelSlug}' no longer exists. "
+            f"Cannot revert migration."
+        )
+
+    # Get the migrated node IDs (Prisma auto-parses JSONB to list)
+    migrated_node_ids: list[str] = (
+        migration.migratedNodeIds
+        if isinstance(migration.migratedNodeIds, list)
+        else json.loads(migration.migratedNodeIds)  # type: ignore
+    )
+    if not migrated_node_ids:
+        raise ValueError("No nodes to revert in this migration")
+
+    # Track if we need to re-enable the source model
+    source_model_was_disabled = not source_model.isEnabled
+    should_re_enable = source_model_was_disabled and re_enable_source_model
+    source_model_re_enabled = False
+
+    # Perform revert atomically
+    async with transaction() as tx:
+        # Re-enable the source model if requested and it was disabled
+        if should_re_enable:
+            await tx.llmmodel.update(
+                where={"id": source_model.id},
+                data={"isEnabled": True},
+            )
+            source_model_re_enabled = True
+
+        # Update only the specific nodes that were migrated
+        # We need to check that they still have the target model (haven't been changed since)
+        # Use a single batch update for efficiency
+        # Format node IDs as PostgreSQL text array literal for comparison
+        node_ids_pg_array = "{" + ",".join(migrated_node_ids) + "}"
+        result = await tx.execute_raw(
+            """
+            UPDATE "AgentNode"
+            SET "constantInput" = JSONB_SET(
+                "constantInput"::jsonb,
+                '{model}',
+                to_jsonb($1::text)
+            )
+            WHERE id::text = ANY($2::text[])
+            AND "constantInput"::jsonb->>'model' = $3
+            """,
+            migration.sourceModelSlug,
+            node_ids_pg_array,
+            migration.targetModelSlug,
+        )
+        nodes_reverted = result if result else 0
+
+        # Mark migration as reverted
+        await tx.llmmodelmigration.update(
+            where={"id": migration_id},
+            data={
+                "isReverted": True,
+                "revertedAt": datetime.now(timezone.utc),
+            },
+        )
+
+    # Calculate nodes that were already changed since migration
+    nodes_already_changed = len(migrated_node_ids) - nodes_reverted
+
+    # Build appropriate message
+    message_parts = [
+        f"Successfully reverted migration: {nodes_reverted} node(s) restored "
+        f"from '{migration.targetModelSlug}' to '{migration.sourceModelSlug}'."
+    ]
+    if nodes_already_changed > 0:
+        message_parts.append(
+            f" {nodes_already_changed} node(s) were already changed and not reverted."
+        )
+    if source_model_re_enabled:
+        message_parts.append(
+            f" Model '{migration.sourceModelSlug}' has been re-enabled."
+        )
+
+    return llm_model.RevertMigrationResponse(
+        migration_id=migration_id,
+        source_model_slug=migration.sourceModelSlug,
+        target_model_slug=migration.targetModelSlug,
+        nodes_reverted=nodes_reverted,
+        nodes_already_changed=nodes_already_changed,
+        source_model_re_enabled=source_model_re_enabled,
+        message="".join(message_parts),
+    )
+
+
+# ============================================================================
+# Creator CRUD operations
+# ============================================================================
+
+
+async def list_creators() -> list[llm_model.LlmModelCreator]:
+    """List all LLM model creators."""
+    records = await prisma.models.LlmModelCreator.prisma().find_many(
+        order={"displayName": "asc"}
+    )
+    return [_map_creator(record) for record in records]
+
+
+async def get_creator(creator_id: str) -> llm_model.LlmModelCreator | None:
+    """Get a specific creator by ID."""
+    record = await prisma.models.LlmModelCreator.prisma().find_unique(
+        where={"id": creator_id}
+    )
+    return _map_creator(record) if record else None
+
+
+async def upsert_creator(
+    request: llm_model.UpsertLlmCreatorRequest,
+    creator_id: str | None = None,
+) -> llm_model.LlmModelCreator:
+    """Create or update a model creator."""
+    data: Any = {
+        "name": request.name,
+        "displayName": request.display_name,
+        "description": request.description,
+        "websiteUrl": request.website_url,
+        "logoUrl": request.logo_url,
+        "metadata": request.metadata,
+    }
+    if creator_id:
+        record = await prisma.models.LlmModelCreator.prisma().update(
+            where={"id": creator_id},
+            data=data,
+        )
+    else:
+        record = await prisma.models.LlmModelCreator.prisma().create(data=data)
+    if record is None:
+        raise ValueError("Failed to create/update creator")
+    return _map_creator(record)
+
+
+async def delete_creator(creator_id: str) -> bool:
+    """
+    Delete a model creator.
+
+    This will set creatorId to NULL on all associated models (due to onDelete: SetNull).
+
+    Args:
+        creator_id: UUID of the creator to delete
+
+    Returns:
+        True if deleted successfully
+
+    Raises:
+        ValueError: If creator not found
+    """
+    creator = await prisma.models.LlmModelCreator.prisma().find_unique(
+        where={"id": creator_id}
+    )
+    if not creator:
+        raise ValueError(f"Creator with id '{creator_id}' not found")
+
+    await prisma.models.LlmModelCreator.prisma().delete(where={"id": creator_id})
+    return True
+
+
+async def get_recommended_model() -> llm_model.LlmModel | None:
+    """
+    Get the currently recommended LLM model.
+
+    Returns:
+        The recommended model, or None if no model is marked as recommended.
+    """
+    record = await prisma.models.LlmModel.prisma().find_first(
+        where={"isRecommended": True, "isEnabled": True},
+        include={"Costs": True, "Creator": True},
+    )
+    return _map_model(record) if record else None
+
+
+async def set_recommended_model(
+    model_id: str,
+) -> tuple[llm_model.LlmModel, str | None]:
+    """
+    Set a model as the recommended model.
+
+    This will clear the isRecommended flag from any other model and set it
+    on the specified model. The model must be enabled.
+
+    Args:
+        model_id: UUID of the model to set as recommended
+
+    Returns:
+        Tuple of (the updated model, previous recommended model slug or None)
+
+    Raises:
+        ValueError: If model not found or not enabled
+    """
+    # First, verify the model exists and is enabled
+    target_model = await prisma.models.LlmModel.prisma().find_unique(
+        where={"id": model_id}
+    )
+    if not target_model:
+        raise ValueError(f"Model with id '{model_id}' not found")
+    if not target_model.isEnabled:
+        raise ValueError(
+            f"Cannot set disabled model '{target_model.slug}' as recommended"
+        )
+
+    # Get the current recommended model (if any)
+    current_recommended = await prisma.models.LlmModel.prisma().find_first(
+        where={"isRecommended": True}
+    )
+    previous_slug = current_recommended.slug if current_recommended else None
+
+    # Use a transaction to ensure atomicity
+    async with transaction() as tx:
+        # Clear isRecommended from all models
+        await tx.llmmodel.update_many(
+            where={"isRecommended": True},
+            data={"isRecommended": False},
+        )
+        # Set the new recommended model
+        await tx.llmmodel.update(
+            where={"id": model_id},
+            data={"isRecommended": True},
+        )
+
+    # Fetch and return the updated model
+    updated_record = await prisma.models.LlmModel.prisma().find_unique(
+        where={"id": model_id},
+        include={"Costs": True, "Creator": True},
+    )
+    if not updated_record:
+        raise ValueError("Failed to fetch updated model")
+
+    return _map_model(updated_record), previous_slug
+
+
+async def get_recommended_model_slug() -> str | None:
+    """
+    Get the slug of the currently recommended LLM model.
+
+    Returns:
+        The slug of the recommended model, or None if no model is marked as recommended.
+    """
+    record = await prisma.models.LlmModel.prisma().find_first(
+        where={"isRecommended": True, "isEnabled": True},
+    )
+    return record.slug if record else None

autogpt_platform/backend/backend/server/v2/llm/model.py

@@ -0,0 +1,211 @@
+from __future__ import annotations
+
+from typing import Any, Optional
+
+import prisma.enums
+import pydantic
+
+
+class LlmModelCost(pydantic.BaseModel):
+    id: str
+    unit: prisma.enums.LlmCostUnit = prisma.enums.LlmCostUnit.RUN
+    credit_cost: int
+    credential_provider: str
+    credential_id: Optional[str] = None
+    credential_type: Optional[str] = None
+    currency: Optional[str] = None
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+
+
+class LlmModelCreator(pydantic.BaseModel):
+    """Represents the organization that created/trained the model (e.g., OpenAI, Meta)."""
+
+    id: str
+    name: str
+    display_name: str
+    description: Optional[str] = None
+    website_url: Optional[str] = None
+    logo_url: Optional[str] = None
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+
+
+class LlmModel(pydantic.BaseModel):
+    id: str
+    slug: str
+    display_name: str
+    description: Optional[str] = None
+    provider_id: str
+    creator_id: Optional[str] = None
+    creator: Optional[LlmModelCreator] = None
+    context_window: int
+    max_output_tokens: Optional[int] = None
+    is_enabled: bool = True
+    is_recommended: bool = False
+    capabilities: dict[str, Any] = pydantic.Field(default_factory=dict)
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+    costs: list[LlmModelCost] = pydantic.Field(default_factory=list)
+
+
+class LlmProvider(pydantic.BaseModel):
+    id: str
+    name: str
+    display_name: str
+    description: Optional[str] = None
+    default_credential_provider: Optional[str] = None
+    default_credential_id: Optional[str] = None
+    default_credential_type: Optional[str] = None
+    supports_tools: bool = True
+    supports_json_output: bool = True
+    supports_reasoning: bool = False
+    supports_parallel_tool: bool = False
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+    models: list[LlmModel] = pydantic.Field(default_factory=list)
+
+
+class LlmProvidersResponse(pydantic.BaseModel):
+    providers: list[LlmProvider]
+
+
+class LlmModelsResponse(pydantic.BaseModel):
+    models: list[LlmModel]
+
+
+class LlmCreatorsResponse(pydantic.BaseModel):
+    creators: list[LlmModelCreator]
+
+
+class UpsertLlmProviderRequest(pydantic.BaseModel):
+    name: str
+    display_name: str
+    description: Optional[str] = None
+    default_credential_provider: Optional[str] = None
+    default_credential_id: Optional[str] = None
+    default_credential_type: Optional[str] = "api_key"
+    supports_tools: bool = True
+    supports_json_output: bool = True
+    supports_reasoning: bool = False
+    supports_parallel_tool: bool = False
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+
+
+class UpsertLlmCreatorRequest(pydantic.BaseModel):
+    name: str
+    display_name: str
+    description: Optional[str] = None
+    website_url: Optional[str] = None
+    logo_url: Optional[str] = None
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+
+
+class LlmModelCostInput(pydantic.BaseModel):
+    unit: prisma.enums.LlmCostUnit = prisma.enums.LlmCostUnit.RUN
+    credit_cost: int
+    credential_provider: str
+    credential_id: Optional[str] = None
+    credential_type: Optional[str] = "api_key"
+    currency: Optional[str] = None
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+
+
+class CreateLlmModelRequest(pydantic.BaseModel):
+    slug: str
+    display_name: str
+    description: Optional[str] = None
+    provider_id: str
+    creator_id: Optional[str] = None
+    context_window: int
+    max_output_tokens: Optional[int] = None
+    is_enabled: bool = True
+    capabilities: dict[str, Any] = pydantic.Field(default_factory=dict)
+    metadata: dict[str, Any] = pydantic.Field(default_factory=dict)
+    costs: list[LlmModelCostInput]
+
+
+class UpdateLlmModelRequest(pydantic.BaseModel):
+    display_name: Optional[str] = None
+    description: Optional[str] = None
+    context_window: Optional[int] = None
+    max_output_tokens: Optional[int] = None
+    is_enabled: Optional[bool] = None
+    capabilities: Optional[dict[str, Any]] = None
+    metadata: Optional[dict[str, Any]] = None
+    provider_id: Optional[str] = None
+    creator_id: Optional[str] = None
+    costs: Optional[list[LlmModelCostInput]] = None
+
+
+class ToggleLlmModelRequest(pydantic.BaseModel):
+    is_enabled: bool
+    migrate_to_slug: Optional[str] = None
+    migration_reason: Optional[str] = None  # e.g., "Provider outage"
+    custom_credit_cost: Optional[int] = None  # Custom pricing during migration
+
+
+class ToggleLlmModelResponse(pydantic.BaseModel):
+    model: LlmModel
+    nodes_migrated: int = 0
+    migrated_to_slug: Optional[str] = None
+    migration_id: Optional[str] = None  # ID of the migration record for revert
+
+
+class DeleteLlmModelResponse(pydantic.BaseModel):
+    deleted_model_slug: str
+    deleted_model_display_name: str
+    replacement_model_slug: str
+    nodes_migrated: int
+    message: str
+
+
+class LlmModelUsageResponse(pydantic.BaseModel):
+    model_slug: str
+    node_count: int
+
+
+# Migration tracking models
+class LlmModelMigration(pydantic.BaseModel):
+    id: str
+    source_model_slug: str
+    target_model_slug: str
+    reason: Optional[str] = None
+    node_count: int
+    custom_credit_cost: Optional[int] = None
+    is_reverted: bool = False
+    created_at: str  # ISO datetime string
+    reverted_at: Optional[str] = None
+
+
+class LlmMigrationsResponse(pydantic.BaseModel):
+    migrations: list[LlmModelMigration]
+
+
+class RevertMigrationRequest(pydantic.BaseModel):
+    re_enable_source_model: bool = (
+        True  # Whether to re-enable the source model if disabled
+    )
+
+
+class RevertMigrationResponse(pydantic.BaseModel):
+    migration_id: str
+    source_model_slug: str
+    target_model_slug: str
+    nodes_reverted: int
+    nodes_already_changed: int = (
+        0  # Nodes that were modified since migration (not reverted)
+    )
+    source_model_re_enabled: bool = False  # Whether the source model was re-enabled
+    message: str
+
+
+class SetRecommendedModelRequest(pydantic.BaseModel):
+    model_id: str
+
+
+class SetRecommendedModelResponse(pydantic.BaseModel):
+    model: LlmModel
+    previous_recommended_slug: Optional[str] = None
+    message: str
+
+
+class RecommendedModelResponse(pydantic.BaseModel):
+    model: Optional[LlmModel] = None
+    slug: Optional[str] = None

autogpt_platform/backend/backend/server/v2/llm/routes.py

@@ -0,0 +1,25 @@
+import autogpt_libs.auth
+import fastapi
+
+from backend.server.v2.llm import db as llm_db
+from backend.server.v2.llm import model as llm_model
+
+router = fastapi.APIRouter(
+    prefix="/llm",
+    tags=["llm"],
+    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+)
+
+
+@router.get("/models", response_model=llm_model.LlmModelsResponse)
+async def list_models():
+    """List all enabled LLM models available to users."""
+    models = await llm_db.list_models(enabled_only=True)
+    return llm_model.LlmModelsResponse(models=models)
+
+
+@router.get("/providers", response_model=llm_model.LlmProvidersResponse)
+async def list_providers():
+    """List all LLM providers with their enabled models."""
+    providers = await llm_db.list_providers(include_models=True, enabled_only=True)
+    return llm_model.LlmProvidersResponse(providers=providers)

autogpt_platform/backend/migrations/20251126113000_add_llm_registry/migration.sql

@@ -0,0 +1,78 @@
+-- CreateEnum
+CREATE TYPE "LlmCostUnit" AS ENUM ('RUN', 'TOKENS');
+
+-- CreateTable
+CREATE TABLE "LlmProvider" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "name" TEXT NOT NULL,
+    "displayName" TEXT NOT NULL,
+    "description" TEXT,
+    "defaultCredentialProvider" TEXT,
+    "defaultCredentialId" TEXT,
+    "defaultCredentialType" TEXT,
+    "supportsTools" BOOLEAN NOT NULL DEFAULT TRUE,
+    "supportsJsonOutput" BOOLEAN NOT NULL DEFAULT TRUE,
+    "supportsReasoning" BOOLEAN NOT NULL DEFAULT FALSE,
+    "supportsParallelTool" BOOLEAN NOT NULL DEFAULT FALSE,
+    "metadata" JSONB NOT NULL DEFAULT '{}'::jsonb,
+
+    CONSTRAINT "LlmProvider_pkey" PRIMARY KEY ("id"),
+    CONSTRAINT "LlmProvider_name_key" UNIQUE ("name")
+);
+
+-- CreateTable
+CREATE TABLE "LlmModel" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "slug" TEXT NOT NULL,
+    "displayName" TEXT NOT NULL,
+    "description" TEXT,
+    "providerId" TEXT NOT NULL,
+    "contextWindow" INTEGER NOT NULL,
+    "maxOutputTokens" INTEGER,
+    "isEnabled" BOOLEAN NOT NULL DEFAULT TRUE,
+    "capabilities" JSONB NOT NULL DEFAULT '{}'::jsonb,
+    "metadata" JSONB NOT NULL DEFAULT '{}'::jsonb,
+
+    CONSTRAINT "LlmModel_pkey" PRIMARY KEY ("id"),
+    CONSTRAINT "LlmModel_slug_key" UNIQUE ("slug")
+);
+
+-- CreateTable
+CREATE TABLE "LlmModelCost" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "unit" "LlmCostUnit" NOT NULL DEFAULT 'RUN',
+    "creditCost" INTEGER NOT NULL,
+    "credentialProvider" TEXT NOT NULL,
+    "credentialId" TEXT,
+    "credentialType" TEXT,
+    "currency" TEXT,
+    "metadata" JSONB NOT NULL DEFAULT '{}'::jsonb,
+    "llmModelId" TEXT NOT NULL,
+
+    CONSTRAINT "LlmModelCost_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateIndex
+CREATE INDEX "LlmModel_providerId_isEnabled_idx" ON "LlmModel"("providerId", "isEnabled");
+
+-- CreateIndex
+CREATE INDEX "LlmModel_slug_idx" ON "LlmModel"("slug");
+
+-- CreateIndex
+CREATE INDEX "LlmModelCost_llmModelId_idx" ON "LlmModelCost"("llmModelId");
+
+-- CreateIndex
+CREATE INDEX "LlmModelCost_credentialProvider_idx" ON "LlmModelCost"("credentialProvider");
+
+-- AddForeignKey
+ALTER TABLE "LlmModel" ADD CONSTRAINT "LlmModel_providerId_fkey" FOREIGN KEY ("providerId") REFERENCES "LlmProvider"("id") ON DELETE RESTRICT ON UPDATE CASCADE;
+
+-- AddForeignKey
+ALTER TABLE "LlmModelCost" ADD CONSTRAINT "LlmModelCost_llmModelId_fkey" FOREIGN KEY ("llmModelId") REFERENCES "LlmModel"("id") ON DELETE CASCADE ON UPDATE CASCADE;
+

autogpt_platform/backend/migrations/20251126120000_seed_llm_registry/migration.sql

@@ -0,0 +1,225 @@
+-- Seed LLM Registry from existing hard-coded data
+-- This migration populates the LlmProvider, LlmModel, and LlmModelCost tables
+-- with data from the existing MODEL_METADATA and MODEL_COST dictionaries
+
+-- Insert Providers
+INSERT INTO "LlmProvider" ("id", "name", "displayName", "description", "defaultCredentialProvider", "defaultCredentialType", "supportsTools", "supportsJsonOutput", "supportsReasoning", "supportsParallelTool", "metadata")
+VALUES
+    (gen_random_uuid(), 'openai', 'OpenAI', 'OpenAI language models', 'openai', 'api_key', true, true, true, true, '{}'::jsonb),
+    (gen_random_uuid(), 'anthropic', 'Anthropic', 'Anthropic Claude models', 'anthropic', 'api_key', true, true, true, false, '{}'::jsonb),
+    (gen_random_uuid(), 'groq', 'Groq', 'Groq inference API', 'groq', 'api_key', false, true, false, false, '{}'::jsonb),
+    (gen_random_uuid(), 'open_router', 'OpenRouter', 'OpenRouter unified API', 'open_router', 'api_key', true, true, false, false, '{}'::jsonb),
+    (gen_random_uuid(), 'aiml_api', 'AI/ML API', 'AI/ML API models', 'aiml_api', 'api_key', false, true, false, false, '{}'::jsonb),
+    (gen_random_uuid(), 'ollama', 'Ollama', 'Ollama local models', 'ollama', 'api_key', false, true, false, false, '{}'::jsonb),
+    (gen_random_uuid(), 'llama_api', 'Llama API', 'Llama API models', 'llama_api', 'api_key', false, true, false, false, '{}'::jsonb),
+    (gen_random_uuid(), 'v0', 'v0', 'v0 by Vercel models', 'v0', 'api_key', true, true, false, false, '{}'::jsonb)
+ON CONFLICT ("name") DO NOTHING;
+
+-- Insert Models (using CTEs to reference provider IDs)
+WITH provider_ids AS (
+    SELECT "id", "name" FROM "LlmProvider"
+)
+INSERT INTO "LlmModel" ("id", "slug", "displayName", "description", "providerId", "contextWindow", "maxOutputTokens", "isEnabled", "capabilities", "metadata")
+SELECT
+    gen_random_uuid(),
+    model_slug,
+    model_display_name,
+    NULL,
+    p."id",
+    context_window,
+    max_output_tokens,
+    true,
+    '{}'::jsonb,
+    '{}'::jsonb
+FROM (VALUES
+    -- OpenAI models
+    ('o3', 'O3', 'openai', 200000, 100000),
+    ('o3-mini', 'O3 Mini', 'openai', 200000, 100000),
+    ('o1', 'O1', 'openai', 200000, 100000),
+    ('o1-mini', 'O1 Mini', 'openai', 128000, 65536),
+    ('gpt-5-2025-08-07', 'GPT 5', 'openai', 400000, 128000),
+    ('gpt-5.1-2025-11-13', 'GPT 5.1', 'openai', 400000, 128000),
+    ('gpt-5-mini-2025-08-07', 'GPT 5 Mini', 'openai', 400000, 128000),
+    ('gpt-5-nano-2025-08-07', 'GPT 5 Nano', 'openai', 400000, 128000),
+    ('gpt-5-chat-latest', 'GPT 5 Chat', 'openai', 400000, 16384),
+    ('gpt-4.1-2025-04-14', 'GPT 4.1', 'openai', 1047576, 32768),
+    ('gpt-4.1-mini-2025-04-14', 'GPT 4.1 Mini', 'openai', 1047576, 32768),
+    ('gpt-4o-mini', 'GPT 4o Mini', 'openai', 128000, 16384),
+    ('gpt-4o', 'GPT 4o', 'openai', 128000, 16384),
+    ('gpt-4-turbo', 'GPT 4 Turbo', 'openai', 128000, 4096),
+    ('gpt-3.5-turbo', 'GPT 3.5 Turbo', 'openai', 16385, 4096),
+    -- Anthropic models
+    ('claude-opus-4-1-20250805', 'Claude 4.1 Opus', 'anthropic', 200000, 32000),
+    ('claude-opus-4-20250514', 'Claude 4 Opus', 'anthropic', 200000, 32000),
+    ('claude-sonnet-4-20250514', 'Claude 4 Sonnet', 'anthropic', 200000, 64000),
+    ('claude-opus-4-5-20251101', 'Claude 4.5 Opus', 'anthropic', 200000, 64000),
+    ('claude-sonnet-4-5-20250929', 'Claude 4.5 Sonnet', 'anthropic', 200000, 64000),
+    ('claude-haiku-4-5-20251001', 'Claude 4.5 Haiku', 'anthropic', 200000, 64000),
+    ('claude-3-7-sonnet-20250219', 'Claude 3.7 Sonnet', 'anthropic', 200000, 64000),
+    ('claude-3-haiku-20240307', 'Claude 3 Haiku', 'anthropic', 200000, 4096),
+    -- AI/ML API models
+    ('Qwen/Qwen2.5-72B-Instruct-Turbo', 'Qwen 2.5 72B', 'aiml_api', 32000, 8000),
+    ('nvidia/llama-3.1-nemotron-70b-instruct', 'Llama 3.1 Nemotron 70B', 'aiml_api', 128000, 40000),
+    ('meta-llama/Llama-3.3-70B-Instruct-Turbo', 'Llama 3.3 70B', 'aiml_api', 128000, NULL),
+    ('meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo', 'Meta Llama 3.1 70B', 'aiml_api', 131000, 2000),
+    ('meta-llama/Llama-3.2-3B-Instruct-Turbo', 'Llama 3.2 3B', 'aiml_api', 128000, NULL),
+    -- Groq models
+    ('llama-3.3-70b-versatile', 'Llama 3.3 70B', 'groq', 128000, 32768),
+    ('llama-3.1-8b-instant', 'Llama 3.1 8B', 'groq', 128000, 8192),
+    -- Ollama models
+    ('llama3.3', 'Llama 3.3', 'ollama', 8192, NULL),
+    ('llama3.2', 'Llama 3.2', 'ollama', 8192, NULL),
+    ('llama3', 'Llama 3', 'ollama', 8192, NULL),
+    ('llama3.1:405b', 'Llama 3.1 405B', 'ollama', 8192, NULL),
+    ('dolphin-mistral:latest', 'Dolphin Mistral', 'ollama', 32768, NULL),
+    -- OpenRouter models
+    ('google/gemini-2.5-pro-preview-03-25', 'Gemini 2.5 Pro', 'open_router', 1050000, 8192),
+    ('google/gemini-3-pro-preview', 'Gemini 3 Pro Preview', 'open_router', 1048576, 65535),
+    ('google/gemini-2.5-flash', 'Gemini 2.5 Flash', 'open_router', 1048576, 65535),
+    ('google/gemini-2.0-flash-001', 'Gemini 2.0 Flash', 'open_router', 1048576, 8192),
+    ('google/gemini-2.5-flash-lite-preview-06-17', 'Gemini 2.5 Flash Lite Preview', 'open_router', 1048576, 65535),
+    ('google/gemini-2.0-flash-lite-001', 'Gemini 2.0 Flash Lite', 'open_router', 1048576, 8192),
+    ('mistralai/mistral-nemo', 'Mistral Nemo', 'open_router', 128000, 4096),
+    ('cohere/command-r-08-2024', 'Command R', 'open_router', 128000, 4096),
+    ('cohere/command-r-plus-08-2024', 'Command R Plus', 'open_router', 128000, 4096),
+    ('deepseek/deepseek-chat', 'DeepSeek Chat', 'open_router', 64000, 2048),
+    ('deepseek/deepseek-r1-0528', 'DeepSeek R1', 'open_router', 163840, 163840),
+    ('perplexity/sonar', 'Perplexity Sonar', 'open_router', 127000, 8000),
+    ('perplexity/sonar-pro', 'Perplexity Sonar Pro', 'open_router', 200000, 8000),
+    ('perplexity/sonar-deep-research', 'Perplexity Sonar Deep Research', 'open_router', 128000, 16000),
+    ('nousresearch/hermes-3-llama-3.1-405b', 'Hermes 3 Llama 3.1 405B', 'open_router', 131000, 4096),
+    ('nousresearch/hermes-3-llama-3.1-70b', 'Hermes 3 Llama 3.1 70B', 'open_router', 12288, 12288),
+    ('openai/gpt-oss-120b', 'GPT OSS 120B', 'open_router', 131072, 131072),
+    ('openai/gpt-oss-20b', 'GPT OSS 20B', 'open_router', 131072, 32768),
+    ('amazon/nova-lite-v1', 'Amazon Nova Lite', 'open_router', 300000, 5120),
+    ('amazon/nova-micro-v1', 'Amazon Nova Micro', 'open_router', 128000, 5120),
+    ('amazon/nova-pro-v1', 'Amazon Nova Pro', 'open_router', 300000, 5120),
+    ('microsoft/wizardlm-2-8x22b', 'WizardLM 2 8x22B', 'open_router', 65536, 4096),
+    ('gryphe/mythomax-l2-13b', 'MythoMax L2 13B', 'open_router', 4096, 4096),
+    ('meta-llama/llama-4-scout', 'Llama 4 Scout', 'open_router', 131072, 131072),
+    ('meta-llama/llama-4-maverick', 'Llama 4 Maverick', 'open_router', 1048576, 1000000),
+    ('x-ai/grok-4', 'Grok 4', 'open_router', 256000, 256000),
+    ('x-ai/grok-4-fast', 'Grok 4 Fast', 'open_router', 2000000, 30000),
+    ('x-ai/grok-4.1-fast', 'Grok 4.1 Fast', 'open_router', 2000000, 30000),
+    ('x-ai/grok-code-fast-1', 'Grok Code Fast 1', 'open_router', 256000, 10000),
+    ('moonshotai/kimi-k2', 'Kimi K2', 'open_router', 131000, 131000),
+    ('qwen/qwen3-235b-a22b-thinking-2507', 'Qwen 3 235B Thinking', 'open_router', 262144, 262144),
+    ('qwen/qwen3-coder', 'Qwen 3 Coder', 'open_router', 262144, 262144),
+    -- Llama API models
+    ('Llama-4-Scout-17B-16E-Instruct-FP8', 'Llama 4 Scout', 'llama_api', 128000, 4028),
+    ('Llama-4-Maverick-17B-128E-Instruct-FP8', 'Llama 4 Maverick', 'llama_api', 128000, 4028),
+    ('Llama-3.3-8B-Instruct', 'Llama 3.3 8B', 'llama_api', 128000, 4028),
+    ('Llama-3.3-70B-Instruct', 'Llama 3.3 70B', 'llama_api', 128000, 4028),
+    -- v0 models
+    ('v0-1.5-md', 'v0 1.5 MD', 'v0', 128000, 64000),
+    ('v0-1.5-lg', 'v0 1.5 LG', 'v0', 512000, 64000),
+    ('v0-1.0-md', 'v0 1.0 MD', 'v0', 128000, 64000)
+) AS models(model_slug, model_display_name, provider_name, context_window, max_output_tokens)
+JOIN provider_ids p ON p."name" = models.provider_name
+ON CONFLICT ("slug") DO NOTHING;
+
+-- Insert Costs (using CTEs to reference model IDs)
+WITH model_ids AS (
+    SELECT "id", "slug", "providerId" FROM "LlmModel"
+),
+provider_ids AS (
+    SELECT "id", "name" FROM "LlmProvider"
+)
+INSERT INTO "LlmModelCost" ("id", "unit", "creditCost", "credentialProvider", "credentialId", "credentialType", "currency", "metadata", "llmModelId")
+SELECT
+    gen_random_uuid(),
+    'RUN'::"LlmCostUnit",
+    cost,
+    p."name",
+    NULL,
+    'api_key',
+    NULL,
+    '{}'::jsonb,
+    m."id"
+FROM (VALUES
+    -- OpenAI costs
+    ('o3', 4),
+    ('o3-mini', 2),
+    ('o1', 16),
+    ('o1-mini', 4),
+    ('gpt-5-2025-08-07', 2),
+    ('gpt-5.1-2025-11-13', 5),
+    ('gpt-5-mini-2025-08-07', 1),
+    ('gpt-5-nano-2025-08-07', 1),
+    ('gpt-5-chat-latest', 5),
+    ('gpt-4.1-2025-04-14', 2),
+    ('gpt-4.1-mini-2025-04-14', 1),
+    ('gpt-4o-mini', 1),
+    ('gpt-4o', 3),
+    ('gpt-4-turbo', 10),
+    ('gpt-3.5-turbo', 1),
+    -- Anthropic costs
+    ('claude-opus-4-1-20250805', 21),
+    ('claude-opus-4-20250514', 21),
+    ('claude-sonnet-4-20250514', 5),
+    ('claude-haiku-4-5-20251001', 4),
+    ('claude-opus-4-5-20251101', 14),
+    ('claude-sonnet-4-5-20250929', 9),
+    ('claude-3-7-sonnet-20250219', 5),
+    ('claude-3-haiku-20240307', 1),
+    -- AI/ML API costs
+    ('Qwen/Qwen2.5-72B-Instruct-Turbo', 1),
+    ('nvidia/llama-3.1-nemotron-70b-instruct', 1),
+    ('meta-llama/Llama-3.3-70B-Instruct-Turbo', 1),
+    ('meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo', 1),
+    ('meta-llama/Llama-3.2-3B-Instruct-Turbo', 1),
+    -- Groq costs
+    ('llama-3.3-70b-versatile', 1),
+    ('llama-3.1-8b-instant', 1),
+    -- Ollama costs
+    ('llama3.3', 1),
+    ('llama3.2', 1),
+    ('llama3', 1),
+    ('llama3.1:405b', 1),
+    ('dolphin-mistral:latest', 1),
+    -- OpenRouter costs
+    ('google/gemini-2.5-pro-preview-03-25', 4),
+    ('google/gemini-3-pro-preview', 5),
+    ('mistralai/mistral-nemo', 1),
+    ('cohere/command-r-08-2024', 1),
+    ('cohere/command-r-plus-08-2024', 3),
+    ('deepseek/deepseek-chat', 2),
+    ('perplexity/sonar', 1),
+    ('perplexity/sonar-pro', 5),
+    ('perplexity/sonar-deep-research', 10),
+    ('nousresearch/hermes-3-llama-3.1-405b', 1),
+    ('nousresearch/hermes-3-llama-3.1-70b', 1),
+    ('amazon/nova-lite-v1', 1),
+    ('amazon/nova-micro-v1', 1),
+    ('amazon/nova-pro-v1', 1),
+    ('microsoft/wizardlm-2-8x22b', 1),
+    ('gryphe/mythomax-l2-13b', 1),
+    ('meta-llama/llama-4-scout', 1),
+    ('meta-llama/llama-4-maverick', 1),
+    ('x-ai/grok-4', 9),
+    ('x-ai/grok-4-fast', 1),
+    ('x-ai/grok-4.1-fast', 1),
+    ('x-ai/grok-code-fast-1', 1),
+    ('moonshotai/kimi-k2', 1),
+    ('qwen/qwen3-235b-a22b-thinking-2507', 1),
+    ('qwen/qwen3-coder', 9),
+    ('google/gemini-2.5-flash', 1),
+    ('google/gemini-2.0-flash-001', 1),
+    ('google/gemini-2.5-flash-lite-preview-06-17', 1),
+    ('google/gemini-2.0-flash-lite-001', 1),
+    ('deepseek/deepseek-r1-0528', 1),
+    ('openai/gpt-oss-120b', 1),
+    ('openai/gpt-oss-20b', 1),
+    -- Llama API costs
+    ('Llama-4-Scout-17B-16E-Instruct-FP8', 1),
+    ('Llama-4-Maverick-17B-128E-Instruct-FP8', 1),
+    ('Llama-3.3-8B-Instruct', 1),
+    ('Llama-3.3-70B-Instruct', 1),
+    -- v0 costs
+    ('v0-1.5-md', 1),
+    ('v0-1.5-lg', 2),
+    ('v0-1.0-md', 1)
+) AS costs(model_slug, cost)
+JOIN model_ids m ON m."slug" = costs.model_slug
+JOIN provider_ids p ON p."id" = m."providerId";
+

autogpt_platform/backend/migrations/20251218100000_add_llm_model_migration/migration.sql

@@ -0,0 +1,25 @@
+-- CreateTable
+CREATE TABLE "LlmModelMigration" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL,
+    "sourceModelSlug" TEXT NOT NULL,
+    "targetModelSlug" TEXT NOT NULL,
+    "reason" TEXT,
+    "migratedNodeIds" JSONB NOT NULL DEFAULT '[]',
+    "nodeCount" INTEGER NOT NULL,
+    "customCreditCost" INTEGER,
+    "isReverted" BOOLEAN NOT NULL DEFAULT false,
+    "revertedAt" TIMESTAMP(3),
+
+    CONSTRAINT "LlmModelMigration_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateIndex
+CREATE INDEX "LlmModelMigration_sourceModelSlug_idx" ON "LlmModelMigration"("sourceModelSlug");
+
+-- CreateIndex
+CREATE INDEX "LlmModelMigration_targetModelSlug_idx" ON "LlmModelMigration"("targetModelSlug");
+
+-- CreateIndex
+CREATE INDEX "LlmModelMigration_isReverted_idx" ON "LlmModelMigration"("isReverted");

autogpt_platform/backend/migrations/20251224100000_add_llm_model_creator/migration.sql

@@ -0,0 +1,127 @@
+-- Add LlmModelCreator table
+-- Creator represents who made/trained the model (e.g., OpenAI, Meta)
+-- This is distinct from Provider who hosts/serves the model (e.g., OpenRouter)
+
+-- Create the LlmModelCreator table
+CREATE TABLE "LlmModelCreator" (
+    "id" TEXT NOT NULL,
+    "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updatedAt" TIMESTAMP(3) NOT NULL,
+    "name" TEXT NOT NULL,
+    "displayName" TEXT NOT NULL,
+    "description" TEXT,
+    "websiteUrl" TEXT,
+    "logoUrl" TEXT,
+    "metadata" JSONB NOT NULL DEFAULT '{}',
+
+    CONSTRAINT "LlmModelCreator_pkey" PRIMARY KEY ("id")
+);
+
+-- Create unique index on name
+CREATE UNIQUE INDEX "LlmModelCreator_name_key" ON "LlmModelCreator"("name");
+
+-- Add creatorId column to LlmModel
+ALTER TABLE "LlmModel" ADD COLUMN "creatorId" TEXT;
+
+-- Add foreign key constraint
+ALTER TABLE "LlmModel" ADD CONSTRAINT "LlmModel_creatorId_fkey"
+    FOREIGN KEY ("creatorId") REFERENCES "LlmModelCreator"("id") ON DELETE SET NULL ON UPDATE CASCADE;
+
+-- Create index on creatorId
+CREATE INDEX "LlmModel_creatorId_idx" ON "LlmModel"("creatorId");
+
+-- Seed creators based on known model creators
+INSERT INTO "LlmModelCreator" ("id", "updatedAt", "name", "displayName", "description", "websiteUrl", "metadata")
+VALUES
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'openai', 'OpenAI', 'Creator of GPT models', 'https://openai.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'anthropic', 'Anthropic', 'Creator of Claude models', 'https://anthropic.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'meta', 'Meta', 'Creator of Llama models', 'https://ai.meta.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'google', 'Google', 'Creator of Gemini models', 'https://deepmind.google', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'mistral', 'Mistral AI', 'Creator of Mistral models', 'https://mistral.ai', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'cohere', 'Cohere', 'Creator of Command models', 'https://cohere.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'deepseek', 'DeepSeek', 'Creator of DeepSeek models', 'https://deepseek.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'perplexity', 'Perplexity AI', 'Creator of Sonar models', 'https://perplexity.ai', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'qwen', 'Qwen (Alibaba)', 'Creator of Qwen models', 'https://qwenlm.github.io', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'xai', 'xAI', 'Creator of Grok models', 'https://x.ai', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'amazon', 'Amazon', 'Creator of Nova models', 'https://aws.amazon.com/bedrock', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'microsoft', 'Microsoft', 'Creator of WizardLM models', 'https://microsoft.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'moonshot', 'Moonshot AI', 'Creator of Kimi models', 'https://moonshot.cn', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'nvidia', 'NVIDIA', 'Creator of Nemotron models', 'https://nvidia.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'nous_research', 'Nous Research', 'Creator of Hermes models', 'https://nousresearch.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'vercel', 'Vercel', 'Creator of v0 models', 'https://vercel.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'cognitive_computations', 'Cognitive Computations', 'Creator of Dolphin models', 'https://erichartford.com', '{}'),
+    (gen_random_uuid(), CURRENT_TIMESTAMP, 'gryphe', 'Gryphe', 'Creator of MythoMax models', 'https://huggingface.co/Gryphe', '{}')
+ON CONFLICT ("name") DO NOTHING;
+
+-- Update existing models with their creators
+-- OpenAI models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'openai')
+WHERE "slug" LIKE 'gpt-%' OR "slug" LIKE 'o1%' OR "slug" LIKE 'o3%' OR "slug" LIKE 'openai/%';
+
+-- Anthropic models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'anthropic')
+WHERE "slug" LIKE 'claude-%';
+
+-- Meta/Llama models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'meta')
+WHERE "slug" LIKE 'llama%' OR "slug" LIKE 'Llama%' OR "slug" LIKE 'meta-llama/%' OR "slug" LIKE '%/llama-%';
+
+-- Google models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'google')
+WHERE "slug" LIKE 'google/%' OR "slug" LIKE 'gemini%';
+
+-- Mistral models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'mistral')
+WHERE "slug" LIKE 'mistral%' OR "slug" LIKE 'mistralai/%';
+
+-- Cohere models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'cohere')
+WHERE "slug" LIKE 'cohere/%' OR "slug" LIKE 'command-%';
+
+-- DeepSeek models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'deepseek')
+WHERE "slug" LIKE 'deepseek/%' OR "slug" LIKE 'deepseek-%';
+
+-- Perplexity models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'perplexity')
+WHERE "slug" LIKE 'perplexity/%' OR "slug" LIKE 'sonar%';
+
+-- Qwen models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'qwen')
+WHERE "slug" LIKE 'Qwen/%' OR "slug" LIKE 'qwen/%';
+
+-- xAI/Grok models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'xai')
+WHERE "slug" LIKE 'x-ai/%' OR "slug" LIKE 'grok%';
+
+-- Amazon models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'amazon')
+WHERE "slug" LIKE 'amazon/%' OR "slug" LIKE 'nova-%';
+
+-- Microsoft models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'microsoft')
+WHERE "slug" LIKE 'microsoft/%' OR "slug" LIKE 'wizardlm%';
+
+-- Moonshot models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'moonshot')
+WHERE "slug" LIKE 'moonshotai/%' OR "slug" LIKE 'kimi%';
+
+-- NVIDIA models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'nvidia')
+WHERE "slug" LIKE 'nvidia/%' OR "slug" LIKE '%nemotron%';
+
+-- Nous Research models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'nous_research')
+WHERE "slug" LIKE 'nousresearch/%' OR "slug" LIKE 'hermes%';
+
+-- Vercel/v0 models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'vercel')
+WHERE "slug" LIKE 'v0-%';
+
+-- Dolphin models (Cognitive Computations / Eric Hartford)
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'cognitive_computations')
+WHERE "slug" LIKE 'dolphin-%';
+
+-- Gryphe models
+UPDATE "LlmModel" SET "creatorId" = (SELECT "id" FROM "LlmModelCreator" WHERE "name" = 'gryphe')
+WHERE "slug" LIKE 'gryphe/%' OR "slug" LIKE 'mythomax%';

autogpt_platform/backend/migrations/20260105120000_add_agent_node_model_index/migration.sql

@@ -0,0 +1,4 @@
+-- CreateIndex
+-- Index for efficient LLM model lookups on AgentNode.constantInput->>'model'
+-- This improves performance of model migration queries in the LLM registry
+CREATE INDEX "AgentNode_constantInput_model_idx" ON "AgentNode" ((("constantInput"->>'model')));

autogpt_platform/backend/migrations/20260106150000_add_gpt52_model/migration.sql

@@ -0,0 +1,52 @@
+-- Add GPT-5.2 model and update O3 slug
+-- This migration adds the new GPT-5.2 model added in dev branch
+
+-- Update O3 slug to match dev branch format
+UPDATE "LlmModel"
+SET "slug" = 'o3-2025-04-16'
+WHERE "slug" = 'o3';
+
+-- Update cost reference for O3 if needed
+-- (costs are linked by model ID, so no update needed)
+
+-- Add GPT-5.2 model
+WITH provider_id AS (
+    SELECT "id" FROM "LlmProvider" WHERE "name" = 'openai'
+)
+INSERT INTO "LlmModel" ("id", "slug", "displayName", "description", "providerId", "contextWindow", "maxOutputTokens", "isEnabled", "capabilities", "metadata")
+SELECT
+    gen_random_uuid(),
+    'gpt-5.2-2025-12-11',
+    'GPT 5.2',
+    'OpenAI GPT-5.2 model',
+    p."id",
+    400000,
+    128000,
+    true,
+    '{}'::jsonb,
+    '{}'::jsonb
+FROM provider_id p
+ON CONFLICT ("slug") DO NOTHING;
+
+-- Add cost for GPT-5.2
+WITH model_id AS (
+    SELECT m."id", p."name" as provider_name
+    FROM "LlmModel" m
+    JOIN "LlmProvider" p ON p."id" = m."providerId"
+    WHERE m."slug" = 'gpt-5.2-2025-12-11'
+)
+INSERT INTO "LlmModelCost" ("id", "unit", "creditCost", "credentialProvider", "credentialId", "credentialType", "currency", "metadata", "llmModelId")
+SELECT
+    gen_random_uuid(),
+    'RUN'::"LlmCostUnit",
+    3,  -- Same cost tier as GPT-5.1
+    m.provider_name,
+    NULL,
+    'api_key',
+    NULL,
+    '{}'::jsonb,
+    m."id"
+FROM model_id m
+WHERE NOT EXISTS (
+    SELECT 1 FROM "LlmModelCost" c WHERE c."llmModelId" = m."id"
+);

autogpt_platform/backend/migrations/20260107100000_add_llm_recommended_model/migration.sql

@@ -0,0 +1,11 @@
+-- Add isRecommended field to LlmModel table
+-- This allows admins to mark a model as the recommended default
+
+ALTER TABLE "LlmModel" ADD COLUMN "isRecommended" BOOLEAN NOT NULL DEFAULT false;
+
+-- Set gpt-4o-mini as the default recommended model (if it exists)
+UPDATE "LlmModel" SET "isRecommended" = true WHERE "slug" = 'gpt-4o-mini' AND "isEnabled" = true;
+
+-- Create unique partial index to enforce only one recommended model at the database level
+-- This prevents multiple rows from having isRecommended = true
+CREATE UNIQUE INDEX "LlmModel_single_recommended_idx" ON "LlmModel" ("isRecommended") WHERE "isRecommended" = true;

autogpt_platform/backend/schema.prisma

@@ -987,6 +987,138 @@ enum APIKeyStatus {
 
 ////////////////////////////////////////////////////////////
 ////////////////////////////////////////////////////////////
+/////////////   LLM REGISTRY AND BILLING DATA   /////////////
+////////////////////////////////////////////////////////////
+////////////////////////////////////////////////////////////
+
+enum LlmCostUnit {
+  RUN
+  TOKENS
+}
+
+model LlmModelCreator {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  name        String  @unique // e.g., "openai", "anthropic", "meta"
+  displayName String // e.g., "OpenAI", "Anthropic", "Meta"
+  description String?
+  websiteUrl  String? // Link to creator's website
+  logoUrl     String? // URL to creator's logo
+
+  metadata Json @default("{}")
+
+  Models LlmModel[]
+}
+
+model LlmProvider {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  name        String @unique
+  displayName String
+  description String?
+
+  defaultCredentialProvider String?
+  defaultCredentialId       String?
+  defaultCredentialType     String?
+
+  supportsTools        Boolean @default(true)
+  supportsJsonOutput   Boolean @default(true)
+  supportsReasoning    Boolean @default(false)
+  supportsParallelTool Boolean @default(false)
+
+  metadata Json @default("{}")
+
+  Models LlmModel[]
+}
+
+model LlmModel {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  slug        String @unique
+  displayName String
+  description String?
+
+  providerId String
+  Provider   LlmProvider @relation(fields: [providerId], references: [id], onDelete: Restrict)
+
+  // Creator is the organization that created/trained the model (e.g., OpenAI, Meta)
+  // This is distinct from the provider who hosts/serves the model (e.g., OpenRouter)
+  creatorId String?
+  Creator   LlmModelCreator? @relation(fields: [creatorId], references: [id], onDelete: SetNull)
+
+  contextWindow   Int
+  maxOutputTokens Int?
+  isEnabled       Boolean @default(true)
+  isRecommended   Boolean @default(false)
+
+  capabilities Json @default("{}")
+  metadata     Json @default("{}")
+
+  Costs LlmModelCost[]
+
+  @@index([providerId, isEnabled])
+  @@index([creatorId])
+  @@index([slug])
+}
+
+model LlmModelCost {
+  id        String     @id @default(uuid())
+  createdAt DateTime   @default(now())
+  updatedAt DateTime   @updatedAt
+  unit      LlmCostUnit @default(RUN)
+
+  creditCost Int
+
+  credentialProvider String
+  credentialId       String?
+  credentialType     String?
+  currency           String?
+
+  metadata Json @default("{}")
+
+  llmModelId String
+  Model      LlmModel @relation(fields: [llmModelId], references: [id], onDelete: Cascade)
+
+  @@index([llmModelId])
+  @@index([credentialProvider])
+}
+
+// Tracks model migrations for revert capability
+// When a model is disabled with migration, we record which nodes were affected
+// so they can be reverted when the original model is back online
+model LlmModelMigration {
+  id        String   @id @default(uuid())
+  createdAt DateTime @default(now())
+  updatedAt DateTime @updatedAt
+
+  sourceModelSlug String // The original model that was disabled
+  targetModelSlug String // The model workflows were migrated to
+  reason          String? // Why the migration happened (e.g., "Provider outage")
+
+  // Track affected nodes as JSON array of node IDs
+  // Format: ["node-uuid-1", "node-uuid-2", ...]
+  migratedNodeIds Json @default("[]")
+  nodeCount       Int // Number of nodes migrated
+
+  // Optional custom pricing during the migration period
+  // If set, this cost should be applied instead of the target model's cost
+  // Note: Requires billing system integration to fully work
+  customCreditCost Int?
+
+  // Revert tracking
+  isReverted Boolean   @default(false)
+  revertedAt DateTime?
+
+  @@index([sourceModelSlug])
+  @@index([targetModelSlug])
+  @@index([isReverted])
+}
 //////////////   OAUTH PROVIDER TABLES    //////////////////
 ////////////////////////////////////////////////////////////
 ////////////////////////////////////////////////////////////

autogpt_platform/frontend/src/app/(platform)/admin/layout.tsx

@@ -1,5 +1,8 @@
+"use client";
+
 import { Sidebar } from "@/components/__legacy__/Sidebar";
 import { Users, DollarSign, UserSearch, FileText } from "lucide-react";
+import { Cpu } from "@phosphor-icons/react";
 
 import { IconSliders } from "@/components/__legacy__/ui/icons";
 
@@ -26,6 +29,11 @@ const sidebarLinkGroups = [
         href: "/admin/execution-analytics",
         icon: <FileText className="h-6 w-6" />,
       },
+      {
+        text: "LLM Registry",
+        href: "/admin/llms",
+        icon: <Cpu size={24} />,
+      },
       {
         text: "Admin User Management",
         href: "/admin/settings",

autogpt_platform/frontend/src/app/(platform)/admin/llms/actions.ts

@@ -0,0 +1,357 @@
+"use server";
+
+import { revalidatePath } from "next/cache";
+
+// Generated API functions
+import {
+  getV2ListLlmProviders,
+  postV2CreateLlmProvider,
+  getV2ListLlmModels,
+  postV2CreateLlmModel,
+  patchV2UpdateLlmModel,
+  patchV2ToggleLlmModelAvailability,
+  deleteV2DeleteLlmModelAndMigrateWorkflows,
+  getV2GetModelUsageCount,
+  getV2ListModelMigrations,
+  postV2RevertAModelMigration,
+  getV2ListModelCreators,
+  postV2CreateModelCreator,
+  patchV2UpdateModelCreator,
+  deleteV2DeleteModelCreator,
+  postV2SetRecommendedModel,
+} from "@/app/api/__generated__/endpoints/admin/admin";
+
+// Generated types
+import type { LlmProvidersResponse } from "@/app/api/__generated__/models/llmProvidersResponse";
+import type { LlmModelsResponse } from "@/app/api/__generated__/models/llmModelsResponse";
+import type { UpsertLlmProviderRequest } from "@/app/api/__generated__/models/upsertLlmProviderRequest";
+import type { CreateLlmModelRequest } from "@/app/api/__generated__/models/createLlmModelRequest";
+import type { UpdateLlmModelRequest } from "@/app/api/__generated__/models/updateLlmModelRequest";
+import type { ToggleLlmModelRequest } from "@/app/api/__generated__/models/toggleLlmModelRequest";
+import type { LlmMigrationsResponse } from "@/app/api/__generated__/models/llmMigrationsResponse";
+import type { LlmCreatorsResponse } from "@/app/api/__generated__/models/llmCreatorsResponse";
+import type { UpsertLlmCreatorRequest } from "@/app/api/__generated__/models/upsertLlmCreatorRequest";
+import type { LlmModelUsageResponse } from "@/app/api/__generated__/models/llmModelUsageResponse";
+
+const ADMIN_LLM_PATH = "/admin/llms";
+
+// =============================================================================
+// Provider Actions
+// =============================================================================
+
+export async function fetchLlmProviders(): Promise<LlmProvidersResponse> {
+  const response = await getV2ListLlmProviders({ include_models: true });
+  if (response.status !== 200) {
+    throw new Error("Failed to fetch LLM providers");
+  }
+  return response.data;
+}
+
+export async function createLlmProviderAction(formData: FormData) {
+  const payload: UpsertLlmProviderRequest = {
+    name: String(formData.get("name") || "").trim(),
+    display_name: String(formData.get("display_name") || "").trim(),
+    description: formData.get("description")
+      ? String(formData.get("description"))
+      : undefined,
+    default_credential_provider: formData.get("default_credential_provider")
+      ? String(formData.get("default_credential_provider")).trim()
+      : undefined,
+    default_credential_id: undefined,
+    default_credential_type: "api_key",
+    supports_tools: formData.get("supports_tools") === "on",
+    supports_json_output: formData.get("supports_json_output") === "on",
+    supports_reasoning: formData.get("supports_reasoning") === "on",
+    supports_parallel_tool: formData.get("supports_parallel_tool") === "on",
+    metadata: {},
+  };
+
+  const response = await postV2CreateLlmProvider(payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to create LLM provider");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+// =============================================================================
+// Model Actions
+// =============================================================================
+
+export async function fetchLlmModels(): Promise<LlmModelsResponse> {
+  const response = await getV2ListLlmModels();
+  if (response.status !== 200) {
+    throw new Error("Failed to fetch LLM models");
+  }
+  return response.data;
+}
+
+export async function createLlmModelAction(formData: FormData) {
+  const providerId = String(formData.get("provider_id"));
+  const creatorId = formData.get("creator_id");
+
+  // Fetch provider to get default credentials
+  const providersResponse = await getV2ListLlmProviders({
+    include_models: false,
+  });
+  if (providersResponse.status !== 200) {
+    throw new Error("Failed to fetch providers");
+  }
+  const provider = providersResponse.data.providers.find(
+    (p) => p.id === providerId,
+  );
+
+  if (!provider) {
+    throw new Error("Provider not found");
+  }
+
+  const payload: CreateLlmModelRequest = {
+    slug: String(formData.get("slug") || "").trim(),
+    display_name: String(formData.get("display_name") || "").trim(),
+    description: formData.get("description")
+      ? String(formData.get("description"))
+      : undefined,
+    provider_id: providerId,
+    creator_id: creatorId ? String(creatorId) : undefined,
+    context_window: Number(formData.get("context_window") || 0),
+    max_output_tokens: formData.get("max_output_tokens")
+      ? Number(formData.get("max_output_tokens"))
+      : undefined,
+    is_enabled: formData.get("is_enabled") === "on",
+    capabilities: {},
+    metadata: {},
+    costs: [
+      {
+        credit_cost: Number(formData.get("credit_cost") || 0),
+        credential_provider:
+          provider.default_credential_provider || provider.name,
+        credential_id: provider.default_credential_id || undefined,
+        credential_type: provider.default_credential_type || "api_key",
+        metadata: {},
+      },
+    ],
+  };
+
+  const response = await postV2CreateLlmModel(payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to create LLM model");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function updateLlmModelAction(formData: FormData) {
+  const modelId = String(formData.get("model_id"));
+  const creatorId = formData.get("creator_id");
+
+  const payload: UpdateLlmModelRequest = {
+    display_name: formData.get("display_name")
+      ? String(formData.get("display_name"))
+      : undefined,
+    description: formData.get("description")
+      ? String(formData.get("description"))
+      : undefined,
+    provider_id: formData.get("provider_id")
+      ? String(formData.get("provider_id"))
+      : undefined,
+    creator_id: creatorId ? String(creatorId) : undefined,
+    context_window: formData.get("context_window")
+      ? Number(formData.get("context_window"))
+      : undefined,
+    max_output_tokens: formData.get("max_output_tokens")
+      ? Number(formData.get("max_output_tokens"))
+      : undefined,
+    is_enabled: formData.get("is_enabled")
+      ? formData.get("is_enabled") === "on"
+      : undefined,
+    costs: formData.get("credit_cost")
+      ? [
+          {
+            credit_cost: Number(formData.get("credit_cost")),
+            credential_provider: String(
+              formData.get("credential_provider") || "",
+            ).trim(),
+            credential_id: formData.get("credential_id")
+              ? String(formData.get("credential_id"))
+              : undefined,
+            credential_type: formData.get("credential_type")
+              ? String(formData.get("credential_type"))
+              : undefined,
+            metadata: {},
+          },
+        ]
+      : undefined,
+  };
+
+  const response = await patchV2UpdateLlmModel(modelId, payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to update LLM model");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function toggleLlmModelAction(formData: FormData): Promise<void> {
+  const modelId = String(formData.get("model_id"));
+  const shouldEnable = formData.get("is_enabled") === "true";
+  const migrateToSlug = formData.get("migrate_to_slug");
+  const migrationReason = formData.get("migration_reason");
+  const customCreditCost = formData.get("custom_credit_cost");
+
+  const payload: ToggleLlmModelRequest = {
+    is_enabled: shouldEnable,
+    migrate_to_slug: migrateToSlug ? String(migrateToSlug) : undefined,
+    migration_reason: migrationReason ? String(migrationReason) : undefined,
+    custom_credit_cost: customCreditCost ? Number(customCreditCost) : undefined,
+  };
+
+  const response = await patchV2ToggleLlmModelAvailability(modelId, payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to toggle LLM model");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function deleteLlmModelAction(formData: FormData): Promise<void> {
+  const modelId = String(formData.get("model_id"));
+  const replacementModelSlug = String(formData.get("replacement_model_slug"));
+
+  if (!replacementModelSlug) {
+    throw new Error("Replacement model is required");
+  }
+
+  const response = await deleteV2DeleteLlmModelAndMigrateWorkflows(modelId, {
+    replacement_model_slug: replacementModelSlug,
+  });
+  if (response.status !== 200) {
+    throw new Error("Failed to delete model");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function fetchLlmModelUsage(
+  modelId: string,
+): Promise<LlmModelUsageResponse> {
+  const response = await getV2GetModelUsageCount(modelId);
+  if (response.status !== 200) {
+    throw new Error("Failed to fetch model usage");
+  }
+  return response.data;
+}
+
+// =============================================================================
+// Migration Actions
+// =============================================================================
+
+export async function fetchLlmMigrations(
+  includeReverted: boolean = false,
+): Promise<LlmMigrationsResponse> {
+  const response = await getV2ListModelMigrations({
+    include_reverted: includeReverted,
+  });
+  if (response.status !== 200) {
+    throw new Error("Failed to fetch migrations");
+  }
+  return response.data;
+}
+
+export async function revertLlmMigrationAction(
+  formData: FormData,
+): Promise<void> {
+  const migrationId = String(formData.get("migration_id"));
+
+  const response = await postV2RevertAModelMigration(migrationId, null);
+  if (response.status !== 200) {
+    throw new Error("Failed to revert migration");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+// =============================================================================
+// Creator Actions
+// =============================================================================
+
+export async function fetchLlmCreators(): Promise<LlmCreatorsResponse> {
+  const response = await getV2ListModelCreators();
+  if (response.status !== 200) {
+    throw new Error("Failed to fetch creators");
+  }
+  return response.data;
+}
+
+export async function createLlmCreatorAction(
+  formData: FormData,
+): Promise<void> {
+  const payload: UpsertLlmCreatorRequest = {
+    name: String(formData.get("name") || "").trim(),
+    display_name: String(formData.get("display_name") || "").trim(),
+    description: formData.get("description")
+      ? String(formData.get("description"))
+      : undefined,
+    website_url: formData.get("website_url")
+      ? String(formData.get("website_url")).trim()
+      : undefined,
+    logo_url: formData.get("logo_url")
+      ? String(formData.get("logo_url")).trim()
+      : undefined,
+    metadata: {},
+  };
+
+  const response = await postV2CreateModelCreator(payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to create creator");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function updateLlmCreatorAction(
+  formData: FormData,
+): Promise<void> {
+  const creatorId = String(formData.get("creator_id"));
+  const payload: UpsertLlmCreatorRequest = {
+    name: String(formData.get("name") || "").trim(),
+    display_name: String(formData.get("display_name") || "").trim(),
+    description: formData.get("description")
+      ? String(formData.get("description"))
+      : undefined,
+    website_url: formData.get("website_url")
+      ? String(formData.get("website_url")).trim()
+      : undefined,
+    logo_url: formData.get("logo_url")
+      ? String(formData.get("logo_url")).trim()
+      : undefined,
+    metadata: {},
+  };
+
+  const response = await patchV2UpdateModelCreator(creatorId, payload);
+  if (response.status !== 200) {
+    throw new Error("Failed to update creator");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+export async function deleteLlmCreatorAction(
+  formData: FormData,
+): Promise<void> {
+  const creatorId = String(formData.get("creator_id"));
+
+  const response = await deleteV2DeleteModelCreator(creatorId);
+  if (response.status !== 200) {
+    throw new Error("Failed to delete creator");
+  }
+  revalidatePath(ADMIN_LLM_PATH);
+}
+
+// =============================================================================
+// Recommended Model Actions
+// =============================================================================
+
+export async function setRecommendedModelAction(
+  formData: FormData,
+): Promise<void> {
+  const modelId = String(formData.get("model_id"));
+
+  const response = await postV2SetRecommendedModel({ model_id: modelId });
+  if (response.status !== 200) {
+    throw new Error("Failed to set recommended model");
+  }
+
+  revalidatePath(ADMIN_LLM_PATH);
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/AddCreatorModal.tsx

@@ -0,0 +1,147 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import { createLlmCreatorAction } from "../actions";
+import { useRouter } from "next/navigation";
+
+export function AddCreatorModal() {
+  const [open, setOpen] = useState(false);
+  const [isSubmitting, setIsSubmitting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const router = useRouter();
+
+  async function handleSubmit(formData: FormData) {
+    setIsSubmitting(true);
+    setError(null);
+    try {
+      await createLlmCreatorAction(formData);
+      setOpen(false);
+      router.refresh();
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to create creator");
+    } finally {
+      setIsSubmitting(false);
+    }
+  }
+
+  return (
+    <Dialog
+      title="Add Creator"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "512px" }}
+    >
+      <Dialog.Trigger>
+        <Button variant="primary" size="small">
+          Add Creator
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          Add a new model creator (the organization that made/trained the
+          model).
+        </div>
+
+        <form action={handleSubmit} className="space-y-4">
+          <div className="grid gap-4 sm:grid-cols-2">
+            <div className="space-y-2">
+              <label
+                htmlFor="name"
+                className="text-sm font-medium text-foreground"
+              >
+                Name (slug) <span className="text-destructive">*</span>
+              </label>
+              <input
+                id="name"
+                required
+                name="name"
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                placeholder="openai"
+              />
+              <p className="text-xs text-muted-foreground">
+                Lowercase identifier (e.g., openai, meta, anthropic)
+              </p>
+            </div>
+            <div className="space-y-2">
+              <label
+                htmlFor="display_name"
+                className="text-sm font-medium text-foreground"
+              >
+                Display Name <span className="text-destructive">*</span>
+              </label>
+              <input
+                id="display_name"
+                required
+                name="display_name"
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                placeholder="OpenAI"
+              />
+            </div>
+          </div>
+
+          <div className="space-y-2">
+            <label
+              htmlFor="description"
+              className="text-sm font-medium text-foreground"
+            >
+              Description
+            </label>
+            <textarea
+              id="description"
+              name="description"
+              rows={2}
+              className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+              placeholder="Creator of GPT models..."
+            />
+          </div>
+
+          <div className="space-y-2">
+            <label
+              htmlFor="website_url"
+              className="text-sm font-medium text-foreground"
+            >
+              Website URL
+            </label>
+            <input
+              id="website_url"
+              name="website_url"
+              type="url"
+              className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+              placeholder="https://openai.com"
+            />
+          </div>
+
+          {error && (
+            <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+              {error}
+            </div>
+          )}
+
+          <Dialog.Footer>
+            <Button
+              variant="ghost"
+              size="small"
+              type="button"
+              onClick={() => {
+                setOpen(false);
+                setError(null);
+              }}
+              disabled={isSubmitting}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="primary"
+              size="small"
+              type="submit"
+              disabled={isSubmitting}
+            >
+              {isSubmitting ? "Creating..." : "Add Creator"}
+            </Button>
+          </Dialog.Footer>
+        </form>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/AddModelModal.tsx

@@ -0,0 +1,314 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import type { LlmProvider } from "@/app/api/__generated__/models/llmProvider";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import { createLlmModelAction } from "../actions";
+import { useRouter } from "next/navigation";
+
+interface Props {
+  providers: LlmProvider[];
+  creators: LlmModelCreator[];
+}
+
+export function AddModelModal({ providers, creators }: Props) {
+  const [open, setOpen] = useState(false);
+  const [selectedCreatorId, setSelectedCreatorId] = useState("");
+  const [isSubmitting, setIsSubmitting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const router = useRouter();
+
+  async function handleSubmit(formData: FormData) {
+    setIsSubmitting(true);
+    setError(null);
+    try {
+      await createLlmModelAction(formData);
+      setOpen(false);
+      router.refresh();
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to create model");
+    } finally {
+      setIsSubmitting(false);
+    }
+  }
+
+  // When provider changes, auto-select matching creator if one exists
+  function handleProviderChange(providerId: string) {
+    const provider = providers.find((p) => p.id === providerId);
+    if (provider) {
+      // Find creator with same name as provider (e.g., "openai" -> "openai")
+      const matchingCreator = creators.find((c) => c.name === provider.name);
+      if (matchingCreator) {
+        setSelectedCreatorId(matchingCreator.id);
+      } else {
+        // No matching creator (e.g., OpenRouter hosts other creators' models)
+        setSelectedCreatorId("");
+      }
+    }
+  }
+
+  return (
+    <Dialog
+      title="Add Model"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "768px", maxHeight: "90vh", overflowY: "auto" }}
+    >
+      <Dialog.Trigger>
+        <Button variant="primary" size="small">
+          Add Model
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          Register a new model slug, metadata, and pricing.
+        </div>
+
+        <form action={handleSubmit} className="space-y-6">
+          {/* Basic Information */}
+          <div className="space-y-4">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">
+                Basic Information
+              </h3>
+              <p className="text-xs text-muted-foreground">
+                Core model details
+              </p>
+            </div>
+            <div className="grid gap-4 sm:grid-cols-2">
+              <div className="space-y-2">
+                <label
+                  htmlFor="slug"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Model Slug <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="slug"
+                  required
+                  name="slug"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="gpt-4.1-mini-2025-04-14"
+                />
+              </div>
+              <div className="space-y-2">
+                <label
+                  htmlFor="display_name"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Display Name <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="display_name"
+                  required
+                  name="display_name"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="GPT 4.1 Mini"
+                />
+              </div>
+            </div>
+            <div className="space-y-2">
+              <label
+                htmlFor="description"
+                className="text-sm font-medium text-foreground"
+              >
+                Description
+              </label>
+              <textarea
+                id="description"
+                name="description"
+                rows={3}
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                placeholder="Optional description..."
+              />
+            </div>
+          </div>
+
+          {/* Model Configuration */}
+          <div className="space-y-4 border-t border-border pt-6">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">
+                Model Configuration
+              </h3>
+              <p className="text-xs text-muted-foreground">
+                Model capabilities and limits
+              </p>
+            </div>
+            <div className="grid gap-4 sm:grid-cols-2">
+              <div className="space-y-2">
+                <label
+                  htmlFor="provider_id"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Provider <span className="text-destructive">*</span>
+                </label>
+                <select
+                  id="provider_id"
+                  required
+                  name="provider_id"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  defaultValue=""
+                  onChange={(e) => handleProviderChange(e.target.value)}
+                >
+                  <option value="" disabled>
+                    Select provider
+                  </option>
+                  {providers.map((provider) => (
+                    <option key={provider.id} value={provider.id}>
+                      {provider.display_name} ({provider.name})
+                    </option>
+                  ))}
+                </select>
+                <p className="text-xs text-muted-foreground">
+                  Who hosts/serves the model
+                </p>
+              </div>
+              <div className="space-y-2">
+                <label
+                  htmlFor="creator_id"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Creator
+                </label>
+                <select
+                  id="creator_id"
+                  name="creator_id"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  value={selectedCreatorId}
+                  onChange={(e) => setSelectedCreatorId(e.target.value)}
+                >
+                  <option value="">No creator selected</option>
+                  {creators.map((creator) => (
+                    <option key={creator.id} value={creator.id}>
+                      {creator.display_name} ({creator.name})
+                    </option>
+                  ))}
+                </select>
+                <p className="text-xs text-muted-foreground">
+                  Who made/trained the model (e.g., OpenAI, Meta)
+                </p>
+              </div>
+            </div>
+            <div className="grid gap-4 sm:grid-cols-2">
+              <div className="space-y-2">
+                <label
+                  htmlFor="context_window"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Context Window <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="context_window"
+                  required
+                  type="number"
+                  name="context_window"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="128000"
+                  min={1}
+                />
+              </div>
+              <div className="space-y-2">
+                <label
+                  htmlFor="max_output_tokens"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Max Output Tokens
+                </label>
+                <input
+                  id="max_output_tokens"
+                  type="number"
+                  name="max_output_tokens"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="16384"
+                  min={1}
+                />
+              </div>
+            </div>
+          </div>
+
+          {/* Pricing */}
+          <div className="space-y-4 border-t border-border pt-6">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">Pricing</h3>
+              <p className="text-xs text-muted-foreground">
+                Credit cost per run (credentials are managed via the provider)
+              </p>
+            </div>
+            <div className="grid gap-4 sm:grid-cols-1">
+              <div className="space-y-2">
+                <label
+                  htmlFor="credit_cost"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Credit Cost <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="credit_cost"
+                  required
+                  type="number"
+                  name="credit_cost"
+                  step="1"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="5"
+                  min={0}
+                />
+              </div>
+            </div>
+            <p className="text-xs text-muted-foreground">
+              Credit cost is always in platform credits. Credentials are
+              inherited from the selected provider.
+            </p>
+          </div>
+
+          {/* Enabled Toggle */}
+          <div className="flex items-center gap-3 border-t border-border pt-6">
+            <input type="hidden" name="is_enabled" value="off" />
+            <input
+              id="is_enabled"
+              type="checkbox"
+              name="is_enabled"
+              defaultChecked
+              className="h-4 w-4 rounded border-input"
+            />
+            <label
+              htmlFor="is_enabled"
+              className="text-sm font-medium text-foreground"
+            >
+              Enabled by default
+            </label>
+          </div>
+
+          {error && (
+            <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+              {error}
+            </div>
+          )}
+
+          <Dialog.Footer>
+            <Button
+              variant="ghost"
+              size="small"
+              type="button"
+              onClick={() => {
+                setOpen(false);
+                setError(null);
+              }}
+              disabled={isSubmitting}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="primary"
+              size="small"
+              type="submit"
+              disabled={isSubmitting}
+            >
+              {isSubmitting ? "Creating..." : "Save Model"}
+            </Button>
+          </Dialog.Footer>
+        </form>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/AddProviderModal.tsx

@@ -0,0 +1,268 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import { createLlmProviderAction } from "../actions";
+import { useRouter } from "next/navigation";
+
+export function AddProviderModal() {
+  const [open, setOpen] = useState(false);
+  const [isSubmitting, setIsSubmitting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const router = useRouter();
+
+  async function handleSubmit(formData: FormData) {
+    setIsSubmitting(true);
+    setError(null);
+    try {
+      await createLlmProviderAction(formData);
+      setOpen(false);
+      router.refresh();
+    } catch (err) {
+      setError(
+        err instanceof Error ? err.message : "Failed to create provider",
+      );
+    } finally {
+      setIsSubmitting(false);
+    }
+  }
+
+  return (
+    <Dialog
+      title="Add Provider"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "768px", maxHeight: "90vh", overflowY: "auto" }}
+    >
+      <Dialog.Trigger>
+        <Button variant="primary" size="small">
+          Add Provider
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          Define a new upstream provider and default credential information.
+        </div>
+
+        {/* Setup Instructions */}
+        <div className="mb-6 rounded-lg border border-primary/30 bg-primary/5 p-4">
+          <div className="space-y-2">
+            <h4 className="text-sm font-semibold text-foreground">
+              Before Adding a Provider
+            </h4>
+            <p className="text-xs text-muted-foreground">
+              To use a new provider, you must first configure its credentials in
+              the backend:
+            </p>
+            <ol className="list-inside list-decimal space-y-1 text-xs text-muted-foreground">
+              <li>
+                Add the credential to{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono">
+                  backend/integrations/credentials_store.py
+                </code>{" "}
+                with a UUID, provider name, and settings secret reference
+              </li>
+              <li>
+                Add it to the{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono">
+                  PROVIDER_CREDENTIALS
+                </code>{" "}
+                dictionary in{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono">
+                  backend/data/block_cost_config.py
+                </code>
+              </li>
+              <li>
+                Use the <strong>same provider name</strong> in the
+                &quot;Credential Provider&quot; field below that matches the key
+                in{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono">
+                  PROVIDER_CREDENTIALS
+                </code>
+              </li>
+            </ol>
+          </div>
+        </div>
+
+        <form action={handleSubmit} className="space-y-6">
+          {/* Basic Information */}
+          <div className="space-y-4">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">
+                Basic Information
+              </h3>
+              <p className="text-xs text-muted-foreground">
+                Core provider details
+              </p>
+            </div>
+            <div className="grid gap-4 sm:grid-cols-2">
+              <div className="space-y-2">
+                <label
+                  htmlFor="name"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Provider Slug <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="name"
+                  required
+                  name="name"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="e.g. openai"
+                />
+              </div>
+              <div className="space-y-2">
+                <label
+                  htmlFor="display_name"
+                  className="text-sm font-medium text-foreground"
+                >
+                  Display Name <span className="text-destructive">*</span>
+                </label>
+                <input
+                  id="display_name"
+                  required
+                  name="display_name"
+                  className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                  placeholder="OpenAI"
+                />
+              </div>
+            </div>
+            <div className="space-y-2">
+              <label
+                htmlFor="description"
+                className="text-sm font-medium text-foreground"
+              >
+                Description
+              </label>
+              <textarea
+                id="description"
+                name="description"
+                rows={3}
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                placeholder="Optional description..."
+              />
+            </div>
+          </div>
+
+          {/* Default Credentials */}
+          <div className="space-y-4 border-t border-border pt-6">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">
+                Default Credentials
+              </h3>
+              <p className="text-xs text-muted-foreground">
+                Credential provider name that matches the key in{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono text-xs">
+                  PROVIDER_CREDENTIALS
+                </code>
+              </p>
+            </div>
+            <div className="space-y-2">
+              <label
+                htmlFor="default_credential_provider"
+                className="text-sm font-medium text-foreground"
+              >
+                Credential Provider <span className="text-destructive">*</span>
+              </label>
+              <input
+                id="default_credential_provider"
+                name="default_credential_provider"
+                required
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm transition-colors placeholder:text-muted-foreground focus:border-primary focus:outline-none focus:ring-2 focus:ring-primary/20"
+                placeholder="openai"
+              />
+              <p className="text-xs text-muted-foreground">
+                <strong>Important:</strong> This must exactly match the key in
+                the{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono text-xs">
+                  PROVIDER_CREDENTIALS
+                </code>{" "}
+                dictionary in{" "}
+                <code className="rounded bg-muted px-1 py-0.5 font-mono text-xs">
+                  block_cost_config.py
+                </code>
+                . Common values: &quot;openai&quot;, &quot;anthropic&quot;,
+                &quot;groq&quot;, &quot;open_router&quot;, etc.
+              </p>
+            </div>
+          </div>
+
+          {/* Capabilities */}
+          <div className="space-y-4 border-t border-border pt-6">
+            <div className="space-y-1">
+              <h3 className="text-sm font-semibold text-foreground">
+                Capabilities
+              </h3>
+              <p className="text-xs text-muted-foreground">
+                Provider feature flags
+              </p>
+            </div>
+            <div className="grid gap-3 sm:grid-cols-2">
+              {[
+                { name: "supports_tools", label: "Supports tools" },
+                { name: "supports_json_output", label: "Supports JSON output" },
+                { name: "supports_reasoning", label: "Supports reasoning" },
+                {
+                  name: "supports_parallel_tool",
+                  label: "Supports parallel tool calls",
+                },
+              ].map(({ name, label }) => (
+                <div
+                  key={name}
+                  className="flex items-center gap-3 rounded-md border border-border bg-muted/30 px-4 py-3 transition-colors hover:bg-muted/50"
+                >
+                  <input type="hidden" name={name} value="off" />
+                  <input
+                    id={name}
+                    type="checkbox"
+                    name={name}
+                    defaultChecked={
+                      name !== "supports_reasoning" &&
+                      name !== "supports_parallel_tool"
+                    }
+                    className="h-4 w-4 rounded border-input"
+                  />
+                  <label
+                    htmlFor={name}
+                    className="text-sm font-medium text-foreground"
+                  >
+                    {label}
+                  </label>
+                </div>
+              ))}
+            </div>
+          </div>
+
+          {error && (
+            <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+              {error}
+            </div>
+          )}
+
+          <Dialog.Footer>
+            <Button
+              variant="ghost"
+              size="small"
+              type="button"
+              onClick={() => {
+                setOpen(false);
+                setError(null);
+              }}
+              disabled={isSubmitting}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="primary"
+              size="small"
+              type="submit"
+              disabled={isSubmitting}
+            >
+              {isSubmitting ? "Creating..." : "Save Provider"}
+            </Button>
+          </Dialog.Footer>
+        </form>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/CreatorsTable.tsx

@@ -0,0 +1,195 @@
+"use client";
+
+import { useState } from "react";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import {
+  Table,
+  TableBody,
+  TableCell,
+  TableHead,
+  TableHeader,
+  TableRow,
+} from "@/components/atoms/Table/Table";
+import { Button } from "@/components/atoms/Button/Button";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { updateLlmCreatorAction } from "../actions";
+import { useRouter } from "next/navigation";
+import { DeleteCreatorModal } from "./DeleteCreatorModal";
+
+export function CreatorsTable({ creators }: { creators: LlmModelCreator[] }) {
+  if (!creators.length) {
+    return (
+      <div className="rounded-lg border border-dashed border-border p-6 text-center text-sm text-muted-foreground">
+        No creators registered yet.
+      </div>
+    );
+  }
+
+  return (
+    <div className="rounded-lg border">
+      <Table>
+        <TableHeader>
+          <TableRow>
+            <TableHead>Creator</TableHead>
+            <TableHead>Description</TableHead>
+            <TableHead>Website</TableHead>
+            <TableHead>Actions</TableHead>
+          </TableRow>
+        </TableHeader>
+        <TableBody>
+          {creators.map((creator) => (
+            <TableRow key={creator.id}>
+              <TableCell>
+                <div className="font-medium">{creator.display_name}</div>
+                <div className="text-xs text-muted-foreground">
+                  {creator.name}
+                </div>
+              </TableCell>
+              <TableCell>
+                <span className="text-sm text-muted-foreground">
+                  {creator.description || "—"}
+                </span>
+              </TableCell>
+              <TableCell>
+                {creator.website_url ? (
+                  <a
+                    href={creator.website_url}
+                    target="_blank"
+                    rel="noopener noreferrer"
+                    className="text-sm text-primary hover:underline"
+                  >
+                    {(() => {
+                      try {
+                        return new URL(creator.website_url).hostname;
+                      } catch {
+                        return creator.website_url;
+                      }
+                    })()}
+                  </a>
+                ) : (
+                  <span className="text-muted-foreground">—</span>
+                )}
+              </TableCell>
+              <TableCell>
+                <div className="flex items-center justify-end gap-2">
+                  <EditCreatorModal creator={creator} />
+                  <DeleteCreatorModal creator={creator} />
+                </div>
+              </TableCell>
+            </TableRow>
+          ))}
+        </TableBody>
+      </Table>
+    </div>
+  );
+}
+
+function EditCreatorModal({ creator }: { creator: LlmModelCreator }) {
+  const [open, setOpen] = useState(false);
+  const [isSubmitting, setIsSubmitting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const router = useRouter();
+
+  async function handleSubmit(formData: FormData) {
+    setIsSubmitting(true);
+    setError(null);
+    try {
+      await updateLlmCreatorAction(formData);
+      setOpen(false);
+      router.refresh();
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to update creator");
+    } finally {
+      setIsSubmitting(false);
+    }
+  }
+
+  return (
+    <Dialog
+      title="Edit Creator"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "512px" }}
+    >
+      <Dialog.Trigger>
+        <Button variant="outline" size="small" className="min-w-0">
+          Edit
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <form action={handleSubmit} className="space-y-4">
+          <input type="hidden" name="creator_id" value={creator.id} />
+
+          <div className="grid gap-4 sm:grid-cols-2">
+            <div className="space-y-2">
+              <label className="text-sm font-medium">Name (slug)</label>
+              <input
+                required
+                name="name"
+                defaultValue={creator.name}
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm"
+              />
+            </div>
+            <div className="space-y-2">
+              <label className="text-sm font-medium">Display Name</label>
+              <input
+                required
+                name="display_name"
+                defaultValue={creator.display_name}
+                className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm"
+              />
+            </div>
+          </div>
+
+          <div className="space-y-2">
+            <label className="text-sm font-medium">Description</label>
+            <textarea
+              name="description"
+              rows={2}
+              defaultValue={creator.description ?? ""}
+              className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm"
+            />
+          </div>
+
+          <div className="space-y-2">
+            <label className="text-sm font-medium">Website URL</label>
+            <input
+              name="website_url"
+              type="url"
+              defaultValue={creator.website_url ?? ""}
+              className="w-full rounded-md border border-input bg-background px-3 py-2 text-sm"
+            />
+          </div>
+
+          {error && (
+            <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+              {error}
+            </div>
+          )}
+
+          <Dialog.Footer>
+            <Button
+              variant="ghost"
+              size="small"
+              type="button"
+              onClick={() => {
+                setOpen(false);
+                setError(null);
+              }}
+              disabled={isSubmitting}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="primary"
+              size="small"
+              type="submit"
+              disabled={isSubmitting}
+            >
+              {isSubmitting ? "Updating..." : "Update"}
+            </Button>
+          </Dialog.Footer>
+        </form>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/DeleteCreatorModal.tsx

@@ -0,0 +1,107 @@
+"use client";
+
+import { useState } from "react";
+import { useRouter } from "next/navigation";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import { deleteLlmCreatorAction } from "../actions";
+
+export function DeleteCreatorModal({ creator }: { creator: LlmModelCreator }) {
+  const [open, setOpen] = useState(false);
+  const [isDeleting, setIsDeleting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const router = useRouter();
+
+  async function handleDelete(formData: FormData) {
+    setIsDeleting(true);
+    setError(null);
+    try {
+      await deleteLlmCreatorAction(formData);
+      setOpen(false);
+      router.refresh();
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to delete creator");
+    } finally {
+      setIsDeleting(false);
+    }
+  }
+
+  return (
+    <Dialog
+      title="Delete Creator"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "480px" }}
+    >
+      <Dialog.Trigger>
+        <Button
+          type="button"
+          variant="outline"
+          size="small"
+          className="min-w-0 text-destructive hover:bg-destructive/10"
+        >
+          Delete
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="space-y-4">
+          <div className="rounded-lg border border-amber-500/30 bg-amber-500/10 p-4 dark:border-amber-400/30 dark:bg-amber-400/10">
+            <div className="flex items-start gap-3">
+              <div className="flex-shrink-0 text-amber-600 dark:text-amber-400">
+                ⚠️
+              </div>
+              <div className="text-sm text-foreground">
+                <p className="font-semibold">You are about to delete:</p>
+                <p className="mt-1">
+                  <span className="font-medium">{creator.display_name}</span>{" "}
+                  <span className="text-muted-foreground">
+                    ({creator.name})
+                  </span>
+                </p>
+                <p className="mt-2 text-muted-foreground">
+                  Models using this creator will have their creator field
+                  cleared. This is safe and won&apos;t affect model
+                  functionality.
+                </p>
+              </div>
+            </div>
+          </div>
+
+          <form action={handleDelete} className="space-y-4">
+            <input type="hidden" name="creator_id" value={creator.id} />
+
+            {error && (
+              <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+                {error}
+              </div>
+            )}
+
+            <Dialog.Footer>
+              <Button
+                variant="ghost"
+                size="small"
+                onClick={() => {
+                  setOpen(false);
+                  setError(null);
+                }}
+                disabled={isDeleting}
+                type="button"
+              >
+                Cancel
+              </Button>
+              <Button
+                type="submit"
+                variant="primary"
+                size="small"
+                disabled={isDeleting}
+                className="bg-destructive text-destructive-foreground hover:bg-destructive/90"
+              >
+                {isDeleting ? "Deleting..." : "Delete Creator"}
+              </Button>
+            </Dialog.Footer>
+          </form>
+        </div>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/DeleteModelModal.tsx

@@ -0,0 +1,198 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import { deleteLlmModelAction, fetchLlmModelUsage } from "../actions";
+
+export function DeleteModelModal({
+  model,
+  availableModels,
+}: {
+  model: LlmModel;
+  availableModels: LlmModel[];
+}) {
+  const [open, setOpen] = useState(false);
+  const [selectedReplacement, setSelectedReplacement] = useState<string>("");
+  const [isDeleting, setIsDeleting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const [usageCount, setUsageCount] = useState<number | null>(null);
+  const [usageLoading, setUsageLoading] = useState(false);
+  const [usageError, setUsageError] = useState<string | null>(null);
+
+  // Filter out the current model and disabled models from replacement options
+  const replacementOptions = availableModels.filter(
+    (m) => m.id !== model.id && m.is_enabled,
+  );
+
+  async function fetchUsage() {
+    setUsageLoading(true);
+    setUsageError(null);
+    try {
+      const usage = await fetchLlmModelUsage(model.id);
+      setUsageCount(usage.node_count);
+    } catch (err) {
+      console.error("Failed to fetch model usage:", err);
+      setUsageError("Failed to load usage count");
+      setUsageCount(null);
+    } finally {
+      setUsageLoading(false);
+    }
+  }
+
+  async function handleDelete(formData: FormData) {
+    setIsDeleting(true);
+    setError(null);
+    try {
+      await deleteLlmModelAction(formData);
+      setOpen(false);
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to delete model");
+    } finally {
+      setIsDeleting(false);
+    }
+  }
+
+  return (
+    <Dialog
+      title="Delete Model"
+      controlled={{
+        isOpen: open,
+        set: async (isOpen) => {
+          setOpen(isOpen);
+          if (isOpen) {
+            setUsageCount(null);
+            setUsageError(null);
+            setError(null);
+            setSelectedReplacement("");
+            await fetchUsage();
+          }
+        },
+      }}
+      styling={{ maxWidth: "600px" }}
+    >
+      <Dialog.Trigger>
+        <Button
+          type="button"
+          variant="outline"
+          size="small"
+          className="min-w-0 text-destructive hover:bg-destructive/10"
+        >
+          Delete
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          This action cannot be undone. All workflows using this model will be
+          migrated to the replacement model you select.
+        </div>
+
+        <div className="space-y-4">
+          <div className="rounded-lg border border-amber-500/30 bg-amber-500/10 p-4 dark:border-amber-400/30 dark:bg-amber-400/10">
+            <div className="flex items-start gap-3">
+              <div className="flex-shrink-0 text-amber-600 dark:text-amber-400">
+                ⚠️
+              </div>
+              <div className="text-sm text-foreground">
+                <p className="font-semibold">You are about to delete:</p>
+                <p className="mt-1">
+                  <span className="font-medium">{model.display_name}</span>{" "}
+                  <span className="text-muted-foreground">({model.slug})</span>
+                </p>
+                {usageLoading && (
+                  <p className="mt-2 text-muted-foreground">
+                    Loading usage count...
+                  </p>
+                )}
+                {usageError && (
+                  <p className="mt-2 text-destructive">{usageError}</p>
+                )}
+                {!usageLoading && !usageError && usageCount !== null && (
+                  <p className="mt-2 font-semibold">
+                    Impact: {usageCount} block{usageCount !== 1 ? "s" : ""}{" "}
+                    currently use this model
+                  </p>
+                )}
+                <p className="mt-2 text-muted-foreground">
+                  All workflows currently using this model will be automatically
+                  updated to use the replacement model you choose below.
+                </p>
+              </div>
+            </div>
+          </div>
+
+          <form action={handleDelete} className="space-y-4">
+            <input type="hidden" name="model_id" value={model.id} />
+            <input
+              type="hidden"
+              name="replacement_model_slug"
+              value={selectedReplacement}
+            />
+
+            <label className="text-sm font-medium">
+              <span className="mb-2 block">
+                Select Replacement Model{" "}
+                <span className="text-destructive">*</span>
+              </span>
+              <select
+                required
+                value={selectedReplacement}
+                onChange={(e) => setSelectedReplacement(e.target.value)}
+                className="w-full rounded border border-input bg-background p-2 text-sm"
+              >
+                <option value="">-- Choose a replacement model --</option>
+                {replacementOptions.map((m) => (
+                  <option key={m.id} value={m.slug}>
+                    {m.display_name} ({m.slug})
+                  </option>
+                ))}
+              </select>
+              {replacementOptions.length === 0 && (
+                <p className="mt-2 text-xs text-destructive">
+                  No replacement models available. You must have at least one
+                  other enabled model before deleting this one.
+                </p>
+              )}
+            </label>
+
+            {error && (
+              <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+                {error}
+              </div>
+            )}
+
+            <Dialog.Footer>
+              <Button
+                variant="ghost"
+                size="small"
+                type="button"
+                onClick={() => {
+                  setOpen(false);
+                  setSelectedReplacement("");
+                  setError(null);
+                }}
+                disabled={isDeleting}
+              >
+                Cancel
+              </Button>
+              <Button
+                type="submit"
+                variant="primary"
+                size="small"
+                disabled={
+                  !selectedReplacement ||
+                  isDeleting ||
+                  replacementOptions.length === 0
+                }
+                className="bg-destructive text-destructive-foreground hover:bg-destructive/90"
+              >
+                {isDeleting ? "Deleting..." : "Delete and Migrate"}
+              </Button>
+            </Dialog.Footer>
+          </form>
+        </div>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/DisableModelModal.tsx

@@ -0,0 +1,287 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import { toggleLlmModelAction, fetchLlmModelUsage } from "../actions";
+
+export function DisableModelModal({
+  model,
+  availableModels,
+}: {
+  model: LlmModel;
+  availableModels: LlmModel[];
+}) {
+  const [open, setOpen] = useState(false);
+  const [isDisabling, setIsDisabling] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const [usageCount, setUsageCount] = useState<number | null>(null);
+  const [selectedMigration, setSelectedMigration] = useState<string>("");
+  const [wantsMigration, setWantsMigration] = useState(false);
+  const [migrationReason, setMigrationReason] = useState("");
+  const [customCreditCost, setCustomCreditCost] = useState<string>("");
+
+  // Filter out the current model and disabled models from replacement options
+  const migrationOptions = availableModels.filter(
+    (m) => m.id !== model.id && m.is_enabled,
+  );
+
+  async function fetchUsage() {
+    try {
+      const usage = await fetchLlmModelUsage(model.id);
+      setUsageCount(usage.node_count);
+    } catch {
+      setUsageCount(null);
+    }
+  }
+
+  async function handleDisable(formData: FormData) {
+    setIsDisabling(true);
+    setError(null);
+    try {
+      await toggleLlmModelAction(formData);
+      setOpen(false);
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to disable model");
+    } finally {
+      setIsDisabling(false);
+    }
+  }
+
+  function resetState() {
+    setError(null);
+    setSelectedMigration("");
+    setWantsMigration(false);
+    setMigrationReason("");
+    setCustomCreditCost("");
+  }
+
+  const hasUsage = usageCount !== null && usageCount > 0;
+
+  return (
+    <Dialog
+      title="Disable Model"
+      controlled={{
+        isOpen: open,
+        set: async (isOpen) => {
+          setOpen(isOpen);
+          if (isOpen) {
+            setUsageCount(null);
+            resetState();
+            await fetchUsage();
+          }
+        },
+      }}
+      styling={{ maxWidth: "600px" }}
+    >
+      <Dialog.Trigger>
+        <Button
+          type="button"
+          variant="outline"
+          size="small"
+          className="min-w-0"
+        >
+          Disable
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          Disabling a model will hide it from users when creating new workflows.
+        </div>
+
+        <div className="space-y-4">
+          <div className="rounded-lg border border-amber-500/30 bg-amber-500/10 p-4 dark:border-amber-400/30 dark:bg-amber-400/10">
+            <div className="flex items-start gap-3">
+              <div className="flex-shrink-0 text-amber-600 dark:text-amber-400">
+                ⚠️
+              </div>
+              <div className="text-sm text-foreground">
+                <p className="font-semibold">You are about to disable:</p>
+                <p className="mt-1">
+                  <span className="font-medium">{model.display_name}</span>{" "}
+                  <span className="text-muted-foreground">({model.slug})</span>
+                </p>
+                {usageCount === null ? (
+                  <p className="mt-2 text-muted-foreground">
+                    Loading usage data...
+                  </p>
+                ) : usageCount > 0 ? (
+                  <p className="mt-2 font-semibold">
+                    Impact: {usageCount} block{usageCount !== 1 ? "s" : ""}{" "}
+                    currently use this model
+                  </p>
+                ) : (
+                  <p className="mt-2 text-muted-foreground">
+                    No workflows are currently using this model.
+                  </p>
+                )}
+              </div>
+            </div>
+          </div>
+
+          {hasUsage && (
+            <div className="space-y-4 rounded-lg border border-border bg-muted/50 p-4">
+              <label className="flex items-start gap-3">
+                <input
+                  type="checkbox"
+                  checked={wantsMigration}
+                  onChange={(e) => {
+                    setWantsMigration(e.target.checked);
+                    if (!e.target.checked) {
+                      setSelectedMigration("");
+                    }
+                  }}
+                  className="mt-1"
+                />
+                <div className="text-sm">
+                  <span className="font-medium">
+                    Migrate existing workflows to another model
+                  </span>
+                  <p className="mt-1 text-muted-foreground">
+                    Creates a revertible migration record. If unchecked,
+                    existing workflows will use automatic fallback to an enabled
+                    model from the same provider.
+                  </p>
+                </div>
+              </label>
+
+              {wantsMigration && (
+                <div className="space-y-4 border-t border-border pt-4">
+                  <label className="block text-sm font-medium">
+                    <span className="mb-2 block">
+                      Replacement Model{" "}
+                      <span className="text-destructive">*</span>
+                    </span>
+                    <select
+                      required
+                      value={selectedMigration}
+                      onChange={(e) => setSelectedMigration(e.target.value)}
+                      className="w-full rounded border border-input bg-background p-2 text-sm"
+                    >
+                      <option value="">-- Choose a replacement model --</option>
+                      {migrationOptions.map((m) => (
+                        <option key={m.id} value={m.slug}>
+                          {m.display_name} ({m.slug})
+                        </option>
+                      ))}
+                    </select>
+                    {migrationOptions.length === 0 && (
+                      <p className="mt-2 text-xs text-destructive">
+                        No other enabled models available for migration.
+                      </p>
+                    )}
+                  </label>
+
+                  <label className="block text-sm font-medium">
+                    <span className="mb-2 block">
+                      Migration Reason{" "}
+                      <span className="font-normal text-muted-foreground">
+                        (optional)
+                      </span>
+                    </span>
+                    <input
+                      type="text"
+                      value={migrationReason}
+                      onChange={(e) => setMigrationReason(e.target.value)}
+                      placeholder="e.g., Provider outage, Cost reduction"
+                      className="w-full rounded border border-input bg-background p-2 text-sm"
+                    />
+                    <p className="mt-1 text-xs text-muted-foreground">
+                      Helps track why the migration was made
+                    </p>
+                  </label>
+
+                  <label className="block text-sm font-medium">
+                    <span className="mb-2 block">
+                      Custom Credit Cost{" "}
+                      <span className="font-normal text-muted-foreground">
+                        (optional)
+                      </span>
+                    </span>
+                    <input
+                      type="number"
+                      min="0"
+                      value={customCreditCost}
+                      onChange={(e) => setCustomCreditCost(e.target.value)}
+                      placeholder="Leave blank to use target model's cost"
+                      className="w-full rounded border border-input bg-background p-2 text-sm"
+                    />
+                    <p className="mt-1 text-xs text-muted-foreground">
+                      Override pricing during this migration (for billing
+                      adjustments)
+                    </p>
+                  </label>
+                </div>
+              )}
+            </div>
+          )}
+
+          <form action={handleDisable} className="space-y-4">
+            <input type="hidden" name="model_id" value={model.id} />
+            <input type="hidden" name="is_enabled" value="false" />
+            {wantsMigration && selectedMigration && (
+              <>
+                <input
+                  type="hidden"
+                  name="migrate_to_slug"
+                  value={selectedMigration}
+                />
+                {migrationReason && (
+                  <input
+                    type="hidden"
+                    name="migration_reason"
+                    value={migrationReason}
+                  />
+                )}
+                {customCreditCost && (
+                  <input
+                    type="hidden"
+                    name="custom_credit_cost"
+                    value={customCreditCost}
+                  />
+                )}
+              </>
+            )}
+
+            {error && (
+              <div className="rounded-lg border border-destructive/30 bg-destructive/10 p-3 text-sm text-destructive">
+                {error}
+              </div>
+            )}
+
+            <Dialog.Footer>
+              <Button
+                variant="ghost"
+                size="small"
+                onClick={() => {
+                  setOpen(false);
+                  resetState();
+                }}
+                disabled={isDisabling}
+              >
+                Cancel
+              </Button>
+              <Button
+                type="submit"
+                variant="primary"
+                size="small"
+                disabled={
+                  isDisabling ||
+                  (wantsMigration && !selectedMigration) ||
+                  usageCount === null
+                }
+              >
+                {isDisabling
+                  ? "Disabling..."
+                  : wantsMigration && selectedMigration
+                    ? "Disable & Migrate"
+                    : "Disable Model"}
+              </Button>
+            </Dialog.Footer>
+          </form>
+        </div>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/EditModelModal.tsx

@@ -0,0 +1,186 @@
+"use client";
+
+import { useState } from "react";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { Button } from "@/components/atoms/Button/Button";
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import type { LlmProvider } from "@/app/api/__generated__/models/llmProvider";
+import { updateLlmModelAction } from "../actions";
+
+export function EditModelModal({
+  model,
+  providers,
+  creators,
+}: {
+  model: LlmModel;
+  providers: LlmProvider[];
+  creators: LlmModelCreator[];
+}) {
+  const [open, setOpen] = useState(false);
+  const cost = model.costs?.[0];
+  const provider = providers.find((p) => p.id === model.provider_id);
+
+  return (
+    <Dialog
+      title="Edit Model"
+      controlled={{ isOpen: open, set: setOpen }}
+      styling={{ maxWidth: "768px", maxHeight: "90vh", overflowY: "auto" }}
+    >
+      <Dialog.Trigger>
+        <Button variant="outline" size="small" className="min-w-0">
+          Edit
+        </Button>
+      </Dialog.Trigger>
+      <Dialog.Content>
+        <div className="mb-4 text-sm text-muted-foreground">
+          Update model metadata and pricing information.
+        </div>
+        <form
+          action={async (formData) => {
+            await updateLlmModelAction(formData);
+            setOpen(false);
+          }}
+          className="space-y-4"
+        >
+          <input type="hidden" name="model_id" value={model.id} />
+
+          <div className="grid gap-4 md:grid-cols-2">
+            <label className="text-sm font-medium">
+              Display Name
+              <input
+                required
+                name="display_name"
+                defaultValue={model.display_name}
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+              />
+            </label>
+            <label className="text-sm font-medium">
+              Provider
+              <select
+                required
+                name="provider_id"
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+                defaultValue={model.provider_id}
+              >
+                {providers.map((p) => (
+                  <option key={p.id} value={p.id}>
+                    {p.display_name} ({p.name})
+                  </option>
+                ))}
+              </select>
+              <span className="text-xs text-muted-foreground">
+                Who hosts/serves the model
+              </span>
+            </label>
+          </div>
+
+          <div className="grid gap-4 md:grid-cols-2">
+            <label className="text-sm font-medium">
+              Creator
+              <select
+                name="creator_id"
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+                defaultValue={model.creator_id ?? ""}
+              >
+                <option value="">No creator selected</option>
+                {creators.map((c) => (
+                  <option key={c.id} value={c.id}>
+                    {c.display_name} ({c.name})
+                  </option>
+                ))}
+              </select>
+              <span className="text-xs text-muted-foreground">
+                Who made/trained the model (e.g., OpenAI, Meta)
+              </span>
+            </label>
+          </div>
+
+          <label className="text-sm font-medium">
+            Description
+            <textarea
+              name="description"
+              rows={2}
+              defaultValue={model.description ?? ""}
+              className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+              placeholder="Optional description..."
+            />
+          </label>
+
+          <div className="grid gap-4 md:grid-cols-2">
+            <label className="text-sm font-medium">
+              Context Window
+              <input
+                required
+                type="number"
+                name="context_window"
+                defaultValue={model.context_window}
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+                min={1}
+              />
+            </label>
+            <label className="text-sm font-medium">
+              Max Output Tokens
+              <input
+                type="number"
+                name="max_output_tokens"
+                defaultValue={model.max_output_tokens ?? undefined}
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+                min={1}
+              />
+            </label>
+          </div>
+
+          <div className="grid gap-4 md:grid-cols-2">
+            <label className="text-sm font-medium">
+              Credit Cost
+              <input
+                required
+                type="number"
+                name="credit_cost"
+                defaultValue={cost?.credit_cost ?? 0}
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+                min={0}
+              />
+              <span className="text-xs text-muted-foreground">
+                Credits charged per run
+              </span>
+            </label>
+            <label className="text-sm font-medium">
+              Credential Provider
+              <select
+                required
+                name="credential_provider"
+                defaultValue={cost?.credential_provider ?? provider?.name ?? ""}
+                className="mt-1 w-full rounded border border-input bg-background p-2 text-sm"
+              >
+                <option value="" disabled>
+                  Select provider
+                </option>
+                {providers.map((p) => (
+                  <option key={p.id} value={p.name}>
+                    {p.display_name} ({p.name})
+                  </option>
+                ))}
+              </select>
+              <span className="text-xs text-muted-foreground">
+                Must match a key in PROVIDER_CREDENTIALS
+              </span>
+            </label>
+          </div>
+          {/* Hidden defaults for credential_type */}
+          <input type="hidden" name="credential_type" value="api_key" />
+
+          <Dialog.Footer>
+            <Button variant="ghost" size="small" onClick={() => setOpen(false)}>
+              Cancel
+            </Button>
+            <Button variant="primary" size="small" type="submit">
+              Update Model
+            </Button>
+          </Dialog.Footer>
+        </form>
+      </Dialog.Content>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/LlmRegistryDashboard.tsx

@@ -0,0 +1,112 @@
+"use client";
+
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import type { LlmModelMigration } from "@/app/api/__generated__/models/llmModelMigration";
+import type { LlmProvider } from "@/app/api/__generated__/models/llmProvider";
+import { AddProviderModal } from "./AddProviderModal";
+import { AddModelModal } from "./AddModelModal";
+import { AddCreatorModal } from "./AddCreatorModal";
+import { ProviderList } from "./ProviderList";
+import { ModelsTable } from "./ModelsTable";
+import { MigrationsTable } from "./MigrationsTable";
+import { CreatorsTable } from "./CreatorsTable";
+import { RecommendedModelSelector } from "./RecommendedModelSelector";
+
+interface Props {
+  providers: LlmProvider[];
+  models: LlmModel[];
+  migrations: LlmModelMigration[];
+  creators: LlmModelCreator[];
+}
+
+export function LlmRegistryDashboard({
+  providers,
+  models,
+  migrations,
+  creators,
+}: Props) {
+  return (
+    <div className="mx-auto p-6">
+      <div className="flex flex-col gap-6">
+        {/* Header */}
+        <div>
+          <h1 className="text-3xl font-bold">LLM Registry</h1>
+          <p className="text-muted-foreground">
+            Manage providers, creators, models, and credit pricing
+          </p>
+        </div>
+
+        {/* Active Migrations Section - Only show if there are migrations */}
+        {migrations.length > 0 && (
+          <div className="rounded-lg border border-primary/30 bg-primary/5 p-6 shadow-sm">
+            <div className="mb-4">
+              <h2 className="text-xl font-semibold">Active Migrations</h2>
+              <p className="mt-1 text-sm text-muted-foreground">
+                These migrations can be reverted to restore workflows to their
+                original model
+              </p>
+            </div>
+            <MigrationsTable migrations={migrations} />
+          </div>
+        )}
+
+        {/* Providers & Creators Section - Side by Side */}
+        <div className="grid gap-6 lg:grid-cols-2">
+          {/* Providers */}
+          <div className="rounded-lg border bg-card p-6 shadow-sm">
+            <div className="mb-4 flex items-center justify-between">
+              <div>
+                <h2 className="text-xl font-semibold">Providers</h2>
+                <p className="mt-1 text-sm text-muted-foreground">
+                  Who hosts/serves the models
+                </p>
+              </div>
+              <AddProviderModal />
+            </div>
+            <ProviderList providers={providers} />
+          </div>
+
+          {/* Creators */}
+          <div className="rounded-lg border bg-card p-6 shadow-sm">
+            <div className="mb-4 flex items-center justify-between">
+              <div>
+                <h2 className="text-xl font-semibold">Creators</h2>
+                <p className="mt-1 text-sm text-muted-foreground">
+                  Who made/trained the models
+                </p>
+              </div>
+              <AddCreatorModal />
+            </div>
+            <CreatorsTable creators={creators} />
+          </div>
+        </div>
+
+        {/* Models Section */}
+        <div className="rounded-lg border bg-card p-6 shadow-sm">
+          <div className="mb-4 flex items-center justify-between">
+            <div>
+              <h2 className="text-xl font-semibold">Models</h2>
+              <p className="mt-1 text-sm text-muted-foreground">
+                Toggle availability, adjust context windows, and update credit
+                pricing
+              </p>
+            </div>
+            <AddModelModal providers={providers} creators={creators} />
+          </div>
+
+          {/* Recommended Model Selector */}
+          <div className="mb-6">
+            <RecommendedModelSelector models={models} />
+          </div>
+
+          <ModelsTable
+            models={models}
+            providers={providers}
+            creators={creators}
+          />
+        </div>
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/MigrationsTable.tsx

@@ -0,0 +1,132 @@
+"use client";
+
+import { useState } from "react";
+import type { LlmModelMigration } from "@/app/api/__generated__/models/llmModelMigration";
+import { Button } from "@/components/atoms/Button/Button";
+import {
+  Table,
+  TableBody,
+  TableCell,
+  TableHead,
+  TableHeader,
+  TableRow,
+} from "@/components/atoms/Table/Table";
+import { revertLlmMigrationAction } from "../actions";
+
+export function MigrationsTable({
+  migrations,
+}: {
+  migrations: LlmModelMigration[];
+}) {
+  if (!migrations.length) {
+    return (
+      <div className="rounded-lg border border-dashed border-border p-6 text-center text-sm text-muted-foreground">
+        No active migrations. Migrations are created when you disable a model
+        with the &quot;Migrate existing workflows&quot; option.
+      </div>
+    );
+  }
+
+  return (
+    <div className="rounded-lg border">
+      <Table>
+        <TableHeader>
+          <TableRow>
+            <TableHead>Migration</TableHead>
+            <TableHead>Reason</TableHead>
+            <TableHead>Nodes Affected</TableHead>
+            <TableHead>Custom Cost</TableHead>
+            <TableHead>Created</TableHead>
+            <TableHead className="text-right">Actions</TableHead>
+          </TableRow>
+        </TableHeader>
+        <TableBody>
+          {migrations.map((migration) => (
+            <MigrationRow key={migration.id} migration={migration} />
+          ))}
+        </TableBody>
+      </Table>
+    </div>
+  );
+}
+
+function MigrationRow({ migration }: { migration: LlmModelMigration }) {
+  const [isReverting, setIsReverting] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+
+  async function handleRevert(formData: FormData) {
+    setIsReverting(true);
+    setError(null);
+    try {
+      await revertLlmMigrationAction(formData);
+    } catch (err) {
+      setError(
+        err instanceof Error ? err.message : "Failed to revert migration",
+      );
+    } finally {
+      setIsReverting(false);
+    }
+  }
+
+  const createdDate = new Date(migration.created_at);
+
+  return (
+    <>
+      <TableRow>
+        <TableCell>
+          <div className="text-sm">
+            <span className="font-medium">{migration.source_model_slug}</span>
+            <span className="mx-2 text-muted-foreground">→</span>
+            <span className="font-medium">{migration.target_model_slug}</span>
+          </div>
+        </TableCell>
+        <TableCell>
+          <div className="text-sm text-muted-foreground">
+            {migration.reason || "—"}
+          </div>
+        </TableCell>
+        <TableCell>
+          <div className="text-sm">{migration.node_count}</div>
+        </TableCell>
+        <TableCell>
+          <div className="text-sm">
+            {migration.custom_credit_cost !== null
+              ? `${migration.custom_credit_cost} credits`
+              : "—"}
+          </div>
+        </TableCell>
+        <TableCell>
+          <div className="text-sm text-muted-foreground">
+            {createdDate.toLocaleDateString()}{" "}
+            {createdDate.toLocaleTimeString([], {
+              hour: "2-digit",
+              minute: "2-digit",
+            })}
+          </div>
+        </TableCell>
+        <TableCell className="text-right">
+          <form action={handleRevert} className="inline">
+            <input type="hidden" name="migration_id" value={migration.id} />
+            <Button
+              type="submit"
+              variant="outline"
+              size="small"
+              disabled={isReverting}
+            >
+              {isReverting ? "Reverting..." : "Revert"}
+            </Button>
+          </form>
+        </TableCell>
+      </TableRow>
+      {error && (
+        <TableRow>
+          <TableCell colSpan={6}>
+            <div className="rounded border border-destructive/30 bg-destructive/10 p-2 text-sm text-destructive">
+              {error}
+            </div>
+          </TableCell>
+        </TableRow>
+      )}
+    </>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/ModelsTable.tsx

@@ -0,0 +1,172 @@
+"use client";
+
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import type { LlmModelCreator } from "@/app/api/__generated__/models/llmModelCreator";
+import type { LlmProvider } from "@/app/api/__generated__/models/llmProvider";
+import {
+  Table,
+  TableBody,
+  TableCell,
+  TableHead,
+  TableHeader,
+  TableRow,
+} from "@/components/atoms/Table/Table";
+import { Button } from "@/components/atoms/Button/Button";
+import { toggleLlmModelAction } from "../actions";
+import { DeleteModelModal } from "./DeleteModelModal";
+import { DisableModelModal } from "./DisableModelModal";
+import { EditModelModal } from "./EditModelModal";
+import { Star } from "@phosphor-icons/react";
+
+export function ModelsTable({
+  models,
+  providers,
+  creators,
+}: {
+  models: LlmModel[];
+  providers: LlmProvider[];
+  creators: LlmModelCreator[];
+}) {
+  if (!models.length) {
+    return (
+      <div className="rounded-lg border border-dashed border-border p-6 text-center text-sm text-muted-foreground">
+        No models registered yet.
+      </div>
+    );
+  }
+
+  const providerLookup = new Map(
+    providers.map((provider) => [provider.id, provider]),
+  );
+
+  return (
+    <div className="rounded-lg border">
+      <Table>
+        <TableHeader>
+          <TableRow>
+            <TableHead>Model</TableHead>
+            <TableHead>Provider</TableHead>
+            <TableHead>Creator</TableHead>
+            <TableHead>Context Window</TableHead>
+            <TableHead>Max Output</TableHead>
+            <TableHead>Cost</TableHead>
+            <TableHead>Status</TableHead>
+            <TableHead>Actions</TableHead>
+          </TableRow>
+        </TableHeader>
+        <TableBody>
+          {models.map((model) => {
+            const cost = model.costs?.[0];
+            const provider = providerLookup.get(model.provider_id);
+            return (
+              <TableRow
+                key={model.id}
+                className={model.is_enabled ? "" : "opacity-60"}
+              >
+                <TableCell>
+                  <div className="font-medium">{model.display_name}</div>
+                  <div className="text-xs text-muted-foreground">
+                    {model.slug}
+                  </div>
+                </TableCell>
+                <TableCell>
+                  {provider ? (
+                    <>
+                      <div>{provider.display_name}</div>
+                      <div className="text-xs text-muted-foreground">
+                        {provider.name}
+                      </div>
+                    </>
+                  ) : (
+                    model.provider_id
+                  )}
+                </TableCell>
+                <TableCell>
+                  {model.creator ? (
+                    <>
+                      <div>{model.creator.display_name}</div>
+                      <div className="text-xs text-muted-foreground">
+                        {model.creator.name}
+                      </div>
+                    </>
+                  ) : (
+                    <span className="text-muted-foreground">—</span>
+                  )}
+                </TableCell>
+                <TableCell>{model.context_window.toLocaleString()}</TableCell>
+                <TableCell>
+                  {model.max_output_tokens
+                    ? model.max_output_tokens.toLocaleString()
+                    : "—"}
+                </TableCell>
+                <TableCell>
+                  {cost ? (
+                    <>
+                      <div className="font-medium">
+                        {cost.credit_cost} credits
+                      </div>
+                      <div className="text-xs text-muted-foreground">
+                        {cost.credential_provider}
+                      </div>
+                    </>
+                  ) : (
+                    "—"
+                  )}
+                </TableCell>
+                <TableCell>
+                  <div className="flex flex-col gap-1">
+                    <span
+                      className={`inline-flex rounded-full px-2.5 py-1 text-xs font-semibold ${
+                        model.is_enabled
+                          ? "bg-primary/10 text-primary"
+                          : "bg-muted text-muted-foreground"
+                      }`}
+                    >
+                      {model.is_enabled ? "Enabled" : "Disabled"}
+                    </span>
+                    {model.is_recommended && (
+                      <span className="inline-flex items-center gap-1 rounded-full bg-amber-500/10 px-2.5 py-1 text-xs font-semibold text-amber-600 dark:text-amber-400">
+                        <Star size={12} weight="fill" />
+                        Recommended
+                      </span>
+                    )}
+                  </div>
+                </TableCell>
+                <TableCell>
+                  <div className="flex items-center justify-end gap-2">
+                    {model.is_enabled ? (
+                      <DisableModelModal
+                        model={model}
+                        availableModels={models}
+                      />
+                    ) : (
+                      <EnableModelButton modelId={model.id} />
+                    )}
+                    <EditModelModal
+                      model={model}
+                      providers={providers}
+                      creators={creators}
+                    />
+                    <DeleteModelModal model={model} availableModels={models} />
+                  </div>
+                </TableCell>
+              </TableRow>
+            );
+          })}
+        </TableBody>
+      </Table>
+    </div>
+  );
+}
+
+function EnableModelButton({ modelId }: { modelId: string }) {
+  return (
+    <form action={toggleLlmModelAction} className="inline">
+      <input type="hidden" name="model_id" value={modelId} />
+      <input type="hidden" name="is_enabled" value="true" />
+      <Button type="submit" variant="outline" size="small" className="min-w-0">
+        Enable
+      </Button>
+    </form>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/ProviderList.tsx

@@ -0,0 +1,71 @@
+import {
+  Table,
+  TableBody,
+  TableCell,
+  TableHead,
+  TableHeader,
+  TableRow,
+} from "@/components/atoms/Table/Table";
+import type { LlmProvider } from "@/app/api/__generated__/models/llmProvider";
+
+export function ProviderList({ providers }: { providers: LlmProvider[] }) {
+  if (!providers.length) {
+    return (
+      <div className="rounded-lg border border-dashed border-border p-6 text-center text-sm text-muted-foreground">
+        No providers configured yet.
+      </div>
+    );
+  }
+
+  return (
+    <div className="rounded-lg border">
+      <Table>
+        <TableHeader>
+          <TableRow>
+            <TableHead>Name</TableHead>
+            <TableHead>Display Name</TableHead>
+            <TableHead>Default Credential</TableHead>
+            <TableHead>Capabilities</TableHead>
+          </TableRow>
+        </TableHeader>
+        <TableBody>
+          {providers.map((provider) => (
+            <TableRow key={provider.id}>
+              <TableCell className="font-medium">{provider.name}</TableCell>
+              <TableCell>{provider.display_name}</TableCell>
+              <TableCell>
+                {provider.default_credential_provider
+                  ? `${provider.default_credential_provider} (${provider.default_credential_id ?? "id?"})`
+                  : "—"}
+              </TableCell>
+              <TableCell className="text-sm text-muted-foreground">
+                <div className="flex flex-wrap gap-2">
+                  {provider.supports_tools && (
+                    <span className="rounded bg-muted px-2 py-0.5 text-xs">
+                      Tools
+                    </span>
+                  )}
+                  {provider.supports_json_output && (
+                    <span className="rounded bg-muted px-2 py-0.5 text-xs">
+                      JSON
+                    </span>
+                  )}
+                  {provider.supports_reasoning && (
+                    <span className="rounded bg-muted px-2 py-0.5 text-xs">
+                      Reasoning
+                    </span>
+                  )}
+                  {provider.supports_parallel_tool && (
+                    <span className="rounded bg-muted px-2 py-0.5 text-xs">
+                      Parallel Tools
+                    </span>
+                  )}
+                </div>
+              </TableCell>
+            </TableRow>
+          ))}
+        </TableBody>
+      </Table>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/components/RecommendedModelSelector.tsx

@@ -0,0 +1,87 @@
+"use client";
+
+import { useState } from "react";
+import { useRouter } from "next/navigation";
+import type { LlmModel } from "@/app/api/__generated__/models/llmModel";
+import { Button } from "@/components/atoms/Button/Button";
+import { setRecommendedModelAction } from "../actions";
+import { Star } from "@phosphor-icons/react";
+
+export function RecommendedModelSelector({ models }: { models: LlmModel[] }) {
+  const router = useRouter();
+  const enabledModels = models.filter((m) => m.is_enabled);
+  const currentRecommended = models.find((m) => m.is_recommended);
+
+  const [selectedModelId, setSelectedModelId] = useState<string>(
+    currentRecommended?.id || "",
+  );
+  const [isSaving, setIsSaving] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+
+  const hasChanges = selectedModelId !== (currentRecommended?.id || "");
+
+  async function handleSave() {
+    if (!selectedModelId) return;
+
+    setIsSaving(true);
+    setError(null);
+    try {
+      const formData = new FormData();
+      formData.set("model_id", selectedModelId);
+      await setRecommendedModelAction(formData);
+      router.refresh();
+    } catch (err) {
+      setError(err instanceof Error ? err.message : "Failed to save");
+    } finally {
+      setIsSaving(false);
+    }
+  }
+
+  return (
+    <div className="rounded-lg border border-border bg-card p-4">
+      <div className="mb-3 flex items-center gap-2">
+        <Star size={20} weight="fill" className="text-amber-500" />
+        <h3 className="text-sm font-semibold">Recommended Model</h3>
+      </div>
+      <p className="mb-3 text-xs text-muted-foreground">
+        The recommended model is shown as the default suggestion in model
+        selection dropdowns throughout the platform.
+      </p>
+
+      <div className="flex items-center gap-3">
+        <select
+          value={selectedModelId}
+          onChange={(e) => setSelectedModelId(e.target.value)}
+          className="flex-1 rounded-md border border-input bg-background px-3 py-2 text-sm"
+          disabled={isSaving}
+        >
+          <option value="">-- Select a model --</option>
+          {enabledModels.map((model) => (
+            <option key={model.id} value={model.id}>
+              {model.display_name} ({model.slug})
+            </option>
+          ))}
+        </select>
+
+        <Button
+          type="button"
+          variant="primary"
+          size="small"
+          onClick={handleSave}
+          disabled={!hasChanges || !selectedModelId || isSaving}
+        >
+          {isSaving ? "Saving..." : "Save"}
+        </Button>
+      </div>
+
+      {error && <p className="mt-2 text-xs text-destructive">{error}</p>}
+
+      {currentRecommended && !hasChanges && (
+        <p className="mt-2 text-xs text-muted-foreground">
+          Currently set to:{" "}
+          <span className="font-medium">{currentRecommended.display_name}</span>
+        </p>
+      )}
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/page.tsx

@@ -0,0 +1,14 @@
+import { withRoleAccess } from "@/lib/withRoleAccess";
+import { getLlmRegistryPageData } from "./useLlmRegistryPage";
+import { LlmRegistryDashboard } from "./components/LlmRegistryDashboard";
+
+async function LlmRegistryPage() {
+  const data = await getLlmRegistryPageData();
+  return <LlmRegistryDashboard {...data} />;
+}
+
+export default async function AdminLlmRegistryPage() {
+  const withAdminAccess = await withRoleAccess(["admin"]);
+  const ProtectedLlmRegistryPage = await withAdminAccess(LlmRegistryPage);
+  return <ProtectedLlmRegistryPage />;
+}

autogpt_platform/frontend/src/app/(platform)/admin/llms/useLlmRegistryPage.ts

@@ -0,0 +1,46 @@
+/**
+ * Server-side data fetching for LLM Registry page.
+ */
+
+import {
+  fetchLlmCreators,
+  fetchLlmMigrations,
+  fetchLlmModels,
+  fetchLlmProviders,
+} from "./actions";
+
+export async function getLlmRegistryPageData() {
+  // Fetch providers and models (required)
+  const [providersResponse, modelsResponse] = await Promise.all([
+    fetchLlmProviders(),
+    fetchLlmModels(),
+  ]);
+
+  // Fetch migrations separately with fallback (table might not exist yet)
+  let migrations: Awaited<ReturnType<typeof fetchLlmMigrations>>["migrations"] =
+    [];
+  try {
+    const migrationsResponse = await fetchLlmMigrations(false);
+    migrations = migrationsResponse.migrations;
+  } catch {
+    // Migrations table might not exist yet - that's ok, just show empty list
+    console.warn("Could not fetch migrations - table may not exist yet");
+  }
+
+  // Fetch creators separately with fallback (table might not exist yet)
+  let creators: Awaited<ReturnType<typeof fetchLlmCreators>>["creators"] = [];
+  try {
+    const creatorsResponse = await fetchLlmCreators();
+    creators = creatorsResponse.creators;
+  } catch {
+    // Creators table might not exist yet - that's ok, just show empty list
+    console.warn("Could not fetch creators - table may not exist yet");
+  }
+
+  return {
+    providers: providersResponse.providers,
+    models: modelsResponse.models,
+    migrations,
+    creators,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/AllBlocksContent/useAllBlockContent.tsx

@@ -7,8 +7,9 @@ import { BlockCategoryResponse } from "@/app/api/__generated__/models/blockCateg
 import { BlockResponse } from "@/app/api/__generated__/models/blockResponse";
 import * as Sentry from "@sentry/nextjs";
 import { getQueryClient } from "@/lib/react-query/queryClient";
-import { useState } from "react";
+import { useState, useEffect } from "react";
 import { useToast } from "@/components/molecules/Toast/use-toast";
+import BackendApi from "@/lib/autogpt-server-api";
 
 export const useAllBlockContent = () => {
   const { toast } = useToast();
@@ -93,6 +94,32 @@ export const useAllBlockContent = () => {
   const isErrorOnLoadingMore = (categoryName: string) =>
     errorLoadingCategories.has(categoryName);
 
+  // Listen for LLM registry refresh notifications
+  useEffect(() => {
+    const api = new BackendApi();
+    const queryClient = getQueryClient();
+
+    const handleNotification = (notification: any) => {
+      if (
+        notification?.type === "LLM_REGISTRY_REFRESH" ||
+        notification?.event === "registry_updated"
+      ) {
+        // Invalidate all block-related queries to force refresh
+        const categoriesQueryKey = getGetV2GetBuilderBlockCategoriesQueryKey();
+        queryClient.invalidateQueries({ queryKey: categoriesQueryKey });
+      }
+    };
+
+    const unsubscribe = api.onWebSocketMessage(
+      "notification",
+      handleNotification,
+    );
+
+    return () => {
+      unsubscribe();
+    };
+  }, []);
+
   return {
     data,
     isLoading,

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeHandle.tsx

@@ -41,6 +41,13 @@ const Dot: FC<{ isConnected: boolean; type?: string }> = memo(
 );
 Dot.displayName = "Dot";
 
+const getSchemaType = (schema: BlockIOSubSchema): string | undefined => {
+  if (schema && "type" in schema && typeof schema.type === "string") {
+    return schema.type;
+  }
+  return undefined;
+};
+
 const NodeHandle: FC<HandleProps> = ({
   keyName,
   schema,
@@ -50,7 +57,8 @@ const NodeHandle: FC<HandleProps> = ({
   title,
   className,
 }) => {
-  const typeClass = `text-sm ${getTypeTextColor(schema.type || "any")} ${
+  const schemaType = getSchemaType(schema);
+  const typeClass = `text-sm ${getTypeTextColor(schemaType || "any")} ${
     side === "left" ? "text-left" : "text-right"
   }`;
 
@@ -66,7 +74,7 @@ const NodeHandle: FC<HandleProps> = ({
         {isRequired ? "*" : ""}
       </span>
       <span className={`${typeClass} data-sentry-unmask flex items-end`}>
-        ({TYPE_NAME[schema.type as keyof typeof TYPE_NAME] || "any"})
+        ({TYPE_NAME[schemaType as keyof typeof TYPE_NAME] || "any"})
       </span>
     </div>
   );
@@ -95,7 +103,7 @@ const NodeHandle: FC<HandleProps> = ({
           className="group -ml-[38px]"
         >
           <div className="pointer-events-none flex items-center">
-            <Dot isConnected={isConnected} type={schema.type} />
+            <Dot isConnected={isConnected} type={schemaType} />
             {label}
           </div>
         </Handle>
@@ -118,7 +126,7 @@ const NodeHandle: FC<HandleProps> = ({
         >
           <div className="pointer-events-none flex items-center">
             {label}
-            <Dot isConnected={isConnected} type={schema.type} />
+            <Dot isConnected={isConnected} type={schemaType} />
           </div>
         </Handle>
       </div>

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeInputs.tsx

@@ -610,8 +610,11 @@ const NodeOneOfDiscriminatorField: FC<{
 
     return oneOfVariants
       .map((variant) => {
-        const variantDiscValue = variant.properties?.[discriminatorProperty]
-          ?.const as string; // NOTE: can discriminators only be strings?
+        const discProperty = variant.properties?.[discriminatorProperty];
+        const variantDiscValue =
+          discProperty && "const" in discProperty
+            ? (discProperty.const as string)
+            : undefined; // NOTE: can discriminators only be strings?
 
         return {
           value: variantDiscValue,
@@ -1124,9 +1127,47 @@ const NodeStringInput: FC<{
   displayName,
 }) => {
   value ||= schema.default || "";
+
+  // Check if we have options with labels (e.g., LLM model picker)
+  const hasOptions = schema.options && schema.options.length > 0;
+  const hasEnum = schema.enum && schema.enum.length > 0;
+
+  // Helper to get display label for a value
+  const getDisplayLabel = (val: string) => {
+    if (hasOptions) {
+      const option = schema.options!.find((opt) => opt.value === val);
+      return option?.label || beautifyString(val);
+    }
+    return beautifyString(val);
+  };
+
   return (
     <div className={className}>
-      {schema.enum && schema.enum.length > 0 ? (
+      {hasOptions ? (
+        // Render options with proper labels (used by LLM model picker)
+        <Select
+          defaultValue={value}
+          onValueChange={(newValue) => handleInputChange(selfKey, newValue)}
+        >
+          <SelectTrigger>
+            <SelectValue placeholder={schema.placeholder || displayName}>
+              {value ? getDisplayLabel(value) : undefined}
+            </SelectValue>
+          </SelectTrigger>
+          <SelectContent className="nodrag">
+            {schema.options!.map((option, index) => (
+              <SelectItem
+                key={index}
+                value={option.value}
+                title={option.description}
+              >
+                {option.label}
+              </SelectItem>
+            ))}
+          </SelectContent>
+        </Select>
+      ) : hasEnum ? (
+        // Fallback to enum with beautified strings
         <Select
           defaultValue={value}
           onValueChange={(newValue) => handleInputChange(selfKey, newValue)}
@@ -1135,8 +1176,8 @@ const NodeStringInput: FC<{
             <SelectValue placeholder={schema.placeholder || displayName} />
           </SelectTrigger>
           <SelectContent className="nodrag">
-            {schema.enum
-              .filter((option) => option)
+            {schema
+              .enum!.filter((option) => option)
               .map((option, index) => (
                 <SelectItem key={index} value={option}>
                   {beautifyString(option)}

autogpt_platform/frontend/src/components/atoms/Table/Table.tsx

@@ -0,0 +1,123 @@
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const Table = React.forwardRef<
+  HTMLTableElement,
+  React.HTMLAttributes<HTMLTableElement>
+>(({ className, ...props }, ref) => (
+  <div className="relative w-full overflow-auto">
+    <table
+      ref={ref}
+      className={cn("w-full caption-bottom text-sm", className)}
+      {...props}
+    />
+  </div>
+));
+Table.displayName = "Table";
+
+const TableHeader = React.forwardRef<
+  HTMLTableSectionElement,
+  React.HTMLAttributes<HTMLTableSectionElement>
+>(({ className, ...props }, ref) => (
+  <thead ref={ref} className={cn("[&_tr]:border-b", className)} {...props} />
+));
+TableHeader.displayName = "TableHeader";
+
+const TableBody = React.forwardRef<
+  HTMLTableSectionElement,
+  React.HTMLAttributes<HTMLTableSectionElement>
+>(({ className, ...props }, ref) => (
+  <tbody
+    ref={ref}
+    className={cn("[&_tr:last-child]:border-0", className)}
+    {...props}
+  />
+));
+TableBody.displayName = "TableBody";
+
+const TableFooter = React.forwardRef<
+  HTMLTableSectionElement,
+  React.HTMLAttributes<HTMLTableSectionElement>
+>(({ className, ...props }, ref) => (
+  <tfoot
+    ref={ref}
+    className={cn(
+      "border-t bg-neutral-100/50 font-medium dark:bg-neutral-800/50 [&>tr]:last:border-b-0",
+      className,
+    )}
+    {...props}
+  />
+));
+TableFooter.displayName = "TableFooter";
+
+const TableRow = React.forwardRef<
+  HTMLTableRowElement,
+  React.HTMLAttributes<HTMLTableRowElement>
+>(({ className, ...props }, ref) => (
+  <tr
+    ref={ref}
+    className={cn(
+      "border-b transition-colors data-[state=selected]:bg-neutral-100 hover:bg-neutral-100/50 dark:data-[state=selected]:bg-neutral-800 dark:hover:bg-neutral-800/50",
+      className,
+    )}
+    {...props}
+  />
+));
+TableRow.displayName = "TableRow";
+
+const TableHead = React.forwardRef<
+  HTMLTableCellElement,
+  React.ThHTMLAttributes<HTMLTableCellElement>
+>(({ className, ...props }, ref) => (
+  <th
+    ref={ref}
+    className={cn(
+      "h-10 px-2 text-left align-middle font-medium text-neutral-500 dark:text-neutral-400 [&:has([role=checkbox])]:pr-0 [&>[role=checkbox]]:translate-y-[2px]",
+      className,
+    )}
+    {...props}
+  />
+));
+TableHead.displayName = "TableHead";
+
+const TableCell = React.forwardRef<
+  HTMLTableCellElement,
+  React.TdHTMLAttributes<HTMLTableCellElement>
+>(({ className, ...props }, ref) => (
+  <td
+    ref={ref}
+    className={cn(
+      "p-2 align-middle [&:has([role=checkbox])]:pr-0 [&>[role=checkbox]]:translate-y-[2px]",
+      className,
+    )}
+    {...props}
+  />
+));
+TableCell.displayName = "TableCell";
+
+const TableCaption = React.forwardRef<
+  HTMLTableCaptionElement,
+  React.HTMLAttributes<HTMLTableCaptionElement>
+>(({ className, ...props }, ref) => (
+  <caption
+    ref={ref}
+    className={cn(
+      "mt-4 text-sm text-neutral-500 dark:text-neutral-400",
+      className,
+    )}
+    {...props}
+  />
+));
+TableCaption.displayName = "TableCaption";
+
+export {
+  Table,
+  TableHeader,
+  TableBody,
+  TableFooter,
+  TableHead,
+  TableRow,
+  TableCell,
+  TableCaption,
+};

autogpt_platform/frontend/src/components/renderers/input-renderer/utils/input-schema-pre-processor.ts

@@ -1,8 +1,19 @@
 import { RJSFSchema } from "@rjsf/utils";
 
+/**
+ * Options type for fields with label/value pairs (e.g., LLM model picker)
+ */
+type SchemaOption = {
+  label: string;
+  value: string;
+  group?: string;
+  description?: string;
+};
+
 /**
  * Pre-processes the input schema to ensure all properties have a type defined.
  * If a property doesn't have a type, it assigns a union of all supported JSON Schema types.
+ * Also converts custom 'options' array to RJSF's enum/enumNames format.
  */
 export function preprocessInputSchema(schema: RJSFSchema): RJSFSchema {
   if (!schema || typeof schema !== "object") {
@@ -19,6 +30,20 @@ export function preprocessInputSchema(schema: RJSFSchema): RJSFSchema {
       if (property && typeof property === "object") {
         const processedProperty = { ...property };
 
+        // Convert custom 'options' array to RJSF's enum/enumNames format
+        // This enables proper label display for dropdowns like the LLM model picker
+        if (
+          (processedProperty as any).options &&
+          Array.isArray((processedProperty as any).options) &&
+          (processedProperty as any).options.length > 0
+        ) {
+          const options = (processedProperty as any).options as SchemaOption[];
+          processedProperty.enum = options.map((opt) => opt.value);
+          (processedProperty as any).enumNames = options.map(
+            (opt) => opt.label,
+          );
+        }
+
         // Only add type if no type is defined AND no anyOf/oneOf/allOf is present
         if (
           !processedProperty.type &&

autogpt_platform/frontend/src/hooks/useAgentGraph.tsx

@@ -77,17 +77,45 @@ export default function useAgentGraph(
 
   // Load available blocks & flows (stable - only loads once)
   useEffect(() => {
-    api
-      .getBlocks()
-      .then((blocks) => {
-        setAllBlocks(blocks);
-      })
-      .catch();
+    const loadBlocks = () => {
+      api
+        .getBlocks()
+        .then((blocks) => {
+          setAllBlocks(blocks);
+        })
+        .catch();
+    };
 
-    api
-      .listGraphs()
-      .then((flows) => setAvailableFlows(flows))
-      .catch();
+    const loadFlows = () => {
+      api
+        .listGraphs()
+        .then((flows) => setAvailableFlows(flows))
+        .catch();
+    };
+
+    // Initial load
+    loadBlocks();
+    loadFlows();
+
+    // Listen for LLM registry refresh notifications to reload blocks
+    const deregisterRegistryRefresh = api.onWebSocketMessage(
+      "notification",
+      (notification) => {
+        if (
+          notification?.type === "LLM_REGISTRY_REFRESH" ||
+          notification?.event === "registry_updated"
+        ) {
+          console.log(
+            "Received LLM registry refresh notification, reloading blocks...",
+          );
+          loadBlocks();
+        }
+      },
+    );
+
+    return () => {
+      deregisterRegistryRefresh();
+    };
   }, [api]);
 
   // Subscribe to execution events

autogpt_platform/frontend/src/lib/autogpt-server-api/client.ts

@@ -43,6 +43,8 @@ import type {
   LibraryAgentPresetUpdatable,
   LibraryAgentResponse,
   LibraryAgentSortEnum,
+  LlmModel,
+  LlmModelCreator,
   MyAgentsResponse,
   NodeExecutionResult,
   NotificationPreference,
@@ -52,6 +54,19 @@ import type {
   ProfileDetails,
   RefundRequest,
   ReviewSubmissionRequest,
+  CreateLlmModelRequest,
+  UpdateLlmModelRequest,
+  ToggleLlmModelRequest,
+  ToggleLlmModelResponse,
+  LlmModelMigration,
+  LlmMigrationsResponse,
+  RevertMigrationResponse,
+  UpsertLlmProviderRequest,
+  UpsertLlmCreatorRequest,
+  LlmModelsResponse,
+  LlmCreatorsResponse,
+  LlmProvider,
+  LlmProvidersResponse,
   Schedule,
   ScheduleCreatable,
   ScheduleID,
@@ -378,6 +393,143 @@ export default class BackendAPI {
     );
   }
 
+  ////////////////////////////////////////
+  /////////////// LLM MODELS /////////////
+  ////////////////////////////////////////
+
+  listLlmModels(): Promise<LlmModelsResponse> {
+    return this._get("/llm/models");
+  }
+
+  listLlmProviders(includeModels = true): Promise<LlmProvidersResponse> {
+    const query = includeModels ? { include_models: true } : undefined;
+    return this._get("/llm/providers", query);
+  }
+
+  listAdminLlmProviders(includeModels = true): Promise<LlmProvidersResponse> {
+    const query = includeModels ? { include_models: true } : undefined;
+    return this._get("/llm/admin/llm/providers", query);
+  }
+
+  createAdminLlmProvider(
+    payload: UpsertLlmProviderRequest,
+  ): Promise<LlmProvider> {
+    return this._request("POST", "/llm/admin/llm/providers", payload);
+  }
+
+  updateAdminLlmProvider(
+    providerId: string,
+    payload: UpsertLlmProviderRequest,
+  ): Promise<LlmProvider> {
+    return this._request(
+      "PATCH",
+      `/llm/admin/llm/providers/${providerId}`,
+      payload,
+    );
+  }
+
+  listAdminLlmModels(providerId?: string): Promise<LlmModelsResponse> {
+    const query = providerId ? { provider_id: providerId } : undefined;
+    return this._get("/llm/admin/llm/models", query);
+  }
+
+  createAdminLlmModel(payload: CreateLlmModelRequest): Promise<LlmModel> {
+    return this._request("POST", "/llm/admin/llm/models", payload);
+  }
+
+  updateAdminLlmModel(
+    modelId: string,
+    payload: UpdateLlmModelRequest,
+  ): Promise<LlmModel> {
+    return this._request("PATCH", `/llm/admin/llm/models/${modelId}`, payload);
+  }
+
+  toggleAdminLlmModel(
+    modelId: string,
+    payload: ToggleLlmModelRequest,
+  ): Promise<ToggleLlmModelResponse> {
+    return this._request(
+      "PATCH",
+      `/llm/admin/llm/models/${modelId}/toggle`,
+      payload,
+    );
+  }
+
+  getAdminLlmModelUsage(
+    modelId: string,
+  ): Promise<{ model_slug: string; node_count: number }> {
+    return this._get(`/llm/admin/llm/models/${modelId}/usage`);
+  }
+
+  deleteAdminLlmModel(
+    modelId: string,
+    replacementModelSlug: string,
+  ): Promise<{
+    deleted_model_slug: string;
+    deleted_model_display_name: string;
+    replacement_model_slug: string;
+    nodes_migrated: number;
+    message: string;
+  }> {
+    return this._request("DELETE", `/llm/admin/llm/models/${modelId}`, {
+      replacement_model_slug: replacementModelSlug,
+    });
+  }
+
+  // Migration management
+  listAdminLlmMigrations(
+    includeReverted: boolean = false,
+  ): Promise<LlmMigrationsResponse> {
+    return this._get(
+      `/llm/admin/llm/migrations?include_reverted=${includeReverted}`,
+    );
+  }
+
+  getAdminLlmMigration(migrationId: string): Promise<LlmModelMigration> {
+    return this._get(`/llm/admin/llm/migrations/${migrationId}`);
+  }
+
+  revertAdminLlmMigration(
+    migrationId: string,
+  ): Promise<RevertMigrationResponse> {
+    return this._request(
+      "POST",
+      `/llm/admin/llm/migrations/${migrationId}/revert`,
+    );
+  }
+
+  // Creator management
+  listAdminLlmCreators(): Promise<LlmCreatorsResponse> {
+    return this._get("/llm/admin/llm/creators");
+  }
+
+  getAdminLlmCreator(creatorId: string): Promise<LlmModelCreator> {
+    return this._get(`/llm/admin/llm/creators/${creatorId}`);
+  }
+
+  createAdminLlmCreator(
+    payload: UpsertLlmCreatorRequest,
+  ): Promise<LlmModelCreator> {
+    return this._request("POST", "/llm/admin/llm/creators", payload);
+  }
+
+  updateAdminLlmCreator(
+    creatorId: string,
+    payload: UpsertLlmCreatorRequest,
+  ): Promise<LlmModelCreator> {
+    return this._request(
+      "PATCH",
+      `/llm/admin/llm/creators/${creatorId}`,
+      payload,
+    );
+  }
+
+  deleteAdminLlmCreator(
+    creatorId: string,
+  ): Promise<{ success: boolean; message: string }> {
+    return this._request("DELETE", `/llm/admin/llm/creators/${creatorId}`);
+  }
+
   // API Key related requests
   async createAPIKey(
     name: string,

autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts

@@ -178,9 +178,17 @@ export type BlockIOTableSubSchema = BlockIOSubSchemaMeta & {
   secret?: boolean;
 };
 
+export type BlockIOStringSubSchemaOption = {
+  label: string;
+  value: string;
+  group?: string;
+  description?: string;
+};
+
 export type BlockIOStringSubSchema = BlockIOSubSchemaMeta & {
   type: "string";
   enum?: string[];
+  options?: BlockIOStringSubSchemaOption[];
   secret?: true;
   const?: string;
   default?: string;
@@ -244,10 +252,8 @@ export type BlockIONullSubSchema = BlockIOSubSchemaMeta & {
 
 // At the time of writing, combined schemas only occur on the first nested level in a
 // block schema. It is typed this way to make the use of these objects less tedious.
-type BlockIOCombinedTypeSubSchema = BlockIOSubSchemaMeta & {
-  type: never;
-  const: never;
-} & (
+type BlockIOCombinedTypeSubSchema = BlockIOSubSchemaMeta &
+  (
     | {
         allOf: [BlockIOSimpleTypeSubSchema];
         secret?: boolean;
@@ -262,6 +268,171 @@ type BlockIOCombinedTypeSubSchema = BlockIOSubSchemaMeta & {
     | BlockIODiscriminatedOneOfSubSchema
   );
 
+////////////////////////////////////////
+///////////// LLM REGISTRY /////////////
+////////////////////////////////////////
+
+export type LlmCostUnit = "RUN" | "TOKENS";
+
+export type LlmModelCostInput = {
+  unit?: LlmCostUnit;
+  credit_cost: number;
+  credential_provider: string;
+  credential_id?: string | null;
+  credential_type?: string | null;
+  currency?: string | null;
+  metadata?: Record<string, any>;
+};
+
+export type LlmModelCost = LlmModelCostInput & {
+  id: string;
+};
+
+// Creator represents the organization that created/trained the model (e.g., OpenAI, Meta)
+// This is distinct from Provider who hosts/serves the model (e.g., OpenRouter)
+export type LlmModelCreator = {
+  id: string;
+  name: string;
+  display_name: string;
+  description?: string | null;
+  website_url?: string | null;
+  logo_url?: string | null;
+  metadata: Record<string, any>;
+};
+
+export type LlmModel = {
+  id: string;
+  slug: string;
+  display_name: string;
+  description?: string | null;
+  provider_id: string;
+  creator_id?: string | null;
+  creator?: LlmModelCreator | null;
+  context_window: number;
+  max_output_tokens?: number | null;
+  is_enabled: boolean;
+  capabilities: Record<string, any>;
+  metadata: Record<string, any>;
+  costs: LlmModelCost[];
+};
+
+export type LlmProvider = {
+  id: string;
+  name: string;
+  display_name: string;
+  description?: string | null;
+  default_credential_provider?: string | null;
+  default_credential_id?: string | null;
+  default_credential_type?: string | null;
+  supports_tools: boolean;
+  supports_json_output: boolean;
+  supports_reasoning: boolean;
+  supports_parallel_tool: boolean;
+  metadata: Record<string, any>;
+  models?: LlmModel[];
+};
+
+export type LlmProvidersResponse = {
+  providers: LlmProvider[];
+};
+
+export type LlmModelsResponse = {
+  models: LlmModel[];
+};
+
+export type LlmCreatorsResponse = {
+  creators: LlmModelCreator[];
+};
+
+export type UpsertLlmCreatorRequest = {
+  name: string;
+  display_name: string;
+  description?: string | null;
+  website_url?: string | null;
+  logo_url?: string | null;
+  metadata?: Record<string, any>;
+};
+
+export type UpsertLlmProviderRequest = {
+  name: string;
+  display_name: string;
+  description?: string | null;
+  default_credential_provider?: string | null;
+  default_credential_id?: string | null;
+  default_credential_type?: string | null;
+  supports_tools?: boolean;
+  supports_json_output?: boolean;
+  supports_reasoning?: boolean;
+  supports_parallel_tool?: boolean;
+  metadata?: Record<string, any>;
+};
+
+export type CreateLlmModelRequest = {
+  slug: string;
+  display_name: string;
+  description?: string | null;
+  provider_id: string;
+  creator_id?: string | null;
+  context_window: number;
+  max_output_tokens?: number | null;
+  is_enabled?: boolean;
+  capabilities?: Record<string, any>;
+  metadata?: Record<string, any>;
+  costs: LlmModelCostInput[];
+};
+
+export type UpdateLlmModelRequest = {
+  display_name?: string;
+  description?: string | null;
+  provider_id?: string;
+  creator_id?: string | null;
+  context_window?: number;
+  max_output_tokens?: number | null;
+  is_enabled?: boolean;
+  capabilities?: Record<string, any>;
+  metadata?: Record<string, any>;
+  costs?: LlmModelCostInput[];
+};
+
+export type ToggleLlmModelRequest = {
+  is_enabled: boolean;
+  migrate_to_slug?: string;
+  migration_reason?: string;
+  custom_credit_cost?: number;
+};
+
+export type ToggleLlmModelResponse = {
+  model: LlmModel;
+  nodes_migrated: number;
+  migrated_to_slug?: string | null;
+  migration_id?: string | null;
+};
+
+// Migration tracking types
+export type LlmModelMigration = {
+  id: string;
+  source_model_slug: string;
+  target_model_slug: string;
+  reason?: string | null;
+  node_count: number;
+  custom_credit_cost?: number | null;
+  is_reverted: boolean;
+  created_at: string;
+  reverted_at?: string | null;
+};
+
+export type LlmMigrationsResponse = {
+  migrations: LlmModelMigration[];
+};
+
+export type RevertMigrationResponse = {
+  migration_id: string;
+  source_model_slug: string;
+  target_model_slug: string;
+  nodes_reverted: number;
+  message: string;
+};
+
 export type BlockIOOneOfSubSchema = {
   oneOf: BlockIOSimpleTypeSubSchema[];
   default?: string | number | boolean | null;
@@ -1123,16 +1294,21 @@ function _handleStringSchema(strSchema: BlockIOStringSubSchema): DataType {
 }
 
 function _handleSingleTypeSchema(subSchema: BlockIOSubSchema): DataType {
-  if (subSchema.type === "string") {
+  const schemaType =
+    "type" in subSchema && typeof subSchema.type === "string"
+      ? subSchema.type
+      : undefined;
+
+  if (schemaType === "string") {
     return _handleStringSchema(subSchema as BlockIOStringSubSchema);
   }
-  if (subSchema.type === "boolean") {
+  if (schemaType === "boolean") {
     return DataType.BOOLEAN;
   }
-  if (subSchema.type === "number" || subSchema.type === "integer") {
+  if (schemaType === "number" || schemaType === "integer") {
     return DataType.NUMBER;
   }
-  if (subSchema.type === "array") {
+  if (schemaType === "array") {
     // Check for table format first
     if ("format" in subSchema && subSchema.format === "table") {
       return DataType.TABLE;
@@ -1143,7 +1319,7 @@ function _handleSingleTypeSchema(subSchema: BlockIOSubSchema): DataType {
     // }
     return DataType.ARRAY;
   }
-  if (subSchema.type === "object") {
+  if (schemaType === "object") {
     if (
       ("additionalProperties" in subSchema && subSchema.additionalProperties) ||
       !("properties" in subSchema)
@@ -1152,7 +1328,7 @@ function _handleSingleTypeSchema(subSchema: BlockIOSubSchema): DataType {
     }
     if (
       Object.values(subSchema.properties).every(
-        (prop) => prop.type === "boolean",
+        (prop) => "type" in prop && prop.type === "boolean",
       )
     ) {
       return DataType.MULTI_SELECT; // if all props are boolean => multi-select

autogpt_platform/frontend/src/lib/utils.ts

@@ -234,17 +234,20 @@ export function fillObjectDefaultsFromSchema(
       // Apply simple default values
       obj[key] ??= propertySchema.default;
     } else if (
+      "type" in propertySchema &&
       propertySchema.type === "object" &&
       "properties" in propertySchema
     ) {
       // Recursively fill defaults for nested objects
       obj[key] = fillObjectDefaultsFromSchema(obj[key] ?? {}, propertySchema);
-    } else if (propertySchema.type === "array") {
+    } else if ("type" in propertySchema && propertySchema.type === "array") {
       obj[key] ??= [];
       // If the array items are objects, fill their defaults as well
       if (
         Array.isArray(obj[key]) &&
-        propertySchema.items?.type === "object" &&
+        propertySchema.items &&
+        "type" in propertySchema.items &&
+        propertySchema.items.type === "object" &&
         "properties" in propertySchema.items
       ) {
         for (const item of obj[key]) {