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Author SHA1 Message Date
Vaayne
1e8251a05e add model catalogs 2025-07-06 21:27:27 +08:00
1213 changed files with 74699 additions and 127214 deletions

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@@ -1,9 +1,9 @@
root = true
[*]
charset = utf-8
indent_style = space
indent_size = 2
end_of_line = lf
insert_final_newline = true
trim_trailing_whitespace = true
root = true
[*]
charset = utf-8
indent_style = space
indent_size = 2
end_of_line = lf
insert_final_newline = true
trim_trailing_whitespace = true

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@@ -1,8 +0,0 @@
NODE_OPTIONS=--max-old-space-size=8000
API_KEY="sk-xxx"
BASE_URL="https://api.siliconflow.cn/v1/"
MODEL="Qwen/Qwen3-235B-A22B-Instruct-2507"
CSLOGGER_MAIN_LEVEL=info
CSLOGGER_RENDERER_LEVEL=info
#CSLOGGER_MAIN_SHOW_MODULES=
#CSLOGGER_RENDERER_SHOW_MODULES=

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@@ -1,2 +0,0 @@
# ignore #7923 eol change and code formatting
4ac8a388347ff35f34de42c3ef4a2f81f03fb3b1

1
.gitattributes vendored
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@@ -1,3 +1,2 @@
* text=auto eol=lf
/.yarn/** linguist-vendored
/.yarn/releases/* binary

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@@ -1,7 +1,7 @@
name: 🐛 错误报告 (中文)
description: 创建一个报告以帮助我们改进
title: '[错误]: '
labels: ['BUG']
labels: ['kind/bug']
body:
- type: markdown
attributes:
@@ -24,8 +24,6 @@ body:
required: true
- label: 我填写了简短且清晰明确的标题,以便开发者在翻阅 Issue 列表时能快速确定大致问题。而不是“一个建议”、“卡住了”等。
required: true
- label: 我确认我正在使用最新版本的 Cherry Studio。
required: true
- type: dropdown
id: platform

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@@ -1,7 +1,7 @@
name: 💡 功能建议 (中文)
description: 为项目提出新的想法
title: '[功能]: '
labels: ['feature']
labels: ['kind/enhancement']
body:
- type: markdown
attributes:

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@@ -1,7 +1,7 @@
name: ❓ 提问 & 讨论 (中文)
description: 寻求帮助、讨论问题、提出疑问等...
title: '[讨论]: '
labels: ['discussion', 'help wanted']
labels: ['kind/question']
body:
- type: markdown
attributes:

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@@ -73,4 +73,4 @@ body:
id: additional
attributes:
label: 附加信息
description: 任何能让我们对您的问题有更多了解的信息,包括截图或相关链接
description: 任何能让我们对您的问题有更多了解的信息,包括截图或相关链接

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@@ -1,7 +1,7 @@
name: 🐛 Bug Report (English)
description: Create a report to help us improve
title: '[Bug]: '
labels: ['BUG']
labels: ['kind/bug']
body:
- type: markdown
attributes:
@@ -24,8 +24,6 @@ body:
required: true
- label: I've filled in short, clear headings so that developers can quickly identify a rough idea of what to expect when flipping through the list of issues. And not "a suggestion", "stuck", etc.
required: true
- label: I've confirmed that I am using the latest version of Cherry Studio.
required: true
- type: dropdown
id: platform

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@@ -1,7 +1,7 @@
name: 💡 Feature Request (English)
description: Suggest an idea for this project
title: '[Feature]: '
labels: ['feature']
labels: ['kind/enhancement']
body:
- type: markdown
attributes:

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@@ -1,7 +1,7 @@
name: ❓ Questions & Discussion
description: Seeking help, discussing issues, asking questions, etc...
title: '[Discussion]: '
labels: ['discussion', 'help wanted']
labels: ['kind/question']
body:
- type: markdown
attributes:

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@@ -73,4 +73,4 @@ body:
id: additional
attributes:
label: Additional Information
description: Any other information that could help us better understand your question, including screenshots or relevant links
description: Any other information that could help us better understand your question, including screenshots or relevant links

View File

@@ -9,115 +9,115 @@ labels:
# skips and removes
- name: skip all
content:
regexes: '[Ss]kip (?:[Aa]ll |)[Ll]abels?'
regexes: "[Ss]kip (?:[Aa]ll |)[Ll]abels?"
- name: remove all
content:
regexes: '[Rr]emove (?:[Aa]ll |)[Ll]abels?'
regexes: "[Rr]emove (?:[Aa]ll |)[Ll]abels?"
- name: skip kind/bug
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)kind/bug(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)kind/bug(?:`|)"
- name: remove kind/bug
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)kind/bug(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)kind/bug(?:`|)"
- name: skip kind/enhancement
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)kind/enhancement(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)kind/enhancement(?:`|)"
- name: remove kind/enhancement
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)kind/enhancement(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)kind/enhancement(?:`|)"
- name: skip kind/question
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)kind/question(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)kind/question(?:`|)"
- name: remove kind/question
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)kind/question(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)kind/question(?:`|)"
- name: skip area/Connectivity
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)area/Connectivity(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)area/Connectivity(?:`|)"
- name: remove area/Connectivity
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)area/Connectivity(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)area/Connectivity(?:`|)"
- name: skip area/UI/UX
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)area/UI/UX(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)area/UI/UX(?:`|)"
- name: remove area/UI/UX
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)area/UI/UX(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)area/UI/UX(?:`|)"
- name: skip kind/documentation
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)kind/documentation(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)kind/documentation(?:`|)"
- name: remove kind/documentation
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)kind/documentation(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)kind/documentation(?:`|)"
- name: skip client:linux
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)client:linux(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)client:linux(?:`|)"
- name: remove client:linux
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)client:linux(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)client:linux(?:`|)"
- name: skip client:mac
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)client:mac(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)client:mac(?:`|)"
- name: remove client:mac
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)client:mac(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)client:mac(?:`|)"
- name: skip client:win
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)client:win(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)client:win(?:`|)"
- name: remove client:win
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)client:win(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)client:win(?:`|)"
- name: skip sig/Assistant
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)sig/Assistant(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)sig/Assistant(?:`|)"
- name: remove sig/Assistant
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)sig/Assistant(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)sig/Assistant(?:`|)"
- name: skip sig/Data
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)sig/Data(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)sig/Data(?:`|)"
- name: remove sig/Data
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)sig/Data(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)sig/Data(?:`|)"
- name: skip sig/MCP
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)sig/MCP(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)sig/MCP(?:`|)"
- name: remove sig/MCP
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)sig/MCP(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)sig/MCP(?:`|)"
- name: skip sig/RAG
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)sig/RAG(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)sig/RAG(?:`|)"
- name: remove sig/RAG
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)sig/RAG(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)sig/RAG(?:`|)"
- name: skip lgtm
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)lgtm(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)lgtm(?:`|)"
- name: remove lgtm
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)lgtm(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)lgtm(?:`|)"
- name: skip License
content:
regexes: '[Ss]kip (?:[Ll]abels? |)(?:`|)License(?:`|)'
regexes: "[Ss]kip (?:[Ll]abels? |)(?:`|)License(?:`|)"
- name: remove License
content:
regexes: '[Rr]emove (?:[Ll]abels? |)(?:`|)License(?:`|)'
regexes: "[Rr]emove (?:[Ll]abels? |)(?:`|)License(?:`|)"
# `Dev Team`
- name: Dev Team
@@ -129,7 +129,7 @@ labels:
# Area labels
- name: area/Connectivity
content: area/Connectivity
regexes: '代理|[Pp]roxy'
regexes: "代理|[Pp]roxy"
skip-if:
- skip all
- skip area/Connectivity
@@ -139,7 +139,7 @@ labels:
- name: area/UI/UX
content: area/UI/UX
regexes: '界面|[Uu][Ii]|重叠|按钮|图标|组件|渲染|菜单|栏目|头像|主题|样式|[Cc][Ss][Ss]'
regexes: "界面|[Uu][Ii]|重叠|按钮|图标|组件|渲染|菜单|栏目|头像|主题|样式|[Cc][Ss][Ss]"
skip-if:
- skip all
- skip area/UI/UX
@@ -150,7 +150,7 @@ labels:
# Kind labels
- name: kind/documentation
content: kind/documentation
regexes: '文档|教程|[Dd]oc(s|umentation)|[Rr]eadme'
regexes: "文档|教程|[Dd]oc(s|umentation)|[Rr]eadme"
skip-if:
- skip all
- skip kind/documentation
@@ -161,7 +161,7 @@ labels:
# Client labels
- name: client:linux
content: client:linux
regexes: '(?:[Ll]inux|[Uu]buntu|[Dd]ebian)'
regexes: "(?:[Ll]inux|[Uu]buntu|[Dd]ebian)"
skip-if:
- skip all
- skip client:linux
@@ -171,7 +171,7 @@ labels:
- name: client:mac
content: client:mac
regexes: '(?:[Mm]ac|[Mm]acOS|[Oo]SX)'
regexes: "(?:[Mm]ac|[Mm]acOS|[Oo]SX)"
skip-if:
- skip all
- skip client:mac
@@ -181,7 +181,7 @@ labels:
- name: client:win
content: client:win
regexes: '(?:[Ww]in|[Ww]indows)'
regexes: "(?:[Ww]in|[Ww]indows)"
skip-if:
- skip all
- skip client:win
@@ -192,7 +192,7 @@ labels:
# SIG labels
- name: sig/Assistant
content: sig/Assistant
regexes: '快捷助手|[Aa]ssistant'
regexes: "快捷助手|[Aa]ssistant"
skip-if:
- skip all
- skip sig/Assistant
@@ -202,7 +202,7 @@ labels:
- name: sig/Data
content: sig/Data
regexes: '[Ww]ebdav|坚果云|备份|同步|数据|Obsidian|Notion|Joplin|思源'
regexes: "[Ww]ebdav|坚果云|备份|同步|数据|Obsidian|Notion|Joplin|思源"
skip-if:
- skip all
- skip sig/Data
@@ -212,7 +212,7 @@ labels:
- name: sig/MCP
content: sig/MCP
regexes: '[Mm][Cc][Pp]'
regexes: "[Mm][Cc][Pp]"
skip-if:
- skip all
- skip sig/MCP
@@ -222,7 +222,7 @@ labels:
- name: sig/RAG
content: sig/RAG
regexes: '知识库|[Rr][Aa][Gg]'
regexes: "知识库|[Rr][Aa][Gg]"
skip-if:
- skip all
- skip sig/RAG
@@ -233,7 +233,7 @@ labels:
# Other labels
- name: lgtm
content: lgtm
regexes: '(?:[Ll][Gg][Tt][Mm]|[Ll]ooks [Gg]ood [Tt]o [Mm]e)'
regexes: "(?:[Ll][Gg][Tt][Mm]|[Ll]ooks [Gg]ood [Tt]o [Mm]e)"
skip-if:
- skip all
- skip lgtm
@@ -243,7 +243,7 @@ labels:
- name: License
content: License
regexes: '(?:[Ll]icense|[Cc]opyright|[Mm][Ii][Tt]|[Aa]pache)'
regexes: "(?:[Ll]icense|[Cc]opyright|[Mm][Ii][Tt]|[Aa]pache)"
skip-if:
- skip all
- skip License

View File

@@ -1,4 +1,4 @@
name: 'Issue Checker'
name: "Issue Checker"
on:
issues:
@@ -19,7 +19,7 @@ jobs:
steps:
- uses: MaaAssistantArknights/issue-checker@v1.14
with:
repo-token: '${{ secrets.GITHUB_TOKEN }}'
repo-token: "${{ secrets.GITHUB_TOKEN }}"
configuration-path: .github/issue-checker.yml
not-before: 2022-08-05T00:00:00Z
include-title: 1
include-title: 1

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@@ -1,8 +1,8 @@
name: 'Stale Issue Management'
name: "Stale Issue Management"
on:
schedule:
- cron: '0 0 * * *'
- cron: "0 0 * * *"
workflow_dispatch:
env:
@@ -24,18 +24,18 @@ jobs:
uses: actions/stale@v9
with:
repo-token: ${{ secrets.GITHUB_TOKEN }}
only-labels: 'needs-more-info'
only-labels: "needs-more-info"
days-before-stale: ${{ env.daysBeforeStale }}
days-before-close: 0 # Close immediately after stale
stale-issue-label: 'inactive'
close-issue-label: 'closed:no-response'
days-before-close: 0 # Close immediately after stale
stale-issue-label: "inactive"
close-issue-label: "closed:no-response"
stale-issue-message: |
This issue has been labeled as needing more information and has been inactive for ${{ env.daysBeforeStale }} days.
It will be closed now due to lack of additional information.
该问题被标记为"需要更多信息"且已经 ${{ env.daysBeforeStale }} 天没有任何活动,将立即关闭。
operations-per-run: 50
exempt-issue-labels: 'pending, Dev Team'
exempt-issue-labels: "pending, Dev Team"
days-before-pr-stale: -1
days-before-pr-close: -1
@@ -45,11 +45,11 @@ jobs:
repo-token: ${{ secrets.GITHUB_TOKEN }}
days-before-stale: ${{ env.daysBeforeStale }}
days-before-close: ${{ env.daysBeforeClose }}
stale-issue-label: 'inactive'
stale-issue-label: "inactive"
stale-issue-message: |
This issue has been inactive for a prolonged period and will be closed automatically in ${{ env.daysBeforeClose }} days.
该问题已长时间处于闲置状态,${{ env.daysBeforeClose }} 天后将自动关闭。
exempt-issue-labels: 'pending, Dev Team, kind/enhancement'
exempt-issue-labels: "pending, Dev Team, kind/enhancement"
days-before-pr-stale: -1 # Completely disable stalling for PRs
days-before-pr-close: -1 # Completely disable closing for PRs

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@@ -93,7 +93,6 @@ jobs:
- name: Build Linux
if: matrix.os == 'ubuntu-latest'
run: |
sudo apt-get install -y rpm
yarn build:npm linux
yarn build:linux
env:

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@@ -1,8 +1,5 @@
name: Pull Request CI
permissions:
contents: read
on:
workflow_dispatch:
pull_request:
@@ -13,8 +10,6 @@ on:
jobs:
build:
runs-on: ubuntu-latest
env:
PRCI: true
steps:
- name: Check out Git repository
@@ -45,14 +40,8 @@ jobs:
- name: Install Dependencies
run: yarn install
- name: Build Check
run: yarn build:check
- name: Lint Check
run: yarn test:lint
- name: Type Check
run: yarn typecheck
- name: i18n Check
run: yarn check:i18n
- name: Test
run: yarn test

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@@ -39,13 +39,6 @@ jobs:
echo "tag=${GITHUB_REF#refs/tags/}" >> $GITHUB_OUTPUT
fi
- name: Set package.json version
shell: bash
run: |
TAG="${{ steps.get-tag.outputs.tag }}"
VERSION="${TAG#v}"
npm version "$VERSION" --no-git-tag-version --allow-same-version
- name: Install Node.js
uses: actions/setup-node@v4
with:
@@ -79,16 +72,14 @@ jobs:
- name: Build Linux
if: matrix.os == 'ubuntu-latest'
run: |
sudo apt-get install -y rpm
yarn build:npm linux
yarn build:linux
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Mac
if: matrix.os == 'macos-latest'
@@ -102,11 +93,10 @@ jobs:
APPLE_ID: ${{ vars.APPLE_ID }}
APPLE_APP_SPECIFIC_PASSWORD: ${{ vars.APPLE_APP_SPECIFIC_PASSWORD }}
APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Windows
if: matrix.os == 'windows-latest'
@@ -115,10 +105,9 @@ jobs:
yarn build:win
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Release
uses: ncipollo/release-action@v1
@@ -127,5 +116,5 @@ jobs:
allowUpdates: true
makeLatest: false
tag: ${{ steps.get-tag.outputs.tag }}
artifacts: 'dist/*.exe,dist/*.zip,dist/*.dmg,dist/*.AppImage,dist/*.snap,dist/*.deb,dist/*.rpm,dist/*.tar.gz,dist/latest*.yml,dist/rc*.yml,dist/beta*.yml,dist/*.blockmap'
token: ${{ secrets.GITHUB_TOKEN }}
artifacts: 'dist/*.exe,dist/*.zip,dist/*.dmg,dist/*.AppImage,dist/*.snap,dist/*.deb,dist/*.rpm,dist/*.tar.gz,dist/latest*.yml,dist/rc*.yml,dist/*.blockmap'
token: ${{ secrets.GITHUB_TOKEN }}

8
.gitignore vendored
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@@ -35,25 +35,17 @@ Thumbs.db
node_modules
dist
out
mcp_server
stats.html
# ENV
.env
.env.*
!.env.example
# Local
local
.aider*
.cursorrules
.cursor/*
.claude/*
.gemini/*
.qwen/*
.trae/*
.claude-code-router/*
CLAUDE.local.md
# vitest
coverage

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@@ -1,11 +1,8 @@
{
"bracketSameLine": true,
"endOfLine": "lf",
"jsonRecursiveSort": true,
"jsonSortOrder": "{\"*\": \"lexical\"}",
"plugins": ["prettier-plugin-sort-json"],
"printWidth": 120,
"semi": false,
"singleQuote": true,
"trailingComma": "none"
"semi": false,
"printWidth": 120,
"trailingComma": "none",
"endOfLine": "lf",
"bracketSameLine": true
}

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@@ -1,8 +1,3 @@
{
"recommendations": [
"dbaeumer.vscode-eslint",
"esbenp.prettier-vscode",
"editorconfig.editorconfig",
"lokalise.i18n-ally"
]
"recommendations": ["dbaeumer.vscode-eslint"]
}

45
.vscode/launch.json vendored
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@@ -1,40 +1,39 @@
{
"compounds": [
{
"configurations": ["Debug Main Process", "Debug Renderer Process"],
"name": "Debug All",
"presentation": {
"order": 1
}
}
],
"version": "0.2.0",
"configurations": [
{
"cwd": "${workspaceRoot}",
"env": {
"REMOTE_DEBUGGING_PORT": "9222"
},
"envFile": "${workspaceFolder}/.env",
"name": "Debug Main Process",
"request": "launch",
"runtimeArgs": ["--inspect", "--sourcemap"],
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite",
"type": "node",
"request": "launch",
"cwd": "${workspaceRoot}",
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite",
"windows": {
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite.cmd"
},
"runtimeArgs": ["--sourcemap"],
"env": {
"REMOTE_DEBUGGING_PORT": "9222"
}
},
{
"name": "Debug Renderer Process",
"port": 9222,
"request": "attach",
"type": "chrome",
"webRoot": "${workspaceFolder}/src/renderer",
"timeout": 60000,
"presentation": {
"hidden": true
},
"request": "attach",
"timeout": 3000000,
"type": "chrome",
"webRoot": "${workspaceFolder}/src/renderer"
}
}
],
"version": "0.2.0"
"compounds": [
{
"name": "Debug All",
"configurations": ["Debug Main Process", "Debug Renderer Process"],
"presentation": {
"order": 1
}
}
]
}

60
.vscode/settings.json vendored
View File

@@ -1,46 +1,44 @@
{
"[css]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.fixAll.eslint": "explicit",
"source.organizeImports": "never"
},
"search.exclude": {
"**/dist/**": true,
".yarn/releases/**": true
},
"[javascript]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[json]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[jsonc]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[markdown]": {
"files.trimTrailingWhitespace": false
},
"[scss]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[typescript]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[typescriptreact]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"editor.codeActionsOnSave": {
"source.fixAll.eslint": "explicit",
"source.organizeImports": "never"
"[json]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[jsonc]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[css]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[scss]": {
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[markdown]": {
"files.trimTrailingWhitespace": false
},
"editor.formatOnSave": true,
"files.eol": "\n",
"i18n-ally.displayLanguage": "zh-cn",
"i18n-ally.enabledFrameworks": ["react-i18next", "i18next"],
"i18n-ally.enabledParsers": ["ts", "js", "json"], // 解析语言
"i18n-ally.fullReloadOnChanged": true, // 界面显示语言
"i18n-ally.keystyle": "nested", // 翻译路径格式
"i18n-ally.localesPaths": ["src/renderer/src/i18n/locales"],
// "i18n-ally.namespace": true, // 开启命名空间
"i18n-ally.enabledFrameworks": ["react-i18next", "i18next"],
"i18n-ally.keystyle": "nested", // 翻译路径格式
"i18n-ally.sortKeys": true, // 排序
"i18n-ally.sourceLanguage": "zh-cn", // 翻译源语言
"i18n-ally.usage.derivedKeyRules": ["{key}_one", "{key}_other"], // 标记单复数形式的键为已翻译
"search.exclude": {
"**/dist/**": true,
".yarn/releases/**": true
}
"i18n-ally.namespace": true, // 开启命名空间
"i18n-ally.enabledParsers": ["ts", "js", "json"], // 解析语言
"i18n-ally.sourceLanguage": "en-us", // 翻译源语言
"i18n-ally.displayLanguage": "zh-cn",
"i18n-ally.fullReloadOnChanged": true // 界面显示语言
}

View File

@@ -1,196 +0,0 @@
diff --git a/client.js b/client.js
index c2b9cd6e46f9f66f901af259661bc2d2f8b38936..9b6b3af1a6573e1ccaf3a1c5f41b48df198cbbe0 100644
--- a/client.js
+++ b/client.js
@@ -26,7 +26,7 @@ Object.defineProperty(exports, "__esModule", { value: true });
exports.AnthropicVertex = exports.BaseAnthropic = void 0;
const client_1 = require("@anthropic-ai/sdk/client");
const Resources = __importStar(require("@anthropic-ai/sdk/resources/index"));
-const google_auth_library_1 = require("google-auth-library");
+// const google_auth_library_1 = require("google-auth-library");
const env_1 = require("./internal/utils/env.js");
const values_1 = require("./internal/utils/values.js");
const headers_1 = require("./internal/headers.js");
@@ -56,7 +56,7 @@ class AnthropicVertex extends client_1.BaseAnthropic {
throw new Error('No region was given. The client should be instantiated with the `region` option or the `CLOUD_ML_REGION` environment variable should be set.');
}
super({
- baseURL: baseURL || `https://${region}-aiplatform.googleapis.com/v1`,
+ baseURL: baseURL || (region === 'global' ? 'https://aiplatform.googleapis.com/v1' : `https://${region}-aiplatform.googleapis.com/v1`),
...opts,
});
this.messages = makeMessagesResource(this);
@@ -64,22 +64,22 @@ class AnthropicVertex extends client_1.BaseAnthropic {
this.region = region;
this.projectId = projectId;
this.accessToken = opts.accessToken ?? null;
- this._auth =
- opts.googleAuth ?? new google_auth_library_1.GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
- this._authClientPromise = this._auth.getClient();
+ // this._auth =
+ // opts.googleAuth ?? new google_auth_library_1.GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
+ // this._authClientPromise = this._auth.getClient();
}
validateHeaders() {
// auth validation is handled in prepareOptions since it needs to be async
}
- async prepareOptions(options) {
- const authClient = await this._authClientPromise;
- const authHeaders = await authClient.getRequestHeaders();
- const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
- if (!this.projectId && projectId) {
- this.projectId = projectId;
- }
- options.headers = (0, headers_1.buildHeaders)([authHeaders, options.headers]);
- }
+ // async prepareOptions(options) {
+ // const authClient = await this._authClientPromise;
+ // const authHeaders = await authClient.getRequestHeaders();
+ // const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
+ // if (!this.projectId && projectId) {
+ // this.projectId = projectId;
+ // }
+ // options.headers = (0, headers_1.buildHeaders)([authHeaders, options.headers]);
+ // }
buildRequest(options) {
if ((0, values_1.isObj)(options.body)) {
// create a shallow copy of the request body so that code that mutates it later
diff --git a/client.mjs b/client.mjs
index 70274cbf38f69f87cbcca9567e77e4a7b938cf90..4dea954b6f4afad565663426b7adfad5de973a7d 100644
--- a/client.mjs
+++ b/client.mjs
@@ -1,6 +1,6 @@
import { BaseAnthropic } from '@anthropic-ai/sdk/client';
import * as Resources from '@anthropic-ai/sdk/resources/index';
-import { GoogleAuth } from 'google-auth-library';
+// import { GoogleAuth } from 'google-auth-library';
import { readEnv } from "./internal/utils/env.mjs";
import { isObj } from "./internal/utils/values.mjs";
import { buildHeaders } from "./internal/headers.mjs";
@@ -29,7 +29,7 @@ export class AnthropicVertex extends BaseAnthropic {
throw new Error('No region was given. The client should be instantiated with the `region` option or the `CLOUD_ML_REGION` environment variable should be set.');
}
super({
- baseURL: baseURL || `https://${region}-aiplatform.googleapis.com/v1`,
+ baseURL: baseURL || (region === 'global' ? 'https://aiplatform.googleapis.com/v1' : `https://${region}-aiplatform.googleapis.com/v1`),
...opts,
});
this.messages = makeMessagesResource(this);
@@ -37,22 +37,22 @@ export class AnthropicVertex extends BaseAnthropic {
this.region = region;
this.projectId = projectId;
this.accessToken = opts.accessToken ?? null;
- this._auth =
- opts.googleAuth ?? new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
- this._authClientPromise = this._auth.getClient();
+ // this._auth =
+ // opts.googleAuth ?? new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
+ //this._authClientPromise = this._auth.getClient();
}
validateHeaders() {
// auth validation is handled in prepareOptions since it needs to be async
}
- async prepareOptions(options) {
- const authClient = await this._authClientPromise;
- const authHeaders = await authClient.getRequestHeaders();
- const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
- if (!this.projectId && projectId) {
- this.projectId = projectId;
- }
- options.headers = buildHeaders([authHeaders, options.headers]);
- }
+ // async prepareOptions(options) {
+ // const authClient = await this._authClientPromise;
+ // const authHeaders = await authClient.getRequestHeaders();
+ // const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
+ // if (!this.projectId && projectId) {
+ // this.projectId = projectId;
+ // }
+ // options.headers = buildHeaders([authHeaders, options.headers]);
+ // }
buildRequest(options) {
if (isObj(options.body)) {
// create a shallow copy of the request body so that code that mutates it later
diff --git a/src/client.ts b/src/client.ts
index a6f9c6be65e4189f4f9601fb560df3f68e7563eb..37b1ad2802e3ca0dae4ca35f9dcb5b22dcf09796 100644
--- a/src/client.ts
+++ b/src/client.ts
@@ -12,22 +12,22 @@ export { BaseAnthropic } from '@anthropic-ai/sdk/client';
const DEFAULT_VERSION = 'vertex-2023-10-16';
const MODEL_ENDPOINTS = new Set<string>(['/v1/messages', '/v1/messages?beta=true']);
-export type ClientOptions = Omit<CoreClientOptions, 'apiKey' | 'authToken'> & {
- region?: string | null | undefined;
- projectId?: string | null | undefined;
- accessToken?: string | null | undefined;
-
- /**
- * Override the default google auth config using the
- * [google-auth-library](https://www.npmjs.com/package/google-auth-library) package.
- *
- * Note that you'll likely have to set `scopes`, e.g.
- * ```ts
- * new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' })
- * ```
- */
- googleAuth?: GoogleAuth | null | undefined;
-};
+// export type ClientOptions = Omit<CoreClientOptions, 'apiKey' | 'authToken'> & {
+// region?: string | null | undefined;
+// projectId?: string | null | undefined;
+// accessToken?: string | null | undefined;
+
+// /**
+// * Override the default google auth config using the
+// * [google-auth-library](https://www.npmjs.com/package/google-auth-library) package.
+// *
+// * Note that you'll likely have to set `scopes`, e.g.
+// * ```ts
+// * new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' })
+// * ```
+// */
+// googleAuth?: GoogleAuth | null | undefined;
+// };
export class AnthropicVertex extends BaseAnthropic {
region: string;
@@ -74,9 +74,9 @@ export class AnthropicVertex extends BaseAnthropic {
this.projectId = projectId;
this.accessToken = opts.accessToken ?? null;
- this._auth =
- opts.googleAuth ?? new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
- this._authClientPromise = this._auth.getClient();
+ // this._auth =
+ // opts.googleAuth ?? new GoogleAuth({ scopes: 'https://www.googleapis.com/auth/cloud-platform' });
+ // this._authClientPromise = this._auth.getClient();
}
messages: MessagesResource = makeMessagesResource(this);
@@ -86,17 +86,17 @@ export class AnthropicVertex extends BaseAnthropic {
// auth validation is handled in prepareOptions since it needs to be async
}
- protected override async prepareOptions(options: FinalRequestOptions): Promise<void> {
- const authClient = await this._authClientPromise;
+ // protected override async prepareOptions(options: FinalRequestOptions): Promise<void> {
+ // const authClient = await this._authClientPromise;
- const authHeaders = await authClient.getRequestHeaders();
- const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
- if (!this.projectId && projectId) {
- this.projectId = projectId;
- }
+ // const authHeaders = await authClient.getRequestHeaders();
+ // const projectId = authClient.projectId ?? authHeaders['x-goog-user-project'];
+ // if (!this.projectId && projectId) {
+ // this.projectId = projectId;
+ // }
- options.headers = buildHeaders([authHeaders, options.headers]);
- }
+ // options.headers = buildHeaders([authHeaders, options.headers]);
+ // }
override buildRequest(options: FinalRequestOptions): {
req: FinalizedRequestInit;

File diff suppressed because it is too large Load Diff

View File

@@ -1,5 +1,5 @@
diff --git a/es/dropdown/dropdown.js b/es/dropdown/dropdown.js
index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8fb1168bdf 100644
index 986877a762b9ad0aca596a8552732cd12d2eaabb..1f18aa2ea745e68950e4cee16d4d655f5c835fd5 100644
--- a/es/dropdown/dropdown.js
+++ b/es/dropdown/dropdown.js
@@ -2,7 +2,7 @@
@@ -11,7 +11,7 @@ index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8f
import classNames from 'classnames';
import RcDropdown from 'rc-dropdown';
import useEvent from "rc-util/es/hooks/useEvent";
@@ -160,8 +160,10 @@ const Dropdown = props => {
@@ -158,8 +158,10 @@ const Dropdown = props => {
className: `${prefixCls}-menu-submenu-arrow`
}, direction === 'rtl' ? (/*#__PURE__*/React.createElement(LeftOutlined, {
className: `${prefixCls}-menu-submenu-arrow-icon`
@@ -24,8 +24,22 @@ index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8f
}))),
mode: "vertical",
selectable: false,
diff --git a/es/dropdown/style/index.js b/es/dropdown/style/index.js
index 768c01783002c6901c85a73061ff6b3e776a60ce..39b1b95a56cdc9fb586a193c3adad5141f5cf213 100644
--- a/es/dropdown/style/index.js
+++ b/es/dropdown/style/index.js
@@ -240,7 +240,8 @@ const genBaseStyle = token => {
marginInlineEnd: '0 !important',
color: token.colorTextDescription,
fontSize: fontSizeIcon,
- fontStyle: 'normal'
+ fontStyle: 'normal',
+ marginTop: 3,
}
}
}),
diff --git a/es/select/useIcons.js b/es/select/useIcons.js
index 572aaaa0899f429cbf8a7181f2eeada545f76dcb..4e175c8d7713dd6422f8bcdc74ee671a835de6ce 100644
index 959115be936ef8901548af2658c5dcfdc5852723..c812edd52123eb0faf4638b1154fcfa1b05b513b 100644
--- a/es/select/useIcons.js
+++ b/es/select/useIcons.js
@@ -4,10 +4,10 @@ import * as React from 'react';
@@ -37,10 +51,10 @@ index 572aaaa0899f429cbf8a7181f2eeada545f76dcb..4e175c8d7713dd6422f8bcdc74ee671a
import SearchOutlined from "@ant-design/icons/es/icons/SearchOutlined";
import { devUseWarning } from '../_util/warning';
+import { ChevronDown } from 'lucide-react';
export default function useIcons({
suffixIcon,
clearIcon,
@@ -54,8 +54,10 @@ export default function useIcons({
export default function useIcons(_ref) {
let {
suffixIcon,
@@ -56,8 +56,10 @@ export default function useIcons(_ref) {
className: iconCls
}));
}

View File

@@ -1,12 +0,0 @@
diff --git a/dist/utils/temp.js b/dist/utils/temp.js
index c0844f640f7927ff87edda13f7c853d10ebb8dd0..3ca3d29e0f4ee700c43ebde47002883955b664b3 100644
--- a/dist/utils/temp.js
+++ b/dist/utils/temp.js
@@ -2,6 +2,7 @@
/* IMPORT */
Object.defineProperty(exports, "__esModule", { value: true });
const path = require("path");
+const process = require("process");
const consts_1 = require("../consts");
const fs_1 = require("./fs");
/* TEMP */

View File

@@ -1,13 +0,0 @@
diff --git a/FileStreamRotator.js b/FileStreamRotator.js
index 639bb9c8f972ba672bd27d9f8b1739d1030cb44b..a12a6d93b61fe782e981027248fa10876151f65f 100644
--- a/FileStreamRotator.js
+++ b/FileStreamRotator.js
@@ -12,7 +12,7 @@
*/
var fs = require('fs');
var path = require('path');
-var moment = require('moment');
+var moment = require('moment').default || require('moment');
var crypto = require('crypto');
var EventEmitter = require('events');

View File

@@ -0,0 +1,279 @@
diff --git a/client.js b/client.js
index 33b4ff6309d5f29187dab4e285d07dac20340bab..8f568637ee9e4677585931fb0284c8165a933f69 100644
--- a/client.js
+++ b/client.js
@@ -433,7 +433,7 @@ class OpenAI {
'User-Agent': this.getUserAgent(),
'X-Stainless-Retry-Count': String(retryCount),
...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
- ...(0, detect_platform_1.getPlatformHeaders)(),
+ // ...(0, detect_platform_1.getPlatformHeaders)(),
'OpenAI-Organization': this.organization,
'OpenAI-Project': this.project,
},
diff --git a/client.mjs b/client.mjs
index c34c18213073540ebb296ea540b1d1ad39527906..1ce1a98256d7e90e26ca963582f235b23e996e73 100644
--- a/client.mjs
+++ b/client.mjs
@@ -430,7 +430,7 @@ export class OpenAI {
'User-Agent': this.getUserAgent(),
'X-Stainless-Retry-Count': String(retryCount),
...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
- ...getPlatformHeaders(),
+ // ...getPlatformHeaders(),
'OpenAI-Organization': this.organization,
'OpenAI-Project': this.project,
},
diff --git a/core/error.js b/core/error.js
index a12d9d9ccd242050161adeb0f82e1b98d9e78e20..fe3a5462480558bc426deea147f864f12b36f9bd 100644
--- a/core/error.js
+++ b/core/error.js
@@ -40,7 +40,7 @@ class APIError extends OpenAIError {
if (!status || !headers) {
return new APIConnectionError({ message, cause: (0, errors_1.castToError)(errorResponse) });
}
- const error = errorResponse?.['error'];
+ const error = errorResponse?.['error'] || errorResponse;
if (status === 400) {
return new BadRequestError(status, error, message, headers);
}
diff --git a/core/error.mjs b/core/error.mjs
index 83cefbaffeb8c657536347322d8de9516af479a2..63334b7972ec04882aa4a0800c1ead5982345045 100644
--- a/core/error.mjs
+++ b/core/error.mjs
@@ -36,7 +36,7 @@ export class APIError extends OpenAIError {
if (!status || !headers) {
return new APIConnectionError({ message, cause: castToError(errorResponse) });
}
- const error = errorResponse?.['error'];
+ const error = errorResponse?.['error'] || errorResponse;
if (status === 400) {
return new BadRequestError(status, error, message, headers);
}
diff --git a/resources/embeddings.js b/resources/embeddings.js
index 2404264d4ba0204322548945ebb7eab3bea82173..8f1bc45cc45e0797d50989d96b51147b90ae6790 100644
--- a/resources/embeddings.js
+++ b/resources/embeddings.js
@@ -5,52 +5,64 @@ exports.Embeddings = void 0;
const resource_1 = require("../core/resource.js");
const utils_1 = require("../internal/utils.js");
class Embeddings extends resource_1.APIResource {
- /**
- * Creates an embedding vector representing the input text.
- *
- * @example
- * ```ts
- * const createEmbeddingResponse =
- * await client.embeddings.create({
- * input: 'The quick brown fox jumped over the lazy dog',
- * model: 'text-embedding-3-small',
- * });
- * ```
- */
- create(body, options) {
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
- // No encoding_format specified, defaulting to base64 for performance reasons
- // See https://github.com/openai/openai-node/pull/1312
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
- if (hasUserProvidedEncodingFormat) {
- (0, utils_1.loggerFor)(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
- }
- const response = this._client.post('/embeddings', {
- body: {
- ...body,
- encoding_format: encoding_format,
- },
- ...options,
- });
- // if the user specified an encoding_format, return the response as-is
- if (hasUserProvidedEncodingFormat) {
- return response;
- }
- // in this stage, we are sure the user did not specify an encoding_format
- // and we defaulted to base64 for performance reasons
- // we are sure then that the response is base64 encoded, let's decode it
- // the returned result will be a float32 array since this is OpenAI API's default encoding
- (0, utils_1.loggerFor)(this._client).debug('embeddings/decoding base64 embeddings from base64');
- return response._thenUnwrap((response) => {
- if (response && response.data) {
- response.data.forEach((embeddingBase64Obj) => {
- const embeddingBase64Str = embeddingBase64Obj.embedding;
- embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(embeddingBase64Str);
- });
- }
- return response;
- });
- }
+ /**
+ * Creates an embedding vector representing the input text.
+ *
+ * @example
+ * ```ts
+ * const createEmbeddingResponse =
+ * await client.embeddings.create({
+ * input: 'The quick brown fox jumped over the lazy dog',
+ * model: 'text-embedding-3-small',
+ * });
+ * ```
+ */
+ create(body, options) {
+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
+ // No encoding_format specified, defaulting to base64 for performance reasons
+ // See https://github.com/openai/openai-node/pull/1312
+ let encoding_format = hasUserProvidedEncodingFormat
+ ? body.encoding_format
+ : "base64";
+ if (body.model.includes("jina")) {
+ encoding_format = undefined;
+ }
+ if (hasUserProvidedEncodingFormat) {
+ (0, utils_1.loggerFor)(this._client).debug(
+ "embeddings/user defined encoding_format:",
+ body.encoding_format
+ );
+ }
+ const response = this._client.post("/embeddings", {
+ body: {
+ ...body,
+ encoding_format: encoding_format,
+ },
+ ...options,
+ });
+ // if the user specified an encoding_format, return the response as-is
+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
+ return response;
+ }
+ // in this stage, we are sure the user did not specify an encoding_format
+ // and we defaulted to base64 for performance reasons
+ // we are sure then that the response is base64 encoded, let's decode it
+ // the returned result will be a float32 array since this is OpenAI API's default encoding
+ (0, utils_1.loggerFor)(this._client).debug(
+ "embeddings/decoding base64 embeddings from base64"
+ );
+ return response._thenUnwrap((response) => {
+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
+ response.data.forEach((embeddingBase64Obj) => {
+ const embeddingBase64Str = embeddingBase64Obj.embedding;
+ embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(
+ embeddingBase64Str
+ );
+ });
+ }
+ return response;
+ });
+ }
}
exports.Embeddings = Embeddings;
//# sourceMappingURL=embeddings.js.map
diff --git a/resources/embeddings.mjs b/resources/embeddings.mjs
index 19dcaef578c194a89759c4360073cfd4f7dd2cbf..0284e9cc615c900eff508eb595f7360a74bd9200 100644
--- a/resources/embeddings.mjs
+++ b/resources/embeddings.mjs
@@ -2,51 +2,61 @@
import { APIResource } from "../core/resource.mjs";
import { loggerFor, toFloat32Array } from "../internal/utils.mjs";
export class Embeddings extends APIResource {
- /**
- * Creates an embedding vector representing the input text.
- *
- * @example
- * ```ts
- * const createEmbeddingResponse =
- * await client.embeddings.create({
- * input: 'The quick brown fox jumped over the lazy dog',
- * model: 'text-embedding-3-small',
- * });
- * ```
- */
- create(body, options) {
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
- // No encoding_format specified, defaulting to base64 for performance reasons
- // See https://github.com/openai/openai-node/pull/1312
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
- if (hasUserProvidedEncodingFormat) {
- loggerFor(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
- }
- const response = this._client.post('/embeddings', {
- body: {
- ...body,
- encoding_format: encoding_format,
- },
- ...options,
- });
- // if the user specified an encoding_format, return the response as-is
- if (hasUserProvidedEncodingFormat) {
- return response;
- }
- // in this stage, we are sure the user did not specify an encoding_format
- // and we defaulted to base64 for performance reasons
- // we are sure then that the response is base64 encoded, let's decode it
- // the returned result will be a float32 array since this is OpenAI API's default encoding
- loggerFor(this._client).debug('embeddings/decoding base64 embeddings from base64');
- return response._thenUnwrap((response) => {
- if (response && response.data) {
- response.data.forEach((embeddingBase64Obj) => {
- const embeddingBase64Str = embeddingBase64Obj.embedding;
- embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
- });
- }
- return response;
- });
- }
+ /**
+ * Creates an embedding vector representing the input text.
+ *
+ * @example
+ * ```ts
+ * const createEmbeddingResponse =
+ * await client.embeddings.create({
+ * input: 'The quick brown fox jumped over the lazy dog',
+ * model: 'text-embedding-3-small',
+ * });
+ * ```
+ */
+ create(body, options) {
+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
+ // No encoding_format specified, defaulting to base64 for performance reasons
+ // See https://github.com/openai/openai-node/pull/1312
+ let encoding_format = hasUserProvidedEncodingFormat
+ ? body.encoding_format
+ : "base64";
+ if (body.model.includes("jina")) {
+ encoding_format = undefined;
+ }
+ if (hasUserProvidedEncodingFormat) {
+ loggerFor(this._client).debug(
+ "embeddings/user defined encoding_format:",
+ body.encoding_format
+ );
+ }
+ const response = this._client.post("/embeddings", {
+ body: {
+ ...body,
+ encoding_format: encoding_format,
+ },
+ ...options,
+ });
+ // if the user specified an encoding_format, return the response as-is
+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
+ return response;
+ }
+ // in this stage, we are sure the user did not specify an encoding_format
+ // and we defaulted to base64 for performance reasons
+ // we are sure then that the response is base64 encoded, let's decode it
+ // the returned result will be a float32 array since this is OpenAI API's default encoding
+ loggerFor(this._client).debug(
+ "embeddings/decoding base64 embeddings from base64"
+ );
+ return response._thenUnwrap((response) => {
+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
+ response.data.forEach((embeddingBase64Obj) => {
+ const embeddingBase64Str = embeddingBase64Obj.embedding;
+ embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
+ });
+ }
+ return response;
+ });
+ }
}
//# sourceMappingURL=embeddings.mjs.map

Binary file not shown.

View File

@@ -1,348 +0,0 @@
diff --git a/src/constants/languages.d.ts b/src/constants/languages.d.ts
new file mode 100644
index 0000000000000000000000000000000000000000..6a2ba5086187622b8ca8887bcc7406018fba8a89
--- /dev/null
+++ b/src/constants/languages.d.ts
@@ -0,0 +1,43 @@
+/**
+ * Languages with existing tesseract traineddata
+ * https://tesseract-ocr.github.io/tessdoc/Data-Files#data-files-for-version-400-november-29-2016
+ */
+
+// Define the language codes as string literals
+type LanguageCode =
+ | 'afr' | 'amh' | 'ara' | 'asm' | 'aze' | 'aze_cyrl' | 'bel' | 'ben' | 'bod' | 'bos'
+ | 'bul' | 'cat' | 'ceb' | 'ces' | 'chi_sim' | 'chi_tra' | 'chr' | 'cym' | 'dan' | 'deu'
+ | 'dzo' | 'ell' | 'eng' | 'enm' | 'epo' | 'est' | 'eus' | 'fas' | 'fin' | 'fra'
+ | 'frk' | 'frm' | 'gle' | 'glg' | 'grc' | 'guj' | 'hat' | 'heb' | 'hin' | 'hrv'
+ | 'hun' | 'iku' | 'ind' | 'isl' | 'ita' | 'ita_old' | 'jav' | 'jpn' | 'kan' | 'kat'
+ | 'kat_old' | 'kaz' | 'khm' | 'kir' | 'kor' | 'kur' | 'lao' | 'lat' | 'lav' | 'lit'
+ | 'mal' | 'mar' | 'mkd' | 'mlt' | 'msa' | 'mya' | 'nep' | 'nld' | 'nor' | 'ori'
+ | 'pan' | 'pol' | 'por' | 'pus' | 'ron' | 'rus' | 'san' | 'sin' | 'slk' | 'slv'
+ | 'spa' | 'spa_old' | 'sqi' | 'srp' | 'srp_latn' | 'swa' | 'swe' | 'syr' | 'tam' | 'tel'
+ | 'tgk' | 'tgl' | 'tha' | 'tir' | 'tur' | 'uig' | 'ukr' | 'urd' | 'uzb' | 'uzb_cyrl'
+ | 'vie' | 'yid';
+
+// Define the language keys as string literals
+type LanguageKey =
+ | 'AFR' | 'AMH' | 'ARA' | 'ASM' | 'AZE' | 'AZE_CYRL' | 'BEL' | 'BEN' | 'BOD' | 'BOS'
+ | 'BUL' | 'CAT' | 'CEB' | 'CES' | 'CHI_SIM' | 'CHI_TRA' | 'CHR' | 'CYM' | 'DAN' | 'DEU'
+ | 'DZO' | 'ELL' | 'ENG' | 'ENM' | 'EPO' | 'EST' | 'EUS' | 'FAS' | 'FIN' | 'FRA'
+ | 'FRK' | 'FRM' | 'GLE' | 'GLG' | 'GRC' | 'GUJ' | 'HAT' | 'HEB' | 'HIN' | 'HRV'
+ | 'HUN' | 'IKU' | 'IND' | 'ISL' | 'ITA' | 'ITA_OLD' | 'JAV' | 'JPN' | 'KAN' | 'KAT'
+ | 'KAT_OLD' | 'KAZ' | 'KHM' | 'KIR' | 'KOR' | 'KUR' | 'LAO' | 'LAT' | 'LAV' | 'LIT'
+ | 'MAL' | 'MAR' | 'MKD' | 'MLT' | 'MSA' | 'MYA' | 'NEP' | 'NLD' | 'NOR' | 'ORI'
+ | 'PAN' | 'POL' | 'POR' | 'PUS' | 'RON' | 'RUS' | 'SAN' | 'SIN' | 'SLK' | 'SLV'
+ | 'SPA' | 'SPA_OLD' | 'SQI' | 'SRP' | 'SRP_LATN' | 'SWA' | 'SWE' | 'SYR' | 'TAM' | 'TEL'
+ | 'TGK' | 'TGL' | 'THA' | 'TIR' | 'TUR' | 'UIG' | 'UKR' | 'URD' | 'UZB' | 'UZB_CYRL'
+ | 'VIE' | 'YID';
+
+// Create a mapped type to ensure each key maps to its specific value
+type LanguagesMap = {
+ [K in LanguageKey]: LanguageCode;
+};
+
+// Declare the exported constant with the specific type
+export const LANGUAGES: LanguagesMap;
+
+// Export the individual types for use in other modules
+export type { LanguageCode, LanguageKey, LanguagesMap };
\ No newline at end of file
diff --git a/src/index.d.ts b/src/index.d.ts
index 1f5a9c8094fe4de7983467f9efb43bdb4de535f2..16dc95cf68663673e37e189b719cb74897b7735f 100644
--- a/src/index.d.ts
+++ b/src/index.d.ts
@@ -1,31 +1,74 @@
+// Import the languages types
+import { LanguagesMap } from "./constants/languages";
+
+/// <reference types="node" />
+
declare namespace Tesseract {
- function createScheduler(): Scheduler
- function createWorker(langs?: string | string[] | Lang[], oem?: OEM, options?: Partial<WorkerOptions>, config?: string | Partial<InitOptions>): Promise<Worker>
- function setLogging(logging: boolean): void
- function recognize(image: ImageLike, langs?: string, options?: Partial<WorkerOptions>): Promise<RecognizeResult>
- function detect(image: ImageLike, options?: Partial<WorkerOptions>): any
+ function createScheduler(): Scheduler;
+ function createWorker(
+ langs?: LanguageCode | LanguageCode[] | Lang[],
+ oem?: OEM,
+ options?: Partial<WorkerOptions>,
+ config?: string | Partial<InitOptions>
+ ): Promise<Worker>;
+ function setLogging(logging: boolean): void;
+ function recognize(
+ image: ImageLike,
+ langs?: LanguageCode,
+ options?: Partial<WorkerOptions>
+ ): Promise<RecognizeResult>;
+ function detect(image: ImageLike, options?: Partial<WorkerOptions>): any;
+
+ // Export languages constant
+ const languages: LanguagesMap;
+
+ type LanguageCode = import("./constants/languages").LanguageCode;
+ type LanguageKey = import("./constants/languages").LanguageKey;
interface Scheduler {
- addWorker(worker: Worker): string
- addJob(action: 'recognize', ...args: Parameters<Worker['recognize']>): Promise<RecognizeResult>
- addJob(action: 'detect', ...args: Parameters<Worker['detect']>): Promise<DetectResult>
- terminate(): Promise<any>
- getQueueLen(): number
- getNumWorkers(): number
+ addWorker(worker: Worker): string;
+ addJob(
+ action: "recognize",
+ ...args: Parameters<Worker["recognize"]>
+ ): Promise<RecognizeResult>;
+ addJob(
+ action: "detect",
+ ...args: Parameters<Worker["detect"]>
+ ): Promise<DetectResult>;
+ terminate(): Promise<any>;
+ getQueueLen(): number;
+ getNumWorkers(): number;
}
interface Worker {
- load(jobId?: string): Promise<ConfigResult>
- writeText(path: string, text: string, jobId?: string): Promise<ConfigResult>
- readText(path: string, jobId?: string): Promise<ConfigResult>
- removeText(path: string, jobId?: string): Promise<ConfigResult>
- FS(method: string, args: any[], jobId?: string): Promise<ConfigResult>
- reinitialize(langs?: string | Lang[], oem?: OEM, config?: string | Partial<InitOptions>, jobId?: string): Promise<ConfigResult>
- setParameters(params: Partial<WorkerParams>, jobId?: string): Promise<ConfigResult>
- getImage(type: imageType): string
- recognize(image: ImageLike, options?: Partial<RecognizeOptions>, output?: Partial<OutputFormats>, jobId?: string): Promise<RecognizeResult>
- detect(image: ImageLike, jobId?: string): Promise<DetectResult>
- terminate(jobId?: string): Promise<ConfigResult>
+ load(jobId?: string): Promise<ConfigResult>;
+ writeText(
+ path: string,
+ text: string,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ readText(path: string, jobId?: string): Promise<ConfigResult>;
+ removeText(path: string, jobId?: string): Promise<ConfigResult>;
+ FS(method: string, args: any[], jobId?: string): Promise<ConfigResult>;
+ reinitialize(
+ langs?: string | Lang[],
+ oem?: OEM,
+ config?: string | Partial<InitOptions>,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ setParameters(
+ params: Partial<WorkerParams>,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ getImage(type: imageType): string;
+ recognize(
+ image: ImageLike,
+ options?: Partial<RecognizeOptions>,
+ output?: Partial<OutputFormats>,
+ jobId?: string
+ ): Promise<RecognizeResult>;
+ detect(image: ImageLike, jobId?: string): Promise<DetectResult>;
+ terminate(jobId?: string): Promise<ConfigResult>;
}
interface Lang {
@@ -34,43 +77,43 @@ declare namespace Tesseract {
}
interface InitOptions {
- load_system_dawg: string
- load_freq_dawg: string
- load_unambig_dawg: string
- load_punc_dawg: string
- load_number_dawg: string
- load_bigram_dawg: string
- }
-
- type LoggerMessage = {
- jobId: string
- progress: number
- status: string
- userJobId: string
- workerId: string
+ load_system_dawg: string;
+ load_freq_dawg: string;
+ load_unambig_dawg: string;
+ load_punc_dawg: string;
+ load_number_dawg: string;
+ load_bigram_dawg: string;
}
-
+
+ type LoggerMessage = {
+ jobId: string;
+ progress: number;
+ status: string;
+ userJobId: string;
+ workerId: string;
+ };
+
interface WorkerOptions {
- corePath: string
- langPath: string
- cachePath: string
- dataPath: string
- workerPath: string
- cacheMethod: string
- workerBlobURL: boolean
- gzip: boolean
- legacyLang: boolean
- legacyCore: boolean
- logger: (arg: LoggerMessage) => void,
- errorHandler: (arg: any) => void
+ corePath: string;
+ langPath: string;
+ cachePath: string;
+ dataPath: string;
+ workerPath: string;
+ cacheMethod: string;
+ workerBlobURL: boolean;
+ gzip: boolean;
+ legacyLang: boolean;
+ legacyCore: boolean;
+ logger: (arg: LoggerMessage) => void;
+ errorHandler: (arg: any) => void;
}
interface WorkerParams {
- tessedit_pageseg_mode: PSM
- tessedit_char_whitelist: string
- tessedit_char_blacklist: string
- preserve_interword_spaces: string
- user_defined_dpi: string
- [propName: string]: any
+ tessedit_pageseg_mode: PSM;
+ tessedit_char_whitelist: string;
+ tessedit_char_blacklist: string;
+ preserve_interword_spaces: string;
+ user_defined_dpi: string;
+ [propName: string]: any;
}
interface OutputFormats {
text: boolean;
@@ -88,36 +131,36 @@ declare namespace Tesseract {
debug: boolean;
}
interface RecognizeOptions {
- rectangle: Rectangle
- pdfTitle: string
- pdfTextOnly: boolean
- rotateAuto: boolean
- rotateRadians: number
+ rectangle: Rectangle;
+ pdfTitle: string;
+ pdfTextOnly: boolean;
+ rotateAuto: boolean;
+ rotateRadians: number;
}
interface ConfigResult {
- jobId: string
- data: any
+ jobId: string;
+ data: any;
}
interface RecognizeResult {
- jobId: string
- data: Page
+ jobId: string;
+ data: Page;
}
interface DetectResult {
- jobId: string
- data: DetectData
+ jobId: string;
+ data: DetectData;
}
interface DetectData {
- tesseract_script_id: number | null
- script: string | null
- script_confidence: number | null
- orientation_degrees: number | null
- orientation_confidence: number | null
+ tesseract_script_id: number | null;
+ script: string | null;
+ script_confidence: number | null;
+ orientation_degrees: number | null;
+ orientation_confidence: number | null;
}
interface Rectangle {
- left: number
- top: number
- width: number
- height: number
+ left: number;
+ top: number;
+ width: number;
+ height: number;
}
enum OEM {
TESSERACT_ONLY,
@@ -126,28 +169,36 @@ declare namespace Tesseract {
DEFAULT,
}
enum PSM {
- OSD_ONLY = '0',
- AUTO_OSD = '1',
- AUTO_ONLY = '2',
- AUTO = '3',
- SINGLE_COLUMN = '4',
- SINGLE_BLOCK_VERT_TEXT = '5',
- SINGLE_BLOCK = '6',
- SINGLE_LINE = '7',
- SINGLE_WORD = '8',
- CIRCLE_WORD = '9',
- SINGLE_CHAR = '10',
- SPARSE_TEXT = '11',
- SPARSE_TEXT_OSD = '12',
- RAW_LINE = '13'
+ OSD_ONLY = "0",
+ AUTO_OSD = "1",
+ AUTO_ONLY = "2",
+ AUTO = "3",
+ SINGLE_COLUMN = "4",
+ SINGLE_BLOCK_VERT_TEXT = "5",
+ SINGLE_BLOCK = "6",
+ SINGLE_LINE = "7",
+ SINGLE_WORD = "8",
+ CIRCLE_WORD = "9",
+ SINGLE_CHAR = "10",
+ SPARSE_TEXT = "11",
+ SPARSE_TEXT_OSD = "12",
+ RAW_LINE = "13",
}
const enum imageType {
COLOR = 0,
GREY = 1,
- BINARY = 2
+ BINARY = 2,
}
- type ImageLike = string | HTMLImageElement | HTMLCanvasElement | HTMLVideoElement
- | CanvasRenderingContext2D | File | Blob | Buffer | OffscreenCanvas;
+ type ImageLike =
+ | string
+ | HTMLImageElement
+ | HTMLCanvasElement
+ | HTMLVideoElement
+ | CanvasRenderingContext2D
+ | File
+ | Blob
+ | (typeof Buffer extends undefined ? never : Buffer)
+ | OffscreenCanvas;
interface Block {
paragraphs: Paragraph[];
text: string;
@@ -179,7 +230,7 @@ declare namespace Tesseract {
text: string;
confidence: number;
baseline: Baseline;
- rowAttributes: RowAttributes
+ rowAttributes: RowAttributes;
bbox: Bbox;
}
interface Paragraph {

120
CLAUDE.md
View File

@@ -1,120 +0,0 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Development Commands
### Environment Setup
- **Prerequisites**: Node.js v22.x.x or higher, Yarn 4.9.1
- **Setup Yarn**: `corepack enable && corepack prepare yarn@4.9.1 --activate`
- **Install Dependencies**: `yarn install`
### Development
- **Start Development**: `yarn dev` - Runs Electron app in development mode
- **Debug Mode**: `yarn debug` - Starts with debugging enabled, use chrome://inspect
### Testing & Quality
- **Run Tests**: `yarn test` - Runs all tests (Vitest)
- **Run E2E Tests**: `yarn test:e2e` - Playwright end-to-end tests
- **Type Check**: `yarn typecheck` - Checks TypeScript for both node and web
- **Lint**: `yarn lint` - ESLint with auto-fix
- **Format**: `yarn format` - Prettier formatting
### Build & Release
- **Build**: `yarn build` - Builds for production (includes typecheck)
- **Platform-specific builds**:
- Windows: `yarn build:win`
- macOS: `yarn build:mac`
- Linux: `yarn build:linux`
## Architecture Overview
### Electron Multi-Process Architecture
- **Main Process** (`src/main/`): Node.js backend handling system integration, file operations, and services
- **Renderer Process** (`src/renderer/`): React-based UI running in Chromium
- **Preload Scripts** (`src/preload/`): Secure bridge between main and renderer processes
### Key Architectural Components
#### Main Process Services (`src/main/services/`)
- **MCPService**: Model Context Protocol server management
- **KnowledgeService**: Document processing and knowledge base management
- **FileStorage/S3Storage/WebDav**: Multiple storage backends
- **WindowService**: Multi-window management (main, mini, selection windows)
- **ProxyManager**: Network proxy handling
- **SearchService**: Full-text search capabilities
#### AI Core (`src/renderer/src/aiCore/`)
- **Middleware System**: Composable pipeline for AI request processing
- **Client Factory**: Supports multiple AI providers (OpenAI, Anthropic, Gemini, etc.)
- **Stream Processing**: Real-time response handling
#### State Management (`src/renderer/src/store/`)
- **Redux Toolkit**: Centralized state management
- **Persistent Storage**: Redux-persist for data persistence
- **Thunks**: Async actions for complex operations
#### Knowledge Management
- **Embeddings**: Vector search with multiple providers (OpenAI, Voyage, etc.)
- **OCR**: Document text extraction (system OCR, Doc2x, Mineru)
- **Preprocessing**: Document preparation pipeline
- **Loaders**: Support for various file formats (PDF, DOCX, EPUB, etc.)
### Build System
- **Electron-Vite**: Development and build tooling (v4.0.0)
- **Rolldown-Vite**: Using experimental rolldown-vite instead of standard vite
- **Workspaces**: Monorepo structure with `packages/` directory
- **Multiple Entry Points**: Main app, mini window, selection toolbar
- **Styled Components**: CSS-in-JS styling with SWC optimization
### Testing Strategy
- **Vitest**: Unit and integration testing
- **Playwright**: End-to-end testing
- **Component Testing**: React Testing Library
- **Coverage**: Available via `yarn test:coverage`
### Key Patterns
- **IPC Communication**: Secure main-renderer communication via preload scripts
- **Service Layer**: Clear separation between UI and business logic
- **Plugin Architecture**: Extensible via MCP servers and middleware
- **Multi-language Support**: i18n with dynamic loading
- **Theme System**: Light/dark themes with custom CSS variables
## Logging Standards
### Usage
```typescript
// Main process
import { loggerService } from '@logger'
const logger = loggerService.withContext('moduleName')
// Renderer process (set window source first)
loggerService.initWindowSource('windowName')
const logger = loggerService.withContext('moduleName')
// Logging
logger.info('message', CONTEXT)
logger.error('message', new Error('error'), CONTEXT)
```
### Log Levels (highest to lowest)
- `error` - Critical errors causing crash/unusable functionality
- `warn` - Potential issues that don't affect core functionality
- `info` - Application lifecycle and key user actions
- `verbose` - Detailed flow information for feature tracing
- `debug` - Development diagnostic info (not for production)
- `silly` - Extreme debugging, low-level information

View File

@@ -13,7 +13,7 @@
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=fr">Français</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=de">Deutsch</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=es">Español</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=it">Italiano</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=it">Itapano</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=ru">Русский</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=pt">Português</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=nl">Nederlands</a></p>
@@ -63,7 +63,7 @@
# 🍒 Cherry Studio
Cherry Studio is a desktop client that supports multiple LLM providers, available on Windows, Mac and Linux.
Cherry Studio is a desktop client that supports for multiple LLM providers, available on Windows, Mac and Linux.
👏 Join [Telegram Group](https://t.me/CherryStudioAI)[Discord](https://discord.gg/wez8HtpxqQ) | [QQ Group(575014769)](https://qm.qq.com/q/lo0D4qVZKi)
@@ -93,7 +93,7 @@ Cherry Studio is a desktop client that supports multiple LLM providers, availabl
3. **Document & Data Processing**:
- 📄 Supports Text, Images, Office, PDF, and more
- 📄 Support for Text, Images, Office, PDF, and more
- ☁️ WebDAV File Management and Backup
- 📊 Mermaid Chart Visualization
- 💻 Code Syntax Highlighting
@@ -110,7 +110,7 @@ Cherry Studio is a desktop client that supports multiple LLM providers, availabl
5. **Enhanced User Experience**:
- 🖥️ Cross-platform Support for Windows, Mac, and Linux
- 📦 Ready to Use - No Environment Setup Required
- 📦 Ready to Use, No Environment Setup Required
- 🎨 Light/Dark Themes and Transparent Window
- 📝 Complete Markdown Rendering
- 🤲 Easy Content Sharing
@@ -121,11 +121,11 @@ We're actively working on the following features and improvements:
1. 🎯 **Core Features**
- Selection Assistant with smart content selection enhancement
- Deep Research with advanced research capabilities
- Memory System with global context awareness
- Document Preprocessing with improved document handling
- MCP Marketplace for Model Context Protocol ecosystem
- Selection Assistant - Smart content selection enhancement
- Deep Research - Advanced research capabilities
- Memory System - Global context awareness
- Document Preprocessing - Improved document handling
- MCP Marketplace - Model Context Protocol ecosystem
2. 🗂 **Knowledge Management**
@@ -199,7 +199,7 @@ To give back to our core contributors and create a virtuous cycle, we have estab
**The inaugural tracking period for this program will be Q3 2025 (July, August, September). Rewards for this cycle will be distributed on October 1st.**
Within any tracking period (e.g., July 1st to September 30th for the first cycle), any developer who contributes more than **30 meaningful commits** to any of Cherry Studio's open-source projects on GitHub will be eligible for the following benefits:
Within any tracking period (e.g., July 1st to September 30th for the first cycle), any developer who contributes more than **30 meaningful commits** to any of Cherry Studio's open-source projects on GitHub is eligible for the following benefits:
- **Cursor Subscription Sponsorship**: Receive a **$70 USD** credit or reimbursement for your [Cursor](https://cursor.sh/) subscription, making AI your most efficient coding partner.
- **Unlimited Model Access**: Get **unlimited** API calls for the **DeepSeek** and **Qwen** models.
@@ -223,17 +223,17 @@ Let's build together.
# 🏢 Enterprise Edition
Building on the Community Edition, we are proud to introduce **Cherry Studio Enterprise Edition**—a privately-deployable AI productivity and management platform designed for modern teams and enterprises.
Building on the Community Edition, we are proud to introduce **Cherry Studio Enterprise Edition**—a privately deployable AI productivity and management platform designed for modern teams and enterprises.
The Enterprise Edition addresses core challenges in team collaboration by centralizing the management of AI resources, knowledge, and data. It empowers organizations to enhance efficiency, foster innovation, and ensure compliance, all while maintaining 100% control over their data in a secure environment.
## Core Advantages
- **Unified Model Management**: Centrally integrate and manage various cloud-based LLMs (e.g., OpenAI, Anthropic, Google Gemini) and locally deployed private models. Employees can use them out-of-the-box without individual configuration.
- **Enterprise-Grade Knowledge Base**: Build, manage, and share team-wide knowledge bases. Ensures knowledge retention and consistency, enabling team members to interact with AI based on unified and accurate information.
- **Enterprise-Grade Knowledge Base**: Build, manage, and share team-wide knowledge bases. Ensure knowledge is retained and consistent, enabling team members to interact with AI based on unified and accurate information.
- **Fine-Grained Access Control**: Easily manage employee accounts and assign role-based permissions for different models, knowledge bases, and features through a unified admin backend.
- **Fully Private Deployment**: Deploy the entire backend service on your on-premises servers or private cloud, ensuring your data remains 100% private and under your control to meet the strictest security and compliance standards.
- **Reliable Backend Services**: Provides stable API services and enterprise-grade data backup and recovery mechanisms to ensure business continuity.
- **Reliable Backend Services**: Provides stable API services, enterprise-grade data backup and recovery mechanisms to ensure business continuity.
## ✨ Online Demo
@@ -247,23 +247,23 @@ The Enterprise Edition addresses core challenges in team collaboration by centra
| Feature | Community Edition | Enterprise Edition |
| :---------------- | :----------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------- |
| **Open Source** | ✅ Yes | ⭕️ Partially released to customers |
| **Open Source** | ✅ Yes | ⭕️ part. released to cust. |
| **Cost** | Free for Personal Use / Commercial License | Buyout / Subscription Fee |
| **Admin Backend** | — | ● Centralized **Model** Access<br>● **Employee** Management<br>● Shared **Knowledge Base**<br>● **Access** Control<br>● **Data** Backup |
| **Server** | — | ✅ Dedicated Private Deployment |
## Get the Enterprise Edition
We believe the Enterprise Edition will become your team's AI productivity engine. If you are interested in Cherry Studio Enterprise Edition and would like to learn more, request a quote, or schedule a demo, please feel free to contact us.
We believe the Enterprise Edition will become your team's AI productivity engine. If you are interested in Cherry Studio Enterprise Edition and would like to learn more, request a quote, or schedule a demo, please contact us.
- **For Business Inquiries & Purchasing**:
**📧 [bd@cherry-ai.com](mailto:bd@cherry-ai.com)**
# 🔗 Related Projects
- [one-api](https://github.com/songquanpeng/one-api): LLM API management and distribution system supporting mainstream models like OpenAI, Azure, and Anthropic. Features a unified API interface, suitable for key management and secondary distribution.
- [one-api](https://github.com/songquanpeng/one-api):LLM API management and distribution system, supporting mainstream models like OpenAI, Azure, and Anthropic. Features unified API interface, suitable for key management and secondary distribution.
- [ublacklist](https://github.com/iorate/ublacklist): Blocks specific sites from appearing in Google search results
- [ublacklist](https://github.com/iorate/ublacklist):Blocks specific sites from appearing in Google search results
# 🚀 Contributors

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@@ -1,64 +0,0 @@
# Security Policy
## 📢 Reporting a Vulnerability
At Cherry Studio, we take security seriously and appreciate your efforts to responsibly disclose vulnerabilities. If you discover a security issue, please report it as soon as possible.
**Please do not create public issues for security-related reports.**
- To report a security issue, please use the GitHub Security Advisories tab to "[Open a draft security advisory](https://github.com/CherryHQ/cherry-studio/security/advisories/new)".
- Include a detailed description of the issue, steps to reproduce, potential impact, and any possible mitigations.
- If applicable, please also attach proof-of-concept code or screenshots.
We will acknowledge your report within **72 hours** and provide a status update as we investigate.
---
## 🔒 Supported Versions
We aim to support the latest released version and one previous minor release.
| Version | Supported |
| --------------- | ---------------- |
| Latest (`main`) | ✅ Supported |
| Previous minor | ✅ Supported |
| Older versions | ❌ Not supported |
If you are using an unsupported version, we strongly recommend updating to the latest release to receive security fixes.
---
## 💡 Security Measures
Cherry Studio integrates several security best practices, including:
- Strict dependency updates and regular vulnerability scanning.
- TypeScript strict mode and linting to reduce potential injection or runtime issues.
- Enforced code formatting and pre-commit hooks.
- Internal security reviews before releases.
- Dedicated MCP (Model Context Protocol) safeguards for model interactions and data privacy.
---
## 🛡️ Disclosure Policy
- We follow a **coordinated disclosure** approach.
- We will not publicly disclose vulnerabilities until a fix has been developed and released.
- Credit will be given to researchers who responsibly disclose vulnerabilities, if requested.
---
## 🤝 Acknowledgements
We greatly appreciate contributions from the security community and strive to recognize all researchers who help keep Cherry Studio safe.
---
## 🌟 Questions?
For any security-related questions not involving vulnerabilities, please reach out to:
**security@cherry-ai.com**
---
Thank you for helping keep Cherry Studio and its users secure!

View File

@@ -8,93 +8,16 @@
; https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist
!include LogicLib.nsh
!include x64.nsh
; https://github.com/electron-userland/electron-builder/issues/1122
!ifndef BUILD_UNINSTALLER
Function checkVCRedist
ReadRegDWORD $0 HKLM "SOFTWARE\Microsoft\VisualStudio\14.0\VC\Runtimes\x64" "Installed"
FunctionEnd
Function checkArchitectureCompatibility
; Initialize variables
StrCpy $0 "0" ; Default to incompatible
StrCpy $1 "" ; System architecture
StrCpy $3 "" ; App architecture
; Check system architecture using built-in NSIS functions
${If} ${RunningX64}
; Check if it's ARM64 by looking at processor architecture
ReadEnvStr $2 "PROCESSOR_ARCHITECTURE"
ReadEnvStr $4 "PROCESSOR_ARCHITEW6432"
${If} $2 == "ARM64"
${OrIf} $4 == "ARM64"
StrCpy $1 "arm64"
${Else}
StrCpy $1 "x64"
${EndIf}
${Else}
StrCpy $1 "x86"
${EndIf}
; Determine app architecture based on build variables
!ifdef APP_ARM64_NAME
!ifndef APP_64_NAME
StrCpy $3 "arm64" ; App is ARM64 only
!endif
!endif
!ifdef APP_64_NAME
!ifndef APP_ARM64_NAME
StrCpy $3 "x64" ; App is x64 only
!endif
!endif
!ifdef APP_64_NAME
!ifdef APP_ARM64_NAME
StrCpy $3 "universal" ; Both architectures available
!endif
!endif
; If no architecture variables are defined, assume x64
${If} $3 == ""
StrCpy $3 "x64"
${EndIf}
; Compare system and app architectures
${If} $3 == "universal"
; Universal build, compatible with all architectures
StrCpy $0 "1"
${ElseIf} $1 == $3
; Architectures match
StrCpy $0 "1"
${Else}
; Architectures don't match
StrCpy $0 "0"
${EndIf}
FunctionEnd
!endif
!macro customInit
Push $0
Push $1
Push $2
Push $3
Push $4
; Check architecture compatibility first
Call checkArchitectureCompatibility
${If} $0 != "1"
MessageBox MB_ICONEXCLAMATION "\
Architecture Mismatch$\r$\n$\r$\n\
This installer is not compatible with your system architecture.$\r$\n\
Your system: $1$\r$\n\
App architecture: $3$\r$\n$\r$\n\
Please download the correct version from:$\r$\n\
https://www.cherry-ai.com/"
ExecShell "open" "https://www.cherry-ai.com/"
Abort
${EndIf}
Call checkVCRedist
${If} $0 != "1"
MessageBox MB_YESNO "\
@@ -120,9 +43,5 @@
Abort
${EndIf}
ContinueInstall:
Pop $4
Pop $3
Pop $2
Pop $1
Pop $0
!macroend
!macroend

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@@ -31,12 +31,6 @@ corepack prepare yarn@4.6.0 --activate
yarn install
```
### ENV
```bash
copy .env.example .env
```
### Start
```bash

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@@ -1,222 +0,0 @@
# Cherry Studio 记忆功能指南
## 功能介绍
Cherry Studio 的记忆功能是一个强大的工具,能够帮助 AI 助手记住对话中的重要信息、用户偏好和上下文。通过记忆功能,您的 AI 助手可以:
- 📝 **记住重要信息**:自动从对话中提取并存储关键事实和信息
- 🧠 **个性化响应**:基于存储的记忆提供更加个性化和相关的回答
- 🔍 **智能检索**:在需要时自动搜索相关记忆,增强对话的连贯性
- 👥 **多用户支持**:为不同用户维护独立的记忆上下文
记忆功能特别适用于需要长期保持上下文的场景,例如个人助手、客户服务、教育辅导等。
## 如何启用记忆功能
### 1. 全局配置(首次设置)
在使用记忆功能之前,您需要先进行全局配置:
1. 点击侧边栏的 **记忆** 图标(记忆棒图标)进入记忆管理页面
2. 点击右上角的 **更多** 按钮(三个点),选择 **设置**
3. 在设置弹窗中配置以下必要项:
- **LLM 模型**:选择用于处理记忆的语言模型(推荐使用 GPT-4 或 Claude 等高级模型)
- **嵌入模型**:选择用于生成向量嵌入的模型(如 text-embedding-3-small
- **嵌入维度**:输入嵌入模型的维度(通常为 1536
4. 点击 **确定** 保存配置
> ⚠️ **注意**:嵌入模型和维度一旦设置后无法更改,请谨慎选择。
### 2. 为助手启用记忆
完成全局配置后,您可以为特定助手启用记忆功能:
1. 进入 **助手** 页面
2. 选择要启用记忆的助手,点击 **编辑**
3. 在助手设置中找到 **记忆** 部分
4. 打开记忆功能开关
5. 保存助手设置
启用后,该助手将在对话过程中自动提取和使用记忆。
## 使用方法
### 查看记忆
1. 点击侧边栏的 **记忆** 图标进入记忆管理页面
2. 您可以看到所有存储的记忆卡片,包括:
- 记忆内容
- 创建时间
- 所属用户
### 添加记忆
手动添加记忆有两种方式:
**方式一:在记忆管理页面添加**
1. 点击右上角的 **添加记忆** 按钮
2. 在弹窗中输入记忆内容
3. 点击 **添加** 保存
**方式二:在对话中自动提取**
- 当助手启用记忆功能后,系统会自动从对话中提取重要信息并存储为记忆
### 编辑记忆
1. 在记忆卡片上点击 **更多** 按钮(三个点)
2. 选择 **编辑**
3. 修改记忆内容
4. 点击 **保存**
### 删除记忆
1. 在记忆卡片上点击 **更多** 按钮
2. 选择 **删除**
3. 确认删除操作
## 记忆搜索
记忆管理页面提供了强大的搜索功能:
1. 在页面顶部的搜索框中输入关键词
2. 系统会实时过滤显示匹配的记忆
3. 搜索支持模糊匹配,可以搜索记忆内容的任何部分
## 用户管理
记忆功能支持多用户,您可以为不同的用户维护独立的记忆库:
### 切换用户
1. 在记忆管理页面,点击右上角的用户选择器
2. 选择要切换到的用户
3. 页面会自动加载该用户的记忆
### 添加新用户
1. 点击用户选择器
2. 选择 **添加新用户**
3. 输入用户 ID支持字母、数字、下划线和连字符
4. 点击 **添加**
### 删除用户
1. 切换到要删除的用户
2. 点击右上角的 **更多** 按钮
3. 选择 **删除用户**
4. 确认删除(注意:这将删除该用户的所有记忆)
> 💡 **提示**默认用户default-user无法删除。
## 设置说明
### LLM 模型
- 用于处理记忆提取和更新的语言模型
- 建议选择能力较强的模型以获得更好的记忆提取效果
- 可随时更改
### 嵌入模型
- 用于将文本转换为向量,支持语义搜索
- 一旦设置后无法更改(为了保证现有记忆的兼容性)
- 推荐使用 OpenAI 的 text-embedding 系列模型
### 嵌入维度
- 嵌入向量的维度,需要与选择的嵌入模型匹配
- 常见维度:
- text-embedding-3-small: 1536
- text-embedding-3-large: 3072
- text-embedding-ada-002: 1536
### 自定义提示词(可选)
- **事实提取提示词**:自定义如何从对话中提取信息
- **记忆更新提示词**:自定义如何更新现有记忆
## 最佳实践
### 1. 合理组织记忆
- 保持记忆简洁明了,每条记忆专注于一个具体信息
- 使用清晰的语言描述事实,避免模糊表达
- 定期审查和清理过时或不准确的记忆
### 2. 多用户场景
- 为不同的使用场景创建独立用户(如工作、个人、学习等)
- 使用有意义的用户 ID便于识别和管理
- 定期备份重要用户的记忆数据
### 3. 模型选择建议
- **LLM 模型**GPT-4、Claude 3 等高级模型能更准确地提取和理解信息
- **嵌入模型**:选择与您的主要使用语言匹配的模型
### 4. 性能优化
- 避免存储过多冗余记忆,这可能影响搜索性能
- 定期整理和合并相似的记忆
- 对于大量记忆的场景,考虑按主题或时间进行分类管理
## 常见问题
### Q: 为什么我无法启用记忆功能?
A: 请确保您已经完成全局配置,包括选择 LLM 模型和嵌入模型。
### Q: 记忆会自动同步到所有助手吗?
A: 不会。每个助手的记忆功能需要单独启用,且记忆是按用户隔离的。
### Q: 如何导出我的记忆数据?
A: 目前系统暂不支持直接导出功能,但所有记忆都存储在本地数据库中。
### Q: 删除的记忆可以恢复吗?
A: 删除操作是永久的,无法恢复。建议在删除前仔细确认。
### Q: 记忆功能会影响对话速度吗?
A: 记忆功能在后台异步处理,不会明显影响对话响应速度。但过多的记忆可能会略微增加搜索时间。
### Q: 如何清空所有记忆?
A: 您可以删除当前用户并重新创建,或者手动删除所有记忆条目。
## 注意事项
### 隐私保护
- 所有记忆数据都存储在您的本地设备上,不会上传到云端
- 请勿在记忆中存储敏感信息(如密码、私钥等)
- 定期审查记忆内容,确保没有意外存储的隐私信息
### 数据安全
- 记忆数据存储在本地数据库中
- 建议定期备份重要数据
- 更换设备时请注意迁移记忆数据
### 使用限制
- 单条记忆的长度建议不超过 500 字
- 每个用户的记忆数量建议控制在 1000 条以内
- 过多的记忆可能影响系统性能
## 技术细节
记忆功能使用了先进的 RAG检索增强生成技术
1. **信息提取**:使用 LLM 从对话中智能提取关键信息
2. **向量化存储**:通过嵌入模型将文本转换为向量,支持语义搜索
3. **智能检索**:在对话时自动搜索相关记忆,提供给 AI 作为上下文
4. **持续学习**:随着对话进行,不断更新和完善记忆库
---
💡 **提示**:记忆功能是 Cherry Studio 的高级特性,合理使用可以大大提升 AI 助手的智能程度和用户体验。如有更多问题,欢迎查阅文档或联系支持团队。

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# CodeBlockView Component Structure
## Overview
CodeBlockView is the core component in Cherry Studio for displaying and manipulating code blocks. It supports multiple view modes and visual previews for special languages, providing rich interactive tools.
## Component Structure
```mermaid
graph TD
A[CodeBlockView] --> B[CodeToolbar]
A --> C[SourceView]
A --> D[SpecialView]
A --> E[StatusBar]
B --> F[CodeToolButton]
C --> G[CodeEditor / CodeViewer]
D --> H[MermaidPreview]
D --> I[PlantUmlPreview]
D --> J[SvgPreview]
D --> K[GraphvizPreview]
F --> L[useCopyTool]
F --> M[useDownloadTool]
F --> N[useViewSourceTool]
F --> O[useSplitViewTool]
F --> P[useRunTool]
F --> Q[useExpandTool]
F --> R[useWrapTool]
F --> S[useSaveTool]
```
## Core Concepts
### View Types
- **preview**: Preview view, where non-source code is displayed as special views
- **edit**: Edit view
### View Modes
- **source**: Source code view mode
- **special**: Special view mode (Mermaid, PlantUML, SVG)
- **split**: Split view mode (source code and special view displayed side by side)
### Special View Languages
- mermaid
- plantuml
- svg
- dot
- graphviz
## Component Details
### CodeBlockView Main Component
Main responsibilities:
1. Managing view mode state
2. Coordinating the display of source code view and special view
3. Managing toolbar tools
4. Handling code execution state
### Subcomponents
#### CodeToolbar
- Toolbar displayed at the top-right corner of the code block
- Contains core and quick tools
- Dynamically displays relevant tools based on context
#### CodeEditor/CodeViewer Source View
- Editable code editor or read-only code viewer
- Uses either component based on settings
- Supports syntax highlighting for multiple programming languages
#### Special View Components
- **MermaidPreview**: Mermaid diagram preview
- **PlantUmlPreview**: PlantUML diagram preview
- **SvgPreview**: SVG image preview
- **GraphvizPreview**: Graphviz diagram preview
All special view components share a common architecture for consistent user experience and functionality. For detailed information about these components and their implementation, see [Image Preview Components Documentation](./ImagePreview-en.md).
#### StatusBar
- Displays Python code execution results
- Can show both text and image results
## Tool System
CodeBlockView uses a hook-based tool system:
```mermaid
graph TD
A[CodeBlockView] --> B[useCopyTool]
A --> C[useDownloadTool]
A --> D[useViewSourceTool]
A --> E[useSplitViewTool]
A --> F[useRunTool]
A --> G[useExpandTool]
A --> H[useWrapTool]
A --> I[useSaveTool]
B --> J[ToolManager]
C --> J
D --> J
E --> J
F --> J
G --> J
H --> J
I --> J
J --> K[CodeToolbar]
```
Each tool hook is responsible for registering specific function tool buttons to the tool manager, which then passes these tools to the CodeToolbar component for rendering.
### Tool Types
- **core**: Core tools, always displayed in the toolbar
- **quick**: Quick tools, displayed in a dropdown menu when there are more than one
### Tool List
1. **Copy**: Copy code or image
2. **Download**: Download code or image
3. **View Source**: Switch between special view and source code view
4. **Split View**: Toggle split view mode
5. **Run**: Run Python code
6. **Expand/Collapse**: Control code block expansion/collapse
7. **Wrap**: Control automatic line wrapping
8. **Save**: Save edited code
## State Management
CodeBlockView manages the following states through React hooks:
1. **viewMode**: Current view mode ('source' | 'special' | 'split')
2. **isRunning**: Python code execution status
3. **executionResult**: Python code execution result
4. **tools**: Toolbar tool list
5. **expandOverride/unwrapOverride**: User override settings for expand/wrap
6. **sourceScrollHeight**: Source code view scroll height
## Interaction Flow
```mermaid
sequenceDiagram
participant U as User
participant CB as CodeBlockView
participant CT as CodeToolbar
participant SV as SpecialView
participant SE as SourceEditor
U->>CB: View code block
CB->>CB: Initialize state
CB->>CT: Register tools
CB->>SV: Render special view (if applicable)
CB->>SE: Render source view
U->>CT: Click tool button
CT->>CB: Trigger tool callback
CB->>CB: Update state
CB->>CT: Re-register tools (if needed)
```
## Special Handling
### HTML Code Blocks
HTML code blocks are specially handled using the HtmlArtifactsCard component.
### Python Code Execution
Supports executing Python code and displaying results using Pyodide to run Python code in the browser.

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@@ -1,180 +0,0 @@
# CodeBlockView 组件结构说明
## 概述
CodeBlockView 是 Cherry Studio 中用于显示和操作代码块的核心组件。它支持多种视图模式和特殊语言的可视化预览,提供丰富的交互工具。
## 组件结构
```mermaid
graph TD
A[CodeBlockView] --> B[CodeToolbar]
A --> C[SourceView]
A --> D[SpecialView]
A --> E[StatusBar]
B --> F[CodeToolButton]
C --> G[CodeEditor / CodeViewer]
D --> H[MermaidPreview]
D --> I[PlantUmlPreview]
D --> J[SvgPreview]
D --> K[GraphvizPreview]
F --> L[useCopyTool]
F --> M[useDownloadTool]
F --> N[useViewSourceTool]
F --> O[useSplitViewTool]
F --> P[useRunTool]
F --> Q[useExpandTool]
F --> R[useWrapTool]
F --> S[useSaveTool]
```
## 核心概念
### 视图类型
- **preview**: 预览视图,非源代码的是特殊视图
- **edit**: 编辑视图
### 视图模式
- **source**: 源代码视图模式
- **special**: 特殊视图模式Mermaid、PlantUML、SVG
- **split**: 分屏模式(源代码和特殊视图并排显示)
### 特殊视图语言
- mermaid
- plantuml
- svg
- dot
- graphviz
## 组件详细说明
### CodeBlockView 主组件
主要负责:
1. 管理视图模式状态
2. 协调源代码视图和特殊视图的显示
3. 管理工具栏工具
4. 处理代码执行状态
### 子组件
#### CodeToolbar 工具栏
- 显示在代码块右上角的工具栏
- 包含核心(core)和快捷(quick)两类工具
- 根据上下文动态显示相关工具
#### CodeEditor/CodeViewer 源代码视图
- 可编辑的代码编辑器或只读的代码查看器
- 根据设置决定使用哪个组件
- 支持多种编程语言高亮
#### 特殊视图组件
- **MermaidPreview**: Mermaid 图表预览
- **PlantUmlPreview**: PlantUML 图表预览
- **SvgPreview**: SVG 图像预览
- **GraphvizPreview**: Graphviz 图表预览
所有特殊视图组件共享通用架构,以确保一致的用户体验和功能。有关这些组件及其实现的详细信息,请参阅 [图像预览组件文档](./ImagePreview-zh.md)。
#### StatusBar 状态栏
- 显示 Python 代码执行结果
- 可显示文本和图像结果
## 工具系统
CodeBlockView 使用基于 hooks 的工具系统:
```mermaid
graph TD
A[CodeBlockView] --> B[useCopyTool]
A --> C[useDownloadTool]
A --> D[useViewSourceTool]
A --> E[useSplitViewTool]
A --> F[useRunTool]
A --> G[useExpandTool]
A --> H[useWrapTool]
A --> I[useSaveTool]
B --> J[ToolManager]
C --> J
D --> J
E --> J
F --> J
G --> J
H --> J
I --> J
J --> K[CodeToolbar]
```
每个工具 hook 负责注册特定功能的工具按钮到工具管理器,工具管理器再将这些工具传递给 CodeToolbar 组件进行渲染。
### 工具类型
- **core**: 核心工具,始终显示在工具栏
- **quick**: 快捷工具当数量大于1时通过下拉菜单显示
### 工具列表
1. **复制(copy)**: 复制代码或图像
2. **下载(download)**: 下载代码或图像
3. **查看源码(view-source)**: 在特殊视图和源码视图间切换
4. **分屏(split-view)**: 切换分屏模式
5. **运行(run)**: 运行 Python 代码
6. **展开/折叠(expand)**: 控制代码块的展开/折叠
7. **换行(wrap)**: 控制代码的自动换行
8. **保存(save)**: 保存编辑的代码
## 状态管理
CodeBlockView 通过 React hooks 管理以下状态:
1. **viewMode**: 当前视图模式 ('source' | 'special' | 'split')
2. **isRunning**: Python 代码执行状态
3. **executionResult**: Python 代码执行结果
4. **tools**: 工具栏工具列表
5. **expandOverride/unwrapOverride**: 用户展开/换行的覆盖设置
6. **sourceScrollHeight**: 源代码视图滚动高度
## 交互流程
```mermaid
sequenceDiagram
participant U as User
participant CB as CodeBlockView
participant CT as CodeToolbar
participant SV as SpecialView
participant SE as SourceEditor
U->>CB: 查看代码块
CB->>CB: 初始化状态
CB->>CT: 注册工具
CB->>SV: 渲染特殊视图(如果适用)
CB->>SE: 渲染源码视图
U->>CT: 点击工具按钮
CT->>CB: 触发工具回调
CB->>CB: 更新状态
CB->>CT: 重新注册工具(如果需要)
```
## 特殊处理
### HTML 代码块
HTML 代码块会被特殊处理,使用 HtmlArtifactsCard 组件显示。
### Python 代码执行
支持执行 Python 代码并显示结果,使用 Pyodide 在浏览器中运行 Python 代码。

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# Image Preview Components
## Overview
Image Preview Components are a set of specialized components in Cherry Studio for rendering and displaying various diagram and image formats. They provide a consistent user experience across different preview types with shared functionality for loading states, error handling, and interactive controls.
## Supported Formats
- **Mermaid**: Interactive diagrams and flowcharts
- **PlantUML**: UML diagrams and system architecture
- **SVG**: Scalable vector graphics
- **Graphviz/DOT**: Graph visualization and network diagrams
## Architecture
```mermaid
graph TD
A[MermaidPreview] --> D[ImagePreviewLayout]
B[PlantUmlPreview] --> D
C[SvgPreview] --> D
E[GraphvizPreview] --> D
D --> F[ImageToolbar]
D --> G[useDebouncedRender]
F --> H[Pan Controls]
F --> I[Zoom Controls]
F --> J[Reset Function]
F --> K[Dialog Control]
G --> L[Debounced Rendering]
G --> M[Error Handling]
G --> N[Loading State]
G --> O[Dependency Management]
```
## Core Components
### ImagePreviewLayout
A common layout wrapper that provides the foundation for all image preview components.
**Features:**
- **Loading State Management**: Shows loading spinner during rendering
- **Error Display**: Displays error messages when rendering fails
- **Toolbar Integration**: Conditionally renders ImageToolbar when enabled
- **Container Management**: Wraps preview content with consistent styling
- **Responsive Design**: Adapts to different container sizes
**Props:**
- `children`: The preview content to be displayed
- `loading`: Boolean indicating if content is being rendered
- `error`: Error message to display if rendering fails
- `enableToolbar`: Whether to show the interactive toolbar
- `imageRef`: Reference to the container element for image manipulation
### ImageToolbar
Interactive toolbar component providing image manipulation controls.
**Features:**
- **Pan Controls**: 4-directional pan buttons (up, down, left, right)
- **Zoom Controls**: Zoom in/out functionality with configurable increments
- **Reset Function**: Restore original pan and zoom state
- **Dialog Control**: Open preview in expanded dialog view
- **Accessible Design**: Full keyboard navigation and screen reader support
**Layout:**
- 3x3 grid layout positioned at bottom-right of preview
- Responsive button sizing
- Tooltip support for all controls
### useDebouncedRender Hook
A specialized React hook for managing preview rendering with performance optimizations.
**Features:**
- **Debounced Rendering**: Prevents excessive re-renders during rapid content changes (default 300ms delay)
- **Automatic Dependency Management**: Handles dependencies for render and condition functions
- **Error Handling**: Catches and manages rendering errors with detailed error messages
- **Loading State**: Tracks rendering progress with automatic state updates
- **Conditional Rendering**: Supports pre-render condition checks
- **Manual Controls**: Provides trigger, cancel, and state management functions
**API:**
```typescript
const { containerRef, error, isLoading, triggerRender, cancelRender, clearError, setLoading } = useDebouncedRender(
value,
renderFunction,
options
)
```
**Options:**
- `debounceDelay`: Customize debounce timing
- `shouldRender`: Function for conditional rendering logic
## Component Implementations
### MermaidPreview
Renders Mermaid diagrams with special handling for visibility detection.
**Special Features:**
- Syntax validation before rendering
- Visibility detection to handle collapsed containers
- SVG coordinate fixing for edge cases
- Integration with mermaid.js library
### PlantUmlPreview
Renders PlantUML diagrams using the online PlantUML server.
**Special Features:**
- Network error handling and retry logic
- Diagram encoding using deflate compression
- Support for light/dark themes
- Server status monitoring
### SvgPreview
Renders SVG content using Shadow DOM for isolation.
**Special Features:**
- Shadow DOM rendering for style isolation
- Direct SVG content injection
- Minimal processing overhead
- Cross-browser compatibility
### GraphvizPreview
Renders Graphviz/DOT diagrams using the viz.js library.
**Special Features:**
- Client-side rendering with viz.js
- Lazy loading of viz.js library
- SVG element generation
- Memory-efficient processing
## Shared Functionality
### Error Handling
All preview components provide consistent error handling:
- Network errors (connection failures)
- Syntax errors (invalid diagram code)
- Server errors (external service failures)
- Rendering errors (library failures)
### Loading States
Standardized loading indicators across all components:
- Spinner animation during processing
- Progress feedback for long operations
- Smooth transitions between states
### Interactive Controls
Common interaction patterns:
- Pan and zoom functionality
- Reset to original view
- Full-screen dialog mode
- Keyboard accessibility
### Performance Optimizations
- Debounced rendering to prevent excessive updates
- Lazy loading of heavy libraries
- Memory management for large diagrams
- Efficient re-rendering strategies
## Integration with CodeBlockView
Image Preview Components integrate seamlessly with CodeBlockView:
- Automatic format detection based on language tags
- Consistent toolbar integration
- Shared state management
- Responsive layout adaptation
For more information about the overall CodeBlockView architecture, see [CodeBlockView Documentation](./CodeBlockView-en.md).

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# 图像预览组件
## 概述
图像预览组件是 Cherry Studio 中用于渲染和显示各种图表和图像格式的专用组件集合。它们为不同预览类型提供一致的用户体验,具有共享的加载状态、错误处理和交互控制功能。
## 支持格式
- **Mermaid**: 交互式图表和流程图
- **PlantUML**: UML 图表和系统架构
- **SVG**: 可缩放矢量图形
- **Graphviz/DOT**: 图形可视化和网络图表
## 架构
```mermaid
graph TD
A[MermaidPreview] --> D[ImagePreviewLayout]
B[PlantUmlPreview] --> D
C[SvgPreview] --> D
E[GraphvizPreview] --> D
D --> F[ImageToolbar]
D --> G[useDebouncedRender]
F --> H[平移控制]
F --> I[缩放控制]
F --> J[重置功能]
F --> K[对话框控制]
G --> L[防抖渲染]
G --> M[错误处理]
G --> N[加载状态]
G --> O[依赖管理]
```
## 核心组件
### ImagePreviewLayout 图像预览布局
为所有图像预览组件提供基础的通用布局包装器。
**功能特性:**
- **加载状态管理**: 在渲染期间显示加载动画
- **错误显示**: 渲染失败时显示错误信息
- **工具栏集成**: 启用时有条件地渲染 ImageToolbar
- **容器管理**: 使用一致的样式包装预览内容
- **响应式设计**: 适应不同的容器尺寸
**属性:**
- `children`: 要显示的预览内容
- `loading`: 指示内容是否正在渲染的布尔值
- `error`: 渲染失败时显示的错误信息
- `enableToolbar`: 是否显示交互式工具栏
- `imageRef`: 用于图像操作的容器元素引用
### ImageToolbar 图像工具栏
提供图像操作控制的交互式工具栏组件。
**功能特性:**
- **平移控制**: 4方向平移按钮上、下、左、右
- **缩放控制**: 放大/缩小功能,支持可配置的增量
- **重置功能**: 恢复原始平移和缩放状态
- **对话框控制**: 在展开对话框中打开预览
- **无障碍设计**: 完整的键盘导航和屏幕阅读器支持
**布局:**
- 3x3 网格布局,位于预览右下角
- 响应式按钮尺寸
- 所有控件的工具提示支持
### useDebouncedRender Hook 防抖渲染钩子
用于管理预览渲染的专用 React Hook具有性能优化功能。
**功能特性:**
- **防抖渲染**: 防止内容快速变化时的过度重新渲染(默认 300ms 延迟)
- **自动依赖管理**: 处理渲染和条件函数的依赖项
- **错误处理**: 捕获和管理渲染错误,提供详细的错误信息
- **加载状态**: 跟踪渲染进度并自动更新状态
- **条件渲染**: 支持预渲染条件检查
- **手动控制**: 提供触发、取消和状态管理功能
**API:**
```typescript
const { containerRef, error, isLoading, triggerRender, cancelRender, clearError, setLoading } = useDebouncedRender(
value,
renderFunction,
options
)
```
**选项:**
- `debounceDelay`: 自定义防抖时间
- `shouldRender`: 条件渲染逻辑函数
## 组件实现
### MermaidPreview Mermaid 预览
渲染 Mermaid 图表,具有可见性检测的特殊处理。
**特殊功能:**
- 渲染前语法验证
- 可见性检测以处理折叠的容器
- 边缘情况的 SVG 坐标修复
- 与 mermaid.js 库集成
### PlantUmlPreview PlantUML 预览
使用在线 PlantUML 服务器渲染 PlantUML 图表。
**特殊功能:**
- 网络错误处理和重试逻辑
- 使用 deflate 压缩的图表编码
- 支持明/暗主题
- 服务器状态监控
### SvgPreview SVG 预览
使用 Shadow DOM 隔离渲染 SVG 内容。
**特殊功能:**
- Shadow DOM 渲染实现样式隔离
- 直接 SVG 内容注入
- 最小化处理开销
- 跨浏览器兼容性
### GraphvizPreview Graphviz 预览
使用 viz.js 库渲染 Graphviz/DOT 图表。
**特殊功能:**
- 使用 viz.js 进行客户端渲染
- viz.js 库的懒加载
- SVG 元素生成
- 内存高效处理
## 共享功能
### 错误处理
所有预览组件提供一致的错误处理:
- 网络错误(连接失败)
- 语法错误(无效的图表代码)
- 服务器错误(外部服务失败)
- 渲染错误(库失败)
### 加载状态
所有组件的标准化加载指示器:
- 处理期间的动画
- 长时间操作的进度反馈
- 状态间的平滑过渡
### 交互控制
通用交互模式:
- 平移和缩放功能
- 重置到原始视图
- 全屏对话框模式
- 键盘无障碍访问
### 性能优化
- 防抖渲染以防止过度更新
- 重型库的懒加载
- 大型图表的内存管理
- 高效的重新渲染策略
## 与 CodeBlockView 的集成
图像预览组件与 CodeBlockView 无缝集成:
- 基于语言标签的自动格式检测
- 一致的工具栏集成
- 共享状态管理
- 响应式布局适应
有关整体 CodeBlockView 架构的更多信息,请参阅 [CodeBlockView 文档](./CodeBlockView-zh.md)。

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# 代码执行功能
本文档说明了代码块的 Python 代码执行功能。该实现利用 [Pyodide][pyodide-link] 在浏览器环境中直接运行 Python 代码,并将其置于 Web Worker 中,以避免阻塞主 UI 线程。
整个实现分为三个主要部分UI 层、服务层和 Worker 层。
## 执行流程图
```mermaid
sequenceDiagram
participant 用户
participant CodeBlockView (UI)
participant PyodideService (服务)
participant PyodideWorker (Worker)
用户->>CodeBlockView (UI): 点击“运行”按钮
CodeBlockView (UI)->>PyodideService (服务): 调用 runScript(code)
PyodideService (服务)->>PyodideWorker (Worker): 发送 postMessage({ id, python: code })
PyodideWorker (Worker)->>PyodideWorker (Worker): 加载 Pyodide 和相关包
PyodideWorker (Worker)->>PyodideWorker (Worker): (按需)注入垫片并合并代码
PyodideWorker (Worker)->>PyodideWorker (Worker): 执行合并后的 Python 代码
PyodideWorker (Worker)-->>PyodideService (服务): 返回 postMessage({ id, output })
PyodideService (服务)-->>CodeBlockView (UI): 返回 { text, image } 对象
CodeBlockView (UI)->>用户: 在状态栏中显示文本和/或图像输出
```
## 1. UI 层
面向用户的代码执行组件是 [CodeBlockView][codeblock-view-link]。
### 关键机制:
- **运行按钮**:当代码块语言为 `python``codeExecution.enabled` 设置为 true 时,`CodeToolbar` 中会条件性地渲染一个“运行”按钮。
- **事件处理**:运行按钮的 `onClick` 事件会触发 `handleRunScript` 函数。
- **服务调用**`handleRunScript` 调用 `pyodideService.runScript(code)`,将代码块中的 Python 代码传递给服务。
- **状态管理与输出显示**:使用 `executionResult` 来管理所有执行输出,只要有任何结果(文本或图像),[StatusBar][statusbar-link] 组件就会被渲染以统一显示。
```typescript
// src/renderer/src/components/CodeBlockView/view.tsx
const [executionResult, setExecutionResult] = useState<{ text: string; image?: string } | null>(null)
const handleRunScript = useCallback(() => {
setIsRunning(true)
setExecutionResult(null)
pyodideService
.runScript(children, {}, codeExecution.timeoutMinutes * 60000)
.then((result) => {
setExecutionResult(result)
})
.catch((error) => {
console.error('Unexpected error:', error)
setExecutionResult({
text: `Unexpected error: ${error.message || 'Unknown error'}`
})
})
.finally(() => {
setIsRunning(false)
})
}, [children, codeExecution.timeoutMinutes]);
// ... 在 JSX 中
{isExecutable && executionResult && (
<StatusBar>
{executionResult.text}
{executionResult.image && (
<ImageOutput>
<img src={executionResult.image} alt="Matplotlib plot" />
</ImageOutput>
)}
</StatusBar>
)}
```
## 2. 服务层
服务层充当 UI 组件和运行 Pyodide 的 Web Worker 之间的桥梁。其逻辑封装在位于单例类 [PyodideService][pyodide-service-link]。
### 主要职责:
- **Worker 管理**:初始化、管理并与 Pyodide Web Worker 通信。
- **请求处理**:使用 `resolvers` Map 管理并发请求,通过唯一 ID 匹配请求和响应。
- **为 UI 提供 API**:向 UI 提供 `runScript(script, context, timeout)` 方法。此方法的返回值已修改为 `Promise<{ text: string; image?: string }>`,以支持包括图像在内的多种输出类型。
- **输出处理**:从 Worker 接收包含文本、错误和可选图像数据的 `output` 对象。它将文本和错误格式化为对用户友好的单个字符串,然后连同图像数据一起包装成对象返回给 UI 层。
- **IPC 端点**:该服务还提供了一个 `python-execution-request` IPC 端点,允许主进程请求执行 Python 代码,展示了其灵活的架构。
## 3. Worker 层
核心的 Python 执行发生在 [pyodide.worker.ts][pyodide-worker-link] 中定义的 Web Worker 内部。这确保了计算密集的 Python 代码不会冻结用户界面。
### Worker 逻辑:
- **Pyodide 加载**Worker 从 CDN 加载 Pyodide 引擎,并设置处理器以捕获 Python 的 `stdout``stderr`
- **动态包安装**:使用 `pyodide.loadPackagesFromImports()` 自动分析并安装代码中导入的依赖包。
- **按需执行垫片代码**Worker 会检查传入的代码中是否包含 "matplotlib" 字符串。如果是,它会先执行一段 Python“垫片”代码确保图像输出到全局命名空间。
- **结果序列化**:执行结果通过 `.toJs()` 等方法被递归转换为可序列化的标准 JavaScript 对象。
- **返回结构化输出**执行后Worker 将一个包含 `id``output` 对象的-消息发回服务层。`output` 对象是一个结构化对象,包含 `result``text``error` 以及一个可选的 `image` 字段(用于 Base64 图像数据)。
### 数据流
最终的数据流如下:
1. **UI 层 ([CodeBlockView][codeblock-view-link])**: 用户点击“运行”按钮。
2. **服务层 ([PyodideService][pyodide-service-link])**:
- 接收到代码执行请求。
- 调用 Web Worker ([pyodide.worker.ts][pyodide-worker-link]),传递用户代码。
3. **Worker 层 ([pyodide.worker.ts][pyodide-worker-link])**:
- 加载 Pyodide 运行时。
- 动态安装代码中 `import` 语句声明的依赖包。
- **注入 Matplotlib 垫片**: 如果代码中包含 `matplotlib`,则在用户代码前拼接垫片代码,强制使用 `AGG` 后端。
- **执行代码并捕获输出**: 在代码执行后,检查 `matplotlib.pyplot` 的所有 figure如果存在图像则将其保存到内存中的 `BytesIO` 对象,并编码为 Base64 字符串。
- **结构化返回**: 将捕获的文本输出和 Base64 图像数据封装在一个 JSON 对象中 (`{ "text": "...", "image": "data:image/png;base64,..." }`) 返回给主线程。
4. **服务层 ([PyodideService][pyodide-service-link])**:
- 接收来自 Worker 的结构化数据。
- 将数据原样传递给 UI 层。
5. **UI 层 ([CodeBlockView][codeblock-view-link])**:
- 接收包含文本和图像数据的对象。
- 使用一个 `useState` 来管理执行结果 (`executionResult`)。
- 在界面上分别渲染文本输出和图像(如果存在)。
<!-- Link Definitions -->
[pyodide-link]: https://pyodide.org/
[codeblock-view-link]: /src/renderer/src/components/CodeBlockView/view.tsx
[pyodide-service-link]: /src/renderer/src/services/PyodideService.ts
[pyodide-worker-link]: /src/renderer/src/workers/pyodide.worker.ts
[statusbar-link]: /src/renderer/src/components/CodeBlockView/StatusBar.tsx

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# 数据库设置字段
此文档包含部分字段的数据类型说明。
## 字段
| 字段名 | 类型 | 说明 |
| ------------------------------ | ------------------------------ | ------------ |
| `translate:target:language` | `LanguageCode` | 翻译目标语言 |
| `translate:source:language` | `LanguageCode` | 翻译源语言 |
| `translate:bidirectional:pair` | `[LanguageCode, LanguageCode]` | 双向翻译对 |

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# `translate_languages` 表技术文档
## 📄 概述
`translate_languages` 记录用户自定义的的语言类型(`Language`)。
### 字段说明
| 字段名 | 类型 | 是否主键 | 索引 | 说明 |
| ---------- | ------ | -------- | ---- | ------------------------------------------------------------------------ |
| `id` | string | ✅ 是 | ✅ | 唯一标识符,主键 |
| `langCode` | string | ❌ 否 | ✅ | 语言代码(如:`zh-cn`, `en-us`, `ja-jp` 等,均为小写),支持普通索引查询 |
| `value` | string | ❌ 否 | ❌ | 语言的名称,用户输入 |
| `emoji` | string | ❌ 否 | ❌ | 语言的emoji用户输入 |
> `langCode` 虽非主键,但在业务层应当避免重复插入相同语言代码。

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# How to Do i18n Gracefully
> [!WARNING]
> This document is machine translated from Chinese. While we strive for accuracy, there may be some imperfections in the translation.
## Enhance Development Experience with the i18n Ally Plugin
i18n Ally is a powerful VSCode extension that provides real-time feedback during development, helping developers detect missing or incorrect translations earlier.
The plugin has already been configured in the project — simply install it to get started.
### Advantages During Development
- **Real-time Preview**: Translated texts are displayed directly in the editor.
- **Error Detection**: Automatically tracks and highlights missing translations or unused keys.
- **Quick Navigation**: Jump to key definitions with Ctrl/Cmd + click.
- **Auto-completion**: Provides suggestions when typing i18n keys.
### Demo
![demo-1](./.assets.how-to-i18n/demo-1.png)
![demo-2](./.assets.how-to-i18n/demo-2.png)
![demo-3](./.assets.how-to-i18n/demo-3.png)
## i18n Conventions
### **Avoid Flat Structure at All Costs**
Never use flat structures like `"add.button.tip": "Add"`. Instead, adopt a clear nested structure:
```json
// Wrong - Flat structure
{
"add.button.tip": "Add",
"delete.button.tip": "Delete"
}
// Correct - Nested structure
{
"add": {
"button": {
"tip": "Add"
}
},
"delete": {
"button": {
"tip": "Delete"
}
}
}
```
#### Why Use Nested Structure?
1. **Natural Grouping**: Related texts are logically grouped by their context through object nesting.
2. **Plugin Requirement**: Tools like i18n Ally require either flat or nested format to properly analyze translation files.
### **Avoid Template Strings in `t()`**
**We strongly advise against using template strings for dynamic interpolation.** While convenient in general JavaScript development, they cause several issues in i18n scenarios.
#### 1. **Plugin Cannot Track Dynamic Keys**
Tools like i18n Ally cannot parse dynamic content within template strings, resulting in:
- No real-time preview
- No detection of missing translations
- No navigation to key definitions
```javascript
// Not recommended - Plugin cannot resolve
const message = t(`fruits.${fruit}`)
```
#### 2. **No Real-time Rendering in Editor**
Template strings appear as raw code instead of the final translated text in IDEs, degrading the development experience.
#### 3. **Harder to Maintain**
Since the plugin cannot track such usages, developers must manually verify the existence of corresponding keys in language files.
### Recommended Approach
To avoid missing keys, all dynamically translated texts should first maintain a `FooKeyMap`, then retrieve the translation text through a function.
For example:
```ts
// src/renderer/src/i18n/label.ts
const themeModeKeyMap = {
dark: 'settings.theme.dark',
light: 'settings.theme.light',
system: 'settings.theme.system'
} as const
export const getThemeModeLabel = (key: string): string => {
return themeModeKeyMap[key] ? t(themeModeKeyMap[key]) : key
}
```
By avoiding template strings, you gain better developer experience, more reliable translation checks, and a more maintainable codebase.
## Automation Scripts
The project includes several scripts to automate i18n-related tasks:
### `check:i18n` - Validate i18n Structure
This script checks:
- Whether all language files use nested structure
- For missing or unused keys
- Whether keys are properly sorted
```bash
yarn check:i18n
```
### `sync:i18n` - Synchronize JSON Structure and Sort Order
This script uses `zh-cn.json` as the source of truth to sync structure across all language files, including:
1. Adding missing keys, with placeholder `[to be translated]`
2. Removing obsolete keys
3. Sorting keys automatically
```bash
yarn sync:i18n
```
### `auto:i18n` - Automatically Translate Pending Texts
This script fills in texts marked as `[to be translated]` using machine translation.
Typically, after adding new texts in `zh-cn.json`, run `sync:i18n`, then `auto:i18n` to complete translations.
Before using this script, set the required environment variables:
```bash
API_KEY="sk-xxx"
BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1/"
MODEL="qwen-plus-latest"
```
Alternatively, add these variables directly to your `.env` file.
```bash
yarn auto:i18n
```
### `update:i18n` - Object-level Translation Update
Updates translations in language files under `src/renderer/src/i18n/translate` at the object level, preserving existing translations and only updating new content.
**Not recommended** — prefer `auto:i18n` for translation tasks.
```bash
yarn update:i18n
```
### Workflow
1. During development, first add the required text in `zh-cn.json`
2. Confirm it displays correctly in the Chinese environment
3. Run `yarn sync:i18n` to propagate the keys to other language files
4. Run `yarn auto:i18n` to perform machine translation
5. Grab a coffee and let the magic happen!
## Best Practices
1. **Use Chinese as Source Language**: All development starts in Chinese, then translates to other languages.
2. **Run Check Script Before Commit**: Use `yarn check:i18n` to catch i18n issues early.
3. **Translate in Small Increments**: Avoid accumulating a large backlog of untranslated content.
4. **Keep Keys Semantically Clear**: Keys should clearly express their purpose, e.g., `user.profile.avatar.upload.error`

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@@ -1,171 +0,0 @@
# 如何优雅地做好 i18n
## 使用i18n ally插件提升开发体验
i18n ally是一个强大的VSCode插件它能在开发阶段提供实时反馈帮助开发者更早发现文案缺失和错译问题。
项目中已经配置好了插件设置,直接安装即可。
### 开发时优势
- **实时预览**:翻译文案会直接显示在编辑器中
- **错误检测**自动追踪标记出缺失的翻译或未使用的key
- **快速跳转**可通过key直接跳转到定义处Ctrl/Cmd + click)
- **自动补全**输入i18n key时提供自动补全建议
### 效果展示
![demo-1](./.assets.how-to-i18n/demo-1.png)
![demo-2](./.assets.how-to-i18n/demo-2.png)
![demo-3](./.assets.how-to-i18n/demo-3.png)
## i18n 约定
### **绝对避免使用flat格式**
绝对避免使用flat格式`"add.button.tip": "添加"`。应采用清晰的嵌套结构:
```json
// 错误示例 - flat结构
{
"add.button.tip": "添加",
"delete.button.tip": "删除"
}
// 正确示例 - 嵌套结构
{
"add": {
"button": {
"tip": "添加"
}
},
"delete": {
"button": {
"tip": "删除"
}
}
}
```
#### 为什么要使用嵌套结构
1. **自然分组**:通过对象结构天然能将相关上下文的文案分到一个组别中
2. **插件要求**i18n ally 插件需要嵌套或flat格式其一的文件才能正常分析
### **避免在`t()`中使用模板字符串**
**强烈建议避免使用模板字符串**进行动态插值。虽然模板字符串在JavaScript开发中非常方便但在国际化场景下会带来一系列问题。
1. **插件无法跟踪**
i18n ally等工具无法解析模板字符串中的动态内容导致
- 无法正确显示实时预览
- 无法检测翻译缺失
- 无法提供跳转到定义的功能
```javascript
// 不推荐 - 插件无法解析
const message = t(`fruits.${fruit}`)
```
2. **编辑器无法实时渲染**
在IDE中模板字符串会显示为原始代码而非最终翻译结果降低了开发体验。
3. **更难以维护**
由于插件无法跟踪这样的文案,编辑器中也无法渲染,开发者必须人工确认语言文件中是否存在相应的文案。
### 推荐做法
为了避免键的缺失,所有需要动态翻译的文本都应当先维护一个`FooKeyMap`,再通过函数获取翻译文本。
例如:
```ts
// src/renderer/src/i18n/label.ts
const themeModeKeyMap = {
dark: 'settings.theme.dark',
light: 'settings.theme.light',
system: 'settings.theme.system'
} as const
export const getThemeModeLabel = (key: string): string => {
return themeModeKeyMap[key] ? t(themeModeKeyMap[key]) : key
}
```
通过避免模板字符串,可以获得更好的开发体验、更可靠的翻译检查以及更易维护的代码库。
## 自动化脚本
项目中有一系列脚本来自动化i18n相关任务
### `check:i18n` - 检查i18n结构
此脚本会检查:
- 所有语言文件是否为嵌套结构
- 是否存在缺失的key
- 是否存在多余的key
- 是否已经有序
```bash
yarn check:i18n
```
### `sync:i18n` - 同步json结构与排序
此脚本以`zh-cn.json`文件为基准,将结构同步到其他语言文件,包括:
1. 添加缺失的键。缺少的翻译内容会以`[to be translated]`标记
2. 删除多余的键
3. 自动排序
```bash
yarn sync:i18n
```
### `auto:i18n` - 自动翻译待翻译文本
次脚本自动将标记为待翻译的文本通过机器翻译填充。
通常,在`zh-cn.json`中添加所需文案后,执行`sync:i18n`即可自动完成翻译。
使用该脚本前,需要配置环境变量,例如:
```bash
API_KEY="sk-xxx"
BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1/"
MODEL="qwen-plus-latest"
```
你也可以通过直接编辑`.env`文件来添加环境变量。
```bash
yarn auto:i18n
```
### `update:i18n` - 对象级别翻译更新
对`src/renderer/src/i18n/translate`中的语言文件进行对象级别的翻译更新,保留已有翻译,只更新新增内容。
**不建议**使用该脚本,更推荐使用`auto:i18n`进行翻译。
```bash
yarn update:i18n
```
### 工作流
1. 开发阶段,先在`zh-cn.json`中添加所需文案
2. 确认在中文环境下显示无误后,使用`yarn sync:i18n`将文案同步到其他语言文件
3. 使用`yarn auto:i18n`进行自动翻译
4. 喝杯咖啡,等翻译完成吧!
## 最佳实践
1. **以中文为源语言**:所有开发首先使用中文,再翻译为其他语言
2. **提交前运行检查脚本**:使用`yarn check:i18n`检查i18n是否有问题
3. **小步提交翻译**:避免积累大量未翻译文本
4. **保持key语义明确**key应能清晰表达其用途如`user.profile.avatar.upload.error`

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@@ -1,191 +0,0 @@
# How to use the LoggerService
This is a developer document on how to use the logger.
CherryStudio uses a unified logging service to print and record logs. **Unless there is a special reason, do not use `console.xxx` to print logs**.
The following are detailed instructions.
## Usage in the `main` process
### Importing
```typescript
import { loggerService } from '@logger'
```
### Setting module information (Required by convention)
After the import statements, set it up as follows:
```typescript
const logger = loggerService.withContext('moduleName')
```
- `moduleName` is the name of the current file's module. It can be named after the filename, main class name, main function name, etc. The principle is to be clear and understandable.
- `moduleName` will be printed in the terminal and will also be present in the file log, making it easier to filter.
### Setting `CONTEXT` information (Optional)
In `withContext`, you can also set other `CONTEXT` information:
```typescript
const logger = loggerService.withContext('moduleName', CONTEXT)
```
- `CONTEXT` is an object of the form `{ key: value, ... }`.
- `CONTEXT` information will not be printed in the terminal, but it will be recorded in the file log, making it easier to filter.
### Logging
In your code, you can call `logger` at any time to record logs. The supported levels are: `error`, `warn`, `info`, `verbose`, `debug`, and `silly`.
For the meaning of each level, please refer to the subsequent sections.
The following are the supported parameters for logging (using `logger.LEVEL` as an example, where `LEVEL` represents one of the levels mentioned above):
```typescript
logger.LEVEL(message)
logger.LEVEL(message, CONTEXT)
logger.LEVEL(message, error)
logger.LEVEL(message, error, CONTEXT)
```
**Only the four calling methods above are supported**.
| Parameter | Type | Description |
| --------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `message` | `string` | Required. This is the core field of the log, containing the main content to be recorded. |
| `CONTEXT` | `object` | Optional. Additional information to be recorded in the log file. It is recommended to use the `{ key: value, ...}` format. |
| `error` | `Error` | Optional. The error stack trace will also be printed.<br />Note that the `error` caught by `catch(error)` is of the `unknown` type. According to TypeScript best practices, you should first use `instanceof` for type checking. If you are certain it is an `Error` type, you can also use a type assertion like `as Error`. |
#### Recording non-`object` type context information
```typescript
const foo = getFoo()
logger.debug(`foo ${foo}`)
```
### Log Levels
- In the development environment, all log levels are printed to the terminal and recorded in the file log.
- In the production environment, the default log level is `info`. Logs are only recorded to the file and are not printed to the terminal.
Changing the log level:
- You can change the log level with `logger.setLevel('newLevel')`.
- `logger.resetLevel()` resets it to the default level.
- `logger.getLevel()` gets the current log level.
**Note:** Changing the log level has a global effect. Please do not change it arbitrarily in your code unless you are very clear about what you are doing.
## Usage in the `renderer` process
Usage in the `renderer` process for _importing_, _setting module information_, and _setting context information_ is **exactly the same** as in the `main` process.
The following section focuses on the differences.
### `initWindowSource`
In the `renderer` process, there are different `window`s. Before starting to use the `logger`, we must set the `window` information:
```typescript
loggerService.initWindowSource('windowName')
```
As a rule, we will set this in the `window`'s `entryPoint.tsx`. This ensures that `windowName` is set before it's used.
- An error will be thrown if `windowName` is not set, and the `logger` will not work.
- `windowName` can only be set once; subsequent attempts to set it will have no effect.
- `windowName` will not be printed in the `devTool`'s `console`, but it will be recorded in the `main` process terminal and the file log.
- `initWindowSource` returns the LoggerService instance, allowing for method chaining.
### Log Levels
- In the development environment, all log levels are printed to the `devTool`'s `console` by default.
- In the production environment, the default log level is `info`, and logs are printed to the `devTool`'s `console`.
- In both development and production environments, `warn` and `error` level logs are, by default, transmitted to the `main` process and recorded in the file log.
- In the development environment, the `main` process terminal will also print the logs transmitted from the renderer.
#### Changing the Log Level
Same as in the `main` process, you can manage the log level using `setLevel('level')`, `resetLevel()`, and `getLevel()`.
Similarly, changing the log level is a global adjustment.
#### Changing the Level Transmitted to `main`
Logs from the `renderer` are sent to `main` to be managed and recorded to a file centrally (according to `main`'s file logging level). By default, only `warn` and `error` level logs are transmitted to `main`.
There are two ways to change the log level for transmission to `main`:
##### Global Change
The following methods can be used to set, reset, and get the log level for transmission to `main`, respectively.
```typescript
logger.setLogToMainLevel('newLevel')
logger.resetLogToMainLevel()
logger.getLogToMainLevel()
```
**Note:** This method has a global effect. Please do not change it arbitrarily in your code unless you are very clear about what you are doing.
##### Per-log Change
By adding `{ logToMain: true }` at the end of the log call, you can force a single log entry to be transmitted to `main` (bypassing the global log level restriction), for example:
```typescript
logger.info('message', { logToMain: true })
```
## About `worker` Threads
- Currently, logging is not supported for workers in the `main` process.
- Logging is supported for workers started in the `renderer` process, but currently these logs are not sent to `main` for recording.
### How to Use Logging in `renderer` Workers
Since worker threads are independent, using LoggerService in them is equivalent to using it in a new `renderer` window. Therefore, you must first call `initWindowSource`.
If the worker is relatively simple (just one file), you can also use method chaining directly:
```typescript
const logger = loggerService.initWindowSource('Worker').withContext('LetsWork')
```
## Filtering Logs with Environment Variables
In a development environment, you can define environment variables to filter displayed logs by level and module. This helps developers focus on their specific logs and improves development efficiency.
Environment variables can be set in the terminal or defined in the `.env` file in the project's root directory. The available variables are as follows:
| Variable Name | Description |
| -------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `CSLOGGER_MAIN_LEVEL` | Log level for the `main` process. Logs below this level will not be displayed. |
| `CSLOGGER_MAIN_SHOW_MODULES` | Filters log modules for the `main` process. Use a comma (`,`) to separate modules. The filter is case-sensitive. Only logs from modules in this list will be displayed. |
| `CSLOGGER_RENDERER_LEVEL` | Log level for the `renderer` process. Logs below this level will not be displayed. |
| `CSLOGGER_RENDERER_SHOW_MODULES` | Filters log modules for the `renderer` process. Use a comma (`,`) to separate modules. The filter is case-sensitive. Only logs from modules in this list will be displayed. |
Example:
```bash
CSLOGGER_MAIN_LEVEL=verbose
CSLOGGER_MAIN_SHOW_MODULES=MCPService,SelectionService
```
Note:
- Environment variables are only effective in the development environment.
- These variables only affect the logs displayed in the terminal or DevTools. They do not affect file logging or the `logToMain` recording logic.
## Log Level Usage Guidelines
There are many log levels. The following are the guidelines that should be followed in CherryStudio for when to use each level:
(Arranged from highest to lowest log level)
| Log Level | Core Definition & Use case | Example |
| :------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **`error`** | **Critical error causing the program to crash or core functionality to become unusable.** <br> This is the highest-priority log, usually requiring immediate reporting or user notification. | - Main or renderer process crash. <br> - Failure to read/write critical user data files (e.g., database, configuration files), preventing the application from running. <br> - All unhandled exceptions. |
| **`warn`** | **Potential issue or unexpected situation that does not affect the program's core functionality.** <br> The program can recover or use a fallback. | - Configuration file `settings.json` is missing; started with default settings. <br> - Auto-update check failed, but does not affect the use of the current version. <br> - A non-essential plugin failed to load. |
| **`info`** | **Records application lifecycle events and key user actions.** <br> This is the default level that should be recorded in a production release to trace the user's main operational path. | - Application start, exit. <br> - User successfully opens/saves a file. <br> - Main window created/closed. <br> - Starting an important task (e.g., "Start video export"). |
| **`verbose`** | **More detailed flow information than `info`, used for tracing specific features.** <br> Enabled when diagnosing issues with a specific feature to help understand the internal execution flow. | - Loading `Toolbar` module. <br> - IPC message `open-file-dialog` sent from the renderer process. <br> - Applying filter 'Sepia' to the image. |
| **`debug`** | **Detailed diagnostic information used during development and debugging.** <br> **Must not be enabled by default in production releases**, as it may contain sensitive data and impact performance. | - Parameters for function `renderImage`: `{ width: 800, ... }`. <br> - Specific data content received by IPC message `save-file`. <br> - Details of Redux/Vuex state changes in the renderer process. |
| **`silly`** | **The most detailed, low-level information, used only for extreme debugging.** <br> Rarely used in regular development; only for solving very difficult problems. | - Real-time mouse coordinates `(x: 150, y: 320)`. <br> - Size of each data chunk when reading a file. <br> - Time taken for each rendered frame. |

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@@ -1,194 +0,0 @@
# 如何使用日志 LoggerService
这是关于如何使用日志的开发者文档。
CherryStudio使用统一的日志服务来打印和记录日志**若无特殊原因,请勿使用`console.xxx`来打印日志**。
以下是详细说明。
## 在`main`进程中使用
### 引入
```typescript
import { loggerService } from '@logger'
```
### 设置module信息规范要求
在import头之后设置
```typescript
const logger = loggerService.withContext('moduleName')
```
- `moduleName`是当前文件模块的名称,命名可以以文件名、主类名、主函数名等,原则是清晰明了
- `moduleName`会在终端中打印出来,也会在文件日志中体现,方便筛选
### 设置`CONTEXT`信息(可选)
`withContext`中,也可以设置其他`CONTEXT`信息:
```typescript
const logger = loggerService.withContext('moduleName', CONTEXT)
```
- `CONTEXT``{ key: value, ... }`
- `CONTEXT`信息不会在终端中打印出来,但是会在文件日志中记录,方便筛选
### 记录日志
在代码中,可以随时调用 `logger` 来记录日志,支持的级别有:`error`, `warn`, `info`, `verbose`, `debug`, `silly`
各级别的含义,请参考后面的章节。
以下支持的记录日志的参数(以 `logger.LEVEL` 举例如何使用,`LEVEL`指代为上述级别):
```typescript
logger.LEVEL(message)
logger.LEVEL(message, CONTEXT)
logger.LEVEL(message, error)
logger.LEVEL(message, error, CONTEXT)
```
**只支持上述四种调用方式**
| 参数 | 类型 | 说明 |
| --------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `message` | `string` | 必填项。这是日志的核心字段,记录的重点内容 |
| `CONTEXT` | `object` | 可选。其他需要再日志文件中记录的信息,建议为`{ key: value, ...}`格式 |
| `error` | `Error` | 可选。同时会打印错误堆栈信息。<br />注意`catch(error)`所捕获的`error``unknown`类型,按照`Typescript`最佳实践,请先用`instanceof`进行类型判断,如果确信一定是`Error`类型,也可用断言`as Error`。 |
#### 记录非`object`类型的上下文信息
```typescript
const foo = getFoo()
logger.debug(`foo ${foo}`)
```
### 记录级别
- 开发环境下,所有级别的日志都会打印到终端,并且记录到文件日志中
- 生产环境下,默认记录级别为`info`,日志只会记录到文件,不会打印到终端
更改日志记录级别:
- 可以通过 `logger.setLevel('newLevel')` 来更改日志记录级别
- `logger.resetLevel()` 可以重置为默认级别
- `logger.getLevel()` 可以获取当前记录记录级别
**注意** 更改日志记录级别是全局生效的,请不要在代码中随意更改,除非你非常清楚自己在做什么
## 在`renderer`进程中使用
`renderer`进程中使用_引入方法_、_设置`module`信息_、*设置`context`信息的方法*和`main`进程中是**完全一样**的。
下面着重讲一下不同之处。
### `initWindowSource`
`renderer`进程中,有不同的`window`,在开始使用`logger`之前,我们必须设置`window`信息:
```typescript
loggerService.initWindowSource('windowName')
```
原则上,我们将在`window``entryPoint.tsx`中进行设置,这可以保证`windowName`在开始使用前已经设置好了。
- 未设置`windowName`会报错,`logger`将不起作用
- `windowName`只能设置一次,重复设置将不生效
- `windowName`不会在`devTool``console`中打印出来,但是会在`main`进程的终端和文件日志中记录
- `initWindowSource`返回的是LoggerService的实例因此可以做链式调用
### 记录级别
- 开发环境下,默认所有级别的日志都会打印到`devTool``console`
- 生产环境下,默认记录级别为`info`,日志会打印到`devTool``console`
- 在开发和生产环境下,默认`warn``error`级别的日志,会传输给`main`进程,并记录到文件日志
- 开发环境下,`main`进程终端中也会打印传输过来的日志
#### 更改日志记录级别
`main`进程中一样,你可以通过`setLevel('level')``resetLevel()``getLevel()`来管理日志记录级别。
同样,该日志记录级别也是全局调整的。
#### 更改传输到`main`的级别
`renderer`的日志发送到`main`,并由`main`统一管理和记录到文件(根据`main`的记录到文件的级别),默认只有`warn``error`级别的日志会传输到`main`
有以下两种方式,可以更改传输到`main`的日志级别:
##### 全局更改
以下方法可以分别设置、重置和获取传输到`main`的日志级别
```typescript
logger.setLogToMainLevel('newLevel')
logger.resetLogToMainLevel()
logger.getLogToMainLevel()
```
**注意** 该方法是全局生效的,请不要在代码中随意更改,除非你非常清楚自己在做什么
##### 单条更改
在日志记录的最末尾,加上`{ logToMain: true }`,即可将本条日志传输到`main`(不受全局日志级别限制),例如:
```typescript
logger.info('message', { logToMain: true })
```
## 关于`worker`线程
- 现在不支持`main`进程中的`worker`的日志。
- 支持`renderer`中起的`worker`的日志,但是现在该日志不会发送给`main`进行记录。
### 如何在`renderer`的`worker`中使用日志
由于`worker`线程是独立的在其中使用LoggerService等同于在一个新`renderer`窗口中使用。因此也必须先`initWindowSource`
如果`worker`比较简单,只有一个文件,也可以使用链式语法直接使用:
```typescript
const logger = loggerService.initWindowSource('Worker').withContext('LetsWork')
```
## 使用环境变量来筛选要显示的日志
在开发环境中可以通过环境变量的定义来筛选要显示的日志的级别和module。开发者可以专注于自己的日志提高开发效率。
环境变量可以在终端中自行设置,或者在开发根目录的`.env`文件中进行定义,可以定义的变量如下:
| 变量名 | 含义 |
| -------------------------------- | ----------------------------------------------------------------------------------------------- |
| `CSLOGGER_MAIN_LEVEL` | 用于`main`进程的日志级别,低于该级别的日志将不显示 |
| `CSLOGGER_MAIN_SHOW_MODULES` | 用于`main`进程的日志module筛选`,`分隔区分大小写。只有在该列表中的module的日志才会显示 |
| `CSLOGGER_RENDERER_LEVEL` | 用于`renderer`进程的日志级别,低于该级别的日志将不显示 |
| `CSLOGGER_RENDERER_SHOW_MODULES` | 用于`renderer`进程的日志module筛选`,`分隔区分大小写。只有在该列表中的module的日志才会显示 |
示例:
```bash
CSLOGGER_MAIN_LEVEL=verbose
CSLOGGER_MAIN_SHOW_MODULES=MCPService,SelectionService
```
注意:
- 环境变量仅在开发环境中生效
- 该变量仅会改变在终端或在devTools中显示的日志不会影响文件日志和`logToMain`的记录逻辑
## 日志级别的使用规范
日志有很多级别什么时候应该用哪个级别下面是在CherryStudio中应该遵循的规范
(按日志级别从高到低排列)
| 日志级别 | 核心定义与使用场景 | 示例 |
| :------------ | :------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------- |
| **`error`** | **严重错误,导致程序崩溃或核心功能无法使用。** <br> 这是最高优的日志,通常需要立即上报或提示用户。 | - 主进程或渲染进程崩溃。 <br> - 无法读写用户关键数据文件(如数据库、配置文件),导致应用无法运行。<br> - 所有未捕获的异常。 |
| **`warn`** | **潜在问题或非预期情况,但不影响程序核心功能。** <br> 程序可以从中恢复或使用备用方案。 | - 配置文件 `settings.json` 缺失,已使用默认配置启动。 <br> - 自动更新检查失败,但不影响当前版本使用。<br> - 某个非核心插件加载失败。 |
| **`info`** | **记录应用生命周期和关键用户行为。** <br> 这是发布版中默认应记录的级别,用于追踪用户的主要操作路径。 | - 应用启动、退出。<br> - 用户成功打开/保存文件。 <br> - 主窗口创建/关闭。<br> - 开始执行一项重要任务(如“开始导出视频”)。 |
| **`verbose`** | **比 `info` 更详细的流程信息,用于追踪特定功能。** <br> 在诊断特定功能问题时开启,帮助理解内部执行流程。 | - 正在加载 `Toolbar` 模块。 <br> - IPC 消息 `open-file-dialog` 已从渲染进程发送。<br> - 正在应用滤镜 'Sepia' 到图像。 |
| **`debug`** | **开发和调试时使用的详细诊断信息。** <br> **严禁在发布版中默认开启**,因为它可能包含敏感数据并影响性能。 | - 函数 `renderImage` 的入参: `{ width: 800, ... }`。<br> - IPC 消息 `save-file` 收到的具体数据内容。<br> - 渲染进程中 Redux/Vuex 的 state 变更详情。 |
| **`silly`** | **最详尽的底层信息,仅用于极限调试。** <br> 几乎不在常规开发中使用,仅为解决棘手问题。 | - 鼠标移动的实时坐标 `(x: 150, y: 320)`。<br> - 读取文件时每个数据块chunk的大小。<br> - 每一次渲染帧的耗时。 |

View File

@@ -80,13 +80,15 @@ import { ChunkType } from '@renderer/types' // 调整路径
export const createSimpleLoggingMiddleware = (): CompletionsMiddleware => {
return (api: MiddlewareAPI<AiProviderMiddlewareCompletionsContext, [CompletionsParams]>) => {
// console.log(`[LoggingMiddleware] Initialized for provider: ${api.getProviderId()}`);
return (next: (context: AiProviderMiddlewareCompletionsContext, params: CompletionsParams) => Promise<any>) => {
return async (context: AiProviderMiddlewareCompletionsContext, params: CompletionsParams): Promise<void> => {
const startTime = Date.now()
// 从 context 中获取 onChunk (它最初来自 params.onChunk)
const onChunk = context.onChunk
logger.debug(
console.log(
`[LoggingMiddleware] Request for ${context.methodName} with params:`,
params.messages?.[params.messages.length - 1]?.content
)
@@ -102,14 +104,14 @@ export const createSimpleLoggingMiddleware = (): CompletionsMiddleware => {
// 如果在之前,那么它需要自己处理 rawSdkResponse 或确保下游会处理。
const duration = Date.now() - startTime
logger.debug(`[LoggingMiddleware] Request for ${context.methodName} completed in ${duration}ms.`)
console.log(`[LoggingMiddleware] Request for ${context.methodName} completed in ${duration}ms.`)
// 假设下游已经通过 onChunk 发送了所有数据。
// 如果这个中间件是链的末端,并且需要确保 BLOCK_COMPLETE 被发送,
// 它可能需要更复杂的逻辑来跟踪何时所有数据都已发送。
} catch (error) {
const duration = Date.now() - startTime
logger.error(`[LoggingMiddleware] Request for ${context.methodName} failed after ${duration}ms:`, error)
console.error(`[LoggingMiddleware] Request for ${context.methodName} failed after ${duration}ms:`, error)
// 如果 onChunk 可用,可以尝试发送一个错误块
if (onChunk) {
@@ -205,7 +207,7 @@ export default middlewareConfig
### 调试技巧
- 在中间件的关键点使用 `logger.debug` 或调试器来检查 `params``context` 的状态以及 `next` 的返回值。
- 在中间件的关键点使用 `console.log` 或调试器来检查 `params``context` 的状态以及 `next` 的返回值。
- 暂时简化中间件链,只保留你正在调试的中间件和最简单的核心逻辑,以隔离问题。
- 编写单元测试来独立验证每个中间件的行为。

View File

@@ -53,6 +53,8 @@ files:
- '!node_modules/pdf-parse/lib/pdf.js/{v1.9.426,v1.10.88,v2.0.550}'
- '!node_modules/mammoth/{mammoth.browser.js,mammoth.browser.min.js}'
- '!node_modules/selection-hook/prebuilds/**/*' # we rebuild .node, don't use prebuilds
- '!node_modules/pdfjs-dist/web/**/*'
- '!node_modules/pdfjs-dist/legacy/web/*'
- '!node_modules/selection-hook/node_modules' # we don't need what in the node_modules dir
- '!node_modules/selection-hook/src' # we don't need source files
- '!**/*.{h,iobj,ipdb,tlog,recipe,vcxproj,vcxproj.filters,Makefile,*.Makefile}' # filter .node build files
@@ -98,7 +100,6 @@ linux:
target:
- target: AppImage
- target: deb
- target: rpm
maintainer: electronjs.org
category: Utility
desktop:
@@ -116,11 +117,9 @@ afterSign: scripts/notarize.js
artifactBuildCompleted: scripts/artifact-build-completed.js
releaseInfo:
releaseNotes: |
输入框快捷菜单增加清除按钮
侧边栏增加代码工具入口,代码工具增加环境变量设置
小程序增加多语言显示
优化 MCP 服务器列表
新增 Web 搜索图标
优化 SVG 预览,优化 HTML 内容样式
修复知识库文档预处理失败问题
稳定性改进和错误修复
划词助手:支持 macOS 系统
文档处理:增加 MinerU、Doc2xMistral 等服务商支持
知识库:新的知识库界面,增加扫描版 PDF 支持
OCRmacOS 增加系统 OCR 支持
服务商:支持一键添加服务商,新增 PH8 大模型开放平台, 支持 PPIO OAuth 登录
修复Linux下数据目录移动问题

View File

@@ -8,9 +8,6 @@ const visualizerPlugin = (type: 'renderer' | 'main') => {
return process.env[`VISUALIZER_${type.toUpperCase()}`] ? [visualizer({ open: true })] : []
}
const isDev = process.env.NODE_ENV === 'development'
const isProd = process.env.NODE_ENV === 'production'
export default defineConfig({
main: {
plugins: [externalizeDepsPlugin(), ...visualizerPlugin('main')],
@@ -18,48 +15,39 @@ export default defineConfig({
alias: {
'@main': resolve('src/main'),
'@types': resolve('src/renderer/src/types'),
'@shared': resolve('packages/shared'),
'@logger': resolve('src/main/services/LoggerService'),
'@mcp-trace/trace-core': resolve('packages/mcp-trace/trace-core'),
'@mcp-trace/trace-node': resolve('packages/mcp-trace/trace-node')
'@shared': resolve('packages/shared')
}
},
build: {
rollupOptions: {
external: ['@libsql/client', 'bufferutil', 'utf-8-validate'],
external: ['@libsql/client', 'bufferutil', 'utf-8-validate', '@cherrystudio/mac-system-ocr'],
output: {
manualChunks: undefined, // 彻底禁用代码分割 - 返回 null 强制单文件打包
inlineDynamicImports: true // 内联所有动态导入,这是关键配置
// 彻底禁用代码分割 - 返回 null 强制单文件打包
manualChunks: undefined,
// 内联所有动态导入,这是关键配置
inlineDynamicImports: true
}
},
sourcemap: isDev
sourcemap: process.env.NODE_ENV === 'development'
},
esbuild: isProd ? { legalComments: 'none' } : {},
optimizeDeps: {
noDiscovery: isDev
noDiscovery: process.env.NODE_ENV === 'development'
}
},
preload: {
plugins: [
react({
tsDecorators: true
}),
externalizeDepsPlugin()
],
plugins: [externalizeDepsPlugin()],
resolve: {
alias: {
'@shared': resolve('packages/shared'),
'@mcp-trace/trace-core': resolve('packages/mcp-trace/trace-core')
'@shared': resolve('packages/shared')
}
},
build: {
sourcemap: isDev
sourcemap: process.env.NODE_ENV === 'development'
}
},
renderer: {
plugins: [
react({
tsDecorators: true,
plugins: [
[
'@swc/plugin-styled-components',
@@ -72,16 +60,20 @@ export default defineConfig({
]
]
}),
...(isDev ? [CodeInspectorPlugin({ bundler: 'vite' })] : []), // 只在开发环境下启用 CodeInspectorPlugin
// 只在开发环境下启用 CodeInspectorPlugin
...(process.env.NODE_ENV === 'development'
? [
CodeInspectorPlugin({
bundler: 'vite'
})
]
: []),
...visualizerPlugin('renderer')
],
resolve: {
alias: {
'@renderer': resolve('src/renderer/src'),
'@shared': resolve('packages/shared'),
'@logger': resolve('src/renderer/src/services/LoggerService'),
'@mcp-trace/trace-core': resolve('packages/mcp-trace/trace-core'),
'@mcp-trace/trace-web': resolve('packages/mcp-trace/trace-web')
'@shared': resolve('packages/shared')
}
},
optimizeDeps: {
@@ -100,11 +92,9 @@ export default defineConfig({
index: resolve(__dirname, 'src/renderer/index.html'),
miniWindow: resolve(__dirname, 'src/renderer/miniWindow.html'),
selectionToolbar: resolve(__dirname, 'src/renderer/selectionToolbar.html'),
selectionAction: resolve(__dirname, 'src/renderer/selectionAction.html'),
traceWindow: resolve(__dirname, 'src/renderer/traceWindow.html')
selectionAction: resolve(__dirname, 'src/renderer/selectionAction.html')
}
}
},
esbuild: isProd ? { legalComments: 'none' } : {}
}
}
})

View File

@@ -26,92 +26,32 @@ export default defineConfig([
'simple-import-sort/exports': 'error',
'unused-imports/no-unused-imports': 'error',
'@eslint-react/no-prop-types': 'error',
'prettier/prettier': ['error']
'prettier/prettier': ['error', { endOfLine: 'auto' }]
}
},
// Configuration for ensuring compatibility with the original ESLint(8.x) rules
{
rules: {
'@typescript-eslint/no-require-imports': 'off',
'@typescript-eslint/no-unused-vars': ['error', { caughtErrors: 'none' }],
'@typescript-eslint/no-unused-expressions': 'off',
'@typescript-eslint/no-empty-object-type': 'off',
'@eslint-react/hooks-extra/no-direct-set-state-in-use-effect': 'off',
'@eslint-react/web-api/no-leaked-event-listener': 'off',
'@eslint-react/web-api/no-leaked-timeout': 'off',
'@eslint-react/no-unknown-property': 'off',
'@eslint-react/no-nested-component-definitions': 'off',
'@eslint-react/dom/no-dangerously-set-innerhtml': 'off',
'@eslint-react/no-array-index-key': 'off',
'@eslint-react/no-unstable-default-props': 'off',
'@eslint-react/no-unstable-context-value': 'off',
'@eslint-react/hooks-extra/prefer-use-state-lazy-initialization': 'off',
'@eslint-react/hooks-extra/no-unnecessary-use-prefix': 'off',
'@eslint-react/no-children-to-array': 'off'
}
},
{
// LoggerService Custom Rules - only apply to src directory
files: ['src/**/*.{ts,tsx,js,jsx}'],
ignores: ['src/**/__tests__/**', 'src/**/__mocks__/**', 'src/**/*.test.*'],
rules: {
'no-restricted-syntax': [
process.env.PRCI ? 'error' : 'warn',
{
selector: 'CallExpression[callee.object.name="console"]',
message:
'❗CherryStudio uses unified LoggerService: 📖 docs/technical/how-to-use-logger-en.md\n❗CherryStudio 使用统一的日志服务:📖 docs/technical/how-to-use-logger-zh.md\n\n'
}
]
}
},
{
files: ['**/*.{ts,tsx,js,jsx}'],
languageOptions: {
ecmaVersion: 2022,
sourceType: 'module'
},
plugins: {
i18n: {
rules: {
'no-template-in-t': {
meta: {
type: 'problem',
docs: {
description: '⚠️不建议在 t() 函数中使用模板字符串,这样会导致渲染结果不可预料',
recommended: true
},
messages: {
noTemplateInT: '⚠️不建议在 t() 函数中使用模板字符串,这样会导致渲染结果不可预料'
}
},
create(context) {
return {
CallExpression(node) {
const { callee, arguments: args } = node
const isTFunction =
(callee.type === 'Identifier' && callee.name === 't') ||
(callee.type === 'MemberExpression' &&
callee.property.type === 'Identifier' &&
callee.property.name === 't')
if (isTFunction && args[0]?.type === 'TemplateLiteral') {
context.report({
node: args[0],
messageId: 'noTemplateInT'
})
}
}
}
}
}
}
...[
{
rules: {
'@typescript-eslint/no-require-imports': 'off',
'@typescript-eslint/no-unused-vars': ['error', { caughtErrors: 'none' }],
'@typescript-eslint/no-unused-expressions': 'off',
'@typescript-eslint/no-empty-object-type': 'off',
'@eslint-react/hooks-extra/no-direct-set-state-in-use-effect': 'off',
'@eslint-react/web-api/no-leaked-event-listener': 'off',
'@eslint-react/web-api/no-leaked-timeout': 'off',
'@eslint-react/no-unknown-property': 'off',
'@eslint-react/no-nested-component-definitions': 'off',
'@eslint-react/dom/no-dangerously-set-innerhtml': 'off',
'@eslint-react/no-array-index-key': 'off',
'@eslint-react/no-unstable-default-props': 'off',
'@eslint-react/no-unstable-context-value': 'off',
'@eslint-react/hooks-extra/prefer-use-state-lazy-initialization': 'off',
'@eslint-react/hooks-extra/no-unnecessary-use-prefix': 'off',
'@eslint-react/no-children-to-array': 'off'
}
},
rules: {
'i18n/no-template-in-t': 'warn'
}
},
],
{
ignores: [
'node_modules/**',

View File

@@ -1,14 +1,11 @@
{
"name": "CherryStudio",
"version": "1.5.7-rc.2",
"version": "1.4.8",
"private": true,
"description": "A powerful AI assistant for producer.",
"main": "./out/main/index.js",
"author": "support@cherry-ai.com",
"homepage": "https://github.com/CherryHQ/cherry-studio",
"engines": {
"node": ">=22.0.0"
},
"workspaces": {
"packages": [
"local",
@@ -16,45 +13,37 @@
],
"installConfig": {
"hoistingLimits": [
"packages/database",
"packages/mcp-trace/trace-core",
"packages/mcp-trace/trace-node",
"packages/mcp-trace/trace-web"
"packages/database"
]
}
},
"scripts": {
"start": "electron-vite preview",
"dev": "dotenv electron-vite dev",
"dev": "electron-vite dev",
"debug": "electron-vite -- --inspect --sourcemap --remote-debugging-port=9222",
"build": "npm run typecheck && electron-vite build",
"build:check": "yarn lint && yarn test",
"build:check": "yarn typecheck && yarn check:i18n && yarn test",
"build:unpack": "dotenv npm run build && electron-builder --dir",
"build:win": "dotenv npm run build && electron-builder --win --x64 --arm64",
"build:win:x64": "dotenv npm run build && electron-builder --win --x64",
"build:win:arm64": "dotenv npm run build && electron-builder --win --arm64",
"build:mac": "dotenv npm run build && electron-builder --mac --arm64 --x64",
"build:mac:arm64": "dotenv npm run build && electron-builder --mac --arm64",
"build:mac:x64": "dotenv npm run build && electron-builder --mac --x64",
"build:linux": "dotenv npm run build && electron-builder --linux --x64 --arm64",
"build:linux:arm64": "dotenv npm run build && electron-builder --linux --arm64",
"build:linux:x64": "dotenv npm run build && electron-builder --linux --x64",
"build:mac": "dotenv electron-vite build && electron-builder --mac --arm64 --x64",
"build:mac:arm64": "dotenv electron-vite build && electron-builder --mac --arm64",
"build:mac:x64": "dotenv electron-vite build && electron-builder --mac --x64",
"build:linux": "dotenv electron-vite build && electron-builder --linux --x64 --arm64",
"build:linux:arm64": "dotenv electron-vite build && electron-builder --linux --arm64",
"build:linux:x64": "dotenv electron-vite build && electron-builder --linux --x64",
"build:npm": "node scripts/build-npm.js",
"release": "node scripts/version.js",
"publish": "yarn build:check && yarn release patch push",
"pulish:artifacts": "cd packages/artifacts && npm publish && cd -",
"generate:agents": "yarn workspace @cherry-studio/database agents",
"generate:icons": "electron-icon-builder --input=./build/logo.png --output=build",
"analyze:renderer": "VISUALIZER_RENDERER=true yarn build",
"analyze:main": "VISUALIZER_MAIN=true yarn build",
"typecheck": "npm run typecheck:node && npm run typecheck:web",
"typecheck:node": "tsc --noEmit -p tsconfig.node.json --composite false",
"typecheck:web": "tsc --noEmit -p tsconfig.web.json --composite false",
"check:i18n": "tsx scripts/check-i18n.ts",
"sync:i18n": "tsx scripts/sync-i18n.ts",
"update:i18n": "dotenv -e .env -- tsx scripts/update-i18n.ts",
"auto:i18n": "dotenv -e .env -- tsx scripts/auto-translate-i18n.ts",
"update:languages": "tsx scripts/update-languages.ts",
"check:i18n": "node scripts/check-i18n.js",
"test": "vitest run --silent",
"test:main": "vitest run --project main",
"test:renderer": "vitest run --project renderer",
@@ -64,23 +53,22 @@
"test:watch": "vitest",
"test:e2e": "yarn playwright test",
"test:lint": "eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts",
"test:scripts": "vitest scripts",
"format": "prettier --write .",
"lint": "eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --fix && yarn typecheck && yarn check:i18n",
"prepare": "git config blame.ignoreRevsFile .git-blame-ignore-revs && husky"
"lint": "eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --fix",
"prepare": "husky"
},
"dependencies": {
"@cherrystudio/pdf-to-img-napi": "^0.0.1",
"@libsql/client": "0.14.0",
"@libsql/win32-x64-msvc": "^0.4.7",
"@strongtz/win32-arm64-msvc": "^0.4.7",
"graceful-fs": "^4.2.11",
"jsdom": "26.1.0",
"macos-release": "^3.4.0",
"node-stream-zip": "^1.15.0",
"officeparser": "^4.2.0",
"notion-helper": "^1.3.22",
"os-proxy-config": "^1.1.2",
"selection-hook": "^1.0.11",
"sharp": "^0.34.3",
"tesseract.js": "patch:tesseract.js@npm%3A6.0.1#~/.yarn/patches/tesseract.js-npm-6.0.1-2562a7e46d.patch",
"pdfjs-dist": "4.10.38",
"selection-hook": "^1.0.4",
"turndown": "7.2.0"
},
"devDependencies": {
@@ -89,10 +77,6 @@
"@agentic/tavily": "^7.3.3",
"@ant-design/v5-patch-for-react-19": "^1.0.3",
"@anthropic-ai/sdk": "^0.41.0",
"@anthropic-ai/vertex-sdk": "patch:@anthropic-ai/vertex-sdk@npm%3A0.11.4#~/.yarn/patches/@anthropic-ai-vertex-sdk-npm-0.11.4-c19cb41edb.patch",
"@aws-sdk/client-bedrock": "^3.840.0",
"@aws-sdk/client-bedrock-runtime": "^3.840.0",
"@aws-sdk/client-s3": "^3.840.0",
"@cherrystudio/embedjs": "^0.1.31",
"@cherrystudio/embedjs-libsql": "^0.1.31",
"@cherrystudio/embedjs-loader-csv": "^0.1.31",
@@ -105,10 +89,6 @@
"@cherrystudio/embedjs-loader-xml": "^0.1.31",
"@cherrystudio/embedjs-ollama": "^0.1.31",
"@cherrystudio/embedjs-openai": "^0.1.31",
"@dnd-kit/core": "^6.3.1",
"@dnd-kit/modifiers": "^9.0.0",
"@dnd-kit/sortable": "^10.0.0",
"@dnd-kit/utilities": "^3.2.2",
"@electron-toolkit/eslint-config-prettier": "^3.0.0",
"@electron-toolkit/eslint-config-ts": "^3.0.0",
"@electron-toolkit/preload": "^3.0.0",
@@ -123,59 +103,47 @@
"@kangfenmao/keyv-storage": "^0.1.0",
"@langchain/community": "^0.3.36",
"@langchain/ollama": "^0.2.1",
"@mistralai/mistralai": "^1.7.5",
"@modelcontextprotocol/sdk": "^1.17.0",
"@mistralai/mistralai": "^1.6.0",
"@modelcontextprotocol/sdk": "^1.11.4",
"@mozilla/readability": "^0.6.0",
"@notionhq/client": "^2.2.15",
"@opentelemetry/api": "^1.9.0",
"@opentelemetry/core": "2.0.0",
"@opentelemetry/exporter-trace-otlp-http": "^0.200.0",
"@opentelemetry/sdk-trace-base": "^2.0.0",
"@opentelemetry/sdk-trace-node": "^2.0.0",
"@opentelemetry/sdk-trace-web": "^2.0.0",
"@playwright/test": "^1.52.0",
"@reduxjs/toolkit": "^2.2.5",
"@shikijs/markdown-it": "^3.9.1",
"@shikijs/markdown-it": "^3.7.0",
"@swc/plugin-styled-components": "^7.1.5",
"@tanstack/react-query": "^5.27.0",
"@tanstack/react-virtual": "^3.13.12",
"@testing-library/dom": "^10.4.0",
"@testing-library/jest-dom": "^6.6.3",
"@testing-library/react": "^16.3.0",
"@testing-library/user-event": "^14.6.1",
"@tryfabric/martian": "^1.2.4",
"@types/cli-progress": "^3",
"@types/diff": "^7",
"@types/fs-extra": "^11",
"@types/lodash": "^4.17.5",
"@types/markdown-it": "^14",
"@types/md5": "^2.3.5",
"@types/node": "^22.17.1",
"@types/node": "^18.19.9",
"@types/pako": "^1.0.2",
"@types/react": "^19.0.12",
"@types/react-dom": "^19.0.4",
"@types/react-infinite-scroll-component": "^5.0.0",
"@types/react-transition-group": "^4.4.12",
"@types/react-window": "^1",
"@types/tinycolor2": "^1",
"@types/word-extractor": "^1",
"@uiw/codemirror-extensions-langs": "^4.25.1",
"@uiw/codemirror-themes-all": "^4.25.1",
"@uiw/react-codemirror": "^4.25.1",
"@uiw/codemirror-extensions-langs": "^4.23.14",
"@uiw/codemirror-themes-all": "^4.23.14",
"@uiw/react-codemirror": "^4.23.14",
"@vitejs/plugin-react-swc": "^3.9.0",
"@vitest/browser": "^3.2.4",
"@vitest/coverage-v8": "^3.2.4",
"@vitest/ui": "^3.2.4",
"@vitest/web-worker": "^3.2.4",
"@viz-js/lang-dot": "^1.0.5",
"@viz-js/viz": "^3.14.0",
"@vitest/browser": "^3.1.4",
"@vitest/coverage-v8": "^3.1.4",
"@vitest/ui": "^3.1.4",
"@vitest/web-worker": "^3.1.4",
"@xyflow/react": "^12.4.4",
"antd": "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch",
"antd": "patch:antd@npm%3A5.24.7#~/.yarn/patches/antd-npm-5.24.7-356a553ae5.patch",
"archiver": "^7.0.1",
"async-mutex": "^0.5.0",
"axios": "^1.7.3",
"browser-image-compression": "^2.0.2",
"chardet": "^2.1.0",
"cli-progress": "^3.12.0",
"code-inspector-plugin": "^0.20.14",
"color": "^5.0.0",
"country-flag-emoji-polyfill": "0.1.8",
@@ -185,12 +153,13 @@
"diff": "^7.0.0",
"docx": "^9.0.2",
"dotenv-cli": "^7.4.2",
"electron": "37.3.1",
"electron": "35.6.0",
"electron-builder": "26.0.15",
"electron-devtools-installer": "^3.2.0",
"electron-log": "^5.1.5",
"electron-store": "^8.2.0",
"electron-updater": "6.6.4",
"electron-vite": "4.0.0",
"electron-vite": "^3.1.0",
"electron-window-state": "^5.0.3",
"emittery": "^1.0.3",
"emoji-picker-element": "^1.22.1",
@@ -201,105 +170,79 @@
"eslint-plugin-unused-imports": "^4.1.4",
"fast-diff": "^1.3.0",
"fast-xml-parser": "^5.2.0",
"fetch-socks": "1.3.2",
"franc-min": "^6.2.0",
"fs-extra": "^11.2.0",
"google-auth-library": "^9.15.1",
"html-to-image": "^1.11.13",
"husky": "^9.1.7",
"i18next": "^23.11.5",
"iconv-lite": "^0.6.3",
"isbinaryfile": "5.0.4",
"jaison": "^2.0.2",
"jest-styled-components": "^7.2.0",
"linguist-languages": "^8.0.0",
"lint-staged": "^15.5.0",
"lodash": "^4.17.21",
"lru-cache": "^11.1.0",
"lucide-react": "^0.525.0",
"macos-release": "^3.4.0",
"lucide-react": "^0.487.0",
"markdown-it": "^14.1.0",
"mermaid": "^11.9.0",
"mermaid": "^11.7.0",
"mime": "^4.0.4",
"motion": "^12.10.5",
"notion-helper": "^1.3.22",
"npx-scope-finder": "^1.2.0",
"openai": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"officeparser": "^4.1.1",
"openai": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"p-queue": "^8.1.0",
"pdf-lib": "^1.17.1",
"playwright": "^1.52.0",
"prettier": "^3.5.3",
"prettier-plugin-sort-json": "^4.1.1",
"proxy-agent": "^6.5.0",
"rc-virtual-list": "^3.18.6",
"react": "^19.0.0",
"react-dom": "^19.0.0",
"react-error-boundary": "^6.0.0",
"react-hotkeys-hook": "^4.6.1",
"react-i18next": "^14.1.2",
"react-infinite-scroll-component": "^6.1.0",
"react-json-view": "^1.21.3",
"react-markdown": "^10.1.0",
"react-redux": "^9.1.2",
"react-router": "6",
"react-router-dom": "6",
"react-spinners": "^0.14.1",
"react-transition-group": "^4.4.5",
"react-window": "^1.8.11",
"redux": "^5.0.1",
"redux-persist": "^6.0.0",
"reflect-metadata": "0.2.2",
"rehype-katex": "^7.0.1",
"rehype-mathjax": "^7.1.0",
"rehype-parse": "^9.0.1",
"rehype-raw": "^7.0.0",
"rehype-stringify": "^10.0.1",
"remark-cjk-friendly": "^1.2.0",
"remark-gfm": "^4.0.1",
"remark-github-blockquote-alert": "^2.0.0",
"remark-math": "^6.0.0",
"remove-markdown": "^0.6.2",
"rollup-plugin-visualizer": "^5.12.0",
"sass": "^1.88.0",
"shiki": "^3.9.1",
"strict-url-sanitise": "^0.0.1",
"shiki": "^3.7.0",
"string-width": "^7.2.0",
"styled-components": "^6.1.11",
"tar": "^7.4.3",
"tiny-pinyin": "^1.3.2",
"tokenx": "^1.1.0",
"tsx": "^4.20.3",
"typescript": "^5.6.2",
"undici": "6.21.2",
"unified": "^11.0.5",
"uuid": "^10.0.0",
"vite": "npm:rolldown-vite@latest",
"vitest": "^3.2.4",
"vite": "6.2.6",
"vitest": "^3.1.4",
"webdav": "^5.8.0",
"winston": "^3.17.0",
"winston-daily-rotate-file": "^5.0.0",
"word-extractor": "^1.0.4",
"zipread": "^1.3.3",
"zod": "^3.25.74"
"zipread": "^1.3.3"
},
"optionalDependencies": {
"@cherrystudio/mac-system-ocr": "^0.2.2"
},
"resolutions": {
"@codemirror/language": "6.11.3",
"@codemirror/lint": "6.8.5",
"@codemirror/view": "6.38.1",
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch",
"pdf-parse@npm:1.1.1": "patch:pdf-parse@npm%3A1.1.1#~/.yarn/patches/pdf-parse-npm-1.1.1-04a6109b2a.patch",
"@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
"@langchain/openai@npm:>=0.1.0 <0.4.0": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
"atomically@npm:^1.7.0": "patch:atomically@npm%3A1.7.0#~/.yarn/patches/atomically-npm-1.7.0-e742e5293b.patch",
"file-stream-rotator@npm:^0.6.1": "patch:file-stream-rotator@npm%3A0.6.1#~/.yarn/patches/file-stream-rotator-npm-0.6.1-eab45fb13d.patch",
"libsql@npm:^0.4.4": "patch:libsql@npm%3A0.4.7#~/.yarn/patches/libsql-npm-0.4.7-444e260fb1.patch",
"node-abi": "4.12.0",
"openai@npm:^4.77.0": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"openai@npm:^4.87.3": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"pdf-parse@npm:1.1.1": "patch:pdf-parse@npm%3A1.1.1#~/.yarn/patches/pdf-parse-npm-1.1.1-04a6109b2a.patch",
"openai@npm:^4.77.0": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"pkce-challenge@npm:^4.1.0": "patch:pkce-challenge@npm%3A4.1.0#~/.yarn/patches/pkce-challenge-npm-4.1.0-fbc51695a3.patch",
"undici": "6.21.2",
"vite": "npm:rolldown-vite@latest",
"tesseract.js@npm:*": "patch:tesseract.js@npm%3A6.0.1#~/.yarn/patches/tesseract.js-npm-6.0.1-2562a7e46d.patch"
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
"openai@npm:^4.87.3": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch"
},
"packageManager": "yarn@4.9.1",
"lint-staged": {

View File

@@ -1,26 +0,0 @@
import { SpanKind, SpanStatusCode } from '@opentelemetry/api'
import { ReadableSpan } from '@opentelemetry/sdk-trace-base'
import { SpanEntity } from '../types/config'
/**
* convert ReadableSpan to SpanEntity
* @param span ReadableSpan
* @returns SpanEntity
*/
export function convertSpanToSpanEntity(span: ReadableSpan): SpanEntity {
return {
id: span.spanContext().spanId,
traceId: span.spanContext().traceId,
parentId: span.parentSpanContext?.spanId || '',
name: span.name,
startTime: span.startTime[0] * 1e3 + Math.floor(span.startTime[1] / 1e6), // 转为毫秒
endTime: span.endTime ? span.endTime[0] * 1e3 + Math.floor(span.endTime[1] / 1e6) : undefined, // 转为毫秒
attributes: { ...span.attributes },
status: SpanStatusCode[span.status.code],
events: span.events,
kind: SpanKind[span.kind],
links: span.links,
modelName: span.attributes?.modelName
} as SpanEntity
}

View File

@@ -1,7 +0,0 @@
import { ReadableSpan } from '@opentelemetry/sdk-trace-base'
export interface TraceCache {
createSpan: (span: ReadableSpan) => void
endSpan: (span: ReadableSpan) => void
clear: () => void
}

View File

@@ -1,163 +0,0 @@
import 'reflect-metadata'
import { SpanStatusCode, trace } from '@opentelemetry/api'
import { context as traceContext } from '@opentelemetry/api'
import { defaultConfig } from '../types/config'
export interface SpanDecoratorOptions {
spanName?: string
traceName?: string
tag?: string
}
export function TraceMethod(traced: SpanDecoratorOptions) {
return function (target: any, propertyKey?: any, descriptor?: PropertyDescriptor | undefined) {
// 兼容静态方法装饰器只传2个参数的情况
if (!descriptor) {
descriptor = Object.getOwnPropertyDescriptor(target, propertyKey)
}
if (!descriptor || typeof descriptor.value !== 'function') {
throw new Error('TraceMethod can only be applied to methods.')
}
const originalMethod = descriptor.value
const traceName = traced.traceName || defaultConfig.defaultTracerName || 'default'
const tracer = trace.getTracer(traceName)
descriptor.value = function (...args: any[]) {
const name = traced.spanName || propertyKey
return tracer.startActiveSpan(name, async (span) => {
try {
span.setAttribute('inputs', convertToString(args))
span.setAttribute('tags', traced.tag || '')
const result = await originalMethod.apply(this, args)
span.setAttribute('outputs', convertToString(result))
span.setStatus({ code: SpanStatusCode.OK })
return result
} catch (error) {
const err = error instanceof Error ? error : new Error(String(error))
span.setStatus({
code: SpanStatusCode.ERROR,
message: err.message
})
span.recordException(err)
throw error
} finally {
span.end()
}
})
}
return descriptor
}
}
export function TraceProperty(traced: SpanDecoratorOptions) {
return (target: any, propertyKey: string, descriptor?: PropertyDescriptor) => {
// 处理箭头函数类属性
const traceName = traced.traceName || defaultConfig.defaultTracerName || 'default'
const tracer = trace.getTracer(traceName)
const name = traced.spanName || propertyKey
if (!descriptor) {
const originalValue = target[propertyKey]
Object.defineProperty(target, propertyKey, {
value: async function (...args: any[]) {
const span = tracer.startSpan(name)
try {
span.setAttribute('inputs', convertToString(args))
span.setAttribute('tags', traced.tag || '')
const result = await originalValue.apply(this, args)
span.setAttribute('outputs', convertToString(result))
return result
} catch (error) {
const err = error instanceof Error ? error : new Error(String(error))
span.recordException(err)
span.setStatus({ code: SpanStatusCode.ERROR, message: err.message })
throw error
} finally {
span.end()
}
},
configurable: true,
writable: true
})
return
}
// 标准方法装饰器逻辑
const originalMethod = descriptor.value
descriptor.value = async function (...args: any[]) {
const span = tracer.startSpan(name)
try {
span.setAttribute('inputs', convertToString(args))
span.setAttribute('tags', traced.tag || '')
const result = await originalMethod.apply(this, args)
span.setAttribute('outputs', convertToString(result))
return result
} catch (error) {
const err = error instanceof Error ? error : new Error(String(error))
span.recordException(err)
span.setStatus({ code: SpanStatusCode.ERROR, message: err.message })
throw error
} finally {
span.end()
}
}
}
}
export function withSpanFunc<F extends (...args: any[]) => any>(
name: string,
tag: string,
fn: F,
args: Parameters<F>
): ReturnType<F> {
const traceName = defaultConfig.defaultTracerName || 'default'
const tracer = trace.getTracer(traceName)
const _name = name || fn.name || 'anonymousFunction'
return traceContext.with(traceContext.active(), () =>
tracer.startActiveSpan(
_name,
{
attributes: {
tags: tag || '',
inputs: JSON.stringify(args)
}
},
(span) => {
// 在这里调用原始函数
const result = fn(...args)
if (result instanceof Promise) {
return result
.then((res) => {
span.setStatus({ code: SpanStatusCode.OK })
span.setAttribute('outputs', convertToString(res))
return res
})
.catch((error) => {
const err = error instanceof Error ? error : new Error(String(error))
span.setStatus({ code: SpanStatusCode.ERROR, message: err.message })
span.recordException(err)
throw error
})
.finally(() => span.end())
} else {
span.setStatus({ code: SpanStatusCode.OK })
span.setAttribute('outputs', convertToString(result))
span.end()
}
return result
}
)
)
}
function convertToString(args: any | any[]): string | boolean | number {
if (typeof args === 'string' || typeof args === 'boolean' || typeof args === 'number') {
return args
}
return JSON.stringify(args)
}

View File

@@ -1,26 +0,0 @@
import { ExportResult, ExportResultCode } from '@opentelemetry/core'
import { ReadableSpan, SpanExporter } from '@opentelemetry/sdk-trace-base'
export type SaveFunction = (spans: ReadableSpan[]) => Promise<void>
export class FunctionSpanExporter implements SpanExporter {
private exportFunction: SaveFunction
constructor(fn: SaveFunction) {
this.exportFunction = fn
}
shutdown(): Promise<void> {
return Promise.resolve()
}
export(spans: ReadableSpan[], resultCallback: (result: ExportResult) => void): void {
this.exportFunction(spans)
.then(() => {
resultCallback({ code: ExportResultCode.SUCCESS })
})
.catch((error) => {
resultCallback({ code: ExportResultCode.FAILED, error: error })
})
}
}

View File

@@ -1,8 +0,0 @@
export * from './core/spanConvert'
export * from './core/traceCache'
export * from './core/traceMethod'
export * from './exporters/FuncSpanExporter'
export * from './processors/CacheSpanProcessor'
export * from './processors/EmitterSpanProcessor'
export * from './processors/FuncSpanProcessor'
export * from './types/config'

View File

@@ -1,40 +0,0 @@
import { Context, trace } from '@opentelemetry/api'
import { BatchSpanProcessor, BufferConfig, ReadableSpan, Span, SpanExporter } from '@opentelemetry/sdk-trace-base'
import { TraceCache } from '../core/traceCache'
export class CacheBatchSpanProcessor extends BatchSpanProcessor {
private cache: TraceCache
constructor(_exporter: SpanExporter, cache: TraceCache, config?: BufferConfig) {
super(_exporter, config)
this.cache = cache
}
override onEnd(span: ReadableSpan): void {
super.onEnd(span)
this.cache.endSpan(span)
}
override onStart(span: Span, parentContext: Context): void {
super.onStart(span, parentContext)
this.cache.createSpan({
name: span.name,
kind: span.kind,
spanContext: () => span.spanContext(),
parentSpanContext: trace.getSpanContext(parentContext),
startTime: span.startTime,
status: span.status,
attributes: span.attributes,
links: span.links,
events: span.events,
duration: span.duration,
ended: span.ended,
resource: span.resource,
instrumentationScope: span.instrumentationScope,
droppedAttributesCount: span.droppedAttributesCount,
droppedEventsCount: span.droppedEventsCount,
droppedLinksCount: span.droppedLinksCount
} as ReadableSpan)
}
}

View File

@@ -1,28 +0,0 @@
import { Context } from '@opentelemetry/api'
import { BatchSpanProcessor, BufferConfig, ReadableSpan, Span, SpanExporter } from '@opentelemetry/sdk-trace-base'
import { EventEmitter } from 'stream'
import { convertSpanToSpanEntity } from '../core/spanConvert'
export const TRACE_DATA_EVENT = 'trace_data_event'
export const ON_START = 'start'
export const ON_END = 'end'
export class EmitterSpanProcessor extends BatchSpanProcessor {
private emitter: EventEmitter
constructor(_exporter: SpanExporter, emitter: NodeJS.EventEmitter, config?: BufferConfig) {
super(_exporter, config)
this.emitter = emitter
}
override onEnd(span: ReadableSpan): void {
super.onEnd(span)
this.emitter.emit(TRACE_DATA_EVENT, ON_END, convertSpanToSpanEntity(span))
}
override onStart(span: Span, parentContext: Context): void {
super.onStart(span, parentContext)
this.emitter.emit(TRACE_DATA_EVENT, ON_START, convertSpanToSpanEntity(span))
}
}

View File

@@ -1,42 +0,0 @@
import { Context, trace } from '@opentelemetry/api'
import { BatchSpanProcessor, BufferConfig, ReadableSpan, Span, SpanExporter } from '@opentelemetry/sdk-trace-base'
export type SpanFunction = (span: ReadableSpan) => void
export class FunctionSpanProcessor extends BatchSpanProcessor {
private start: SpanFunction
private end: SpanFunction
constructor(_exporter: SpanExporter, start: SpanFunction, end: SpanFunction, config?: BufferConfig) {
super(_exporter, config)
this.start = start
this.end = end
}
override onEnd(span: ReadableSpan): void {
super.onEnd(span)
this.end(span)
}
override onStart(span: Span, parentContext: Context): void {
super.onStart(span, parentContext)
this.start({
name: span.name,
kind: span.kind,
spanContext: () => span.spanContext(),
parentSpanContext: trace.getSpanContext(parentContext),
startTime: span.startTime,
status: span.status,
attributes: span.attributes,
links: span.links,
events: span.events,
duration: span.duration,
ended: span.ended,
resource: span.resource,
instrumentationScope: span.instrumentationScope,
droppedAttributesCount: span.droppedAttributesCount,
droppedEventsCount: span.droppedEventsCount,
droppedLinksCount: span.droppedLinksCount
} as ReadableSpan)
}
}

View File

@@ -1,65 +0,0 @@
import { Link } from '@opentelemetry/api'
import { TimedEvent } from '@opentelemetry/sdk-trace-base'
export type AttributeValue =
| string
| number
| boolean
| Array<null | undefined | string>
| Array<null | undefined | number>
| Array<null | undefined | boolean>
| { [key: string]: string | number | boolean }
| Array<null | undefined | { [key: string]: string | number | boolean }>
export type Attributes = {
[key: string]: AttributeValue
}
export interface TelemetryConfig {
serviceName: string
endpoint?: string
headers?: Record<string, string>
defaultTracerName?: string
}
export interface TraceConfig extends TelemetryConfig {
maxAttributesPerSpan?: number
}
export interface TraceEntity {
id: string
name: string
}
export interface TokenUsage {
prompt_tokens: number
completion_tokens: number
total_tokens: number
prompt_tokens_details?: {
[key: string]: number
}
}
export interface SpanEntity {
id: string
name: string
parentId: string
traceId: string
status: string
kind: string
attributes: Attributes | undefined
isEnd: boolean
events: TimedEvent[] | undefined
startTime: number
endTime: number | null
links: Link[] | undefined
topicId?: string
usage?: TokenUsage
modelName?: string
}
export const defaultConfig: TelemetryConfig = {
serviceName: 'default',
headers: {},
defaultTracerName: 'default'
}

View File

@@ -1,46 +0,0 @@
import { trace, Tracer } from '@opentelemetry/api'
import { AsyncLocalStorageContextManager } from '@opentelemetry/context-async-hooks'
import { W3CTraceContextPropagator } from '@opentelemetry/core'
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http'
import { BatchSpanProcessor, ConsoleSpanExporter, SpanProcessor } from '@opentelemetry/sdk-trace-base'
import { NodeTracerProvider } from '@opentelemetry/sdk-trace-node'
import { defaultConfig, TraceConfig } from '../trace-core/types/config'
export class NodeTracer {
private static provider: NodeTracerProvider
private static defaultTracer: Tracer
private static spanProcessor: SpanProcessor
static init(config?: TraceConfig, spanProcessor?: SpanProcessor) {
if (config) {
defaultConfig.serviceName = config.serviceName || defaultConfig.serviceName
defaultConfig.endpoint = config.endpoint || defaultConfig.endpoint
defaultConfig.headers = config.headers || defaultConfig.headers
defaultConfig.defaultTracerName = config.defaultTracerName || defaultConfig.defaultTracerName
}
this.spanProcessor = spanProcessor || new BatchSpanProcessor(this.getExporter())
this.provider = new NodeTracerProvider({
spanProcessors: [this.spanProcessor]
})
this.provider.register({
propagator: new W3CTraceContextPropagator(),
contextManager: new AsyncLocalStorageContextManager()
})
this.defaultTracer = trace.getTracer(config?.defaultTracerName || 'default')
}
private static getExporter(config?: TraceConfig) {
if (config && config.endpoint) {
return new OTLPTraceExporter({
url: `${config.endpoint}/v1/traces`,
headers: config.headers || undefined
})
}
return new ConsoleSpanExporter()
}
public static getTracer() {
return this.defaultTracer
}
}

View File

@@ -1,75 +0,0 @@
import { Context, ContextManager, ROOT_CONTEXT } from '@opentelemetry/api'
export class TopicContextManager implements ContextManager {
private topicContextStack: Map<string, Context[]>
private _topicContexts: Map<string, Context>
constructor() {
// topicId -> context
this.topicContextStack = new Map()
this._topicContexts = new Map()
}
// 绑定一个context到topicId
startContextForTopic(topicId, context: Context) {
const currentContext = this.getCurrentContext(topicId)
this._topicContexts.set(topicId, context)
if (!this.topicContextStack.has(topicId) && !this.topicContextStack.get(topicId)) {
this.topicContextStack.set(topicId, [currentContext])
} else {
this.topicContextStack.get(topicId)?.push(currentContext)
}
}
// 获取topicId对应的context
getContextForTopic(topicId) {
return this.getCurrentContext(topicId)
}
endContextForTopic(topicId) {
const context = this.getHistoryContext(topicId)
this._topicContexts.set(topicId, context)
}
cleanContextForTopic(topicId) {
this.topicContextStack.delete(topicId)
this._topicContexts.delete(topicId)
}
private getHistoryContext(topicId): Context {
const hasContext = this.topicContextStack.has(topicId) && this.topicContextStack.get(topicId)
const context = hasContext && hasContext.length > 0 && hasContext.pop()
return context ? context : ROOT_CONTEXT
}
private getCurrentContext(topicId): Context {
const hasContext = this._topicContexts.has(topicId) && this._topicContexts.get(topicId)
return hasContext || ROOT_CONTEXT
}
// OpenTelemetry接口实现
active() {
// 不支持全局active必须显式传递
return ROOT_CONTEXT
}
with(_, fn, thisArg, ...args) {
// 直接调用fn不做全局active切换
return fn.apply(thisArg, args)
}
bind(target, context) {
// 显式绑定
target.__ot_context = context
return target
}
enable() {
return this
}
disable() {
this._topicContexts.clear()
return this
}
}

View File

@@ -1,3 +0,0 @@
export * from './TopicContextManager'
export * from './traceContextPromise'
export * from './webTracer'

View File

@@ -1,99 +0,0 @@
import { Context, context } from '@opentelemetry/api'
const originalPromise = globalThis.Promise
class TraceContextPromise<T> extends Promise<T> {
_context: Context
constructor(
executor: (resolve: (value: T | PromiseLike<T>) => void, reject: (reason?: any) => void) => void,
ctx?: Context
) {
const capturedContext = ctx || context.active()
super((resolve, reject) => {
context.with(capturedContext, () => {
executor(
(value) => context.with(capturedContext, () => resolve(value)),
(reason) => context.with(capturedContext, () => reject(reason))
)
})
})
this._context = capturedContext
}
// 兼容 Promise.resolve/reject
static resolve(): Promise<void>
static resolve<T>(value: T | PromiseLike<T>): Promise<T>
static resolve<T>(value: T | PromiseLike<T>, ctx?: Context): Promise<T>
static resolve<T>(value?: T | PromiseLike<T>, ctx?: Context): Promise<T | void> {
return new TraceContextPromise<T | void>((resolve) => resolve(value as T), ctx)
}
static reject<T = never>(reason?: any): Promise<T>
static reject<T = never>(reason?: any, ctx?: Context): Promise<T> {
return new TraceContextPromise<T>((_, reject) => reject(reason), ctx)
}
static all<T>(values: (T | PromiseLike<T>)[]): Promise<T[]> {
// 尝试从缓存获取 context
let capturedContext = context.active()
const newValues = values.map((v) => {
if (v instanceof Promise && !(v instanceof TraceContextPromise)) {
return new TraceContextPromise((resolve, reject) => v.then(resolve, reject), capturedContext)
} else if (typeof v === 'function') {
// 如果 v 是一个 Function使用 context 传递 trace 上下文
return (...args: any[]) => context.with(capturedContext, () => v(...args))
} else {
return v
}
})
if (Array.isArray(values) && values.length > 0 && values[0] instanceof TraceContextPromise) {
capturedContext = (values[0] as TraceContextPromise<any>)._context
}
return originalPromise.all(newValues) as Promise<T[]>
}
static race<T>(values: (T | PromiseLike<T>)[]): Promise<T> {
const capturedContext = context.active()
return new TraceContextPromise<T>((resolve, reject) => {
originalPromise.race(values).then(
(result) => context.with(capturedContext, () => resolve(result)),
(err) => context.with(capturedContext, () => reject(err))
)
}, capturedContext)
}
static allSettled<T>(values: (T | PromiseLike<T>)[]): Promise<PromiseSettledResult<T>[]> {
const capturedContext = context.active()
return new TraceContextPromise<PromiseSettledResult<T>[]>((resolve, reject) => {
originalPromise.allSettled(values).then(
(result) => context.with(capturedContext, () => resolve(result)),
(err) => context.with(capturedContext, () => reject(err))
)
}, capturedContext)
}
static any<T>(values: (T | PromiseLike<T>)[]): Promise<T> {
const capturedContext = context.active()
return new TraceContextPromise<T>((resolve, reject) => {
originalPromise.any(values).then(
(result) => context.with(capturedContext, () => resolve(result)),
(err) => context.with(capturedContext, () => reject(err))
)
}, capturedContext)
}
}
/**
* 用 TraceContextPromise 替换全局 Promise
*/
export function instrumentPromises() {
globalThis.Promise = TraceContextPromise as unknown as PromiseConstructor
}
/**
* 恢复原生 Promise
*/
export function uninstrumentPromises() {
globalThis.Promise = originalPromise
}

View File

@@ -1,46 +0,0 @@
import { W3CTraceContextPropagator } from '@opentelemetry/core'
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http'
import { BatchSpanProcessor, ConsoleSpanExporter, SpanProcessor } from '@opentelemetry/sdk-trace-base'
import { WebTracerProvider } from '@opentelemetry/sdk-trace-web'
import { defaultConfig, TraceConfig } from '../trace-core/types/config'
import { TopicContextManager } from './TopicContextManager'
export const contextManager = new TopicContextManager()
export class WebTracer {
private static provider: WebTracerProvider
private static processor: SpanProcessor
static init(config?: TraceConfig, spanProcessor?: SpanProcessor) {
if (config) {
defaultConfig.serviceName = config.serviceName || defaultConfig.serviceName
defaultConfig.endpoint = config.endpoint || defaultConfig.endpoint
defaultConfig.headers = config.headers || defaultConfig.headers
defaultConfig.defaultTracerName = config.defaultTracerName || defaultConfig.defaultTracerName
}
this.processor = spanProcessor || new BatchSpanProcessor(this.getExporter())
this.provider = new WebTracerProvider({
spanProcessors: [this.processor]
})
this.provider.register({
propagator: new W3CTraceContextPropagator(),
contextManager: contextManager
})
}
private static getExporter() {
if (defaultConfig.endpoint) {
return new OTLPTraceExporter({
url: `${defaultConfig.endpoint}/v1/traces`,
headers: defaultConfig.headers
})
}
return new ConsoleSpanExporter()
}
}
export const startContext = contextManager.startContextForTopic.bind(contextManager)
export const getContext = contextManager.getContextForTopic.bind(contextManager)
export const endContext = contextManager.endContextForTopic.bind(contextManager)
export const cleanContext = contextManager.cleanContextForTopic.bind(contextManager)

View File

@@ -20,8 +20,6 @@ export enum IpcChannel {
App_HandleZoomFactor = 'app:handle-zoom-factor',
App_Select = 'app:select',
App_HasWritePermission = 'app:has-write-permission',
App_ResolvePath = 'app:resolve-path',
App_IsPathInside = 'app:is-path-inside',
App_Copy = 'app:copy',
App_SetStopQuitApp = 'app:set-stop-quit-app',
App_SetAppDataPath = 'app:set-app-data-path',
@@ -33,9 +31,6 @@ export enum IpcChannel {
App_GetBinaryPath = 'app:get-binary-path',
App_InstallUvBinary = 'app:install-uv-binary',
App_InstallBunBinary = 'app:install-bun-binary',
App_LogToMain = 'app:log-to-main',
App_SaveData = 'app:save-data',
App_SetFullScreen = 'app:set-full-screen',
App_MacIsProcessTrusted = 'app:mac-is-process-trusted',
App_MacRequestProcessTrust = 'app:mac-request-process-trust',
@@ -79,9 +74,6 @@ export enum IpcChannel {
Mcp_ServersChanged = 'mcp:servers-changed',
Mcp_ServersUpdated = 'mcp:servers-updated',
Mcp_CheckConnectivity = 'mcp:check-connectivity',
Mcp_UploadDxt = 'mcp:upload-dxt',
Mcp_AbortTool = 'mcp:abort-tool',
Mcp_GetServerVersion = 'mcp:get-server-version',
// Python
Python_Execute = 'python:execute',
@@ -115,13 +107,10 @@ export enum IpcChannel {
// VertexAI
VertexAI_GetAuthHeaders = 'vertexai:get-auth-headers',
VertexAI_GetAccessToken = 'vertexai:get-access-token',
VertexAI_ClearAuthCache = 'vertexai:clear-auth-cache',
Windows_ResetMinimumSize = 'window:reset-minimum-size',
Windows_SetMinimumSize = 'window:set-minimum-size',
Windows_Resize = 'window:resize',
Windows_GetSize = 'window:get-size',
KnowledgeBase_Create = 'knowledge-base:create',
KnowledgeBase_Reset = 'knowledge-base:reset',
@@ -156,9 +145,6 @@ export enum IpcChannel {
File_Base64File = 'file:base64File',
File_GetPdfInfo = 'file:getPdfInfo',
Fs_Read = 'fs:read',
Fs_ReadText = 'fs:readText',
File_OpenWithRelativePath = 'file:openWithRelativePath',
File_IsTextFile = 'file:isTextFile',
// file service
FileService_Upload = 'file-service:upload',
@@ -179,15 +165,6 @@ export enum IpcChannel {
Backup_CheckConnection = 'backup:checkConnection',
Backup_CreateDirectory = 'backup:createDirectory',
Backup_DeleteWebdavFile = 'backup:deleteWebdavFile',
Backup_BackupToLocalDir = 'backup:backupToLocalDir',
Backup_RestoreFromLocalBackup = 'backup:restoreFromLocalBackup',
Backup_ListLocalBackupFiles = 'backup:listLocalBackupFiles',
Backup_DeleteLocalBackupFile = 'backup:deleteLocalBackupFile',
Backup_BackupToS3 = 'backup:backupToS3',
Backup_RestoreFromS3 = 'backup:restoreFromS3',
Backup_ListS3Files = 'backup:listS3Files',
Backup_DeleteS3File = 'backup:deleteS3File',
Backup_CheckS3Connection = 'backup:checkS3Connection',
// zip
Zip_Compress = 'zip:compress',
@@ -252,38 +229,5 @@ export enum IpcChannel {
Selection_ActionWindowMinimize = 'selection:action-window-minimize',
Selection_ActionWindowPin = 'selection:action-window-pin',
Selection_ProcessAction = 'selection:process-action',
Selection_UpdateActionData = 'selection:update-action-data',
// Memory
Memory_Add = 'memory:add',
Memory_Search = 'memory:search',
Memory_List = 'memory:list',
Memory_Delete = 'memory:delete',
Memory_Update = 'memory:update',
Memory_Get = 'memory:get',
Memory_SetConfig = 'memory:set-config',
Memory_DeleteUser = 'memory:delete-user',
Memory_DeleteAllMemoriesForUser = 'memory:delete-all-memories-for-user',
Memory_GetUsersList = 'memory:get-users-list',
// TRACE
TRACE_SAVE_DATA = 'trace:saveData',
TRACE_GET_DATA = 'trace:getData',
TRACE_SAVE_ENTITY = 'trace:saveEntity',
TRACE_GET_ENTITY = 'trace:getEntity',
TRACE_BIND_TOPIC = 'trace:bindTopic',
TRACE_CLEAN_TOPIC = 'trace:cleanTopic',
TRACE_TOKEN_USAGE = 'trace:tokenUsage',
TRACE_CLEAN_HISTORY = 'trace:cleanHistory',
TRACE_OPEN_WINDOW = 'trace:openWindow',
TRACE_SET_TITLE = 'trace:setTitle',
TRACE_ADD_END_MESSAGE = 'trace:addEndMessage',
TRACE_CLEAN_LOCAL_DATA = 'trace:cleanLocalData',
TRACE_ADD_STREAM_MESSAGE = 'trace:addStreamMessage',
// CodeTools
CodeTools_Run = 'code-tools:run',
// OCR
OCR_ocr = 'ocr:ocr'
Selection_UpdateActionData = 'selection:update-action-data'
}

View File

@@ -1,127 +1,311 @@
import { languages } from './languages'
export const imageExts = ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.webp']
export const videoExts = ['.mp4', '.avi', '.mov', '.wmv', '.flv', '.mkv']
export const audioExts = ['.mp3', '.wav', '.ogg', '.flac', '.aac']
export const documentExts = ['.pdf', '.doc', '.docx', '.pptx', '.xlsx', '.odt', '.odp', '.ods']
export const thirdPartyApplicationExts = ['.draftsExport']
export const bookExts = ['.epub']
/**
* A flat array of all file extensions known by the linguist database.
* This is the primary source for identifying code files.
*/
const linguistExtSet = new Set<string>()
for (const lang of Object.values(languages)) {
if (lang.extensions) {
for (const ext of lang.extensions) {
linguistExtSet.add(ext)
}
}
}
export const codeLangExts = Array.from(linguistExtSet)
/**
* A categorized map of custom text-based file extensions that are NOT included
* in the linguist database. This is for special cases or project-specific files.
*/
export const customTextExts = new Map([
const textExtsByCategory = new Map([
[
'language',
[
'.js',
'.mjs',
'.cjs',
'.ts',
'.jsx',
'.tsx', // JavaScript/TypeScript
'.py', // Python
'.java', // Java
'.cs', // C#
'.cpp',
'.c',
'.h',
'.hpp',
'.cc',
'.cxx',
'.cppm',
'.ipp',
'.ixx', // C/C++
'.php', // PHP
'.rb', // Ruby
'.pl', // Perl
'.go', // Go
'.rs', // Rust
'.swift', // Swift
'.kt',
'.kts', // Kotlin
'.scala', // Scala
'.lua', // Lua
'.groovy', // Groovy
'.dart', // Dart
'.hs', // Haskell
'.clj',
'.cljs', // Clojure
'.elm', // Elm
'.erl', // Erlang
'.ex',
'.exs', // Elixir
'.ml',
'.mli', // OCaml
'.fs', // F#
'.r',
'.R', // R
'.sol', // Solidity
'.awk', // AWK
'.cob', // COBOL
'.asm',
'.s', // Assembly
'.lisp',
'.lsp', // Lisp
'.coffee', // CoffeeScript
'.ino', // Arduino
'.jl', // Julia
'.nim', // Nim
'.zig', // Zig
'.d', // D语言
'.pas', // Pascal
'.vb', // Visual Basic
'.rkt', // Racket
'.scm', // Scheme
'.hx', // Haxe
'.as', // ActionScript
'.pde', // Processing
'.f90',
'.f',
'.f03',
'.for',
'.f95', // Fortran
'.adb',
'.ads', // Ada
'.pro', // Prolog
'.m',
'.mm', // Objective-C/MATLAB
'.rpy', // Ren'Py
'.ets', // OpenHarmony,
'.uniswap', // DeFi
'.usf', // Unreal shader format
'.ush' // Unreal shader header
'.vy', // Vyper
'.shader',
'.glsl',
'.frag',
'.vert',
'.gd' // Godot
]
],
[
'script',
[
'.sh', // Shell
'.bat',
'.cmd', // Windows批处理
'.ps1', // PowerShell
'.tcl',
'.do', // Tcl
'.ahk', // AutoHotkey
'.zsh', // Zsh
'.fish', // Fish shell
'.csh', // C shell
'.vbs', // VBScript
'.applescript', // AppleScript
'.au3', // AutoIt
'.bash',
'.nu'
]
],
[
'style',
[
'.css', // CSS
'.less', // Less
'.scss',
'.sass', // Sass
'.styl', // Stylus
'.pcss', // PostCSS
'.postcss' // PostCSS
]
],
[
'template',
[
'.vm' // Velocity
'.vue', // Vue.js
'.pug',
'.jade', // Pug/Jade
'.haml', // Haml
'.slim', // Slim
'.tpl', // 通用模板
'.ejs', // EJS
'.hbs', // Handlebars
'.mustache', // Mustache
'.twig', // Twig
'.blade', // Blade (Laravel)
'.liquid', // Liquid
'.jinja',
'.jinja2',
'.j2', // Jinja
'.erb', // ERB
'.vm', // Velocity
'.ftl', // FreeMarker
'.svelte', // Svelte
'.astro' // Astro
]
],
[
'config',
[
'.babelrc', // Babel
'.bashrc',
'.browserslistrc',
'.ini', // INI配置
'.conf',
'.config', // 通用配置
'.dockerignore', // Docker ignore
'.eslintignore',
'.eslintrc', // ESLint
'.fishrc', // Fish shell配置
'.htaccess', // Apache配置
'.npmignore',
'.npmrc', // npm
'.prettierignore',
'.prettierrc', // Prettier
'.env', // 环境变量
'.toml', // TOML
'.cfg', // 通用配置
'.properties', // Java属性
'.desktop', // Linux桌面文件
'.service', // systemd服务
'.rc',
'.bashrc',
'.zshrc', // Shell配置
'.fishrc', // Fish shell配置
'.vimrc', // Vim配置
'.htaccess', // Apache配置
'.robots', // robots.txt
'.editorconfig', // EditorConfig
'.eslintrc', // ESLint
'.prettierrc', // Prettier
'.babelrc', // Babel
'.npmrc', // npm
'.dockerignore', // Docker ignore
'.npmignore',
'.yarnrc',
'.zshrc'
'.prettierignore',
'.eslintignore',
'.browserslistrc',
'.json5',
'.tfvars'
]
],
[
'document',
[
'.authors', // 作者文件
'.txt',
'.text', // 纯文本
'.md',
'.mdx', // Markdown
'.html',
'.htm',
'.xhtml', // HTML
'.xml', // XML
'.org', // Org-mode
'.wiki', // Wiki
'.tex',
'.bib', // LaTeX
'.rst', // reStructuredText
'.rtf', // 富文本
'.nfo', // 信息文件
'.adoc',
'.asciidoc', // AsciiDoc
'.pod', // Perl文档
'.1',
'.2',
'.3',
'.4',
'.5',
'.6',
'.7',
'.8',
'.9', // man页面
'.man', // man页面
'.texi',
'.texinfo', // Texinfo
'.readme',
'.me', // README
'.changelog', // 变更日志
'.license', // 许可证
'.nfo', // 信息文件
'.readme',
'.text' // 纯文本
'.authors', // 作者文件
'.po',
'.pot'
]
],
[
'data',
[
'.json', // JSON
'.jsonc', // JSON with comments
'.yaml',
'.yml', // YAML
'.csv',
'.tsv', // 分隔值文件
'.edn', // Clojure数据
'.jsonl',
'.ndjson', // 换行分隔JSON
'.geojson', // GeoJSON
'.gpx', // GPS Exchange
'.kml', // Keyhole Markup
'.rss',
'.atom', // Feed格式
'.ldif',
'.map',
'.ndjson' // 换行分隔JSON
'.vcf', // vCard
'.ics', // iCalendar
'.ldif', // LDAP数据交换
'.pbtxt',
'.map'
]
],
[
'build',
[
'.bazel', // Bazel
'.gradle', // Gradle
'.make',
'.mk', // Make
'.cmake', // CMake
'.sbt', // SBT
'.rake', // Rake
'.spec', // RPM spec
'.pom',
'.build', // Meson
'.pom'
'.bazel' // Bazel
]
],
[
'database',
[
'.sql', // SQL
'.ddl',
'.dml', // DDL/DML
'.psql' // PostgreSQL
'.plsql', // PL/SQL
'.psql', // PostgreSQL
'.cypher', // Cypher
'.sparql' // SPARQL
]
],
[
'web',
[
'.openapi', // API文档
'.swagger'
'.graphql',
'.gql', // GraphQL
'.proto', // Protocol Buffers
'.thrift', // Thrift
'.wsdl', // WSDL
'.raml', // RAML
'.swagger',
'.openapi' // API文档
]
],
[
'version',
[
'.bzrignore', // Bazaar ignore
'.gitignore', // Git ignore
'.gitattributes', // Git attributes
'.githistory', // Git history
'.gitconfig', // Git config
'.hgignore', // Mercurial ignore
'.svnignore' // SVN ignore
'.bzrignore', // Bazaar ignore
'.svnignore', // SVN ignore
'.githistory' // Git history
]
],
[
'subtitle',
[
'.ass', // 字幕格式
'.sub'
'.srt',
'.sub',
'.ass' // 字幕格式
]
],
[
@@ -134,26 +318,54 @@ export const customTextExts = new Map([
[
'eda',
[
'.cir',
'.v',
'.sv',
'.svh', // Verilog/SystemVerilog
'.vhd',
'.vhdl', // VHDL
'.lef',
'.def', // LEF/DEF
'.edif', // EDIF
'.il',
'.ils', // SKILL
'.lef',
'.net',
'.scs', // Spectre
'.sdf', // SDF
'.spi'
'.sdc',
'.xdc', // 约束文件
'.sp',
'.spi',
'.cir',
'.net', // SPICE
'.scs', // Spectre
'.asc', // LTspice
'.tf', // Technology File
'.il',
'.ils' // SKILL
]
],
[
'game',
[
'.mtl', // Material Template Library
'.x3d', // X3D文件
'.gltf', // glTF JSON
'.prefab', // Unity预制体 (YAML格式)
'.meta' // Unity元数据文件 (YAML格式)
]
],
[
'other',
[
'.mcfunction', // Minecraft函数
'.jsp', // JSP
'.aspx', // ASP.NET
'.ipynb', // Jupyter Notebook
'.cake',
'.ctp', // CakePHP
'.cfm',
'.cfc' // ColdFusion
]
]
])
/**
* A comprehensive list of all text-based file extensions, combining the
* extensive list from the linguist database with our custom additions.
* The Set ensures there are no duplicates.
*/
export const textExts = [...new Set([...Array.from(customTextExts.values()).flat(), ...codeLangExts])]
export const textExts = Array.from(textExtsByCategory.values()).flat()
export const ZOOM_LEVELS = [0.25, 0.33, 0.5, 0.67, 0.75, 0.8, 0.9, 1, 1.1, 1.25, 1.5, 1.75, 2, 2.5, 3, 4, 5]
@@ -194,7 +406,8 @@ export const defaultLanguage = 'en-US'
export enum FeedUrl {
PRODUCTION = 'https://releases.cherry-ai.com',
GITHUB_LATEST = 'https://github.com/CherryHQ/cherry-studio/releases/latest/download'
GITHUB_LATEST = 'https://github.com/CherryHQ/cherry-studio/releases/latest/download',
PRERELEASE_LOWEST = 'https://github.com/CherryHQ/cherry-studio/releases/download/v1.4.0'
}
export enum UpgradeChannel {
@@ -206,15 +419,3 @@ export enum UpgradeChannel {
export const defaultTimeout = 10 * 1000 * 60
export const occupiedDirs = ['logs', 'Network', 'Partitions/webview/Network']
export const MIN_WINDOW_WIDTH = 1080
export const SECOND_MIN_WINDOW_WIDTH = 520
export const MIN_WINDOW_HEIGHT = 600
export const defaultByPassRules = 'localhost,127.0.0.1,::1'
export enum codeTools {
qwenCode = 'qwen-code',
claudeCode = 'claude-code',
geminiCli = 'gemini-cli',
openaiCodex = 'openai-codex'
}

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@@ -1,32 +0,0 @@
export type LogSourceWithContext = {
process: 'main' | 'renderer'
window?: string // only for renderer process
module?: string
context?: Record<string, any>
}
type NullableObject = object | undefined | null
export type LogContextData = [] | [Error | NullableObject] | [Error | NullableObject, ...NullableObject[]]
export type LogLevel = 'error' | 'warn' | 'info' | 'debug' | 'verbose' | 'silly' | 'none'
export const LEVEL = {
ERROR: 'error',
WARN: 'warn',
INFO: 'info',
DEBUG: 'debug',
VERBOSE: 'verbose',
SILLY: 'silly',
NONE: 'none'
} satisfies Record<string, LogLevel>
export const LEVEL_MAP: Record<LogLevel, number> = {
error: 10,
warn: 8,
info: 6,
debug: 4,
verbose: 2,
silly: 0,
none: -1
}

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9112
resources/data/agents.json Normal file

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@@ -0,0 +1,47 @@
id: 01-ai/yi-large
canonical_slug: 01-ai/yi-large
hugging_face_id: ''
name: '01.AI: Yi Large'
type: chat
created: 1719273600
description: |-
The Yi Large model was designed by 01.AI with the following usecases in mind: knowledge search, data classification, human-like chat bots, and customer service.
It stands out for its multilingual proficiency, particularly in Spanish, Chinese, Japanese, German, and French.
Check out the [launch announcement](https://01-ai.github.io/blog/01.ai-yi-large-llm-launch) to learn more.
context_length: 32768
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Yi
instruct_type: null
pricing:
prompt: '0.000003'
completion: '0.000003'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- top_k
- repetition_penalty
- response_format
- structured_outputs
- logit_bias
- logprobs
- top_logprobs
model_provider: 01-ai

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@@ -0,0 +1,42 @@
id: aetherwiing/mn-starcannon-12b
canonical_slug: aetherwiing/mn-starcannon-12b
hugging_face_id: aetherwiing/MN-12B-Starcannon-v2
name: 'Aetherwiing: Starcannon 12B'
type: chat
created: 1723507200
description: |-
Starcannon 12B v2 is a creative roleplay and story writing model, based on Mistral Nemo, using [nothingiisreal/mn-celeste-12b](/nothingiisreal/mn-celeste-12b) as a base, with [intervitens/mini-magnum-12b-v1.1](https://huggingface.co/intervitens/mini-magnum-12b-v1.1) merged in using the [TIES](https://arxiv.org/abs/2306.01708) method.
Although more similar to Magnum overall, the model remains very creative, with a pleasant writing style. It is recommended for people wanting more variety than Magnum, and yet more verbose prose than Celeste.
context_length: 16384
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Mistral
instruct_type: chatml
pricing:
prompt: '0.0000008'
completion: '0.0000012'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- top_k
- min_p
- seed
model_provider: aetherwiing

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@@ -0,0 +1,38 @@
id: ai21/jamba-1.6-large
canonical_slug: ai21/jamba-1.6-large
hugging_face_id: ai21labs/AI21-Jamba-Large-1.6
name: 'AI21: Jamba 1.6 Large'
type: chat
created: 1741905173
description: |-
AI21 Jamba Large 1.6 is a high-performance hybrid foundation model combining State Space Models (Mamba) with Transformer attention mechanisms. Developed by AI21, it excels in extremely long-context handling (256K tokens), demonstrates superior inference efficiency (up to 2.5x faster than comparable models), and supports structured JSON output and tool-use capabilities. It has 94 billion active parameters (398 billion total), optimized quantization support (ExpertsInt8), and multilingual proficiency in languages such as English, Spanish, French, Portuguese, Italian, Dutch, German, Arabic, and Hebrew.
Usage of this model is subject to the [Jamba Open Model License](https://www.ai21.com/licenses/jamba-open-model-license).
context_length: 256000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.000002'
completion: '0.000008'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- tool_choice
- max_tokens
- temperature
- top_p
- stop
model_provider: ai21

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@@ -0,0 +1,38 @@
id: ai21/jamba-1.6-mini
canonical_slug: ai21/jamba-1.6-mini
hugging_face_id: ai21labs/AI21-Jamba-Mini-1.6
name: 'AI21: Jamba Mini 1.6'
type: chat
created: 1741905171
description: |-
AI21 Jamba Mini 1.6 is a hybrid foundation model combining State Space Models (Mamba) with Transformer attention mechanisms. With 12 billion active parameters (52 billion total), this model excels in extremely long-context tasks (up to 256K tokens) and achieves superior inference efficiency, outperforming comparable open models on tasks such as retrieval-augmented generation (RAG) and grounded question answering. Jamba Mini 1.6 supports multilingual tasks across English, Spanish, French, Portuguese, Italian, Dutch, German, Arabic, and Hebrew, along with structured JSON output and tool-use capabilities.
Usage of this model is subject to the [Jamba Open Model License](https://www.ai21.com/licenses/jamba-open-model-license).
context_length: 256000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.0000002'
completion: '0.0000004'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- tool_choice
- max_tokens
- temperature
- top_p
- stop
model_provider: ai21

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@@ -0,0 +1,34 @@
id: aion-labs/aion-1.0-mini
canonical_slug: aion-labs/aion-1.0-mini
hugging_face_id: FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview
name: 'AionLabs: Aion-1.0-Mini'
type: chat
created: 1738697107
description: Aion-1.0-Mini 32B parameter model is a distilled version of the DeepSeek-R1 model, designed for strong performance in reasoning domains such as mathematics, coding, and logic. It is a modified variant of a FuseAI model that outperforms R1-Distill-Qwen-32B and R1-Distill-Llama-70B, with benchmark results available on its [Hugging Face page](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview), independently replicated for verification.
context_length: 131072
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.0000007'
completion: '0.0000014'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- reasoning
- include_reasoning
model_provider: aion-labs

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@@ -0,0 +1,34 @@
id: aion-labs/aion-1.0
canonical_slug: aion-labs/aion-1.0
hugging_face_id: ''
name: 'AionLabs: Aion-1.0'
type: chat
created: 1738697557
description: Aion-1.0 is a multi-model system designed for high performance across various tasks, including reasoning and coding. It is built on DeepSeek-R1, augmented with additional models and techniques such as Tree of Thoughts (ToT) and Mixture of Experts (MoE). It is Aion Lab's most powerful reasoning model.
context_length: 131072
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.000004'
completion: '0.000008'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- reasoning
- include_reasoning
model_provider: aion-labs

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@@ -0,0 +1,32 @@
id: aion-labs/aion-rp-llama-3.1-8b
canonical_slug: aion-labs/aion-rp-llama-3.1-8b
hugging_face_id: ''
name: 'AionLabs: Aion-RP 1.0 (8B)'
type: chat
created: 1738696718
description: Aion-RP-Llama-3.1-8B ranks the highest in the character evaluation portion of the RPBench-Auto benchmark, a roleplaying-specific variant of Arena-Hard-Auto, where LLMs evaluate each others responses. It is a fine-tuned base model rather than an instruct model, designed to produce more natural and varied writing.
context_length: 32768
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.0000002'
completion: '0.0000002'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
model_provider: aion-labs

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@@ -0,0 +1,39 @@
id: alfredpros/codellama-7b-instruct-solidity
canonical_slug: alfredpros/codellama-7b-instruct-solidity
hugging_face_id: AlfredPros/CodeLlama-7b-Instruct-Solidity
name: 'AlfredPros: CodeLLaMa 7B Instruct Solidity'
type: chat
created: 1744641874
description: A finetuned 7 billion parameters Code LLaMA - Instruct model to generate Solidity smart contract using 4-bit QLoRA finetuning provided by PEFT library.
context_length: 4096
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: alpaca
pricing:
prompt: '0.0000008'
completion: '0.0000012'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- top_k
- min_p
- seed
model_provider: alfredpros

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@@ -0,0 +1,44 @@
id: all-hands/openhands-lm-32b-v0.1
canonical_slug: all-hands/openhands-lm-32b-v0.1
hugging_face_id: all-hands/openhands-lm-32b-v0.1
name: OpenHands LM 32B V0.1
type: chat
created: 1743613013
description: |-
OpenHands LM v0.1 is a 32B open-source coding model fine-tuned from Qwen2.5-Coder-32B-Instruct using reinforcement learning techniques outlined in SWE-Gym. It is optimized for autonomous software development agents and achieves strong performance on SWE-Bench Verified, with a 37.2% resolve rate. The model supports a 128K token context window, making it well-suited for long-horizon code reasoning and large codebase tasks.
OpenHands LM is designed for local deployment and runs on consumer-grade GPUs such as a single 3090. It enables fully offline agent workflows without dependency on proprietary APIs. This release is intended as a research preview, and future updates aim to improve generalizability, reduce repetition, and offer smaller variants.
context_length: 16384
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Other
instruct_type: null
pricing:
prompt: '0.0000026'
completion: '0.0000034'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- tool_choice
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- top_k
- min_p
- seed
model_provider: all-hands

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@@ -0,0 +1,48 @@
id: alpindale/goliath-120b
canonical_slug: alpindale/goliath-120b
hugging_face_id: alpindale/goliath-120b
name: Goliath 120B
type: chat
created: 1699574400
description: |-
A large LLM created by combining two fine-tuned Llama 70B models into one 120B model. Combines Xwin and Euryale.
Credits to
- [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge the model - [mergekit](https://github.com/cg123/mergekit).
- [@Undi95](https://huggingface.co/Undi95) for helping with the merge ratios.
#merge
context_length: 6144
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Llama2
instruct_type: airoboros
pricing:
prompt: '0.00001'
completion: '0.0000125'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- logit_bias
- top_k
- min_p
- seed
- top_a
model_provider: alpindale

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@@ -0,0 +1,42 @@
id: alpindale/magnum-72b
canonical_slug: alpindale/magnum-72b
hugging_face_id: alpindale/magnum-72b-v1
name: Magnum 72B
type: chat
created: 1720656000
description: |-
From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the first in a new family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.
The model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.
context_length: 16384
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Qwen
instruct_type: chatml
pricing:
prompt: '0.000004'
completion: '0.000006'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- top_k
- min_p
- seed
model_provider: alpindale

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@@ -0,0 +1,39 @@
id: amazon/nova-lite-v1
canonical_slug: amazon/nova-lite-v1
hugging_face_id: ''
name: 'Amazon: Nova Lite 1.0'
type: chat
created: 1733437363
description: |-
Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite can handle real-time customer interactions, document analysis, and visual question-answering tasks with high accuracy.
With an input context of 300K tokens, it can analyze multiple images or up to 30 minutes of video in a single input.
context_length: 300000
architecture:
modality: text+image->text
input_modalities:
- text
- image
output_modalities:
- text
tokenizer: Nova
instruct_type: null
pricing:
prompt: '0.00000006'
completion: '0.00000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0.00009'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: amazon

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@@ -0,0 +1,35 @@
id: amazon/nova-micro-v1
canonical_slug: amazon/nova-micro-v1
hugging_face_id: ''
name: 'Amazon: Nova Micro 1.0'
type: chat
created: 1733437237
description: Amazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at a very low cost. With a context length of 128K tokens and optimized for speed and cost, Amazon Nova Micro excels at tasks such as text summarization, translation, content classification, interactive chat, and brainstorming. It has simple mathematical reasoning and coding abilities.
context_length: 128000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Nova
instruct_type: null
pricing:
prompt: '0.000000035'
completion: '0.00000014'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: amazon

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@@ -0,0 +1,41 @@
id: amazon/nova-pro-v1
canonical_slug: amazon/nova-pro-v1
hugging_face_id: ''
name: 'Amazon: Nova Pro 1.0'
type: chat
created: 1733436303
description: |-
Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December 2024, it achieves state-of-the-art performance on key benchmarks including visual question answering (TextVQA) and video understanding (VATEX).
Amazon Nova Pro demonstrates strong capabilities in processing both visual and textual information and at analyzing financial documents.
**NOTE**: Video input is not supported at this time.
context_length: 300000
architecture:
modality: text+image->text
input_modalities:
- text
- image
output_modalities:
- text
tokenizer: Nova
instruct_type: null
pricing:
prompt: '0.0000008'
completion: '0.0000032'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0.0012'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: amazon

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@@ -0,0 +1,43 @@
id: anthracite-org/magnum-v2-72b
canonical_slug: anthracite-org/magnum-v2-72b
hugging_face_id: anthracite-org/magnum-v2-72b
name: Magnum v2 72B
type: chat
created: 1727654400
description: |-
From the maker of [Goliath](https://openrouter.ai/models/alpindale/goliath-120b), Magnum 72B is the seventh in a family of models designed to achieve the prose quality of the Claude 3 models, notably Opus & Sonnet.
The model is based on [Qwen2 72B](https://openrouter.ai/models/qwen/qwen-2-72b-instruct) and trained with 55 million tokens of highly curated roleplay (RP) data.
context_length: 32768
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Qwen
instruct_type: chatml
pricing:
prompt: '0.000003'
completion: '0.000003'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- logit_bias
- top_k
- min_p
- seed
model_provider: anthracite-org

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@@ -0,0 +1,44 @@
id: anthracite-org/magnum-v4-72b
canonical_slug: anthracite-org/magnum-v4-72b
hugging_face_id: anthracite-org/magnum-v4-72b
name: Magnum v4 72B
type: chat
created: 1729555200
description: |-
This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus).
The model is fine-tuned on top of [Qwen2.5 72B](https://openrouter.ai/qwen/qwen-2.5-72b-instruct).
context_length: 16384
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Qwen
instruct_type: chatml
pricing:
prompt: '0.0000025'
completion: '0.000003'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- stop
- frequency_penalty
- presence_penalty
- repetition_penalty
- top_k
- min_p
- seed
- logit_bias
- top_a
model_provider: anthracite-org

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@@ -0,0 +1,34 @@
id: anthropic/claude-2:beta
canonical_slug: anthropic/claude-2
hugging_face_id: ''
name: 'Anthropic: Claude v2 (self-moderated)'
type: chat
created: 1700611200
description: 'Claude 2 delivers advancements in key capabilities for enterprises—including an industry-leading 200K token context window, significant reductions in rates of model hallucination, system prompts and a new beta feature: tool use.'
context_length: 200000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,34 @@
id: anthropic/claude-2.0:beta
canonical_slug: anthropic/claude-2.0
hugging_face_id: ''
name: 'Anthropic: Claude v2.0 (self-moderated)'
type: chat
created: 1690502400
description: Anthropic's flagship model. Superior performance on tasks that require complex reasoning. Supports hundreds of pages of text.
context_length: 100000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,34 @@
id: anthropic/claude-2.0
canonical_slug: anthropic/claude-2.0
hugging_face_id: ''
name: 'Anthropic: Claude v2.0'
type: chat
created: 1690502400
description: Anthropic's flagship model. Superior performance on tasks that require complex reasoning. Supports hundreds of pages of text.
context_length: 100000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,34 @@
id: anthropic/claude-2.1:beta
canonical_slug: anthropic/claude-2.1
hugging_face_id: ''
name: 'Anthropic: Claude v2.1 (self-moderated)'
type: chat
created: 1700611200
description: 'Claude 2 delivers advancements in key capabilities for enterprises—including an industry-leading 200K token context window, significant reductions in rates of model hallucination, system prompts and a new beta feature: tool use.'
context_length: 200000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,34 @@
id: anthropic/claude-2.1
canonical_slug: anthropic/claude-2.1
hugging_face_id: ''
name: 'Anthropic: Claude v2.1'
type: chat
created: 1700611200
description: 'Claude 2 delivers advancements in key capabilities for enterprises—including an industry-leading 200K token context window, significant reductions in rates of model hallucination, system prompts and a new beta feature: tool use.'
context_length: 200000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,34 @@
id: anthropic/claude-2
canonical_slug: anthropic/claude-2
hugging_face_id: ''
name: 'Anthropic: Claude v2'
type: chat
created: 1700611200
description: 'Claude 2 delivers advancements in key capabilities for enterprises—including an industry-leading 200K token context window, significant reductions in rates of model hallucination, system prompts and a new beta feature: tool use.'
context_length: 200000
architecture:
modality: text->text
input_modalities:
- text
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.000008'
completion: '0.000024'
input_cache_read: ''
input_cache_write: ''
request: '0'
image: '0'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,43 @@
id: anthropic/claude-3-haiku:beta
canonical_slug: anthropic/claude-3-haiku
hugging_face_id: ''
name: 'Anthropic: Claude 3 Haiku (self-moderated)'
type: chat
created: 1710288000
description: |-
Claude 3 Haiku is Anthropic's fastest and most compact model for
near-instant responsiveness. Quick and accurate targeted performance.
See the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-haiku)
#multimodal
context_length: 200000
architecture:
modality: text+image->text
input_modalities:
- text
- image
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.00000025'
completion: '0.00000125'
input_cache_read: '0.00000003'
input_cache_write: '0.0000003'
request: '0'
image: '0.0004'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- tool_choice
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

View File

@@ -0,0 +1,43 @@
id: anthropic/claude-3-haiku
canonical_slug: anthropic/claude-3-haiku
hugging_face_id: ''
name: 'Anthropic: Claude 3 Haiku'
type: chat
created: 1710288000
description: |-
Claude 3 Haiku is Anthropic's fastest and most compact model for
near-instant responsiveness. Quick and accurate targeted performance.
See the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-haiku)
#multimodal
context_length: 200000
architecture:
modality: text+image->text
input_modalities:
- text
- image
output_modalities:
- text
tokenizer: Claude
instruct_type: null
pricing:
prompt: '0.00000025'
completion: '0.00000125'
input_cache_read: '0.00000003'
input_cache_write: '0.0000003'
request: '0'
image: '0.0004'
web_search: '0'
internal_reasoning: '0'
unit: 1
currency: USD
supported_parameters:
- tools
- tool_choice
- max_tokens
- temperature
- top_p
- top_k
- stop
model_provider: anthropic

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