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mcpctl/src/mcpd/tests/chat-service.test.ts

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feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
import { describe, it, expect, vi } from 'vitest';
import { ChatService, MAX_ITERATIONS, TOOL_NAME_SEPARATOR, type ChatToolDispatcher } from '../src/services/chat.service.js';
import type { AgentService } from '../src/services/agent.service.js';
import type { LlmService } from '../src/services/llm.service.js';
import type { LlmAdapterRegistry } from '../src/services/llm/dispatcher.js';
import type { LlmAdapter, NonStreamingResult, InferContext } from '../src/services/llm/types.js';
import type { IChatRepository } from '../src/repositories/chat.repository.js';
import type { IPromptRepository } from '../src/repositories/prompt.repository.js';
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
import type { IPersonalityRepository } from '../src/repositories/personality.repository.js';
import type { ChatMessage, ChatThread, Prompt, Personality, PersonalityPrompt } from '@prisma/client';
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
const NOW = new Date();
function mockChatRepo(): IChatRepository & { _msgs: ChatMessage[]; _threads: ChatThread[] } {
const msgs: ChatMessage[] = [];
const threads: ChatThread[] = [];
let idCounter = 1;
return {
_msgs: msgs,
_threads: threads,
createThread: vi.fn(async ({ agentId, ownerId, title }) => {
const t: ChatThread = {
id: `thread-${String(idCounter++)}`,
agentId,
ownerId,
title: title ?? '',
lastTurnAt: NOW,
createdAt: NOW,
updatedAt: NOW,
};
threads.push(t);
return t;
}),
findThread: vi.fn(async (id: string) => threads.find((t) => t.id === id) ?? null),
listThreadsByAgent: vi.fn(async (agentId: string) => threads.filter((t) => t.agentId === agentId)),
listMessages: vi.fn(async (threadId: string) =>
msgs.filter((m) => m.threadId === threadId).sort((a, b) => a.turnIndex - b.turnIndex)),
appendMessage: vi.fn(async (input) => {
const turnIndex = input.turnIndex ?? msgs.filter((m) => m.threadId === input.threadId).length;
const m: ChatMessage = {
id: `msg-${String(idCounter++)}`,
threadId: input.threadId,
turnIndex,
role: input.role,
content: input.content,
toolCalls: (input.toolCalls ?? null) as ChatMessage['toolCalls'],
toolCallId: input.toolCallId ?? null,
status: input.status ?? 'complete',
createdAt: NOW,
};
msgs.push(m);
return m;
}),
updateStatus: vi.fn(async (id: string, status) => {
const m = msgs.find((x) => x.id === id);
if (!m) throw new Error('not found');
m.status = status;
return m;
}),
markPendingAsError: vi.fn(async (threadId: string) => {
let n = 0;
for (const m of msgs) {
if (m.threadId === threadId && m.status === 'pending') {
m.status = 'error';
n += 1;
}
}
return n;
}),
touchThread: vi.fn(async () => undefined),
nextTurnIndex: vi.fn(async (threadId: string) =>
msgs.filter((m) => m.threadId === threadId).length),
};
}
function mockPromptRepo(rows: Prompt[] = []): IPromptRepository {
return {
findAll: vi.fn(async () => rows),
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
findGlobal: vi.fn(async () => rows.filter((p) => p.projectId === null && p.agentId === null)),
findByAgent: vi.fn(async (agentId: string) => rows.filter((p) => p.agentId === agentId)),
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
findById: vi.fn(async (id: string) => rows.find((p) => p.id === id) ?? null),
findByNameAndProject: vi.fn(async () => null),
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
findByNameAndAgent: vi.fn(async () => null),
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
create: vi.fn(),
update: vi.fn(),
delete: vi.fn(),
} as unknown as IPromptRepository;
}
function mockTools(impl: Partial<ChatToolDispatcher> = {}): ChatToolDispatcher {
return {
listTools: impl.listTools ?? vi.fn(async () => []),
callTool: impl.callTool ?? vi.fn(async () => ({ ok: true })),
};
}
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
function mockAgents(opts: { defaultPersonality?: { id: string; name: string } | null } = {}): AgentService {
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
return {
getByName: vi.fn(async (name: string) => ({
id: `agent-${name}`,
name,
description: 'desc',
systemPrompt: 'You are a helpful agent.',
llm: { id: 'llm-1', name: 'qwen3-thinking' },
project: name === 'no-project'
? null
: { id: 'proj-1', name: 'mcpctl-dev' },
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
defaultPersonality: opts.defaultPersonality ?? null,
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
proxyModelName: null,
defaultParams: { temperature: 0.5 },
extras: {},
ownerId: 'owner-1',
version: 1,
createdAt: NOW,
updatedAt: NOW,
})),
} as unknown as AgentService;
}
function mockLlms(): LlmService {
return {
getByName: vi.fn(async (name: string) => ({
id: 'llm-1', name, type: 'openai', model: 'qwen3-thinking',
url: '', tier: 'fast', description: '',
apiKeyRef: null, extraConfig: {},
version: 1, createdAt: NOW, updatedAt: NOW,
})),
resolveApiKey: vi.fn(async () => 'fake-key'),
} as unknown as LlmService;
}
/** Adapter that yields a scripted sequence of canned responses, one per call. */
function scriptedAdapter(responses: NonStreamingResult[]): LlmAdapter {
let i = 0;
return {
kind: 'scripted',
infer: vi.fn(async (_ctx: InferContext) => {
const r = responses[i] ?? responses[responses.length - 1];
i += 1;
if (r === undefined) throw new Error('no scripted response');
return r;
}),
stream: async function*(_ctx: InferContext) {
yield { data: '[DONE]', done: true };
},
};
}
function adapterRegistry(adapter: LlmAdapter): LlmAdapterRegistry {
return { get: () => adapter } as unknown as LlmAdapterRegistry;
}
function chatCompletion(content: string): NonStreamingResult {
return {
status: 200,
body: {
id: 'cmpl-1',
object: 'chat.completion',
choices: [{ index: 0, message: { role: 'assistant', content }, finish_reason: 'stop' }],
},
};
}
function toolCall(name: string, args: Record<string, unknown>): NonStreamingResult {
return {
status: 200,
body: {
id: 'cmpl-1',
object: 'chat.completion',
choices: [{
index: 0,
message: {
role: 'assistant',
content: '',
tool_calls: [{
id: `call-${name}`,
type: 'function',
function: { name, arguments: JSON.stringify(args) },
}],
},
finish_reason: 'tool_calls',
}],
},
};
}
describe('ChatService', () => {
it('plain text turn — persists user + assistant rows and returns the reply', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('hello back')]);
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
);
const result = await svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
});
expect(result.assistant).toBe('hello back');
const stored = chatRepo._msgs.filter((m) => m.threadId === result.threadId);
expect(stored.map((m) => m.role)).toEqual(['user', 'assistant']);
expect(stored[1]?.status).toBe('complete');
});
it('runs a full tool-use round-trip and ends with a text reply', async () => {
const chatRepo = mockChatRepo();
const tools = mockTools({
listTools: vi.fn(async () => [{
name: `grafana${TOOL_NAME_SEPARATOR}query`,
description: 'query grafana',
parameters: { type: 'object', properties: {} },
}]),
callTool: vi.fn(async () => ({ rows: [{ value: 42 }] })),
});
const adapter = scriptedAdapter([
toolCall(`grafana${TOOL_NAME_SEPARATOR}query`, { q: 'cpu' }),
chatCompletion('the answer is 42'),
]);
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
const result = await svc.chat({
agentName: 'reviewer',
userMessage: 'what is cpu?',
ownerId: 'owner-1',
});
expect(result.assistant).toBe('the answer is 42');
expect(tools.callTool).toHaveBeenCalledWith({
projectId: 'proj-1',
serverName: 'grafana',
toolName: 'query',
args: { q: 'cpu' },
});
const stored = chatRepo._msgs.filter((m) => m.threadId === result.threadId);
expect(stored.map((m) => m.role)).toEqual(['user', 'assistant', 'tool', 'assistant']);
// No `pending` rows leaked.
expect(stored.every((m) => m.status === 'complete')).toBe(true);
// Tool turn's toolCallId links back.
const toolTurn = stored.find((m) => m.role === 'tool');
expect(toolTurn?.toolCallId).toBe(`call-grafana${TOOL_NAME_SEPARATOR}query`);
});
it('caps the loop at MAX_ITERATIONS when the model never settles', async () => {
const chatRepo = mockChatRepo();
const tools = mockTools({
listTools: vi.fn(async () => [{
name: `g${TOOL_NAME_SEPARATOR}t`,
description: '',
parameters: { type: 'object' },
}]),
callTool: vi.fn(async () => ({})),
});
// Always return a tool_call → the loop never reaches a terminal turn.
const adapter = scriptedAdapter([toolCall(`g${TOOL_NAME_SEPARATOR}t`, {})]);
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
await expect(svc.chat({
agentName: 'reviewer',
userMessage: 'loop forever',
ownerId: 'owner-1',
})).rejects.toThrow(new RegExp(`exceeded ${String(MAX_ITERATIONS)}`));
// After failure, no row should remain `pending`.
expect(chatRepo._msgs.every((m) => m.status !== 'pending')).toBe(true);
});
it('flips pending rows to error when the adapter throws mid-loop', async () => {
const chatRepo = mockChatRepo();
const tools = mockTools({
listTools: vi.fn(async () => [{
name: `g${TOOL_NAME_SEPARATOR}t`, description: '', parameters: {},
}]),
callTool: vi.fn(async () => ({})),
});
const adapter: LlmAdapter = {
kind: 'fail-after-one',
infer: vi.fn()
.mockResolvedValueOnce(toolCall(`g${TOOL_NAME_SEPARATOR}t`, {}))
.mockRejectedValueOnce(new Error('upstream blew up')),
stream: async function*() { yield { data: '[DONE]', done: true }; },
};
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
await expect(svc.chat({
agentName: 'reviewer',
userMessage: 'go',
ownerId: 'owner-1',
})).rejects.toThrow('upstream blew up');
expect(chatRepo._msgs.some((m) => m.status === 'error')).toBe(false);
expect(chatRepo._msgs.every((m) => m.status !== 'pending')).toBe(true);
});
it('merges per-call params over agent.defaultParams (override wins)', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
);
await svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
params: { temperature: 0.9, max_tokens: 256 },
});
const ctx = inferSpy.mock.calls[0][0] as InferContext;
expect(ctx.body.temperature).toBe(0.9);
expect(ctx.body.max_tokens).toBe(256);
});
it('forwards `extra` keys into the body for provider-specific knobs', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
);
await svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
params: { extra: { metadata: { user_id: 'abc' }, repetition_penalty: 1.05 } },
});
const ctx = inferSpy.mock.calls[0][0] as InferContext;
expect((ctx.body as Record<string, unknown>)['repetition_penalty']).toBe(1.05);
expect((ctx.body as Record<string, unknown>)['metadata']).toEqual({ user_id: 'abc' });
});
it('builds a system block from agent.systemPrompt + project prompts (priority desc)', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const prompts: Prompt[] = [
{
id: 'p1', name: 'low', content: 'LOW prompt',
projectId: 'proj-1', priority: 1, summary: null, chapters: null,
linkTarget: null, version: 1, createdAt: NOW, updatedAt: NOW,
},
{
id: 'p2', name: 'high', content: 'HIGH prompt',
projectId: 'proj-1', priority: 9, summary: null, chapters: null,
linkTarget: null, version: 1, createdAt: NOW, updatedAt: NOW,
},
];
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(prompts), mockTools(),
);
await svc.chat({ agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1' });
const ctx = inferSpy.mock.calls[0][0] as InferContext;
const sys = ctx.body.messages.find((m) => m.role === 'system');
expect(typeof sys?.content).toBe('string');
const text = sys?.content as string;
// High-priority prompt comes before low-priority.
expect(text.indexOf('HIGH prompt')).toBeLessThan(text.indexOf('LOW prompt'));
// Agent's own system prompt leads.
expect(text.indexOf('You are a helpful agent.')).toBeLessThan(text.indexOf('HIGH prompt'));
});
it('refuses tool calls when the agent has no project attached', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([toolCall(`x${TOOL_NAME_SEPARATOR}y`, {})]);
const tools = mockTools({
listTools: vi.fn(async () => [{ name: `x${TOOL_NAME_SEPARATOR}y`, description: '', parameters: {} }]),
});
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
await expect(svc.chat({
agentName: 'no-project',
userMessage: 'go',
ownerId: 'owner-1',
})).rejects.toThrow(/Project/);
});
it('honours tools_allowlist (filters tools before sending to adapter)', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const tools = mockTools({
listTools: vi.fn(async () => [
{ name: `s1${TOOL_NAME_SEPARATOR}a`, description: '', parameters: {} },
{ name: `s1${TOOL_NAME_SEPARATOR}b`, description: '', parameters: {} },
]),
});
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
await svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
params: { tools_allowlist: [`s1${TOOL_NAME_SEPARATOR}a`] },
});
const ctx = inferSpy.mock.calls[0][0] as InferContext;
expect(ctx.body.tools).toHaveLength(1);
expect(ctx.body.tools?.[0]?.function.name).toBe(`s1${TOOL_NAME_SEPARATOR}a`);
});
fix(agents): close gaps from /gstack-review P1 — thread reads now enforce ownership ======================================== chat.service.ts / routes/agent-chat.ts GET /api/v1/threads/:id/messages was previously RBAC-mapped to view:agents (no resourceName scope) with the route comment promising "service-level owner check enforces fine-grained access" — but the service didn't actually check. Any caller with view:agents could read another user's thread by guessing/learning the threadId. CUIDs are hard to brute-force but they leak: SSE `final` chunks, agents-plugin `_meta.threadId`, and several response bodies surface them. Now ChatService.listMessages(threadId, ownerId) loads the thread, returns 404 (not 403, to avoid id-enumeration via differential status codes) if ownerId doesn't match. Regression test in chat-service.test.ts covers Alice/Bob isolation + nonexistent-thread same-shape 404. P2 — AgentChatRequestSchema strict mode ======================================== validation/agent.schema.ts `.merge()` does NOT inherit `.strict()` from AgentChatParamsSchema. Typo'd fields (e.g. `temprature`) silently fell through and the agent silently used the default — debuggable only by reading the LLM call payload. Re-applied `.strict()` on the merged schema. P2 — per-agent maxIterations override + clamp ============================================== chat.service.ts Loop cap was a hard-coded module constant (12), wrong for both research-style agents (need higher) and cheap-probe agents (could opt lower). Now reads `agent.extras.maxIterations`, clamps 1..50, falls back to 12 default. The clamp is the soft-DoS guard: a hostile agent definition with `maxIterations:1000000` can't burn unbounded LLM calls per request. Both chat() and chatStream() use ctx.maxIterations now. Regression test covers low-cap override (rejects with `exceeded 2`) and hostile-value clamp (rejects with `exceeded 50`). P3 — SSE write to closed socket ================================ routes/agent-chat.ts When the upstream adapter throws after some chunks were already written AND the client disconnected, the catch block tried to flush more chunks to a closed socket. Without an `on('error')` handler Node emits unhandled error events; once Pino is wired to alerts this'd page on every disconnect-mid-stream. writeSseChunk now checks `reply.raw.destroyed || writableEnded` before write. P3 — BACKEND_TOKEN_DEAD preserves original stack ================================================= services/secret-backend-rotator.service.ts When wrapping mintRoleToken/lookupSelf failures as BACKEND_TOKEN_DEAD, the new Error() discarded the original throw — hard to tell whether the inner failure was a network blip vs an OpenBao API mismatch vs DNS. Now uses `new Error(msg, { cause: err })` so the inner stack survives. P3 — .gitignore .claude/scheduled_tasks.lock ============================================= This persisted state file was leaking into every `git status`. Tests ===== mcpd 761/761 (+2 regression tests). mcplocal 715/715. cli 430/430. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 23:53:19 +01:00
feat(chat): surface reasoning_content as `thinking` chunks; fix --no-stream timeout Reasoning models (qwen3-thinking, deepseek-reasoner, OpenAI o1 family) emit their scratchpad as `delta.reasoning_content` (or `delta.reasoning`, or `delta.provider_specific_fields.reasoning_content` when LiteLLM passes through from vLLM) — separate from `delta.content`. Before this commit mcpd's parseStreamingChunk only watched `content`, so the model's 30-90s reasoning phase looked like dead air to the REPL: streaming connection open, no chunks, no progress. Caught during the agents-feature shakedown when qwen3-thinking sat silent for 90s on a docmost__list_pages call. mcpd ==== chat.service.ts - parseStreamingChunk extracts a `reasoningDelta` from the chunk body, accepting all four spellings (reasoning_content / reasoning / provider_specific_fields.{reasoning_content,reasoning}). Future providers can add their own field names by extending the fallback chain. - chatStream yields `{ type: 'thinking', delta }` chunks as reasoning arrives, alongside the existing `{ type: 'text', delta }` for content. - Reasoning is intentionally NOT persisted to the thread. It's the model's scratchpad, not part of the conversation. Subsequent turns don't see it. - Adds 'thinking' to the ChatStreamChunk.type union. CLI === chat.ts - streamOnce handles 'thinking' chunks: writes them dim+italic to stderr (ANSI 2;3m) so the model's reasoning visually flows like a quote block while the final answer streams to stdout. Plain text when stderr isn't a TTY (pipe to file → no escape codes leak). - chatRequestNonStream replaces the shared ApiClient.post() for the --no-stream path. ApiClient defaults to a 10s timeout, way too tight for any chat that calls a tool: LLM round + tool dispatch + LLM summary easily exceeds 10s. The new helper uses the same 600s timeout the streaming path has been using all along. Tests: chat-service.test.ts (+2): - reasoning_content deltas surface as `thinking` chunks (not text); reasoning is NOT persisted to the assistant turn's content. - LiteLLM's provider_specific_fields.reasoning_content shape parses identically to the vendor-native shape. mcpd 777/777, cli 430/430. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 17:04:01 +01:00
// Regression: reasoning_content (qwen3-thinking, deepseek-reasoner, o1)
// streams as `thinking` chunks, separate from `text`.
// Without this, the model's 30-90s reasoning phase looks like dead air to
// the REPL — caught by user feedback during the agents-feature shakedown.
it('chatStream surfaces reasoning_content deltas as `thinking` chunks', async () => {
const chatRepo = mockChatRepo();
// Adapter that yields a sequence of openai-format chunks: 2 reasoning
// deltas, then 1 content delta, then [DONE].
const adapter: LlmAdapter = {
kind: 'scripted-thinking',
infer: vi.fn(),
stream: async function*() {
yield { data: JSON.stringify({ choices: [{ delta: { reasoning_content: 'Let me think... ' }, finish_reason: null }] }) };
yield { data: JSON.stringify({ choices: [{ delta: { reasoning_content: 'OK, ready.' }, finish_reason: null }] }) };
yield { data: JSON.stringify({ choices: [{ delta: { content: 'DONE' }, finish_reason: 'stop' }] }) };
yield { data: '[DONE]', done: true };
},
};
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
);
const chunks: Array<{ type: string; delta?: string }> = [];
for await (const chunk of svc.chatStream({
agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1',
})) {
chunks.push({ type: chunk.type, delta: chunk.delta });
}
// Expect: 2 thinking + 1 text + 1 final
expect(chunks.filter((c) => c.type === 'thinking').map((c) => c.delta))
.toEqual(['Let me think... ', 'OK, ready.']);
expect(chunks.filter((c) => c.type === 'text').map((c) => c.delta)).toEqual(['DONE']);
expect(chunks.find((c) => c.type === 'final')).toBeDefined();
// Reasoning is NOT persisted to the thread — only assistant content.
const assistantTurn = chatRepo._msgs.find((m) => m.role === 'assistant');
expect(assistantTurn?.content).toBe('DONE');
expect(assistantTurn?.content).not.toContain('Let me think');
});
// Regression: provider_specific_fields.reasoning_content shape (LiteLLM
// passthrough from vLLM) is also recognized.
it('chatStream recognizes LiteLLM provider_specific_fields.reasoning_content', async () => {
const chatRepo = mockChatRepo();
const adapter: LlmAdapter = {
kind: 'scripted-litellm',
infer: vi.fn(),
stream: async function*() {
yield { data: JSON.stringify({ choices: [{ delta: { provider_specific_fields: { reasoning_content: 'thinking via litellm...' } }, finish_reason: null }] }) };
yield { data: JSON.stringify({ choices: [{ delta: { content: 'ok' }, finish_reason: 'stop' }] }) };
yield { data: '[DONE]', done: true };
},
};
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
);
const chunks: Array<{ type: string; delta?: string }> = [];
for await (const chunk of svc.chatStream({
agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1',
})) {
chunks.push({ type: chunk.type, delta: chunk.delta });
}
expect(chunks.filter((c) => c.type === 'thinking').map((c) => c.delta))
.toEqual(['thinking via litellm...']);
});
fix(agents): close gaps from /gstack-review P1 — thread reads now enforce ownership ======================================== chat.service.ts / routes/agent-chat.ts GET /api/v1/threads/:id/messages was previously RBAC-mapped to view:agents (no resourceName scope) with the route comment promising "service-level owner check enforces fine-grained access" — but the service didn't actually check. Any caller with view:agents could read another user's thread by guessing/learning the threadId. CUIDs are hard to brute-force but they leak: SSE `final` chunks, agents-plugin `_meta.threadId`, and several response bodies surface them. Now ChatService.listMessages(threadId, ownerId) loads the thread, returns 404 (not 403, to avoid id-enumeration via differential status codes) if ownerId doesn't match. Regression test in chat-service.test.ts covers Alice/Bob isolation + nonexistent-thread same-shape 404. P2 — AgentChatRequestSchema strict mode ======================================== validation/agent.schema.ts `.merge()` does NOT inherit `.strict()` from AgentChatParamsSchema. Typo'd fields (e.g. `temprature`) silently fell through and the agent silently used the default — debuggable only by reading the LLM call payload. Re-applied `.strict()` on the merged schema. P2 — per-agent maxIterations override + clamp ============================================== chat.service.ts Loop cap was a hard-coded module constant (12), wrong for both research-style agents (need higher) and cheap-probe agents (could opt lower). Now reads `agent.extras.maxIterations`, clamps 1..50, falls back to 12 default. The clamp is the soft-DoS guard: a hostile agent definition with `maxIterations:1000000` can't burn unbounded LLM calls per request. Both chat() and chatStream() use ctx.maxIterations now. Regression test covers low-cap override (rejects with `exceeded 2`) and hostile-value clamp (rejects with `exceeded 50`). P3 — SSE write to closed socket ================================ routes/agent-chat.ts When the upstream adapter throws after some chunks were already written AND the client disconnected, the catch block tried to flush more chunks to a closed socket. Without an `on('error')` handler Node emits unhandled error events; once Pino is wired to alerts this'd page on every disconnect-mid-stream. writeSseChunk now checks `reply.raw.destroyed || writableEnded` before write. P3 — BACKEND_TOKEN_DEAD preserves original stack ================================================= services/secret-backend-rotator.service.ts When wrapping mintRoleToken/lookupSelf failures as BACKEND_TOKEN_DEAD, the new Error() discarded the original throw — hard to tell whether the inner failure was a network blip vs an OpenBao API mismatch vs DNS. Now uses `new Error(msg, { cause: err })` so the inner stack survives. P3 — .gitignore .claude/scheduled_tasks.lock ============================================= This persisted state file was leaking into every `git status`. Tests ===== mcpd 761/761 (+2 regression tests). mcplocal 715/715. cli 430/430. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 23:53:19 +01:00
// Regression: per-agent maxIterations override + clamp.
// Found by /gstack-review on 2026-04-25.
// Without the clamp, a hostile agent definition with `extras.maxIterations:1000000`
// could spin the loop into a near-infinite tool-call burn.
it('per-agent extras.maxIterations clamps below default and refuses absurd values', async () => {
const chatRepo = mockChatRepo();
const tools = mockTools({
listTools: vi.fn(async () => [{
name: `g${TOOL_NAME_SEPARATOR}t`, description: '', parameters: {},
}]),
callTool: vi.fn(async () => ({})),
});
// Agent with maxIterations=2 — only 2 tool-call rounds allowed before bail.
const agentsLowCap = {
getByName: vi.fn(async () => ({
id: 'agent-low', name: 'low', description: '', systemPrompt: '',
llm: { id: 'llm-1', name: 'qwen3-thinking' },
project: { id: 'proj-1', name: 'mcpctl-dev' },
proxyModelName: null, defaultParams: {},
extras: { maxIterations: 2 },
ownerId: 'owner-1', version: 1, createdAt: NOW, updatedAt: NOW,
})),
} as unknown as AgentService;
const adapter = scriptedAdapter([toolCall(`g${TOOL_NAME_SEPARATOR}t`, {})]);
const svc = new ChatService(
agentsLowCap, mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), tools,
);
await expect(svc.chat({
agentName: 'low', userMessage: 'spin', ownerId: 'owner-1',
})).rejects.toThrow(/exceeded 2 iterations/);
// Hostile agent with maxIterations=1000000 — must clamp to 50, not iterate forever.
const agentsHostile = {
getByName: vi.fn(async () => ({
id: 'agent-bad', name: 'bad', description: '', systemPrompt: '',
llm: { id: 'llm-1', name: 'qwen3-thinking' },
project: { id: 'proj-1', name: 'mcpctl-dev' },
proxyModelName: null, defaultParams: {},
extras: { maxIterations: 1_000_000 },
ownerId: 'owner-1', version: 1, createdAt: NOW, updatedAt: NOW,
})),
} as unknown as AgentService;
const adapter2 = scriptedAdapter([toolCall(`g${TOOL_NAME_SEPARATOR}t`, {})]);
const chatRepo2 = mockChatRepo();
const svc2 = new ChatService(
agentsHostile, mockLlms(), adapterRegistry(adapter2),
chatRepo2, mockPromptRepo(), tools,
);
await expect(svc2.chat({
agentName: 'bad', userMessage: 'spin', ownerId: 'owner-1',
})).rejects.toThrow(/exceeded 50 iterations/);
});
// Regression: thread message reads must enforce ownership.
// Found by /gstack-review on 2026-04-25.
// Without this, any caller with `view:agents` could read another user's thread
// by guessing/learning the threadId (CUIDs leak through SSE chunks + tool _meta).
it('listMessages refuses a thread owned by another user (404, not 403, to avoid id-enumeration)', async () => {
const chatRepo = mockChatRepo();
// Pre-seed a thread owned by 'alice'
await chatRepo.createThread({ agentId: 'agent-x', ownerId: 'alice' });
const aliceThread = chatRepo._threads[0]!;
await chatRepo.appendMessage({
threadId: aliceThread.id,
role: 'user',
content: 'private to alice',
});
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(scriptedAdapter([chatCompletion('ok')])),
chatRepo, mockPromptRepo(), mockTools(),
);
// Bob requests Alice's thread by id — must 404.
await expect(svc.listMessages(aliceThread.id, 'bob'))
.rejects.toThrow(/not found/i);
// Alice gets her own messages.
const aliceMessages = await svc.listMessages(aliceThread.id, 'alice');
expect(aliceMessages.map((m) => m.content)).toEqual(['private to alice']);
// Genuinely missing thread — same 404 shape (no oracle leak).
await expect(svc.listMessages('cnonexistent000000000000000', 'alice'))
.rejects.toThrow(/not found/i);
});
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
// ── Agent-direct prompts + personality overlay (Stage 3 system block) ──
it('injects agent-direct prompts BETWEEN agent.systemPrompt and project prompts', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const prompts: Prompt[] = [
// Project prompt
{
id: 'p-proj', name: 'proj', content: 'PROJECT_TEXT',
projectId: 'proj-1', agentId: null, priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
},
// Agent-direct prompt
{
id: 'p-direct', name: 'direct', content: 'AGENT_DIRECT_TEXT',
projectId: null, agentId: 'agent-reviewer', priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
},
];
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(prompts), mockTools(),
);
await svc.chat({ agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1' });
const sys = (inferSpy.mock.calls[0][0] as InferContext).body.messages.find((m) => m.role === 'system');
const text = sys?.content as string;
expect(text.indexOf('You are a helpful agent.')).toBeLessThan(text.indexOf('AGENT_DIRECT_TEXT'));
expect(text.indexOf('AGENT_DIRECT_TEXT')).toBeLessThan(text.indexOf('PROJECT_TEXT'));
});
it('appends personality-bound prompts after project prompts when --personality is passed', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const projectPrompt: Prompt = {
id: 'p-proj', name: 'proj', content: 'PROJECT_TEXT',
projectId: 'proj-1', agentId: null, priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
};
const personalityPrompt: Prompt = {
id: 'p-pers', name: 'pers', content: 'PERSONALITY_TEXT',
projectId: null, agentId: null, priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
};
const personalities = mockPersonalityRepo({
'pers-grumpy': {
personality: makePersonality({ id: 'pers-grumpy', name: 'grumpy', agentId: 'agent-reviewer' }),
bindings: [{ promptId: personalityPrompt.id, priority: 5 }],
},
}, [projectPrompt, personalityPrompt]);
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo([projectPrompt, personalityPrompt]), mockTools(),
personalities,
);
await svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
personalityName: 'grumpy',
});
const sys = (inferSpy.mock.calls[0][0] as InferContext).body.messages.find((m) => m.role === 'system');
const text = sys?.content as string;
expect(text.indexOf('PROJECT_TEXT')).toBeLessThan(text.indexOf('PERSONALITY_TEXT'));
});
it('falls back to agent.defaultPersonality when --personality is omitted', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const personalityPrompt: Prompt = {
id: 'p-pers', name: 'pers', content: 'DEFAULT_PERSONALITY_TEXT',
projectId: null, agentId: null, priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
};
const personalities = mockPersonalityRepo({
'pers-default': {
personality: makePersonality({ id: 'pers-default', name: 'default', agentId: 'agent-reviewer' }),
bindings: [{ promptId: personalityPrompt.id, priority: 5 }],
},
}, [personalityPrompt]);
const svc = new ChatService(
mockAgents({ defaultPersonality: { id: 'pers-default', name: 'default' } }),
mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo([personalityPrompt]), mockTools(),
personalities,
);
await svc.chat({ agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1' });
const sys = (inferSpy.mock.calls[0][0] as InferContext).body.messages.find((m) => m.role === 'system');
expect(sys?.content as string).toContain('DEFAULT_PERSONALITY_TEXT');
});
it('throws when --personality references a name the agent does not own', async () => {
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const personalities = mockPersonalityRepo({});
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo(), mockTools(),
personalities,
);
await expect(svc.chat({
agentName: 'reviewer',
userMessage: 'hi',
ownerId: 'owner-1',
personalityName: 'ghost',
})).rejects.toThrow(/Personality not found/);
});
it('preserves today\'s system block when no personality and no agent-direct prompts exist', async () => {
// Regression guard: backwards-compatible by construction.
const chatRepo = mockChatRepo();
const adapter = scriptedAdapter([chatCompletion('ok')]);
const inferSpy = adapter.infer as ReturnType<typeof vi.fn>;
const projectPrompt: Prompt = {
id: 'p-proj', name: 'proj', content: 'ONLY_PROJECT_TEXT',
projectId: 'proj-1', agentId: null, priority: 5, summary: null,
chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
};
const svc = new ChatService(
mockAgents(), mockLlms(), adapterRegistry(adapter),
chatRepo, mockPromptRepo([projectPrompt]), mockTools(),
);
await svc.chat({ agentName: 'reviewer', userMessage: 'hi', ownerId: 'owner-1' });
const sys = (inferSpy.mock.calls[0][0] as InferContext).body.messages.find((m) => m.role === 'system');
const text = sys?.content as string;
expect(text).toContain('You are a helpful agent.');
expect(text).toContain('ONLY_PROJECT_TEXT');
});
feat(agents): mcpd repos + Agent/Chat services with tool-use loop (Stage 2) Layers the persistence-side logic on top of the Stage 1 schema. AgentService mirrors LlmService's CRUD shape with name-resolved llm/project references and yaml round-trip support; ChatService is the orchestrator that drives one chat turn end-to-end: build the merged system block (agent.systemPrompt + project Prompts ordered by priority desc + per-call systemAppend), persist the user turn, run the adapter, dispatch any tool_calls through an injected ChatToolDispatcher, persist tool turns linked back via toolCallId, and loop until the model returns terminal text. Per-call params resolve LiteLLM-style: request body → agent.defaultParams → adapter default. The escape hatch `extra` is forwarded as-is so each adapter can cherry-pick provider-specific knobs (Anthropic metadata, vLLM repetition_penalty, etc.) without code changes here. Persistence is non-transactional across the loop because tool calls can take minutes; long-held DB transactions would starve other writers. Instead each in-flight assistant turn is written `pending` and flipped to `complete` only after its tool results land. On failure or max-iter overrun, every `pending` row in the thread is flipped to `error` so the trail is auditable. Tools are namespaced on the wire as `<server>__<tool>`, unmarshalled at dispatch time; `tools_allowlist` filters before the model sees the list. Tests: agent-service.test.ts (7) — CRUD with name-resolved llm/project, conflict on duplicate, llm switch, project detach, listByProject filtering, upsertByName branch coverage. chat-service.test.ts (9) — plain text turn, full text→tool→text loop with toolCallId linkage, max-iter cap leaves zero pending, adapter-throws leaves zero pending, body→defaultParams merge, `extra` passthrough, project-Prompt priority ordering in the system block, tool-without- project rejection, tools_allowlist filtering. All 16 green; full mcpd suite still 737/737. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 16:38:38 +01:00
});
feat(mcpd): personality routes + chat system block overlay (Stage 3) End-to-end backend wiring for the agents-feature evolution. After this stage you can curl all the endpoints; CLI + Web UI follow. Routes (new): GET /api/v1/agents/:agentName/personalities POST /api/v1/agents/:agentName/personalities GET /api/v1/personalities/:id PUT /api/v1/personalities/:id DELETE /api/v1/personalities/:id GET /api/v1/personalities/:id/prompts POST /api/v1/personalities/:id/prompts DELETE /api/v1/personalities/:id/prompts/:promptId GET /api/v1/agents/:agentName/prompts (agent-direct) Routes (extended): POST /api/v1/prompts now resolves `agent: <name>` like `project: <name>` POST /api/v1/agents/:name/chat accepts `personality: <name>` RBAC: `personalities` segment maps to the `agents` resource so view/edit/create/delete on the parent agent governs personality access. No new RBAC roles — piggybacking keeps the surface flat. System block (chat.service.ts): agent.systemPrompt + agent-direct prompts (Prompt.agentId === agent.id, priority desc) + project prompts (existing behavior, priority desc) + personality prompts (PersonalityPrompt[chosen], priority desc) + systemAppend Personality is selected by request body `personality: <name>`, falling back to `agent.defaultPersonalityId` if unset. A typo'd flag throws 404 rather than silently dropping back to no overlay — failing loudly on misconfiguration is the only way users learn it didn't apply. Backwards-compatible by construction: when no agent-direct prompts exist and no personality is selected, the resulting block is byte- identical to the old layout (verified by a regression test). Tests: 5 new chat-service.test cases cover ordering, default- personality fallback, missing-personality 404, and the regression guard. mcpd suite: 801/801 (was 796). Typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 19:27:59 +01:00
// ── Helpers for personality-overlay tests ──
function makePersonality(overrides: Partial<Personality> = {}): Personality {
return {
id: `pers-${Math.random().toString(36).slice(2, 8)}`,
name: 'p',
description: '',
agentId: 'agent-reviewer',
priority: 5,
createdAt: NOW,
updatedAt: NOW,
...overrides,
};
}
interface MockPersonalityFixture {
personality: Personality;
bindings: Array<{ promptId: string; priority: number }>;
}
function mockPersonalityRepo(
fixtures: Record<string, MockPersonalityFixture>,
prompts: Prompt[] = [],
): IPersonalityRepository {
const byId = new Map<string, MockPersonalityFixture>(Object.entries(fixtures));
const promptsById = new Map<string, Prompt>(prompts.map((p) => [p.id, p]));
return {
findAll: vi.fn(async () => [...byId.values()].map((f) => f.personality)),
findByAgent: vi.fn(async (agentId: string) =>
[...byId.values()].filter((f) => f.personality.agentId === agentId).map((f) => f.personality)),
findById: vi.fn(async (id: string) => byId.get(id)?.personality ?? null),
findByNameAndAgent: vi.fn(async (name: string, agentId: string) => {
for (const f of byId.values()) {
if (f.personality.name === name && f.personality.agentId === agentId) {
return f.personality;
}
}
return null;
}),
create: vi.fn(),
update: vi.fn(),
delete: vi.fn(),
listPrompts: vi.fn(async (personalityId: string) => {
const fixture = byId.get(personalityId);
if (!fixture) return [];
return fixture.bindings.map<PersonalityPrompt & { prompt: Prompt }>((b) => ({
id: `bind-${b.promptId}`,
personalityId,
promptId: b.promptId,
priority: b.priority,
createdAt: NOW,
prompt: promptsById.get(b.promptId) ?? ({
id: b.promptId, name: 'p', content: '',
projectId: null, agentId: null, priority: b.priority,
summary: null, chapters: null, linkTarget: null, version: 1,
createdAt: NOW, updatedAt: NOW,
} as Prompt),
}));
}),
attachPrompt: vi.fn(),
detachPrompt: vi.fn(),
findBinding: vi.fn(async () => null),
};
}