feat(wizard): rework agent onboarding flow (#2471)

* feat(wizard): rework agent onboarding flow

* fix(web): support LAN development access

* fix(wizard): parse ranked model selection entries

* feat(wizard): add inbound bot verification

* feat(wizard): add floating page bot verification

* fix(wizard): repair HTTP bot inbound test setup

* feat(wizard): streamline custom model onboarding

* feat(wizard): label page bot test preview

* style(space): apply ruff formatting

* fix(wizard): polish AI engine onboarding

* fix(wizard): clarify local account message test

* feat(wizard): animate AI engine transitions

* fix(wizard): align AI engine setup headers

---------

Co-authored-by: langbot-dev <langbot@users.noreply.github.com>
Co-authored-by: RockChinQ <rockchinq@gmail.com>

src/langbot/pkg/api/http/controller/groups/pipelines/pipelines.py

@@ -39,7 +39,13 @@ class PipelinesRouterGroup(group.RouterGroup):
             permission=Permission.RESOURCE_MANAGE,
         )
         async def _(request_context: RequestContext) -> str:
-            pipeline_uuid = await self.ap.pipeline_service.create_pipeline(request_context, await quart.request.json)
+            pipeline_data = await quart.request.json
+            create_as_default = pipeline_data.get('is_default') is True
+            pipeline_uuid = await self.ap.pipeline_service.create_pipeline(
+                request_context,
+                pipeline_data,
+                default=create_as_default,
+            )
             return self.success(data={'uuid': pipeline_uuid})
 
         @self.route(

src/langbot/pkg/api/http/controller/groups/platform/bots.py

@@ -113,6 +113,24 @@ class BotsRouterGroup(group.RouterGroup):
             )
             return self.success(data={'sent': True})
 
+        @self.route(
+            '/<bot_uuid>/test-inbound',
+            methods=['POST'],
+            auth_type=group.AuthType.USER_TOKEN,
+            permission=Permission.RESOURCE_MANAGE,
+        )
+        async def _(bot_uuid: str, request_context: RequestContext) -> str:
+            json_data = await quart.request.get_json(silent=True) or {}
+            try:
+                result = await self.ap.bot_service.send_http_bot_test_message(
+                    request_context,
+                    bot_uuid,
+                    str(json_data.get('message') or ''),
+                )
+            except ValueError as exc:
+                return self.http_status(400, -1, str(exc))
+            return self.success(data=result)
+
         @self.route(
             '/<bot_uuid>/admins',
             methods=['GET'],

src/langbot/pkg/api/http/controller/groups/system.py

@@ -206,6 +206,20 @@ class SystemRouterGroup(group.RouterGroup):
 
             return self.success(data={})
 
+        @self.route(
+            '/wizard/recommended-model',
+            methods=['GET'],
+            auth_type=group.AuthType.USER_TOKEN,
+            permission=Permission.RESOURCE_MANAGE,
+        )
+        async def _(request_context: RequestContext) -> str:
+            """Resolve Space's best available chat model to this Workspace."""
+            try:
+                model = await self.ap.space_service.get_recommended_chat_model(request_context)
+            except ValueError as exc:
+                return self.http_status(503, -1, str(exc))
+            return self.success(data=model)
+
         @self.route(
             '/tasks',
             methods=['GET'],

src/langbot/pkg/api/http/service/bot.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import uuid
+import json
 import sqlalchemy
 
 from ....core import app
@@ -8,6 +9,8 @@ from ....entity.persistence import bot as persistence_bot
 from ....entity.persistence import pipeline as persistence_pipeline
 from ....workspace.errors import WorkspaceNotFoundError
 from .tenant import TenantContext, require_workspace_uuid, scope_statement
+from ....utils import httpclient
+from ....platform.sources import http_bot_signing
 
 
 class BotService:
@@ -80,6 +83,7 @@ class BotService:
             'wecomcs',
             'LINE',
             'lark',
+            'http_bot',
         ]:
             webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
             extra_webhook_prefix = self.ap.instance_config.data['api'].get('extra_webhook_prefix', '')
@@ -216,6 +220,53 @@ class BotService:
 
         return [log.to_json() for log in logs], total_count
 
+    async def send_http_bot_test_message(
+        self,
+        context: TenantContext,
+        bot_uuid: str,
+        message: str,
+    ) -> dict:
+        """Send a signed test message through the HTTP Bot public ingress."""
+        bot = await self.get_bot(context, bot_uuid, include_secret=True)
+        if bot is None:
+            raise WorkspaceNotFoundError('Bot not found')
+        if bot.get('adapter') != 'http_bot':
+            raise ValueError('Inbound test is only available for HTTP Bot')
+        if not bot.get('enable'):
+            raise ValueError('Bot must be enabled before sending a test message')
+
+        text = message.strip()
+        if not text or len(text) > 2000:
+            raise ValueError('Test message must contain 1 to 2000 characters')
+
+        payload = {
+            'session_id': f'wizard-{uuid.uuid4().hex}',
+            'sender': {'id': 'wizard-user', 'name': 'Wizard Test'},
+            'message': [{'type': 'Plain', 'text': text}],
+        }
+        body = json.dumps(payload, ensure_ascii=False, separators=(',', ':')).encode()
+        config = bot.get('adapter_config') or {}
+        headers = {'Content-Type': 'application/json'}
+        if config.get('signature_required', True):
+            secret = str(config.get('inbound_secret') or '')
+            if not secret:
+                raise ValueError('HTTP Bot inbound signing secret is required')
+            timestamp, signature = http_bot_signing.sign(secret, body)
+            headers[http_bot_signing.HEADER_TIMESTAMP] = timestamp
+            headers[http_bot_signing.HEADER_SIGNATURE] = signature
+
+        port = int(self.ap.instance_config.data.get('api', {}).get('port', 5300))
+        session = httpclient.get_session()
+        async with session.post(
+            f'http://127.0.0.1:{port}/bots/{bot_uuid}',
+            data=body,
+            headers=headers,
+        ) as response:
+            result = await httpclient.read_json_limited(response)
+            if response.status not in {200, 202}:
+                raise ValueError(result.get('msg') or f'HTTP Bot test failed with status {response.status}')
+            return result.get('data') or {}
+
     async def send_message(
         self,
         context: TenantContext,

src/langbot/pkg/api/http/service/space.py

@@ -11,6 +11,9 @@ import sqlalchemy
 from ....core import app
 from ....entity.persistence import user
 from ....entity.dto.space_model import SpaceModel
+from ....entity.dto.space_model import SpaceModelSelection
+from ....entity.persistence import model as persistence_model
+from ....cloud.model_catalog import LANGBOT_MODELS_PROVIDER_REQUESTER
 
 
 _CREDITS_CACHE_TTL_SECONDS = 60
@@ -238,3 +241,76 @@ class SpaceService:
                 raise ValueError(f'Failed to get models: {data.get("msg")}')
             models_data = data.get('data', {}).get('models', [])
             return [SpaceModel.model_validate(model_dict) for model_dict in models_data]
+
+    async def get_model_selection(self, category: str) -> typing.List[SpaceModelSelection]:
+        """Return Space models in the availability-ranked selection order."""
+        space_url = self._get_space_config()['url']
+        session = httpclient.get_session()
+        async with session.get(
+            f'{space_url}/api/v1/models/selection',
+            params={'category': category},
+        ) as response:
+            if response.status != 200:
+                error = await httpclient.read_text_limited(response)
+                raise ValueError(f'Failed to get model selection: {error}')
+            payload = await httpclient.read_json_limited(response)
+            if payload.get('code') != 0:
+                raise ValueError(f'Failed to get model selection: {payload.get("msg")}')
+
+            data = payload.get('data', [])
+            if isinstance(data, dict):
+                data = data.get('models', data.get('items', []))
+            if not isinstance(data, list):
+                raise ValueError('Failed to get model selection: invalid response')
+
+            models = []
+            for selection in data:
+                if isinstance(selection, dict) and isinstance(selection.get('model'), dict):
+                    models.append(selection['model'])
+                else:
+                    models.append(selection)
+            return [SpaceModelSelection.model_validate(model) for model in models]
+
+    async def get_recommended_chat_model(self, context: typing.Any) -> dict:
+        """Resolve Space's first ranked chat model to a local Workspace model."""
+        selection = await self.get_model_selection('chat')
+        if not selection:
+            raise ValueError('No recommended chat model is available')
+        recommended = selection[0]
+
+        async def find_local_model():
+            result = await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.select(persistence_model.LLMModel)
+                .join(
+                    persistence_model.ModelProvider,
+                    sqlalchemy.and_(
+                        persistence_model.ModelProvider.workspace_uuid == persistence_model.LLMModel.workspace_uuid,
+                        persistence_model.ModelProvider.uuid == persistence_model.LLMModel.provider_uuid,
+                    ),
+                )
+                .where(
+                    persistence_model.LLMModel.workspace_uuid == context.workspace_uuid,
+                    persistence_model.ModelProvider.requester == LANGBOT_MODELS_PROVIDER_REQUESTER,
+                    sqlalchemy.or_(
+                        persistence_model.LLMModel.uuid == recommended.uuid,
+                        persistence_model.LLMModel.name == recommended.model_id,
+                    ),
+                )
+            )
+            return result.first()
+
+        local_model = await find_local_model()
+        if local_model is None:
+            # OSS synchronizes the public catalog locally. Refresh once in case
+            # the recommendation was published after this process started.
+            from ..context import ExecutionContext
+
+            try:
+                await self.ap.model_mgr.sync_new_models_from_space(ExecutionContext.from_request(context))
+            except Exception:
+                pass
+            local_model = await find_local_model()
+
+        if local_model is None:
+            raise ValueError('Recommended chat model is not available in this Workspace')
+        return {'uuid': local_model.uuid, 'name': local_model.name}

src/langbot/pkg/api/mcp/server.py

@@ -147,7 +147,16 @@ class LangBotMCPServer:
         )
         async def create_pipeline(pipeline_data: dict) -> str:
             context = _authorized(Permission.RESOURCE_MANAGE)
-            return _dump({'uuid': await ap.pipeline_service.create_pipeline(context, pipeline_data)})
+            create_as_default = pipeline_data.get('is_default') is True
+            return _dump(
+                {
+                    'uuid': await ap.pipeline_service.create_pipeline(
+                        context,
+                        pipeline_data,
+                        default=create_as_default,
+                    )
+                }
+            )
 
         @mcp.tool(description='Update a pipeline by UUID. `pipeline_data` matches the PUT body.')
         async def update_pipeline(pipeline_uuid: str, pipeline_data: dict) -> str: