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>
This commit is contained in:
Dongchuan Fu
2026-08-28 01:30:30 +08:00
committed by GitHub
parent 855ae2bdba
commit be3734ffda
33 changed files with 2319 additions and 271 deletions
@@ -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(
@@ -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'],
@@ -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'],
+51
View File
@@ -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,
+76
View File
@@ -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}
+10 -1
View File
@@ -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:
@@ -47,3 +47,10 @@ class SpaceModel(pydantic.BaseModel):
status: str
created_at: str | None = None
updated_at: str | None = None
class SpaceModelSelection(pydantic.BaseModel):
"""Minimal model identity returned by the ranked selection endpoint."""
uuid: str
model_id: str