Files
boocode/apps/server/src/services/inference/stream-phase.ts
indifferentketchup 8c200216eb refactor: codebase audit cleanup — dead code, dedup, module splits
Multi-agent audit + aggressive cleanup across server/web/coder/booterm,
delivered behind a DEFER discipline so none of the in-flight files were
touched. Removes dead code/deps/columns, dedups server + coder helpers,
and splits the oversized modules (tools.ts, opencode-server.ts,
sentinel-summaries, turn.ts, TerminalPane.tsx) behind stable contracts.
Adds 78 parity/unit tests (server 587, coder 323); fixes two latent bugs
(ChatPane queue keys, FileViewerOverlay blank-line parity).

Intended tag: v2.7.12-audit-cleanup.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-02 21:12:29 +00:00

149 lines
5.3 KiB
TypeScript

// P5 (SPLIT SKETCH): stream-phase.ts is now the BooCode I/O layer for the
// stream phase — `executeStreamPhase` owns the row UPDATE, message_started
// frame, debounced content flush, throttled usage publish, model-context
// lookup, and tool-whitelist filter. The generic AI-SDK adapter
// (streamCompletion / toModelMessages / buildAiTools / sampler helpers) moved
// to ./stream-phase-adapter.ts, which has no SQL/broker/publish deps and is
// unit-testable on its own. The adapter's public names are re-exported below so
// existing importers of './stream-phase.js' (sentinel-summaries, synthesis
// pipeline, the helper tests) keep working unchanged.
import type { Agent, Session } from '../../types/api.js';
import * as modelContext from '../model-context.js';
import { toolJsonSchemas, type ToolJsonSchema } from '../tools.js';
import { matchToolGlob } from '../agents.js';
import type { OpenAiMessage } from './payload.js';
import { createContentFlusher } from './content-flusher.js';
import type {
StreamPhaseState,
InferenceContext,
StreamResult,
TurnArgs,
} from './types.js';
import { streamCompletion, samplerOptsFromAgent } from './stream-phase-adapter.js';
export {
streamCompletion,
samplerOptsFromAgent,
type StreamOptions,
type SamplerOpts,
type StreamAdapterContext,
} from './stream-phase-adapter.js';
export async function executeStreamPhase(
ctx: InferenceContext,
args: TurnArgs,
session: Session,
messages: OpenAiMessage[],
state: StreamPhaseState,
agent: Agent | null,
// v1.11.8: when false, web_search and web_fetch are stripped from the
// tool list sent to the LLM, so the model can't even attempt them.
webToolsEnabled: boolean,
): Promise<StreamResult> {
const { sessionId, chatId, assistantMessageId, signal } = args;
const startedRow = await ctx.sql<{ started_at: string }[]>`
UPDATE messages
SET started_at = clock_timestamp()
WHERE id = ${assistantMessageId}
RETURNING started_at
`;
state.startedAt = startedRow[0]?.started_at ?? null;
ctx.publish(sessionId, {
type: 'message_started',
message_id: assistantMessageId,
chat_id: chatId,
role: 'assistant',
});
const flusher = createContentFlusher(ctx.sql, assistantMessageId, () => state.accumulated);
// Tool whitelist: if an agent is set, filter the global tool list to only the
// tool names it allows. v1.15.0-mcp-multi: uses matchToolGlob for glob
// pattern support (e.g. `context7_*`, `!web_*`). When no agent: send all tools.
// v1.11.8: a second filter strips web_search + web_fetch unless the chat
// has them explicitly enabled. Counts as an opt-in security boundary: the
// model can't summon a tool that wasn't offered to it.
const WEB_TOOL_NAMES: ReadonlySet<string> = new Set(['web_search', 'web_fetch']);
const effectiveTools: ToolJsonSchema[] = (agent
? toolJsonSchemas().filter((t) => matchToolGlob(t.function.name, agent.tools))
: toolJsonSchemas()
).filter((t) => webToolsEnabled || !WEB_TOOL_NAMES.has(t.function.name));
// v1.12.2: ctx_max lookup is cached after the first hit per model, so this
// is a Map probe in steady state. We capture nCtx once at the top of the
// stream so the throttled usage publish doesn't refetch each tick.
const mctxForStream = await modelContext.getModelContext(session.model);
const nCtxForStream = mctxForStream?.n_ctx ?? null;
// v1.12.2 → v1.13.1-A: live usage publishes were throttled to ~500ms when
// the manual SSE parser saw `parsed.usage` per chunk. AI SDK v6 surfaces
// usage only at stream end (result.usage promise), so the throttle is
// effectively a single trailing publish. ChatThroughput will tick once at
// stream completion rather than mid-stream — known regression vs v1.12.2,
// recovered if a future dispatch interpolates from delta cadence.
const USAGE_THROTTLE_MS = 500;
let lastUsageAt = 0;
let pendingUsage: { p: number | null; c: number | null } | null = null;
let usageTimer: NodeJS.Timeout | null = null;
const flushUsage = () => {
if (!pendingUsage) return;
const { p, c } = pendingUsage;
pendingUsage = null;
lastUsageAt = Date.now();
ctx.publish(sessionId, {
type: 'usage',
message_id: assistantMessageId,
chat_id: chatId,
completion_tokens: c,
ctx_used: p,
ctx_max: nCtxForStream,
});
};
try {
return await streamCompletion(
ctx,
session.model,
messages,
{
tools: effectiveTools,
...samplerOptsFromAgent(agent),
},
(delta) => {
state.accumulated += delta;
ctx.publish(sessionId, {
type: 'delta',
message_id: assistantMessageId,
chat_id: chatId,
content: delta,
});
ctx.log.debug({ sessionId, delta }, 'inference delta');
flusher.scheduleFlush();
},
(prompt, completion) => {
pendingUsage = { p: prompt, c: completion };
const elapsed = Date.now() - lastUsageAt;
if (elapsed >= USAGE_THROTTLE_MS) {
flushUsage();
} else if (!usageTimer) {
usageTimer = setTimeout(() => {
usageTimer = null;
flushUsage();
}, USAGE_THROTTLE_MS - elapsed);
}
},
signal,
agent,
);
} finally {
if (usageTimer) {
clearTimeout(usageTimer);
usageTimer = null;
}
await flusher.drain();
}
}