Tool and parameter descriptions were handed to the LLM in Chinese on every
runtime regardless of locale: the English metadata table in
packages/tools/src/tool-metadata.ts had no caller, the desktop translateTool
looked up i18n keys that exist in no locale file, and the MCP server had no
locale at all.
Fill the table for every tool whose definition text is Chinese (37 entries,
only translating what the definitions write in Chinese so the two copies
cannot drift), and route the four consumers through getLocalizedToolMetadata:
the cross-chat agent adapters, the CLI Web agent adapter, the desktop shared
tool adapter (replacing the dead translateTool), and the MCP server, which
now resolves its locale from config.locale.lang or the system locale for both
the standalone binary and the chatlab mcp subcommand.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
CLI dropped completed tool results from replay. Persist bounded results by call ID with error state.
CLI 续聊遗漏已完成的工具结果；按调用 ID 保存限长结果和错误状态。
Add SQLite reload regression for concurrent calls and truncated answers.
新增 SQLite 重载回归，覆盖并行调用与回答截断。
Preserve partial output and token usage in CLI turns and edited UI rounds while leaving ordinary failures and cancellation unchanged. Use OutputLimitError across agent runners so incomplete turns remain visibly unsuccessful but can be reloaded and continued.
Cover real stream handling, SQLite persistence, reload, CLI continuation, and unsuccessful one-shot JSON output.
Preserve repeated same-second WeFlow and EchoTrace messages while consuming existing fallback occurrences one for one across overlapping imports and merged sources.
中文：将用户与助手消息合并为单事务写入，失败时不再留下孤儿消息或误报成功。
English: Persist user and assistant messages in one transaction so failures leave no orphaned turn or false success.
Remove the proactive-memory preference and its cross-platform runtime plumbing so memory behavior has one clear contract. Normalize away the obsolete setting and keep source type limited to provenance.
Resolve private ranking display names, apply privacy preprocessing consistently across cached recaps and structural labels, and bound model-visible overview payloads to the configured tool budget.
Count complete tool payloads with the runtime tokenizer so Chinese evidence respects the configured model context budget.\n\nResolve contact sources incrementally with cancellation checks and targeted member lookups to keep long cross-chat investigations responsive.
Match ownerless QQ exports safely across UID and UIN drift, preserve merged message scopes through single and batch imports, and apply only sender mappings proven by overlapping platform message IDs. Reject incomplete group mappings to avoid member identity corruption.
The CLI tsup build inlines @openchatlab/node-runtime into dist chunks.
Both sqlite-vec and @huggingface/transformers load platform-specific
native packages at runtime (sqlite-vec-linux-arm64, onnxruntime-node,
sharp), so inlining them breaks global/npm and Docker installs of
chatlab-cli: the bundled chunks reference native packages that were
never installed, and configuring the semantic index vector model fails
with HTTP 500 (Cannot find package 'sqlite-vec-linux-arm64').
Declare both packages as chatlab-cli dependencies and mark them as tsup
external so they are installed from npm with their native bindings,
matching how better-sqlite3 and @node-rs/jieba are already handled.
Preserve batch support through telemetry, forward item-scoped progress across Desktop and CLI Web, and retain original backend failure details for diagnostics and unfinished results.
Add self-hosted Umami reporting alongside existing telemetry across Desktop and CLI Web.
Track normalized startup, import, feature, and AI usage with a stable anonymous ID and strict privacy allowlists. Keep incremental usage platform-independent and preserve accurate failure classifications and platform metadata across import paths.
Chris ChengandClaude Opus 5
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