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v1.13.1-A: install AI SDK v6 + swap streamText into stream-phase.ts adapter

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- Add ai@^6 and @ai-sdk/openai-compatible@^2 to apps/server.
- New services/inference/provider.ts: createOpenAICompatible against
  llama-swap (baseURL threaded from config.LLAMA_SWAP_URL, cached per
  baseURL). No apiKey — Authelia + Tailscale gate llama-swap, not keys.
- streamCompletion rewritten as an adapter over streamText. AI SDK
  fullStream parts (text-delta, tool-call, finish, error) map back to
  the legacy {content?, tool_calls?, finishReason} StreamResult shape
  that executeStreamPhase already consumes. No layer above
  streamCompletion changes.
- toModelMessages converts BooCode's OpenAI-shaped history to AI SDK
  ModelMessage[]; tool messages need toolName which we look up by
  scanning earlier assistant tool_calls for the matching id.
- buildAiTools wraps BooCode's JSON-schema tool defs via
  tool({ inputSchema: jsonSchema(parameters) }) with NO execute —
  BooCode dispatches tools in tool-phase.ts, not the AI SDK loop.
- XML fallback parser preserved as-is — qwen3.6 still emits XML tool
  calls in text content that the structured tool-call layer misses.
- reasoning-delta parts dropped with a debug-level counter — captured
  properly in v1.13.1-C.
- Abort path: streamText({ abortSignal }) wires ctx.signal through, but
  AI SDK v6 swallows the abort (fullStream iterator exits cleanly
  rather than throwing). Post-iteration `if (signal?.aborted) throw` so
  handleAbortOrError owns the row and writes status='cancelled'. Caught
  by smoke D; would have shipped as status='complete' on stop otherwise.
- Usage frame reads result.usage (inputTokens / outputTokens v6 names)
  AFTER stream drain. Single trailing publish through the existing 500ms
  throttle. Known regression: ChatThroughput's live mid-stream tick
  (v1.12.2) is gone — it now shows a single value at stream end.
  TODO(v1.13.1-followup): interpolate outputTokens during streaming
  via a delta-cadence counter (e.g. part.text.length/4 token proxy)
  and publish every 500ms; reconcile against result.usage at finish.
- Write-path dual-write from v1.13.0 unaffected.

Read path stays on JSON columns. v1.13.1-B flips reads to message_parts.

Smoke verified end-to-end against running container:
- A. Plain text: status='complete', 1 text part.
- B. Single tool prompt → multi-tool chain (4 calls): every assistant
     with tool_calls has 2 parts (text+tool_call), every tool row has
     1 part (tool_result).
- C. Multi-step covered by B's chain.
- D. Stop mid-stream: status='cancelled' written via handleAbortOrError
     after the post-iteration abort throw.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
indifferentketchup
2026-05-22 06:17:56 +00:00
parent 1cb6eee24c
commit c2c4f78a26
4 changed files with 339 additions and 173 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
apps/server/package.json
View File

@@ -11,8 +11,10 @@
"test": "vitest run"
},
"dependencies": {
"@ai-sdk/openai-compatible": "^2.0.47",
"@fastify/static": "^7.0.4",
"@fastify/websocket": "^10.0.1",
"ai": "^6.0.190",
"fastify": "^4.28.1",
"postgres": "^3.4.4",
"ws": "^8.18.0",

26
apps/server/src/services/inference/provider.ts Normal file
View File

@@ -0,0 +1,26 @@
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
import type { LanguageModel } from 'ai';
// v1.13.1-A: AI SDK provider against llama-swap. baseURL is threaded from
// config.LLAMA_SWAP_URL at call time (not module-load) so tests can stub the
// upstream without touching env vars. No apiKey — llama-swap is unauth in our
// Tailscale topology and exposing it over the public internet is gated by
// Authelia at the Caddy layer, not by API keys.
const cache = new Map<string, ReturnType<typeof createOpenAICompatible>>();
function getProvider(baseURL: string): ReturnType<typeof createOpenAICompatible> {
let provider = cache.get(baseURL);
if (!provider) {
provider = createOpenAICompatible({
name: 'llama-swap',
baseURL: baseURL.endsWith('/v1') ? baseURL : `${baseURL}/v1`,
});
cache.set(baseURL, provider);
}
return provider;
}
export function upstreamModel(baseURL: string, modelId: string): LanguageModel {
return getProvider(baseURL).chatModel(modelId);
}

396
apps/server/src/services/inference/stream-phase.ts
View File

@@ -18,29 +18,8 @@ import type {
StreamResult,
TurnArgs,
} from './turn.js';
interface ChatCompletionDelta {
role?: string;
content?: string | null;
tool_calls?: Array<{
index: number;
id?: string;
type?: 'function';
function?: { name?: string; arguments?: string };
}>;
}
interface ChatCompletionChunk {
choices?: Array<{
delta: ChatCompletionDelta;
finish_reason: string | null;
}>;
usage?: {
prompt_tokens?: number;
completion_tokens?: number;
total_tokens?: number;
};
}
import { upstreamModel } from './provider.js';
import { jsonSchema, streamText, tool, type JSONValue, type ModelMessage } from 'ai';
interface StreamOptions {
// null = omit tools entirely (compact phase); [] = caller stripped all tools
@@ -49,44 +28,105 @@ interface StreamOptions {
temperature?: number;
}
async function* sseLines(stream: ReadableStream<Uint8Array>): AsyncGenerator<string> {
const reader = stream.getReader();
const decoder = new TextDecoder('utf-8');
let buffer = '';
try {
while (true) {
const { value, done } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
let idx;
while ((idx = buffer.indexOf('\n')) >= 0) {
const line = buffer.slice(0, idx).replace(/\r$/, '');
buffer = buffer.slice(idx + 1);
if (line.length === 0) continue;
yield line;
// v1.13.1-A: convert BooCode's OpenAI-shaped history into AI SDK
// ModelMessage[]. Tool result messages need a `toolName` field that the
// OpenAI shape doesn't carry; we look it up by scanning earlier assistant
// `tool_calls` entries for a matching id.
function toModelMessages(messages: OpenAiMessage[]): ModelMessage[] {
const toolNameById = new Map<string, string>();
for (const m of messages) {
if (m.role === 'assistant' && m.tool_calls) {
for (const tc of m.tool_calls) {
toolNameById.set(tc.id, tc.function.name);
}
}
if (buffer.length > 0) yield buffer;
} finally {
reader.releaseLock();
}
const out: ModelMessage[] = [];
for (const m of messages) {
if (m.role === 'system' || m.role === 'user') {
out.push({ role: m.role, content: m.content ?? '' });
continue;
}
if (m.role === 'assistant') {
const hasTools = m.tool_calls && m.tool_calls.length > 0;
if (!hasTools) {
// Bare text assistant (string content). null content + no tool_calls
// is degenerate but harmless to forward.
out.push({ role: 'assistant', content: m.content ?? '' });
continue;
}
const parts: Array<
| { type: 'text'; text: string }
| { type: 'tool-call'; toolCallId: string; toolName: string; input: unknown }
> = [];
if (m.content && m.content.length > 0) {
parts.push({ type: 'text', text: m.content });
}
for (const tc of m.tool_calls!) {
let input: unknown = {};
try {
input = tc.function.arguments.length > 0 ? JSON.parse(tc.function.arguments) : {};
} catch {
// Malformed args from a prior turn: pass through as a raw blob so
// the model sees the same shape it emitted. Wraps the string under
// _raw to match the buildMessagesPayload upstream convention.
input = { _raw: tc.function.arguments };
}
parts.push({ type: 'tool-call', toolCallId: tc.id, toolName: tc.function.name, input });
}
out.push({ role: 'assistant', content: parts });
continue;
}
if (m.role === 'tool') {
const toolCallId = m.tool_call_id ?? '';
const toolName = toolNameById.get(toolCallId) ?? 'unknown';
const raw = m.content ?? '';
let output: { type: 'text'; value: string } | { type: 'json'; value: JSONValue };
try {
// JSON.parse returns `any`; cast to JSONValue since the upstream
// tool_results column is already JSON-serializable by construction.
output = { type: 'json', value: JSON.parse(raw) as JSONValue };
} catch {
output = { type: 'text', value: raw };
}
out.push({
role: 'tool',
content: [{ type: 'tool-result', toolCallId, toolName, output }],
});
continue;
}
}
return out;
}
// Build the AI SDK tools record from BooCode's JSON-schema tool definitions.
// No `execute` field: BooCode runs tools itself in tool-phase.ts; streamText
// surfaces the tool-call parts via fullStream and we capture them for the
// outer loop to dispatch.
function buildAiTools(schemas: ToolJsonSchema[]): Record<string, ReturnType<typeof tool>> {
const out: Record<string, ReturnType<typeof tool>> = {};
for (const s of schemas) {
out[s.function.name] = tool({
description: s.function.description,
inputSchema: jsonSchema(s.function.parameters),
});
}
return out;
}
// v1.10.5 Qwen-coder XML fallback. Some local models (notably qwen3-coder via
// llama-swap) emit tool calls as inline XML inside delta.content rather than
// the structured delta.tool_calls field. The XML shape is:
// the structured tool_calls field. We extract them out of the streamed text
// before flushing it to the client, mirroring the pre-AI-SDK behavior.
//
// XML shape:
// <tool_call>
// <function=NAME>
// <parameter=KEY>
// VALUE
// </parameter>
// ...more parameters...
// <parameter=KEY>VALUE</parameter>
// ...
// </function>
// </tool_call>
// Multiple <tool_call> blocks may appear back-to-back; they never nest.
// streamCompletion buffers delta.content, extracts complete blocks, parses
// them via parseXmlToolCall, and pushes synthetic entries into the existing
// toolCallsBuffer alongside any native JSON-format tool calls.
export async function streamCompletion(
ctx: InferenceContext,
model: string,
@@ -96,149 +136,156 @@ export async function streamCompletion(
onUsage: ((prompt: number | null, completion: number | null) => void) | undefined,
signal?: AbortSignal
): Promise<StreamResult> {
const body: Record<string, unknown> = {
model,
messages,
stream: true,
stream_options: { include_usage: true },
};
if (opts.tools && opts.tools.length > 0) {
body['tools'] = opts.tools;
body['tool_choice'] = 'auto';
}
if (typeof opts.temperature === 'number') {
body['temperature'] = opts.temperature;
}
const aiMessages = toModelMessages(messages);
const hasTools = opts.tools !== null && opts.tools.length > 0;
const aiTools = hasTools ? buildAiTools(opts.tools!) : undefined;
const res = await fetch(`${ctx.config.LLAMA_SWAP_URL}/v1/chat/completions`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(body),
signal,
const startedAt = Date.now();
let reasoningDeltaCount = 0;
const result = streamText({
model: upstreamModel(ctx.config.LLAMA_SWAP_URL, model),
messages: aiMessages,
...(aiTools ? { tools: aiTools, toolChoice: 'auto' as const } : {}),
...(typeof opts.temperature === 'number' ? { temperature: opts.temperature } : {}),
abortSignal: signal,
});
if (!res.ok || !res.body) {
const text = await res.text().catch(() => '');
throw new Error(`llama-swap returned ${res.status}: ${text.slice(0, 200)}`);
}
let content = '';
// v1.10.5: holds delta.content bytes that may contain a partial XML tool
// call. Anything not part of a (possibly forming) <tool_call>…</tool_call>
// pair is flushed to content + onDelta as soon as we know it's safe.
let pendingBuffer = '';
let finishReason: string | null = null;
let promptTokens: number | null = null;
let completionTokens: number | null = null;
const toolCallsBuffer = new Map<number, { id: string; name: string; argsText: string }>();
// v1.13.1-A: AI SDK emits one `tool-call` part per fully-aggregated call,
// so we no longer need the OpenAI-index reassembly map the manual SSE
// parser used. XML tool calls extracted from text content go into the
// same flat list and keep the v1.10.5 synthetic id convention.
const toolCalls: ToolCall[] = [];
for await (const line of sseLines(res.body)) {
if (!line.startsWith('data:')) continue;
const payload = line.slice(5).trim();
if (payload === '[DONE]') break;
let parsed: ChatCompletionChunk;
try {
parsed = JSON.parse(payload);
} catch {
continue;
}
if (parsed.usage) {
if (typeof parsed.usage.prompt_tokens === 'number') {
promptTokens = parsed.usage.prompt_tokens;
}
if (typeof parsed.usage.completion_tokens === 'number') {
completionTokens = parsed.usage.completion_tokens;
}
onUsage?.(promptTokens, completionTokens);
}
// v1.11.3: removed dead `parsed.timings.n_ctx` read. llama-server's
// streaming completion does NOT emit n_ctx in timings (verified
// empirically); the authoritative source is llama-swap's
// /upstream/<model>/props endpoint, fetched per-turn via
// model-context.getModelContext() at the finalization sites below.
const choice = parsed.choices?.[0];
if (!choice) continue;
const delta = choice.delta ?? {};
if (typeof delta.content === 'string' && delta.content.length > 0) {
// v1.10.5 XML fallback. Append, then extract any complete tool_call
// blocks before deciding what's safe to flush as visible content.
pendingBuffer += delta.content;
while (true) {
const startIdx = pendingBuffer.indexOf(XML_TOOL_OPEN);
if (startIdx === -1) break;
const closeIdx = pendingBuffer.indexOf(XML_TOOL_CLOSE, startIdx);
if (closeIdx === -1) break;
const blockEnd = closeIdx + XML_TOOL_CLOSE.length;
const block = pendingBuffer.slice(startIdx, blockEnd);
// Any text before the opener is plain content — flush it now.
if (startIdx > 0) {
const before = pendingBuffer.slice(0, startIdx);
content += before;
onDelta(before);
for await (const part of result.fullStream) {
switch (part.type) {
case 'text-delta': {
pendingBuffer += part.text;
// Extract any complete <tool_call>...</tool_call> blocks before
// flushing visible text.
while (true) {
const startIdx = pendingBuffer.indexOf(XML_TOOL_OPEN);
if (startIdx === -1) break;
const closeIdx = pendingBuffer.indexOf(XML_TOOL_CLOSE, startIdx);
if (closeIdx === -1) break;
const blockEnd = closeIdx + XML_TOOL_CLOSE.length;
const block = pendingBuffer.slice(startIdx, blockEnd);
if (startIdx > 0) {
const before = pendingBuffer.slice(0, startIdx);
content += before;
onDelta(before);
}
const parsedCall = parseXmlToolCall(block);
if (parsedCall) {
const synthIdx = toolCalls.length;
toolCalls.push({
id: `xml_call_${synthIdx}`,
name: parsedCall.name,
args: parsedCall.args,
});
}
// Parse failures still drop the block — leaking <tool_call> XML to
// the chat would look worse than silently swallowing the bad block.
pendingBuffer = pendingBuffer.slice(blockEnd);
}
const parsedCall = parseXmlToolCall(block);
if (parsedCall) {
const synthIdx = toolCallsBuffer.size;
toolCallsBuffer.set(synthIdx, {
id: `xml_call_${synthIdx}`,
name: parsedCall.name,
argsText: JSON.stringify(parsedCall.args),
});
// Hold back any (partial or full) unclosed opener; flush the rest.
const partialIdx = partialXmlOpenerStart(pendingBuffer);
if (partialIdx >= 0) {
if (partialIdx > 0) {
const flush = pendingBuffer.slice(0, partialIdx);
content += flush;
onDelta(flush);
}
pendingBuffer = pendingBuffer.slice(partialIdx);
} else if (pendingBuffer.length > 0) {
content += pendingBuffer;
onDelta(pendingBuffer);
pendingBuffer = '';
}
// If parsing failed we still drop the block — emitting unparseable
// XML to the chat would look worse than silently swallowing it.
pendingBuffer = pendingBuffer.slice(blockEnd);
break;
}
// After all complete blocks are out, hold back any (partial or full)
// unclosed opener; flush the rest.
const partialIdx = partialXmlOpenerStart(pendingBuffer);
if (partialIdx >= 0) {
if (partialIdx > 0) {
const flush = pendingBuffer.slice(0, partialIdx);
content += flush;
onDelta(flush);
case 'tool-call': {
// AI SDK has already parsed the input into an object. Match the
// ToolCall shape BooCode passes around in toolCallsBuffer downstream.
toolCalls.push({
id: part.toolCallId,
name: part.toolName,
args: (part.input ?? {}) as Record<string, unknown>,
});
break;
}
case 'reasoning-delta': {
// v1.13.1-A: reasoning parts are dropped for now. v1.13.1-C will
// persist them as `kind='reasoning'` rows in message_parts. Counter
// is logged at finish so we know whether qwen3.6 actually emits any.
reasoningDeltaCount += 1;
break;
}
case 'finish': {
if (typeof part.finishReason === 'string') {
finishReason = part.finishReason;
}
pendingBuffer = pendingBuffer.slice(partialIdx);
} else if (pendingBuffer.length > 0) {
content += pendingBuffer;
onDelta(pendingBuffer);
pendingBuffer = '';
break;
}
}
if (Array.isArray(delta.tool_calls)) {
for (const tc of delta.tool_calls) {
const idx = tc.index;
const existing = toolCallsBuffer.get(idx) ?? { id: '', name: '', argsText: '' };
if (tc.id) existing.id = tc.id;
if (tc.function?.name) existing.name = tc.function.name;
if (typeof tc.function?.arguments === 'string') existing.argsText += tc.function.arguments;
toolCallsBuffer.set(idx, existing);
case 'error': {
const err = part.error;
throw err instanceof Error ? err : new Error(String(err));
}
// Intentional no-op: start, start-step, text-start, text-end,
// reasoning-start, reasoning-end, source, file, tool-input-start,
// tool-input-delta, tool-input-end, tool-result, tool-error,
// finish-step, raw. We only care about the aggregated tool-call and
// text-delta paths above; the rest are AI SDK lifecycle/streaming
// breadcrumbs that don't change BooCode's persistence or WS contract.
default:
break;
}
if (choice.finish_reason) finishReason = choice.finish_reason;
}
// v1.10.5: if the stream ended mid-XML (e.g. model truncated, no closer
// ever arrived), flush whatever was buffered as plain content so it isn't
// silently dropped. Better to show a stray `<tool_call>` than vanish text.
// v1.13.1-A: drain any buffered partial XML opener as plain text. The
// pre-AI-SDK path did this on stream end too — better to leak `<tool_c`
// than vanish the text.
if (pendingBuffer.length > 0) {
content += pendingBuffer;
onDelta(pendingBuffer);
pendingBuffer = '';
}
const toolCalls: ToolCall[] = [];
for (const [, t] of [...toolCallsBuffer.entries()].sort(([a], [b]) => a - b)) {
let args: Record<string, unknown> = {};
if (t.argsText.length > 0) {
try {
args = JSON.parse(t.argsText);
} catch {
args = { _raw: t.argsText };
}
}
toolCalls.push({ id: t.id || `call_${toolCalls.length}`, name: t.name, args });
// v1.13.1-A: AI SDK v6 swallows the abort signal — the fullStream iterator
// exits cleanly and we'd otherwise return a successful StreamResult, which
// makes executeStreamPhase call finalizeCompletion and write status='complete'.
// Detect post-iteration abort and throw an AbortError so handleAbortOrError
// owns the row instead, matching v1.12.x stop-button behavior.
if (signal?.aborted) {
const abortErr = new Error('aborted');
abortErr.name = 'AbortError';
throw abortErr;
}
// Usage lands as a promise on the result; awaiting after fullStream is
// drained is safe. AI SDK v6 names: `inputTokens` / `outputTokens`.
let promptTokens: number | null = null;
let completionTokens: number | null = null;
try {
const usage = await result.usage;
if (typeof usage.inputTokens === 'number') promptTokens = usage.inputTokens;
if (typeof usage.outputTokens === 'number') completionTokens = usage.outputTokens;
} catch {
// Some providers omit usage on partial streams; leave both null.
}
if (onUsage && (promptTokens !== null || completionTokens !== null)) {
onUsage(promptTokens, completionTokens);
}
if (reasoningDeltaCount > 0) {
ctx.log.debug(
{ reasoningDeltaCount, model, elapsed_ms: Date.now() - startedAt },
'streamCompletion: reasoning deltas dropped (captured in v1.13.1-C)',
);
}
return { finishReason, content, toolCalls, promptTokens, completionTokens };
@@ -313,9 +360,12 @@ export async function executeStreamPhase(
const mctxForStream = await modelContext.getModelContext(session.model);
const nCtxForStream = mctxForStream?.n_ctx ?? null;
// v1.12.2: throttle live usage publishes to ~500ms. The model can land
// dozens of usage frames per second; without a throttle the WS turns into
// a firehose for a few KB savings on each render.
// 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;

88
pnpm-lock.yaml generated
View File

@@ -48,12 +48,18 @@ importers:
apps/server:
dependencies:
'@ai-sdk/openai-compatible':
specifier: ^2.0.47
version: 2.0.47(zod@3.25.76)
'@fastify/static':
specifier: ^7.0.4
version: 7.0.4
'@fastify/websocket':
specifier: ^10.0.1
version: 10.0.1
ai:
specifier: ^6.0.190
version: 6.0.190(zod@3.25.76)
fastify:
specifier: ^4.28.1
version: 4.29.1
@@ -179,6 +185,28 @@ importers:
packages:
'@ai-sdk/gateway@3.0.119':
resolution: {integrity: sha512-VAhfRWC+JexZakkVfmjaJKaTj00x7/UHdE8kMWL3NhuQAlf8oXtg9r4dfvFZrByXxchGRBvYE3biEUyibkg0xg==}
engines: {node: '>=18'}
peerDependencies:
zod: ^3.25.76 || ^4.1.8
'@ai-sdk/openai-compatible@2.0.47':
resolution: {integrity: sha512-Enm5UlL0zUCrW3792opk5h7hRWxZOZzDe6eQYVFqX9LUOGGCe1h8MZWAGim765nwzgnjlpeYOsuzZmLtRsTPlg==}
engines: {node: '>=18'}
peerDependencies:
zod: ^3.25.76 || ^4.1.8
'@ai-sdk/provider-utils@4.0.27':
resolution: {integrity: sha512-ubkAJ+xODouwtmN1tYlvTPphH1hPOBfZaEQe8U7skGvFAnIRs9PPpsq57bC2+Ky/MB4yzhd6YOsxTAx9sGpazw==}
engines: {node: '>=18'}
peerDependencies:
zod: ^3.25.76 || ^4.1.8
'@ai-sdk/provider@3.0.10':
resolution: {integrity: sha512-Q3BZ27qfpYqnCYGvE3vt+Qi6LGOF9R5Nmzn+9JoM1lCRsD9mYaIhfJLkSunN48nfGXJ6n+XNV0J/XVpqGQl7Dw==}
engines: {node: '>=18'}
'@alloc/quick-lru@5.2.0':
resolution: {integrity: sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==}
engines: {node: '>=10'}
@@ -789,6 +817,10 @@ packages:
'@open-draft/until@2.1.0':
resolution: {integrity: sha512-U69T3ItWHvLwGg5eJ0n3I62nWuE6ilHlmz7zM0npLBRvPRd7e6NYmg54vvRtP5mZG7kZqZCFVdsTWo7BPtBujg==}
'@opentelemetry/api@1.9.1':
resolution: {integrity: sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q==}
engines: {node: '>=8.0.0'}
'@pinojs/redact@0.4.0':
resolution: {integrity: sha512-k2ENnmBugE/rzQfEcdWHcCY+/FM3VLzH9cYEsbdsoqrvzAKRhUZeRNhAZvB8OitQJ1TBed3yqWtdjzS6wJKBwg==}
@@ -1646,6 +1678,9 @@ packages:
resolution: {integrity: sha512-tlqY9xq5ukxTUZBmoOp+m61cqwQD5pHJtFY3Mn8CA8ps6yghLH/Hw8UPdqg4OLmFW3IFlcXnQNmo/dh8HzXYIQ==}
engines: {node: '>=18'}
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