fix(assistant): align resource tools with application services

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

@@ -253,7 +253,8 @@ class AssistantService:
                 await self._save(context, conversation, 'running')
                 try:
                     result = await execute_tool(self.ap, context, func['name'], json.loads(func['arguments'] or '{}'))
-                except Exception:
+                except Exception as exc:
+                    self.ap.logger.warning('Management assistant tool %s failed (%s)', func['name'], type(exc).__name__)
                     self._append_result(
                         conversation,
                         call,

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

@@ -89,13 +89,18 @@ async def execute_tool(ap, context, name: str, arguments: dict):
     args = validate_call(context, name, arguments).model_dump(mode='json')
     if name == 'list_resources':
         readers = {
-            'models': ap.model_service.get_llm_models,
-            'embedding_models': ap.model_service.get_embedding_models,
+            'models': ap.llm_model_service.get_llm_models,
+            'embedding_models': ap.embedding_models_service.get_embedding_models,
             'pipelines': ap.pipeline_service.get_pipelines,
             'knowledge_bases': ap.knowledge_service.get_knowledge_bases,
             'knowledge_engines': ap.knowledge_service.list_knowledge_engines,
         }
-        return redact_secrets(await readers[args['kind']](context))
+        resources = await readers[args['kind']](context)
+        if args['kind'] != 'knowledge_engines':
+            # Lists discover resources; get_pipeline / get_knowledge_schema supply configuration details.
+            fields = ('uuid', 'name', 'description', 'abilities', 'knowledge_engine_plugin_id')
+            resources = [{key: item[key] for key in fields if key in item} for item in resources]
+        return {'total': len(resources), 'items': redact_secrets(resources)}
     if name == 'get_pipeline':
         return await ap.pipeline_service.get_pipeline(context, args['pipeline_uuid'])
     if name == 'get_knowledge_schema':

tests/unit_tests/api/test_management_assistant.py

@@ -3,7 +3,7 @@
 import asyncio
 import logging
 from types import SimpleNamespace
-from unittest.mock import AsyncMock
+from unittest.mock import AsyncMock, create_autospec
 
 import pytest
 import sqlalchemy as sa
@@ -13,7 +13,7 @@ from langbot_plugin.api.entities.builtin.provider.message import Message
 from langbot.pkg.api.http.authz import Permission
 from langbot.pkg.api.http.context import RequestContext, PrincipalContext, PrincipalType, WorkspaceContext
 from langbot.pkg.api.http.service.assistant import AssistantError, AssistantService
-from langbot.pkg.api.http.service.assistant_tools import validate_call
+from langbot.pkg.api.http.service.assistant_tools import execute_tool, validate_call
 from langbot.pkg.entity.persistence.assistant import AssistantConversation
 
 
@@ -145,3 +145,33 @@ def test_tool_arguments_cannot_select_identity_or_shell():
         validate_call(context(), 'create_pipeline', {'name': 'test', 'workspace_uuid': 'other'})
     with pytest.raises(ValueError):
         validate_call(context(), 'exec', {'command': 'echo unsafe'})
+
+
+@pytest.mark.asyncio
+async def test_resource_readers_match_application_services():
+    from langbot.pkg.core.app import Application
+    from langbot.pkg.api.http.service.model import LLMModelsService, EmbeddingModelsService
+    from langbot.pkg.api.http.service.pipeline import PipelineService
+    from langbot.pkg.api.http.service.knowledge import KnowledgeService
+
+    ap = create_autospec(Application, instance=True, spec_set=True)
+    ap.llm_model_service = create_autospec(LLMModelsService, instance=True)
+    ap.embedding_models_service = create_autospec(EmbeddingModelsService, instance=True)
+    ap.pipeline_service = create_autospec(PipelineService, instance=True)
+    ap.knowledge_service = create_autospec(KnowledgeService, instance=True)
+    ctx = context()
+    for kind, reader in (
+        ('models', ap.llm_model_service.get_llm_models),
+        ('embedding_models', ap.embedding_models_service.get_embedding_models),
+        ('pipelines', ap.pipeline_service.get_pipelines),
+        ('knowledge_bases', ap.knowledge_service.get_knowledge_bases),
+        ('knowledge_engines', ap.knowledge_service.list_knowledge_engines),
+    ):
+        reader.return_value = [{'name': kind}]
+        if kind != 'knowledge_engines':
+            reader.return_value[0]['config'] = {'large_or_private': 'omitted from discovery'}
+        assert await execute_tool(ap, ctx, 'list_resources', {'kind': kind}) == {
+            'total': 1,
+            'items': [{'name': kind}],
+        }
+        reader.assert_awaited_once_with(ctx)

web/src/app/home/components/WorkspaceAssistant.tsx

@@ -2,6 +2,7 @@ import { useEffect, useRef, useState } from 'react';
 import { MessageCircle, Plus, Send, X, LoaderCircle } from 'lucide-react';
 import { useTranslation } from 'react-i18next';
 import ReactMarkdown from 'react-markdown';
+import remarkGfm from 'remark-gfm';
 import { backendClient, useCurrentWorkspace, userInfo } from '@/app/infra/http';
 import { Button } from '@/components/ui/button';
 import {
@@ -230,6 +231,7 @@ function AssistantPanel({ storageKey }: { storageKey: string }) {
                   className={`rounded-xl p-3 text-sm break-words ${message.role === 'user' ? 'ml-6 bg-primary/10' : 'bg-muted'}`}
                 >
                   <ReactMarkdown
+                    remarkPlugins={[remarkGfm]}
                     components={{
                       img: () => null,
                       a: ({ href, children }) => (