Build: Release v2.80.28
This commit is contained in:
g1nation
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"result": "Final report with inconsistencies. This should be long enough to pass validation.",
|
||||
"createdAt": 1778419501265,
|
||||
"createdAt": 1778420449683,
|
||||
"modelVersion": "unknown"
|
||||
}
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"result": "[CONFLICT WARNING] 성능이 200% 증가했습니다. vs 그러나 동시에 50% 감소했습니다. 최적화와 성능 저하가 동시에 발견됨.",
|
||||
"createdAt": 1778419501264,
|
||||
"createdAt": 1778420449675,
|
||||
"modelVersion": "unknown"
|
||||
}
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"result": "Detailed Execution Plan: 1. Research 2. Analyze 3. Write report with high quality.",
|
||||
"createdAt": 1778419501204,
|
||||
"createdAt": 1778420449670,
|
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"modelVersion": "unknown"
|
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}
|
||||
+2
-2
@@ -1,5 +1,5 @@
|
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{
|
||||
"result": "---\nid: stress_conflict_1778419501171\ndate: 2026-05-10T13:25:01.265Z\ntype: knowledge_artifact\nstandard: P-Reinforce v3.0\ntags: [automated, connect_ai, brain_sync]\n---\n\n## 📌 Brief Summary\nFinal report with inconsistencies. This should be long enough to pass validation.\n\nFinal report with inconsistencies. This should be long enough to pass validation.\n\n---\n## 💡 Astra의 선제적 제안 (Proactive Next Actions)\nFinal report with inconsistencies. This should be long enough to pass validation.\n---\n## 🛡️ Reliability & Audit Summary\n> [!NOTE]\n> 이 문서는 ConnectAI의 **Intelligent Resilience** 엔진에 의해 검증 및 정제되었습니다.\n\n| Metric | Value | Status |\n| :--- | :--- | :--- |\n| **Conflict Risk** | `60/100` | ⚠️ Medium |\n| **Fallbacks Used** | `0` | ✅ None |\n| **Auto Retries** | `0` | ✅ Stable |\n| **Deduplication** | `0` | Standard |\n| **Processing Time** | `0.1s` | ✅ Fast |\n\n### 🔍 Decision Audit Trail\n- **[PLANNER]** 전략 수립 중... (32ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (1ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (61ms)\n",
|
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"createdAt": 1778419501265,
|
||||
"result": "---\nid: stress_conflict_1778420449655\ndate: 2026-05-10T13:40:49.687Z\ntype: knowledge_artifact\nstandard: P-Reinforce v3.0\ntags: [automated, connect_ai, brain_sync]\n---\n\n## 📌 Brief Summary\nFinal report with inconsistencies. This should be long enough to pass validation.\n\nFinal report with inconsistencies. This should be long enough to pass validation.\n\n---\n## 💡 Astra의 선제적 제안 (Proactive Next Actions)\nFinal report with inconsistencies. This should be long enough to pass validation.\n---\n## 🛡️ Reliability & Audit Summary\n> [!NOTE]\n> 이 문서는 ConnectAI의 **Intelligent Resilience** 엔진에 의해 검증 및 정제되었습니다.\n\n| Metric | Value | Status |\n| :--- | :--- | :--- |\n| **Conflict Risk** | `60/100` | ⚠️ Medium |\n| **Fallbacks Used** | `0` | ✅ None |\n| **Auto Retries** | `0` | ✅ Stable |\n| **Deduplication** | `0` | Standard |\n| **Processing Time** | `0.0s` | ✅ Fast |\n\n### 🔍 Decision Audit Trail\n- **[PLANNER]** 전략 수립 중... (11ms)\n- **[RESEARCHER]** 핵심 정보 수집 및 분석 중... (4ms)\n- **[WRITER]** 최종 리포트 작성 및 편집 중... (9ms)\n",
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"createdAt": 1778420449687,
|
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"modelVersion": "unknown"
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}
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+11
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@@ -1,8 +1,8 @@
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{
|
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"missionId": "stress_conflict_1778419501171",
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"missionId": "stress_conflict_1778420449655",
|
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"status": "completed",
|
||||
"startTime": "2026-05-10T13:25:01.171Z",
|
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"totalElapsedMs": 94,
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"startTime": "2026-05-10T13:40:49.655Z",
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"totalElapsedMs": 32,
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"results": {
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"planner": "Detailed Execution Plan: 1. Research 2. Analyze 3. Write report with high quality.",
|
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"researcher": "[CONFLICT WARNING] 성능이 200% 증가했습니다. vs 그러나 동시에 50% 감소했습니다. 최적화와 성능 저하가 동시에 발견됨.",
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@@ -16,30 +16,30 @@
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{
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"from": "idle",
|
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"to": "planner",
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"durationMs": 32,
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"durationMs": 11,
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"message": "전략 수립 중...",
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"ts": "2026-05-10T13:25:01.203Z"
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"ts": "2026-05-10T13:40:49.666Z"
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},
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{
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"from": "planner",
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"to": "researcher",
|
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"durationMs": 1,
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"durationMs": 4,
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"message": "핵심 정보 수집 및 분석 중...",
|
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"ts": "2026-05-10T13:25:01.204Z"
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"ts": "2026-05-10T13:40:49.670Z"
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},
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{
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"from": "researcher",
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"to": "writer",
|
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"durationMs": 61,
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"durationMs": 9,
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"message": "최종 리포트 작성 및 편집 중...",
|
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"ts": "2026-05-10T13:25:01.265Z"
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"ts": "2026-05-10T13:40:49.679Z"
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},
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{
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"from": "writer",
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"to": "completed",
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"durationMs": 0,
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"durationMs": 8,
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"message": "미션 완료",
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"ts": "2026-05-10T13:25:01.265Z"
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"ts": "2026-05-10T13:40:49.687Z"
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}
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],
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"resilienceMetrics": {
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@@ -1,5 +1,15 @@
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# Astra Patch Notes
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## v2.80.28 (2026-05-10)
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### 🏛️ Knowledge Architecture & Skill Scoping
|
||||
- **지식 맵핑 고도화 (Knowledge Mapping):** `agentKnowledgeMap.ts` 및 `scopedBrainRetriever.ts` 도입을 통해 에이전트별로 검색할 지식 범위를 정교하게 제한하고 관리하는 기능을 추가했습니다.
|
||||
- **사이드바 UI 안정화:** 미디어 폴더의 `sidebar.html`, `sidebar.js`를 갱신하여 사용자 인터랙션과 상태 동기화의 정합성을 개선했습니다.
|
||||
- **패키징 최적화:** 최신 빌드 파이프라인을 통해 `astra-2.80.28.vsix` 패키지를 생성하고, 스트레스 테스트를 통해 엔진의 복원력을 재검증했습니다.
|
||||
- **시스템 안정성 강화:** `extension.ts` 및 `agentHandlers.ts` 내의 비동기 처리 로직을 보완하여 다중 에이전트 실행 시의 안정성을 확보했습니다.
|
||||
|
||||
---
|
||||
|
||||
|
||||
## v2.64.0 (2026-05-04)
|
||||
### 🛡️ Resilient Pipeline & Stability Overhaul
|
||||
- **상태 영속성 및 재개 (State Persistence & Resume):** 미션 진행 상태를 디스크(`.astra/missions/`)에 실시간 저장하며, 크래시나 오류 발생 시 마지막 단계부터 자율 재개하는 기능 도입.
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@
|
||||
"name": "astra",
|
||||
"displayName": "Astra",
|
||||
"description": "The personal intelligence layer for Antigravity and VS Code. A private cognitive partner for deep project context, memory, and proactive strategic decision-making.",
|
||||
"version": "2.80.27",
|
||||
"version": "2.80.28",
|
||||
"publisher": "g1nation",
|
||||
"license": "MIT",
|
||||
"icon": "assets/icon.png",
|
||||
|
||||
+135
-19
@@ -39,6 +39,7 @@ import {
|
||||
} from './features/secondBrainTrace';
|
||||
import { MemoryManager } from './memory';
|
||||
import { RetrievalOrchestrator } from './retrieval';
|
||||
import { resolveScopeForAgent } from './skills/agentKnowledgeMap';
|
||||
|
||||
export interface ChatMessage {
|
||||
role: 'user' | 'assistant' | 'system';
|
||||
@@ -245,6 +246,7 @@ export class AgentExecutor {
|
||||
systemPrompt?: string,
|
||||
runId?: number,
|
||||
agentSkillContext?: string,
|
||||
agentSkillFile?: string,
|
||||
negativePrompt?: string,
|
||||
designerContext?: string,
|
||||
secondBrainTraceEnabled?: boolean,
|
||||
@@ -414,7 +416,7 @@ export class AgentExecutor {
|
||||
const secondBrainTraceCtx = secondBrainTrace
|
||||
? `\n\n${renderSecondBrainTraceContext(secondBrainTrace)}`
|
||||
: '';
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||||
const memoryCtx = this.buildMemoryContext(prompt || '', activeBrain);
|
||||
const memoryCtx = this.buildMemoryContext(prompt || '', activeBrain, options.agentSkillFile);
|
||||
|
||||
// ──────────────────────────────────────────────────────────────────
|
||||
// [Agent Mode v3] 에이전트가 선택된 경우, Astra 기본 포맷/페르소나 섹션을
|
||||
@@ -524,6 +526,12 @@ export class AgentExecutor {
|
||||
if (!reader) throw new Error("Response body is not readable.");
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
// try/finally guarantees the reader's lock is released on every
|
||||
// exit path (normal end, AbortError, parse exception, stale-run
|
||||
// early return). Without this, downstream consumers — including
|
||||
// any retry path that wants to drain the same body — fail with
|
||||
// "lock() request could not be registered" because the previous
|
||||
// reader still holds the stream lock.
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
@@ -555,6 +563,8 @@ export class AgentExecutor {
|
||||
logError('Stream reading error.', { engine, apiUrl, error: err?.message || String(err) });
|
||||
this.webview?.postMessage({ type: 'error', value: `Connection lost: ${err.message}` });
|
||||
}
|
||||
} finally {
|
||||
try { reader.releaseLock(); } catch { /* reader may already be released on AbortError */ }
|
||||
}
|
||||
}
|
||||
|
||||
@@ -579,6 +589,38 @@ export class AgentExecutor {
|
||||
requestTimeoutHandle = undefined;
|
||||
}
|
||||
|
||||
// ── Empty-response auto-recovery ──
|
||||
// Streaming failed silently (network blip, model cold-start, context
|
||||
// overflow, etc.). Before surfacing the error to the user, try one
|
||||
// non-streaming retry: many LM Studio failures are streaming-only
|
||||
// (the SSE channel drops mid-token while a single POST returns the
|
||||
// whole answer fine). This covers the most common "empty response"
|
||||
// pattern users hit without the user having to click anything.
|
||||
//
|
||||
// Only attempts recovery on loopDepth === 0 — we don't want to
|
||||
// ping-pong inside the autonomous action loop.
|
||||
if (!aiResponseText.trim() && !this.abortController?.signal.aborted && loopDepth === 0) {
|
||||
try {
|
||||
logInfo('Empty stream — trying non-streaming fallback.', { engine, model: actualModel, apiUrl });
|
||||
const fallback = await this.callNonStreaming({
|
||||
baseUrl: ollamaUrl,
|
||||
modelName: actualModel,
|
||||
engine,
|
||||
messages: messagesForRequest,
|
||||
temperature,
|
||||
signal: this.abortController?.signal,
|
||||
});
|
||||
if (fallback && fallback.trim()) {
|
||||
aiResponseText = fallback;
|
||||
logInfo('Non-streaming fallback recovered the answer.', { engine, model: actualModel, length: fallback.length });
|
||||
}
|
||||
} catch (recoverErr: any) {
|
||||
logError('Non-streaming fallback also failed.', {
|
||||
engine, model: actualModel, error: recoverErr?.message ?? String(recoverErr),
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// 5. Execute Actions
|
||||
const rationale = this.parseRationale(aiResponseText);
|
||||
let assistantContent = this.enforceLocalPathReviewAnswer(
|
||||
@@ -630,14 +672,26 @@ export class AgentExecutor {
|
||||
this.statusBarManager.updateStatus(AgentStatus.Executing);
|
||||
const report = await this.executeActions(aiResponseText, rootPath, activeBrain);
|
||||
if (!assistantContent.trim() && report.length === 0) {
|
||||
logError('Model returned an empty response without actions.', { model: actualModel, engine, apiUrl, loopDepth });
|
||||
const promptCharCount = messagesForRequest.reduce((sum, m) => sum + (m.content?.length ?? 0), 0);
|
||||
logError('Model returned an empty response without actions.', {
|
||||
model: actualModel, engine, apiUrl, loopDepth,
|
||||
promptCharCount, messageCount: messagesForRequest.length,
|
||||
fallbackTried: loopDepth === 0 ? 'yes' : 'no',
|
||||
});
|
||||
this.webview.postMessage({
|
||||
type: 'error',
|
||||
value: [
|
||||
'AI engine returned an empty response.',
|
||||
'AI 엔진이 빈 응답을 반환했습니다 (스트리밍 + non-streaming 폴백 모두 실패).',
|
||||
`Engine: ${engine}`,
|
||||
`Model: ${actualModel}`,
|
||||
'The request reached the local LLM server, but no usable content was returned. Try another model, restart the local server, or reduce the prompt/context size.'
|
||||
`Prompt size: ${promptCharCount.toLocaleString()} chars across ${messagesForRequest.length} message(s)`,
|
||||
'',
|
||||
'다음을 시도해보세요:',
|
||||
' • LM Studio에서 모델이 실제로 로드되어 있는지 확인',
|
||||
promptCharCount > 16000
|
||||
? ' • 프롬프트가 너무 큽니다 (16k chars 초과). Skill/Brain 컨텍스트를 좁혀 보세요.'
|
||||
: ' • 다른 모델로 전환하거나 LM Studio 서버를 재시작',
|
||||
' • Settings에서 maxContextSize 또는 memoryLongTermFiles 줄이기',
|
||||
].join('\n')
|
||||
});
|
||||
return;
|
||||
@@ -809,20 +863,24 @@ export class AgentExecutor {
|
||||
if (!reader) throw new Error("Agent response body is not readable.");
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
const chunk = decoder.decode(value, { stream: true });
|
||||
const lines = chunk.split('\n');
|
||||
for (const line of lines) {
|
||||
const trimmed = line.trim();
|
||||
if (!trimmed || trimmed === 'data: [DONE]') continue;
|
||||
try {
|
||||
const json = JSON.parse(trimmed.startsWith('data: ') ? trimmed.slice(6) : trimmed);
|
||||
const content = json.choices?.[0]?.delta?.content || json.message?.content || '';
|
||||
responseText += content;
|
||||
} catch (e) { }
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
const chunk = decoder.decode(value, { stream: true });
|
||||
const lines = chunk.split('\n');
|
||||
for (const line of lines) {
|
||||
const trimmed = line.trim();
|
||||
if (!trimmed || trimmed === 'data: [DONE]') continue;
|
||||
try {
|
||||
const json = JSON.parse(trimmed.startsWith('data: ') ? trimmed.slice(6) : trimmed);
|
||||
const content = json.choices?.[0]?.delta?.content || json.message?.content || '';
|
||||
responseText += content;
|
||||
} catch (e) { }
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
try { reader.releaseLock(); } catch { /* already released */ }
|
||||
}
|
||||
return responseText;
|
||||
}
|
||||
@@ -1962,7 +2020,7 @@ export class AgentExecutor {
|
||||
});
|
||||
}
|
||||
|
||||
private buildMemoryContext(currentPrompt: string, activeBrain: BrainProfile): string {
|
||||
private buildMemoryContext(currentPrompt: string, activeBrain: BrainProfile, agentSkillFile?: string): string {
|
||||
const config = getConfig();
|
||||
if (!config.memoryEnabled) return '';
|
||||
|
||||
@@ -1976,6 +2034,12 @@ export class AgentExecutor {
|
||||
const workspaceFolders = vscode.workspace.workspaceFolders;
|
||||
const workspacePath = workspaceFolders ? workspaceFolders[0].uri.fsPath : undefined;
|
||||
|
||||
// Resolve scope folders from the agent ↔ knowledge map. When the user
|
||||
// hasn't selected an agent (or the selection has no mapping), `folders`
|
||||
// is empty and the orchestrator falls back to whole-brain search —
|
||||
// keeping the legacy behavior intact.
|
||||
const scope = resolveScopeForAgent(agentSkillFile, activeBrain.localBrainPath);
|
||||
|
||||
// Use the Unified RAG Pipeline
|
||||
const result = this.retrievalOrchestrator.retrieve(currentPrompt, {
|
||||
brain: activeBrain,
|
||||
@@ -1986,7 +2050,8 @@ export class AgentExecutor {
|
||||
totalBudget: 8000,
|
||||
retrievalRatio: 0.4
|
||||
},
|
||||
brainFileLimit: config.memoryLongTermFiles
|
||||
brainFileLimit: config.memoryLongTermFiles,
|
||||
scopeFolders: scope.folders
|
||||
});
|
||||
|
||||
return this.retrievalOrchestrator.buildContextString(result);
|
||||
@@ -2117,6 +2182,57 @@ export class AgentExecutor {
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Non-streaming chat completion. Used as a recovery path when the
|
||||
* streaming endpoint returns an empty response — common with LM Studio
|
||||
* when a model is mid-load or the SSE channel drops.
|
||||
*
|
||||
* The body is consumed via `await response.text()` (single read), so
|
||||
* there's no ReadableStream lock to release and no chance of the
|
||||
* "lock() request could not be registered" error this method is helping
|
||||
* to avoid.
|
||||
*/
|
||||
private async callNonStreaming(params: {
|
||||
baseUrl: string;
|
||||
modelName: string;
|
||||
engine: 'lmstudio' | 'ollama';
|
||||
messages: ChatMessage[];
|
||||
temperature: number;
|
||||
signal?: AbortSignal;
|
||||
}): Promise<string> {
|
||||
const { baseUrl, modelName, engine, messages, temperature, signal } = params;
|
||||
const apiUrl = buildApiUrl(baseUrl, engine, 'chat');
|
||||
const variants = this.buildEngineMessageVariants(messages, engine);
|
||||
const body = {
|
||||
model: modelName,
|
||||
messages: variants[0].messages,
|
||||
stream: false,
|
||||
...(engine === 'lmstudio'
|
||||
? { max_tokens: 4096, temperature }
|
||||
: { options: { num_ctx: 32768, num_predict: 4096, temperature } }),
|
||||
};
|
||||
const response = await fetch(apiUrl, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(body),
|
||||
signal,
|
||||
});
|
||||
if (!response.ok) {
|
||||
const errText = await response.text().catch(() => '');
|
||||
throw new Error(`Non-streaming fallback returned ${response.status}: ${summarizeText(errText, 200)}`);
|
||||
}
|
||||
const text = await response.text();
|
||||
try {
|
||||
const json = JSON.parse(text);
|
||||
if (engine === 'lmstudio') {
|
||||
return json?.choices?.[0]?.message?.content ?? '';
|
||||
}
|
||||
return json?.message?.content ?? json?.response ?? '';
|
||||
} catch {
|
||||
return '';
|
||||
}
|
||||
}
|
||||
|
||||
private normalizeMessages(messages: ChatMessage[]) {
|
||||
return messages.map((message) => {
|
||||
const normalizedContent = typeof message.content === 'string'
|
||||
|
||||
@@ -48,6 +48,19 @@ export class LMStudioStreamer implements IChatStreamer {
|
||||
signal: req.signal,
|
||||
});
|
||||
|
||||
// Bridge AbortSignal → prediction.cancel(): without this, an aborted
|
||||
// request keeps generating on the LM Studio server. The orphaned
|
||||
// prediction holds locks on the model handle, which is a known cause
|
||||
// of "lock() request could not be registered" on the very next
|
||||
// request — the reused handle is still bound to a dead prediction.
|
||||
const onAbort = () => {
|
||||
try { (prediction as any)?.cancel?.(); } catch { /* swallow — best effort */ }
|
||||
};
|
||||
if (req.signal) {
|
||||
if (req.signal.aborted) onAbort();
|
||||
else req.signal.addEventListener('abort', onAbort, { once: true });
|
||||
}
|
||||
|
||||
try {
|
||||
for await (const fragment of prediction as AsyncIterable<{ content: string }>) {
|
||||
if (req.signal?.aborted) return;
|
||||
@@ -59,6 +72,8 @@ export class LMStudioStreamer implements IChatStreamer {
|
||||
if (err?.name === 'AbortError') return;
|
||||
logError('LM Studio SDK chat stream failed.', { model: trimmedModel, error: err?.message ?? String(err) });
|
||||
throw err;
|
||||
} finally {
|
||||
req.signal?.removeEventListener?.('abort', onAbort);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
+22
-3
@@ -16,6 +16,7 @@ import * as fs from 'fs';
|
||||
import * as path from 'path';
|
||||
import { BrainProfile } from '../config';
|
||||
import { findBrainFiles, summarizeText } from '../utils';
|
||||
import { isInside } from '../lib/paths';
|
||||
import { MemoryManager } from '../memory';
|
||||
import { RetrievalChunk, RetrievalResult, ContextBudgetConfig } from './types';
|
||||
import { tokenize, expandQuery, scoreTfIdf, extractBestExcerpt } from './scoring';
|
||||
@@ -33,6 +34,14 @@ interface RetrievalOptions {
|
||||
contextBudget?: Partial<ContextBudgetConfig>;
|
||||
brainFileLimit?: number;
|
||||
includeRawConversations?: boolean;
|
||||
/**
|
||||
* Optional absolute folder paths constraining brain-file search to those
|
||||
* subtrees. When provided and non-empty, only brain files inside one of
|
||||
* the folders are considered. Empty / undefined preserves whole-brain
|
||||
* search (legacy behavior). Folders that escape the brain root are
|
||||
* silently dropped by the caller (see `agentKnowledgeMap.resolveScopeForAgent`).
|
||||
*/
|
||||
scopeFolders?: string[];
|
||||
}
|
||||
|
||||
export class RetrievalOrchestrator {
|
||||
@@ -50,15 +59,21 @@ export class RetrievalOrchestrator {
|
||||
fusionLog.push(`Expanded tokens: [${expandedTokens.slice(0, 15).join(', ')}]`);
|
||||
|
||||
// ── ① Brain File Search (TF-IDF enhanced) ──
|
||||
const scopeFolders = options.scopeFolders ?? [];
|
||||
const brainChunks = this.searchBrainFiles(
|
||||
query,
|
||||
expandedTokens,
|
||||
options.brain,
|
||||
options.brainFileLimit || 8,
|
||||
options.includeRawConversations || false
|
||||
options.includeRawConversations || false,
|
||||
scopeFolders
|
||||
);
|
||||
allChunks.push(...brainChunks);
|
||||
fusionLog.push(`Brain search: ${brainChunks.length} chunks found`);
|
||||
fusionLog.push(
|
||||
scopeFolders.length > 0
|
||||
? `Brain search (scoped to ${scopeFolders.length} folder(s)): ${brainChunks.length} chunks`
|
||||
: `Brain search: ${brainChunks.length} chunks found`
|
||||
);
|
||||
|
||||
// ── ② Memory Layers ──
|
||||
const memoryChunks = this.searchMemoryLayers(
|
||||
@@ -106,10 +121,14 @@ export class RetrievalOrchestrator {
|
||||
expandedTokens: string[],
|
||||
brain: BrainProfile,
|
||||
limit: number,
|
||||
includeRaw: boolean
|
||||
includeRaw: boolean,
|
||||
scopeFolders: string[] = []
|
||||
): RetrievalChunk[] {
|
||||
try {
|
||||
const scoped = (file: string) => scopeFolders.length === 0
|
||||
|| scopeFolders.some((folder) => isInside(folder, file));
|
||||
const allFiles = findBrainFiles(brain.localBrainPath)
|
||||
.filter(scoped)
|
||||
.filter((file) => includeRaw || !this.isRawConversation(path.relative(brain.localBrainPath, file)));
|
||||
|
||||
if (allFiles.length === 0) return [];
|
||||
|
||||
@@ -1807,6 +1807,7 @@ export class SidebarChatProvider implements vscode.WebviewViewProvider, BridgeIn
|
||||
internetEnabled: internet,
|
||||
visionContent: imageFiles,
|
||||
agentSkillContext,
|
||||
agentSkillFile: typeof agentFile === 'string' ? agentFile : undefined,
|
||||
negativePrompt,
|
||||
designerContext,
|
||||
secondBrainTraceEnabled: secondBrainTrace !== false,
|
||||
|
||||
Reference in New Issue
Block a user