Files
boocode/apps/coder/src/routes/skills.ts
indifferentketchup 649ce71eff feat: single-source cross-app wire contracts in @boocode/contracts (v2.7.13)
Move all hand-synced cross-app wire contracts into one built workspace
package, @boocode/contracts, consumed by server/web/coder/coder-web via
workspace:* + a per-subpath exports map. The ws-frames and provider-config
Zod schemas are schema-first (z.infer); MessageMetadata, ErrorReason,
AgentSessionConfig, the provider snapshot types, and WorktreeRiskReport are
each single-sourced. Deletes the byte-identical copies and their parity
tests, fixes a live AgentSessionConfig drift (coder dead copy removed,
unified to the web required/nullable shape), removes the dead pending_change
WS arms in the fallback SPA, and inverts the build order (contracts builds
first) across root build, Dockerfile, and the coder deploy docs. Reverses
the shared-package decision declined in v2.5.12.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-02 21:24:08 +00:00

125 lines
4.9 KiB
TypeScript

import type { FastifyInstance } from 'fastify';
import { z } from 'zod';
import type { Sql } from '../db.js';
import type { Broker } from '@boocode/server/broker';
import type { WsFrame } from '@boocode/contracts/ws-frames';
import { getSkillBody } from '@boocode/server/skills';
import {
buildSkillInvokeSyntheticFrames,
buildSkillInvokeUserFrames,
DEFAULT_SKILL_USER_MESSAGE,
runSkillInvokeTransaction,
} from '@boocode/server/skill-invoke';
import { resolveChatId } from './chat-resolve.js';
const SkillInvokeBody = z.object({
pane_id: z.string().min(1).max(200),
skill_name: z.string().min(1),
user_message: z.string().max(64_000).nullable().optional(),
// v2.5.9: when set to an external provider, the skill runs UNDER that agent —
// its body is injected into a dispatched task instead of native inference.
provider: z.string().max(100).optional(),
model: z.string().max(200).optional(),
mode_id: z.string().max(200).optional(),
thinking_option_id: z.string().max(200).optional(),
});
interface InferenceApi {
enqueue: (sessionId: string, chatId: string, assistantId: string, user: string) => void;
hasActive: (chatId: string) => boolean;
}
export function registerSkillRoutes(
app: FastifyInstance,
sql: Sql,
broker: Broker,
inference: InferenceApi,
): void {
app.post<{ Params: { sessionId: string } }>(
'/api/sessions/:sessionId/skill_invoke',
async (req, reply) => {
const parsed = SkillInvokeBody.safeParse(req.body);
if (!parsed.success) {
reply.code(400);
return { error: 'invalid body', details: parsed.error.flatten() };
}
const sessionId = req.params.sessionId;
const { pane_id, skill_name, provider, model, mode_id, thinking_option_id } = parsed.data;
const sessionRows = await sql<{ id: string; project_id: string }[]>`
SELECT id, project_id FROM sessions WHERE id = ${sessionId}
`;
if (sessionRows.length === 0) {
reply.code(404);
return { error: 'session not found' };
}
const chatId = await resolveChatId(sql, sessionId, pane_id);
if (!chatId) {
reply.code(404);
return { error: 'pane not found' };
}
if (inference.hasActive(chatId)) {
reply.code(409);
return { error: 'inference already running on this chat' };
}
const userText = parsed.data.user_message?.trim()
? parsed.data.user_message
: DEFAULT_SKILL_USER_MESSAGE;
const body = await getSkillBody(skill_name);
if (body === null) {
reply.code(404);
return { error: 'unknown_skill', message: `unknown skill: ${skill_name}` };
}
// v2.5.9: external agent → run the skill UNDER that agent. The skill body
// stays server-side (like the native path's tool message) and is injected
// into a dispatched task; the agent receives the skill instructions + the
// user's text. Mirrors the messages-route external-provider dispatch.
if (provider && provider !== 'boocode') {
const [userMsg] = await sql<{ id: string }[]>`
INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
VALUES (${sessionId}, ${chatId}, 'user', ${userText}, 'complete', clock_timestamp())
RETURNING id
`;
broker.publishFrame(sessionId, { type: 'message_started', message_id: userMsg!.id, chat_id: chatId, role: 'user' } as WsFrame);
broker.publishFrame(sessionId, { type: 'delta', message_id: userMsg!.id, chat_id: chatId, content: userText } as WsFrame);
broker.publishFrame(sessionId, { type: 'message_complete', message_id: userMsg!.id, chat_id: chatId } as WsFrame);
const taskInput = `${body}\n\n---\n\n${userText}`;
const [task] = await sql<{ id: string; state: string }[]>`
INSERT INTO tasks (project_id, input, agent, model, mode_id, thinking_option_id, session_id, chat_id)
VALUES (${sessionRows[0]!.project_id}, ${taskInput}, ${provider}, ${model ?? null}, ${mode_id ?? null}, ${thinking_option_id ?? null}, ${sessionId}, ${chatId})
RETURNING id, state
`;
await sql`UPDATE chats SET updated_at = clock_timestamp() WHERE id = ${chatId}`;
reply.code(202);
return { user_message_id: userMsg!.id, task_id: task!.id, dispatched: true };
}
const { result, toolCall } = await runSkillInvokeTransaction(sql, {
sessionId,
chatId,
skillName: skill_name,
skillBody: body,
userText,
});
for (const frame of buildSkillInvokeSyntheticFrames(chatId, result, toolCall, body)) {
broker.publishFrame(sessionId, frame as WsFrame);
}
for (const frame of buildSkillInvokeUserFrames(chatId, result.user_message_id, userText)) {
broker.publishFrame(sessionId, frame as WsFrame);
}
inference.enqueue(sessionId, chatId, result.assistant_message_id, 'default');
reply.code(202);
return result;
},
);
}