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Author SHA1 Message Date
Vaayne
1e8251a05e add model catalogs 2025-07-06 21:27:27 +08:00
1487 changed files with 78016 additions and 172236 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

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@@ -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

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@@ -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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@@ -51,7 +51,7 @@ jobs:
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
with:
ref: main
@@ -93,19 +93,17 @@ 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 }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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 }}
NODE_OPTIONS: --max-old-space-size=8192
- name: Build Mac
if: matrix.os == 'macos-latest'
run: |
yarn build:npm mac
yarn build:mac
env:
CSC_LINK: ${{ secrets.CSC_LINK }}
@@ -113,24 +111,19 @@ 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_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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'
run: |
yarn build:npm windows
yarn build:win
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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 }}
NODE_OPTIONS: --max-old-space-size=8192
- name: Rename artifacts with nightly format
shell: bash
@@ -226,7 +219,7 @@ jobs:
shell: bash
- name: Download all artifacts
uses: actions/download-artifact@v5
uses: actions/download-artifact@v4
with:
path: all-artifacts
merge-multiple: false

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@@ -1,8 +1,5 @@
name: Pull Request CI
permissions:
contents: read
on:
workflow_dispatch:
pull_request:
@@ -13,12 +10,10 @@ on:
jobs:
build:
runs-on: ubuntu-latest
env:
PRCI: true
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
- name: Install Node.js
uses: actions/setup-node@v4
@@ -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

View File

@@ -25,7 +25,7 @@ jobs:
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
with:
fetch-depth: 0
@@ -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:
@@ -79,21 +72,20 @@ 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 }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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 }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
- name: Build Mac
if: matrix.os == 'macos-latest'
run: |
sudo -H pip install setuptools
yarn build:npm mac
yarn build:mac
env:
CSC_LINK: ${{ secrets.CSC_LINK }}
@@ -101,24 +93,21 @@ 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_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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'
run: |
yarn build:npm windows
yarn build:win
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYIN_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYIN_CLIENT_SECRET }}
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 }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
- 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 }}

11
.gitignore vendored
View File

@@ -35,34 +35,23 @@ 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
.vitest-cache
vitest.config.*.timestamp-*
# TypeScript incremental build
.tsbuildinfo
# playwright
playwright-report
test-results

View File

@@ -7,5 +7,3 @@ tsconfig.*.json
CHANGELOG*.md
agents.json
src/renderer/src/integration/nutstore/sso/lib
AGENT.md
src/main/integration/cherryin/index.js

View File

@@ -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
}

View File

@@ -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
View File

@@ -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

@@ -1,30 +0,0 @@
diff --git a/index.js b/index.js
index dc071739e79876dff88e1be06a9168e294222d13..b9df7525c62bdf777e89e732e1b0c81f84d872f2 100644
--- a/index.js
+++ b/index.js
@@ -380,7 +380,7 @@ if (!nativeBinding || process.env.NAPI_RS_FORCE_WASI) {
}
}
-if (!nativeBinding) {
+if (!nativeBinding && process.platform !== 'linux') {
if (loadErrors.length > 0) {
throw new Error(
`Cannot find native binding. ` +
@@ -392,6 +392,13 @@ if (!nativeBinding) {
throw new Error(`Failed to load native binding`)
}
-module.exports = nativeBinding
-module.exports.OcrAccuracy = nativeBinding.OcrAccuracy
-module.exports.recognize = nativeBinding.recognize
+if (process.platform === 'linux') {
+ module.exports = {OcrAccuracy: {
+ Fast: 0,
+ Accurate: 1
+ }, recognize: () => Promise.resolve({text: '', confidence: 1.0})}
+}else{
+ module.exports = nativeBinding
+ module.exports.OcrAccuracy = nativeBinding.OcrAccuracy
+ module.exports.recognize = nativeBinding.recognize
+}

View File

@@ -1,48 +0,0 @@
diff --git a/dist/index.cjs b/dist/index.cjs
index 8e560a4406c5cc616c11bb9fd5455ac0dcf47fa3..c7cd0d65ddc971bff71e89f610de82cfdaa5a8c7 100644
--- a/dist/index.cjs
+++ b/dist/index.cjs
@@ -413,6 +413,19 @@ var DragHandlePlugin = ({
}
return false;
},
+ scroll(view) {
+ if (!element || locked) {
+ return false;
+ }
+ if (view.hasFocus()) {
+ hideHandle();
+ currentNode = null;
+ currentNodePos = -1;
+ onNodeChange == null ? void 0 : onNodeChange({ editor, node: null, pos: -1 });
+ return false;
+ }
+ return false;
+ },
mouseleave(_view, e) {
if (locked) {
return false;
diff --git a/dist/index.js b/dist/index.js
index 39e4c3ef9986cd25544d9d3994cf6a9ada74b145..378d9130abbfdd0e1e4f743b5b537743c9ab07d0 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -387,6 +387,19 @@ var DragHandlePlugin = ({
}
return false;
},
+ scroll(view) {
+ if (!element || locked) {
+ return false;
+ }
+ if (view.hasFocus()) {
+ hideHandle();
+ currentNode = null;
+ currentNodePos = -1;
+ onNodeChange == null ? void 0 : onNodeChange({ editor, node: null, pos: -1 });
+ return false;
+ }
+ return false;
+ },
mouseleave(_view, e) {
if (locked) {
return false;

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

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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>
@@ -57,13 +57,13 @@
<div align="center">
<a href="https://hellogithub.com/repository/1605492e1e2a4df3be07abfa4578dd37" target="_blank" style="text-decoration: none"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=1605492e1e2a4df3be07abfa4578dd37" alt="FeaturedHelloGitHub" width="220" height="55" /></a>
<a href="https://trendshift.io/repositories/14318" target="_blank" style="text-decoration: none"><img src="https://trendshift.io/api/badge/repositories/14318" alt="CherryHQ%2Fcherry-studio | Trendshift" width="220" height="55" /></a>
<a href="https://trendshift.io/repositories/11772" target="_blank" style="text-decoration: none"><img src="https://trendshift.io/api/badge/repositories/11772" alt="kangfenmao%2Fcherry-studio | Trendshift" width="220" height="55" /></a>
<a href="https://www.producthunt.com/posts/cherry-studio?embed=true&utm_source=badge-featured&utm_medium=badge&utm_souce=badge-cherry&#0045;studio" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=496640&theme=light" alt="Cherry&#0032;Studio - AI&#0032;Chatbots&#0044;&#0032;AI&#0032;Desktop&#0032;Client | Product Hunt" width="220" height="55" /></a>
</div>
# 🍒 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

View File

@@ -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

@@ -8,7 +8,5 @@
<true/>
<key>com.apple.security.cs.allow-dyld-environment-variables</key>
<true/>
<key>com.apple.security.cs.disable-library-validation</key>
<true/>
</dict>
</plist>

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

View File

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

View File

@@ -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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# 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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@@ -1,11 +0,0 @@
# 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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@@ -1,16 +0,0 @@
# `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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@@ -1,177 +0,0 @@
# 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. |

View File

@@ -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

@@ -53,16 +53,14 @@ 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
- '!node_modules/tesseract.js-core/{tesseract-core.js,tesseract-core.wasm,tesseract-core.wasm.js}' # we don't need source files
- '!node_modules/tesseract.js-core/{tesseract-core-lstm.js,tesseract-core-lstm.wasm,tesseract-core-lstm.wasm.js}' # we don't need source files
- '!node_modules/tesseract.js-core/{tesseract-core-simd-lstm.js,tesseract-core-simd-lstm.wasm,tesseract-core-simd-lstm.wasm.js}' # we don't need source files
- '!**/*.{h,iobj,ipdb,tlog,recipe,vcxproj,vcxproj.filters,Makefile,*.Makefile}' # filter .node build files
asarUnpack:
- resources/**
- '**/*.{metal,exp,lib}'
- 'node_modules/@img/sharp-libvips-*/**'
win:
executableName: Cherry Studio
artifactName: ${productName}-${version}-${arch}-setup.${ext}
@@ -102,7 +100,6 @@ linux:
target:
- target: AppImage
- target: deb
- target: rpm
maintainer: electronjs.org
category: Utility
desktop:
@@ -115,18 +112,14 @@ publish:
url: https://releases.cherry-ai.com
electronDownload:
mirror: https://npmmirror.com/mirrors/electron/
beforePack: scripts/before-pack.js
afterPack: scripts/after-pack.js
afterSign: scripts/notarize.js
artifactBuildCompleted: scripts/artifact-build-completed.js
releaseInfo:
releaseNotes: |
🔧 性能优化:
- 优化AI服务连接方式提升响应速度和稳定性
- 改进模型列表获取功能,减少不必要的网络请求
- 增强各AI服务商的兼容性和连接可靠性
🐛 问题修复:
- 修复部分AI服务商连接失败的问题
- 修复模型配置加载时的潜在错误
- 提升应用整体稳定性和容错能力
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

@@ -4,15 +4,10 @@ import { defineConfig, externalizeDepsPlugin } from 'electron-vite'
import { resolve } from 'path'
import { visualizer } from 'rollup-plugin-visualizer'
import pkg from './package.json' assert { type: 'json' }
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')],
@@ -20,51 +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'),
'@cherrystudio/ai-core/provider': resolve('packages/aiCore/src/core/providers'),
'@cherrystudio/ai-core/built-in/plugins': resolve('packages/aiCore/src/core/plugins/built-in'),
'@cherrystudio/ai-core': resolve('packages/aiCore/src')
'@shared': resolve('packages/shared')
}
},
build: {
rollupOptions: {
external: ['bufferutil', 'utf-8-validate', 'electron', ...Object.keys(pkg.dependencies)],
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',
@@ -77,20 +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'),
'@cherrystudio/ai-core/provider': resolve('packages/aiCore/src/core/providers'),
'@cherrystudio/ai-core/built-in/plugins': resolve('packages/aiCore/src/core/plugins/built-in'),
'@cherrystudio/ai-core': resolve('packages/aiCore/src'),
'@cherrystudio/extension-table-plus': resolve('packages/extension-table-plus/src')
'@shared': resolve('packages/shared')
}
},
optimizeDeps: {
@@ -109,11 +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/**',
@@ -122,8 +62,7 @@ export default defineConfig([
'.yarn/**',
'.gitignore',
'scripts/cloudflare-worker.js',
'src/main/integration/nutstore/sso/lib/**',
'src/main/integration/cherryin/index.js'
'src/main/integration/nutstore/sso/lib/**'
]
}
])

View File

@@ -1,14 +1,11 @@
{
"name": "CherryStudio",
"version": "1.6.0-beta.6",
"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/extension-table-plus"
"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": "concurrently -n \"node,web\" -c \"cyan,magenta\" \"npm run typecheck:node\" \"npm run typecheck:web\"",
"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",
@@ -64,42 +53,30 @@
"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",
"@napi-rs/system-ocr": "patch:@napi-rs/system-ocr@npm%3A1.0.2#~/.yarn/patches/@napi-rs-system-ocr-npm-1.0.2-59e7a78e8b.patch",
"@strongtz/win32-arm64-msvc": "^0.4.7",
"ai-sdk-provider-claude-code": "^1.1.3",
"express": "^5.1.0",
"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": {
"@agentic/exa": "^7.3.3",
"@agentic/searxng": "^7.3.3",
"@agentic/tavily": "^7.3.3",
"@ai-sdk/amazon-bedrock": "^3.0.0",
"@ai-sdk/google-vertex": "^3.0.0",
"@ai-sdk/mistral": "^2.0.0",
"@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/ai-core": "workspace:*",
"@cherrystudio/embedjs": "^0.1.31",
"@cherrystudio/embedjs-libsql": "^0.1.31",
"@cherrystudio/embedjs-loader-csv": "^0.1.31",
@@ -112,11 +89,6 @@
"@cherrystudio/embedjs-loader-xml": "^0.1.31",
"@cherrystudio/embedjs-ollama": "^0.1.31",
"@cherrystudio/embedjs-openai": "^0.1.31",
"@cherrystudio/extension-table-plus": "workspace:^",
"@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",
@@ -127,102 +99,67 @@
"@eslint-react/eslint-plugin": "^1.36.1",
"@eslint/js": "^9.22.0",
"@google/genai": "patch:@google/genai@npm%3A1.0.1#~/.yarn/patches/@google-genai-npm-1.0.1-e26f0f9af7.patch",
"@hello-pangea/dnd": "^18.0.1",
"@hello-pangea/dnd": "^16.6.0",
"@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",
"@openrouter/ai-sdk-provider": "^1.1.2",
"@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": "^3.12.0",
"@swc/plugin-styled-components": "^8.0.4",
"@tanstack/react-query": "^5.85.5",
"@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",
"@tiptap/extension-collaboration": "^3.2.0",
"@tiptap/extension-drag-handle": "patch:@tiptap/extension-drag-handle@npm%3A3.2.0#~/.yarn/patches/@tiptap-extension-drag-handle-npm-3.2.0-5a9ebff7c9.patch",
"@tiptap/extension-drag-handle-react": "^3.2.0",
"@tiptap/extension-image": "^3.2.0",
"@tiptap/extension-list": "^3.2.0",
"@tiptap/extension-mathematics": "^3.2.0",
"@tiptap/extension-mention": "^3.2.0",
"@tiptap/extension-node-range": "^3.2.0",
"@tiptap/extension-table-of-contents": "^3.2.0",
"@tiptap/extension-typography": "^3.2.0",
"@tiptap/extension-underline": "^3.2.0",
"@tiptap/pm": "^3.2.0",
"@tiptap/react": "^3.2.0",
"@tiptap/starter-kit": "^3.2.0",
"@tiptap/suggestion": "^3.2.0",
"@tiptap/y-tiptap": "^3.0.0",
"@truto/turndown-plugin-gfm": "^1.0.2",
"@tryfabric/martian": "^1.2.4",
"@types/cli-progress": "^3",
"@types/express": "^5.0.3",
"@types/diff": "^7",
"@types/fs-extra": "^11",
"@types/he": "^1",
"@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/turndown": "^5.0.5",
"@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",
"ai": "^5.0.29",
"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",
"chokidar": "^4.0.3",
"cli-progress": "^3.12.0",
"code-inspector-plugin": "^0.20.14",
"color": "^5.0.0",
"concurrently": "^9.2.1",
"country-flag-emoji-polyfill": "0.1.8",
"dayjs": "^1.11.11",
"dexie": "^4.0.8",
"dexie-react-hooks": "^1.1.7",
"diff": "^8.0.2",
"diff": "^7.0.0",
"docx": "^9.0.2",
"dompurify": "^3.2.6",
"dotenv-cli": "^7.4.2",
"electron": "37.4.0",
"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",
@@ -233,118 +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",
"he": "^1.2.0",
"html-tags": "^5.1.0",
"html-to-image": "^1.11.13",
"htmlparser2": "^10.0.0",
"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": "^8.1.0",
"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": "^11.10.1",
"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": "^3.12.0",
"strict-url-sanitise": "^0.0.1",
"shiki": "^3.7.0",
"string-width": "^7.2.0",
"striptags": "^3.2.0",
"styled-components": "^6.1.11",
"tar": "^7.4.3",
"tiny-pinyin": "^1.3.2",
"tokenx": "^1.1.0",
"tsx": "^4.20.3",
"turndown-plugin-gfm": "^1.0.2",
"typescript": "^5.6.2",
"undici": "6.21.2",
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"prettier --write"
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}

View File

@@ -1,514 +0,0 @@
# AI Core 基于 Vercel AI SDK 的技术架构
## 1. 架构设计理念
### 1.1 设计目标
- **简化分层**`models`(模型层)→ `runtime`(运行时层),清晰的职责分离
- **统一接口**:使用 Vercel AI SDK 统一不同 AI Provider 的接口差异
- **动态导入**:通过动态导入实现按需加载,减少打包体积
- **最小包装**:直接使用 AI SDK 的类型和接口,避免重复定义
- **插件系统**:基于钩子的通用插件架构,支持请求全生命周期扩展
- **类型安全**:利用 TypeScript 和 AI SDK 的类型系统确保类型安全
- **轻量级**:专注核心功能,保持包的轻量和高效
- **包级独立**:作为独立包管理,便于复用和维护
- **Agent就绪**:为将来集成 OpenAI Agents SDK 预留扩展空间
### 1.2 核心优势
- **标准化**AI SDK 提供统一的模型接口,减少适配工作
- **简化设计**函数式API避免过度抽象
- **更好的开发体验**:完整的 TypeScript 支持和丰富的生态系统
- **性能优化**AI SDK 内置优化和最佳实践
- **模块化设计**:独立包结构,支持跨项目复用
- **可扩展插件**:通用的流转换和参数处理插件系统
- **面向未来**:为 OpenAI Agents SDK 集成做好准备
## 2. 整体架构图
```mermaid
graph TD
subgraph "用户应用 (如 Cherry Studio)"
UI["用户界面"]
Components["应用组件"]
end
subgraph "packages/aiCore (AI Core 包)"
subgraph "Runtime Layer (运行时层)"
RuntimeExecutor["RuntimeExecutor (运行时执行器)"]
PluginEngine["PluginEngine (插件引擎)"]
RuntimeAPI["Runtime API (便捷函数)"]
end
subgraph "Models Layer (模型层)"
ModelFactory["createModel() (模型工厂)"]
ProviderCreator["ProviderCreator (提供商创建器)"]
end
subgraph "Core Systems (核心系统)"
subgraph "Plugins (插件)"
PluginManager["PluginManager (插件管理)"]
BuiltInPlugins["Built-in Plugins (内置插件)"]
StreamTransforms["Stream Transforms (流转换)"]
end
subgraph "Middleware (中间件)"
MiddlewareWrapper["wrapModelWithMiddlewares() (中间件包装)"]
end
subgraph "Providers (提供商)"
Registry["Provider Registry (注册表)"]
Factory["Provider Factory (工厂)"]
end
end
end
subgraph "Vercel AI SDK"
AICore["ai (核心库)"]
OpenAI["@ai-sdk/openai"]
Anthropic["@ai-sdk/anthropic"]
Google["@ai-sdk/google"]
XAI["@ai-sdk/xai"]
Others["其他 19+ Providers"]
end
subgraph "Future: OpenAI Agents SDK"
AgentSDK["@openai/agents (未来集成)"]
AgentExtensions["Agent Extensions (预留)"]
end
UI --> RuntimeAPI
Components --> RuntimeExecutor
RuntimeAPI --> RuntimeExecutor
RuntimeExecutor --> PluginEngine
RuntimeExecutor --> ModelFactory
PluginEngine --> PluginManager
ModelFactory --> ProviderCreator
ModelFactory --> MiddlewareWrapper
ProviderCreator --> Registry
Registry --> Factory
Factory --> OpenAI
Factory --> Anthropic
Factory --> Google
Factory --> XAI
Factory --> Others
RuntimeExecutor --> AICore
AICore --> streamText
AICore --> generateText
AICore --> streamObject
AICore --> generateObject
PluginManager --> StreamTransforms
PluginManager --> BuiltInPlugins
%% 未来集成路径
RuntimeExecutor -.-> AgentSDK
AgentSDK -.-> AgentExtensions
```
## 3. 包结构设计
### 3.1 新架构文件结构
```
packages/aiCore/
├── src/
│ ├── core/ # 核心层 - 内部实现
│ │ ├── models/ # 模型层 - 模型创建和配置
│ │ │ ├── factory.ts # 模型工厂函数 ✅
│ │ │ ├── ModelCreator.ts # 模型创建器 ✅
│ │ │ ├── ConfigManager.ts # 配置管理器 ✅
│ │ │ ├── types.ts # 模型类型定义 ✅
│ │ │ └── index.ts # 模型层导出 ✅
│ │ ├── runtime/ # 运行时层 - 执行和用户API
│ │ │ ├── executor.ts # 运行时执行器 ✅
│ │ │ ├── pluginEngine.ts # 插件引擎 ✅
│ │ │ ├── types.ts # 运行时类型定义 ✅
│ │ │ └── index.ts # 运行时导出 ✅
│ │ ├── middleware/ # 中间件系统
│ │ │ ├── wrapper.ts # 模型包装器 ✅
│ │ │ ├── manager.ts # 中间件管理器 ✅
│ │ │ ├── types.ts # 中间件类型 ✅
│ │ │ └── index.ts # 中间件导出 ✅
│ │ ├── plugins/ # 插件系统
│ │ │ ├── types.ts # 插件类型定义 ✅
│ │ │ ├── manager.ts # 插件管理器 ✅
│ │ │ ├── built-in/ # 内置插件 ✅
│ │ │ │ ├── logging.ts # 日志插件 ✅
│ │ │ │ ├── webSearchPlugin/ # 网络搜索插件 ✅
│ │ │ │ ├── toolUsePlugin/ # 工具使用插件 ✅
│ │ │ │ └── index.ts # 内置插件导出 ✅
│ │ │ ├── README.md # 插件文档 ✅
│ │ │ └── index.ts # 插件导出 ✅
│ │ ├── providers/ # 提供商管理
│ │ │ ├── registry.ts # 提供商注册表 ✅
│ │ │ ├── factory.ts # 提供商工厂 ✅
│ │ │ ├── creator.ts # 提供商创建器 ✅
│ │ │ ├── types.ts # 提供商类型 ✅
│ │ │ ├── utils.ts # 工具函数 ✅
│ │ │ └── index.ts # 提供商导出 ✅
│ │ ├── options/ # 配置选项
│ │ │ ├── factory.ts # 选项工厂 ✅
│ │ │ ├── types.ts # 选项类型 ✅
│ │ │ ├── xai.ts # xAI 选项 ✅
│ │ │ ├── openrouter.ts # OpenRouter 选项 ✅
│ │ │ ├── examples.ts # 示例配置 ✅
│ │ │ └── index.ts # 选项导出 ✅
│ │ └── index.ts # 核心层导出 ✅
│ ├── types.ts # 全局类型定义 ✅
│ └── index.ts # 包主入口文件 ✅
├── package.json # 包配置文件 ✅
├── tsconfig.json # TypeScript 配置 ✅
├── README.md # 包说明文档 ✅
└── AI_SDK_ARCHITECTURE.md # 本文档 ✅
```
## 4. 架构分层详解
### 4.1 Models Layer (模型层)
**职责**:统一的模型创建和配置管理
**核心文件**
- `factory.ts`: 模型工厂函数 (`createModel`, `createModels`)
- `ProviderCreator.ts`: 底层提供商创建和模型实例化
- `types.ts`: 模型配置类型定义
**设计特点**
- 函数式设计,避免不必要的类抽象
- 统一的模型配置接口
- 自动处理中间件应用
- 支持批量模型创建
**核心API**
```typescript
// 模型配置接口
export interface ModelConfig {
providerId: ProviderId
modelId: string
options: ProviderSettingsMap[ProviderId]
middlewares?: LanguageModelV1Middleware[]
}
// 核心模型创建函数
export async function createModel(config: ModelConfig): Promise<LanguageModel>
export async function createModels(configs: ModelConfig[]): Promise<LanguageModel[]>
```
### 4.2 Runtime Layer (运行时层)
**职责**运行时执行器和用户面向的API接口
**核心组件**
- `executor.ts`: 运行时执行器类
- `plugin-engine.ts`: 插件引擎原PluginEnabledAiClient
- `index.ts`: 便捷函数和工厂方法
**设计特点**
- 提供三种使用方式:类实例、静态工厂、函数式调用
- 自动集成模型创建和插件处理
- 完整的类型安全支持
- 为 OpenAI Agents SDK 预留扩展接口
**核心API**
```typescript
// 运行时执行器
export class RuntimeExecutor<T extends ProviderId = ProviderId> {
static create<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T],
plugins?: AiPlugin[]
): RuntimeExecutor<T>
async streamText(modelId: string, params: StreamTextParams): Promise<StreamTextResult>
async generateText(modelId: string, params: GenerateTextParams): Promise<GenerateTextResult>
async streamObject(modelId: string, params: StreamObjectParams): Promise<StreamObjectResult>
async generateObject(modelId: string, params: GenerateObjectParams): Promise<GenerateObjectResult>
}
// 便捷函数式API
export async function streamText<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T],
modelId: string,
params: StreamTextParams,
plugins?: AiPlugin[]
): Promise<StreamTextResult>
```
### 4.3 Plugin System (插件系统)
**职责**:可扩展的插件架构
**核心组件**
- `PluginManager`: 插件生命周期管理
- `built-in/`: 内置插件集合
- 流转换收集和应用
**设计特点**
- 借鉴 Rollup 的钩子分类设计
- 支持流转换 (`experimental_transform`)
- 内置常用插件(日志、计数等)
- 完整的生命周期钩子
**插件接口**
```typescript
export interface AiPlugin {
name: string
enforce?: 'pre' | 'post'
// 【First】首个钩子 - 只执行第一个返回值的插件
resolveModel?: (modelId: string, context: AiRequestContext) => string | null | Promise<string | null>
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null | Promise<any | null>
// 【Sequential】串行钩子 - 链式执行,支持数据转换
transformParams?: (params: any, context: AiRequestContext) => any | Promise<any>
transformResult?: (result: any, context: AiRequestContext) => any | Promise<any>
// 【Parallel】并行钩子 - 不依赖顺序,用于副作用
onRequestStart?: (context: AiRequestContext) => void | Promise<void>
onRequestEnd?: (context: AiRequestContext, result: any) => void | Promise<void>
onError?: (error: Error, context: AiRequestContext) => void | Promise<void>
// 【Stream】流处理
transformStream?: () => TransformStream
}
```
### 4.4 Middleware System (中间件系统)
**职责**AI SDK原生中间件支持
**核心组件**
- `ModelWrapper.ts`: 模型包装函数
**设计哲学**
- 直接使用AI SDK的 `wrapLanguageModel`
- 与插件系统分离,职责明确
- 函数式设计,简化使用
```typescript
export function wrapModelWithMiddlewares(model: LanguageModel, middlewares: LanguageModelV1Middleware[]): LanguageModel
```
### 4.5 Provider System (提供商系统)
**职责**AI Provider注册表和动态导入
**核心组件**
- `registry.ts`: 19+ Provider配置和类型
- `factory.ts`: Provider配置工厂
**支持的Providers**
- OpenAI, Anthropic, Google, XAI
- Azure OpenAI, Amazon Bedrock, Google Vertex
- Groq, Together.ai, Fireworks, DeepSeek
- 等19+ AI SDK官方支持的providers
## 5. 使用方式
### 5.1 函数式调用 (推荐 - 简单场景)
```typescript
import { streamText, generateText } from '@cherrystudio/ai-core/runtime'
// 直接函数调用
const stream = await streamText(
'anthropic',
{ apiKey: 'your-api-key' },
'claude-3',
{ messages: [{ role: 'user', content: 'Hello!' }] },
[loggingPlugin]
)
```
### 5.2 执行器实例 (推荐 - 复杂场景)
```typescript
import { createExecutor } from '@cherrystudio/ai-core/runtime'
// 创建可复用的执行器
const executor = createExecutor('openai', { apiKey: 'your-api-key' }, [plugin1, plugin2])
// 多次使用
const stream = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
const result = await executor.generateText('gpt-4', {
messages: [{ role: 'user', content: 'How are you?' }]
})
```
### 5.3 静态工厂方法
```typescript
import { RuntimeExecutor } from '@cherrystudio/ai-core/runtime'
// 静态创建
const executor = RuntimeExecutor.create('anthropic', { apiKey: 'your-api-key' })
await executor.streamText('claude-3', { messages: [...] })
```
### 5.4 直接模型创建 (高级用法)
```typescript
import { createModel } from '@cherrystudio/ai-core/models'
import { streamText } from 'ai'
// 直接创建模型使用
const model = await createModel({
providerId: 'openai',
modelId: 'gpt-4',
options: { apiKey: 'your-api-key' },
middlewares: [middleware1, middleware2]
})
// 直接使用 AI SDK
const result = await streamText({ model, messages: [...] })
```
## 6. 为 OpenAI Agents SDK 预留的设计
### 6.1 架构兼容性
当前架构完全兼容 OpenAI Agents SDK 的集成需求:
```typescript
// 当前的模型创建
const model = await createModel({
providerId: 'anthropic',
modelId: 'claude-3',
options: { apiKey: 'xxx' }
})
// 将来可以直接用于 OpenAI Agents SDK
import { Agent, run } from '@openai/agents'
const agent = new Agent({
model, // ✅ 直接兼容 LanguageModel 接口
name: 'Assistant',
instructions: '...',
tools: [tool1, tool2]
})
const result = await run(agent, 'user input')
```
### 6.2 预留的扩展点
1. **runtime/agents/** 目录预留
2. **AgentExecutor** 类预留
3. **Agent工具转换插件** 预留
4. **多Agent编排** 预留
### 6.3 未来架构扩展
```
packages/aiCore/src/core/
├── runtime/
│ ├── agents/ # 🚀 未来添加
│ │ ├── AgentExecutor.ts
│ │ ├── WorkflowManager.ts
│ │ └── ConversationManager.ts
│ ├── executor.ts
│ └── index.ts
```
## 7. 架构优势
### 7.1 简化设计
- **移除过度抽象**删除了orchestration层和creation层的复杂包装
- **函数式优先**models层使用函数而非类
- **直接明了**runtime层直接提供用户API
### 7.2 职责清晰
- **Models**: 专注模型创建和配置
- **Runtime**: 专注执行和用户API
- **Plugins**: 专注扩展功能
- **Providers**: 专注AI Provider管理
### 7.3 类型安全
- 完整的 TypeScript 支持
- AI SDK 类型的直接复用
- 避免类型重复定义
### 7.4 灵活使用
- 三种使用模式满足不同需求
- 从简单函数调用到复杂执行器
- 支持直接AI SDK使用
### 7.5 面向未来
- 为 OpenAI Agents SDK 集成做好准备
- 清晰的扩展点和架构边界
- 模块化设计便于功能添加
## 8. 技术决策记录
### 8.1 为什么选择简化的两层架构?
- **职责分离**models专注创建runtime专注执行
- **模块化**:每层都有清晰的边界和职责
- **扩展性**为Agent功能预留了清晰的扩展空间
### 8.2 为什么选择函数式设计?
- **简洁性**:避免不必要的类设计
- **性能**:减少对象创建开销
- **易用性**:函数调用更直观
### 8.3 为什么分离插件和中间件?
- **职责明确**: 插件处理应用特定需求
- **原生支持**: 中间件使用AI SDK原生功能
- **灵活性**: 两套系统可以独立演进
## 9. 总结
AI Core架构实现了
### 9.1 核心特点
-**简化架构**: 2层核心架构职责清晰
-**函数式设计**: models层完全函数化
-**类型安全**: 统一的类型定义和AI SDK类型复用
-**插件扩展**: 强大的插件系统
-**多种使用方式**: 满足不同复杂度需求
-**Agent就绪**: 为OpenAI Agents SDK集成做好准备
### 9.2 核心价值
- **统一接口**: 一套API支持19+ AI providers
- **灵活使用**: 函数式、实例式、静态工厂式
- **强类型**: 完整的TypeScript支持
- **可扩展**: 插件和中间件双重扩展能力
- **高性能**: 最小化包装直接使用AI SDK
- **面向未来**: Agent SDK集成架构就绪
### 9.3 未来发展
这个架构提供了:
- **优秀的开发体验**: 简洁的API和清晰的使用模式
- **强大的扩展能力**: 为Agent功能预留了完整的架构空间
- **良好的维护性**: 职责分离明确,代码易于维护
- **广泛的适用性**: 既适合简单调用也适合复杂应用

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@@ -1,433 +0,0 @@
# @cherrystudio/ai-core
Cherry Studio AI Core 是一个基于 Vercel AI SDK 的统一 AI Provider 接口包,为 AI 应用提供强大的抽象层和插件化架构。
## ✨ 核心亮点
### 🏗️ 优雅的架构设计
- **简化分层**`models`(模型层)→ `runtime`(运行时层),清晰的职责分离
- **函数式优先**:避免过度抽象,提供简洁直观的 API
- **类型安全**:完整的 TypeScript 支持,直接复用 AI SDK 类型系统
- **最小包装**:直接使用 AI SDK 的接口,避免重复定义和性能损耗
### 🔌 强大的插件系统
- **生命周期钩子**:支持请求全生命周期的扩展点
- **流转换支持**:基于 AI SDK 的 `experimental_transform` 实现流处理
- **插件分类**First、Sequential、Parallel 三种钩子类型,满足不同场景
- **内置插件**webSearch、logging、toolUse 等开箱即用的功能
### 🌐 统一多 Provider 接口
- **扩展注册**:支持自定义 Provider 注册,无限扩展能力
- **配置统一**:统一的配置接口,简化多 Provider 管理
### 🚀 多种使用方式
- **函数式调用**:适合简单场景的直接函数调用
- **执行器实例**:适合复杂场景的可复用执行器
- **静态工厂**:便捷的静态创建方法
- **原生兼容**:完全兼容 AI SDK 原生 Provider Registry
### 🔮 面向未来
- **Agent 就绪**:为 OpenAI Agents SDK 集成预留架构空间
- **模块化设计**:独立包结构,支持跨项目复用
- **渐进式迁移**:可以逐步从现有 AI SDK 代码迁移
## 特性
- 🚀 统一的 AI Provider 接口
- 🔄 动态导入支持
- 🛠️ TypeScript 支持
- 📦 强大的插件系统
- 🌍 内置webSearch(Openai,Google,Anthropic,xAI)
- 🎯 多种使用模式(函数式/实例式/静态工厂)
- 🔌 可扩展的 Provider 注册系统
- 🧩 完整的中间件支持
- 📊 插件统计和调试功能
## 支持的 Providers
基于 [AI SDK 官方支持的 providers](https://ai-sdk.dev/providers/ai-sdk-providers)
**核心 Providers内置支持:**
- OpenAI
- Anthropic
- Google Generative AI
- OpenAI-Compatible
- xAI (Grok)
- Azure OpenAI
- DeepSeek
**扩展 Providers通过注册API支持:**
- Google Vertex AI
- ...
- 自定义 Provider
## 安装
```bash
npm install @cherrystudio/ai-core ai
```
### React Native
如果你在 React Native 项目中使用此包,需要在 `metro.config.js` 中添加以下配置:
```javascript
// metro.config.js
const { getDefaultConfig } = require('expo/metro-config')
const config = getDefaultConfig(__dirname)
// 添加对 @cherrystudio/ai-core 的支持
config.resolver.resolverMainFields = ['react-native', 'browser', 'main']
config.resolver.platforms = ['ios', 'android', 'native', 'web']
module.exports = config
```
还需要安装你要使用的 AI SDK provider:
```bash
npm install @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google
```
## 使用示例
### 基础用法
```typescript
import { AiCore } from '@cherrystudio/ai-core'
// 创建 OpenAI executor
const executor = AiCore.create('openai', {
apiKey: 'your-api-key'
})
// 流式生成
const result = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
// 非流式生成
const response = await executor.generateText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
```
### 便捷函数
```typescript
import { createOpenAIExecutor } from '@cherrystudio/ai-core'
// 快速创建 OpenAI executor
const executor = createOpenAIExecutor({
apiKey: 'your-api-key'
})
// 使用 executor
const result = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
```
### 多 Provider 支持
```typescript
import { AiCore } from '@cherrystudio/ai-core'
// 支持多种 AI providers
const openaiExecutor = AiCore.create('openai', { apiKey: 'openai-key' })
const anthropicExecutor = AiCore.create('anthropic', { apiKey: 'anthropic-key' })
const googleExecutor = AiCore.create('google', { apiKey: 'google-key' })
const xaiExecutor = AiCore.create('xai', { apiKey: 'xai-key' })
```
### 扩展 Provider 注册
对于非内置的 providers可以通过注册 API 扩展支持:
```typescript
import { registerProvider, AiCore } from '@cherrystudio/ai-core'
// 方式一:导入并注册第三方 provider
import { createGroq } from '@ai-sdk/groq'
registerProvider({
id: 'groq',
name: 'Groq',
creator: createGroq,
supportsImageGeneration: false
})
// 现在可以使用 Groq
const groqExecutor = AiCore.create('groq', { apiKey: 'groq-key' })
// 方式二:动态导入方式注册
registerProvider({
id: 'mistral',
name: 'Mistral AI',
import: () => import('@ai-sdk/mistral'),
creatorFunctionName: 'createMistral'
})
const mistralExecutor = AiCore.create('mistral', { apiKey: 'mistral-key' })
```
## 🔌 插件系统
AI Core 提供了强大的插件系统,支持请求全生命周期的扩展。
### 内置插件
#### webSearchPlugin - 网络搜索插件
为不同 AI Provider 提供统一的网络搜索能力:
```typescript
import { webSearchPlugin } from '@cherrystudio/ai-core/built-in/plugins'
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [
webSearchPlugin({
openai: {
/* OpenAI 搜索配置 */
},
anthropic: { maxUses: 5 },
google: {
/* Google 搜索配置 */
},
xai: {
mode: 'on',
returnCitations: true,
maxSearchResults: 5,
sources: [{ type: 'web' }, { type: 'x' }, { type: 'news' }]
}
})
])
```
#### loggingPlugin - 日志插件
提供详细的请求日志记录:
```typescript
import { createLoggingPlugin } from '@cherrystudio/ai-core/built-in/plugins'
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [
createLoggingPlugin({
logLevel: 'info',
includeParams: true,
includeResult: false
})
])
```
#### promptToolUsePlugin - 提示工具使用插件
为不支持原生 Function Call 的模型提供 prompt 方式的工具调用:
```typescript
import { createPromptToolUsePlugin } from '@cherrystudio/ai-core/built-in/plugins'
// 对于不支持 function call 的模型
const executor = AiCore.create(
'providerId',
{
apiKey: 'your-key',
baseURL: 'https://your-model-endpoint'
},
[
createPromptToolUsePlugin({
enabled: true,
// 可选:自定义系统提示符构建
buildSystemPrompt: (userPrompt, tools) => {
return `${userPrompt}\n\nAvailable tools: ${Object.keys(tools).join(', ')}`
}
})
]
)
```
### 自定义插件
创建自定义插件非常简单:
```typescript
import { definePlugin } from '@cherrystudio/ai-core'
const customPlugin = definePlugin({
name: 'custom-plugin',
enforce: 'pre', // 'pre' | 'post' | undefined
// 在请求开始时记录日志
onRequestStart: async (context) => {
console.log(`Starting request for model: ${context.modelId}`)
},
// 转换请求参数
transformParams: async (params, context) => {
// 添加自定义系统消息
if (params.messages) {
params.messages.unshift({
role: 'system',
content: 'You are a helpful assistant.'
})
}
return params
},
// 处理响应结果
transformResult: async (result, context) => {
// 添加元数据
if (result.text) {
result.metadata = {
processedAt: new Date().toISOString(),
modelId: context.modelId
}
}
return result
}
})
// 使用自定义插件
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [customPlugin])
```
### 使用 AI SDK 原生 Provider 注册表
> https://ai-sdk.dev/docs/reference/ai-sdk-core/provider-registry
除了使用内建的 provider 管理,你还可以使用 AI SDK 原生的 `createProviderRegistry` 来构建自己的 provider 注册表。
#### 基本用法示例
```typescript
import { createClient } from '@cherrystudio/ai-core'
import { createProviderRegistry } from 'ai'
import { createOpenAI } from '@ai-sdk/openai'
import { anthropic } from '@ai-sdk/anthropic'
// 1. 创建 AI SDK 原生注册表
export const registry = createProviderRegistry({
// register provider with prefix and default setup:
anthropic,
// register provider with prefix and custom setup:
openai: createOpenAI({
apiKey: process.env.OPENAI_API_KEY
})
})
// 2. 创建client,'openai'可以传空或者传providerId(内建的provider)
const client = PluginEnabledAiClient.create('openai', {
apiKey: process.env.OPENAI_API_KEY
})
// 3. 方式1使用内建逻辑传统方式
const result1 = await client.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello with built-in logic!' }]
})
// 4. 方式2使用自定义注册表灵活方式
const result2 = await client.streamText({
model: registry.languageModel('openai:gpt-4'),
messages: [{ role: 'user', content: 'Hello with custom registry!' }]
})
// 5. 支持的重载方法
await client.generateObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ name: z.string() }),
messages: [{ role: 'user', content: 'Generate a user' }]
})
await client.streamObject({
model: registry.languageModel('anthropic:claude-3-opus-20240229'),
schema: z.object({ items: z.array(z.string()) }),
messages: [{ role: 'user', content: 'Generate a list' }]
})
```
#### 与插件系统配合使用
更强大的是,你还可以将自定义注册表与 Cherry Studio 的插件系统结合使用:
```typescript
import { PluginEnabledAiClient } from '@cherrystudio/ai-core'
import { createProviderRegistry } from 'ai'
import { createOpenAI } from '@ai-sdk/openai'
import { anthropic } from '@ai-sdk/anthropic'
// 1. 创建带插件的客户端
const client = PluginEnabledAiClient.create(
'openai',
{
apiKey: process.env.OPENAI_API_KEY
},
[LoggingPlugin, RetryPlugin]
)
// 2. 创建自定义注册表
const registry = createProviderRegistry({
openai: createOpenAI({ apiKey: process.env.OPENAI_API_KEY }),
anthropic: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY })
})
// 3. 方式1使用内建逻辑 + 完整插件系统
await client.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello with plugins!' }]
})
// 4. 方式2使用自定义注册表 + 有限插件支持
await client.streamText({
model: registry.languageModel('anthropic:claude-3-opus-20240229'),
messages: [{ role: 'user', content: 'Hello from Claude!' }]
})
// 5. 支持的方法
await client.generateObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ name: z.string() }),
messages: [{ role: 'user', content: 'Generate a user' }]
})
await client.streamObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ items: z.array(z.string()) }),
messages: [{ role: 'user', content: 'Generate a list' }]
})
```
#### 混合使用的优势
- **灵活性**:可以根据需要选择使用内建逻辑或自定义注册表
- **兼容性**:完全兼容 AI SDK 的 `createProviderRegistry` API
- **渐进式**:可以逐步迁移现有代码,无需一次性重构
- **插件支持**:自定义注册表仍可享受插件系统的部分功能
- **最佳实践**:结合两种方式的优点,既有动态加载的性能优势,又有统一注册表的便利性
## 📚 相关资源
- [Vercel AI SDK 文档](https://ai-sdk.dev/)
- [Cherry Studio 项目](https://github.com/CherryHQ/cherry-studio)
- [AI SDK Providers](https://ai-sdk.dev/providers/ai-sdk-providers)
## 未来版本
- 🔮 多 Agent 编排
- 🔮 可视化插件配置
- 🔮 实时监控和分析
- 🔮 云端插件同步
## 📄 License
MIT License - 详见 [LICENSE](https://github.com/CherryHQ/cherry-studio/blob/main/LICENSE) 文件
---
**Cherry Studio AI Core** - 让 AI 开发更简单、更强大、更灵活 🚀

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/**
* Hub Provider 使用示例
*
* 演示如何使用简化后的Hub Provider功能来路由到多个底层provider
*/
import { createHubProvider, initializeProvider, providerRegistry } from '../src/index'
async function demonstrateHubProvider() {
try {
// 1. 初始化底层providers
console.log('📦 初始化底层providers...')
initializeProvider('openai', {
apiKey: process.env.OPENAI_API_KEY || 'sk-test-key'
})
initializeProvider('anthropic', {
apiKey: process.env.ANTHROPIC_API_KEY || 'sk-ant-test-key'
})
// 2. 创建Hub Provider自动包含所有已初始化的providers
console.log('🌐 创建Hub Provider...')
const aihubmixProvider = createHubProvider({
hubId: 'aihubmix',
debug: true
})
// 3. 注册Hub Provider
providerRegistry.registerProvider('aihubmix', aihubmixProvider)
console.log('✅ Hub Provider "aihubmix" 注册成功')
// 4. 使用Hub Provider访问不同的模型
console.log('\n🚀 使用Hub模型...')
// 通过Hub路由到OpenAI
const openaiModel = providerRegistry.languageModel('aihubmix:openai:gpt-4')
console.log('✓ OpenAI模型已获取:', openaiModel.modelId)
// 通过Hub路由到Anthropic
const anthropicModel = providerRegistry.languageModel('aihubmix:anthropic:claude-3.5-sonnet')
console.log('✓ Anthropic模型已获取:', anthropicModel.modelId)
// 5. 演示错误处理
console.log('\n❌ 演示错误处理...')
try {
// 尝试访问未初始化的provider
providerRegistry.languageModel('aihubmix:google:gemini-pro')
} catch (error) {
console.log('预期错误:', error.message)
}
try {
// 尝试使用错误的模型ID格式
providerRegistry.languageModel('aihubmix:invalid-format')
} catch (error) {
console.log('预期错误:', error.message)
}
// 6. 多个Hub Provider示例
console.log('\n🔄 创建多个Hub Provider...')
const localHubProvider = createHubProvider({
hubId: 'local-ai'
})
providerRegistry.registerProvider('local-ai', localHubProvider)
console.log('✅ Hub Provider "local-ai" 注册成功')
console.log('\n🎉 Hub Provider演示完成')
} catch (error) {
console.error('💥 演示过程中发生错误:', error)
}
}
// 演示简化的使用方式
function simplifiedUsageExample() {
console.log('\n📝 简化使用示例:')
console.log(`
// 1. 初始化providers
initializeProvider('openai', { apiKey: 'sk-xxx' })
initializeProvider('anthropic', { apiKey: 'sk-ant-xxx' })
// 2. 创建并注册Hub Provider
const hubProvider = createHubProvider({ hubId: 'aihubmix' })
providerRegistry.registerProvider('aihubmix', hubProvider)
// 3. 直接使用
const model1 = providerRegistry.languageModel('aihubmix:openai:gpt-4')
const model2 = providerRegistry.languageModel('aihubmix:anthropic:claude-3.5-sonnet')
`)
}
// 运行演示
if (require.main === module) {
demonstrateHubProvider()
simplifiedUsageExample()
}
export { demonstrateHubProvider, simplifiedUsageExample }

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/**
* Image Generation Example
* 演示如何使用 aiCore 的文生图功能
*/
import { createExecutor, generateImage } from '../src/index'
async function main() {
// 方式1: 使用执行器实例
console.log('📸 创建 OpenAI 图像生成执行器...')
const executor = createExecutor('openai', {
apiKey: process.env.OPENAI_API_KEY!
})
try {
console.log('🎨 使用执行器生成图像...')
const result1 = await executor.generateImage('dall-e-3', {
prompt: 'A futuristic cityscape at sunset with flying cars',
size: '1024x1024',
n: 1
})
console.log('✅ 图像生成成功!')
console.log('📊 结果:', {
imagesCount: result1.images.length,
mediaType: result1.image.mediaType,
hasBase64: !!result1.image.base64,
providerMetadata: result1.providerMetadata
})
} catch (error) {
console.error('❌ 执行器生成失败:', error)
}
// 方式2: 使用直接调用 API
try {
console.log('🎨 使用直接 API 生成图像...')
const result2 = await generateImage('openai', { apiKey: process.env.OPENAI_API_KEY! }, 'dall-e-3', {
prompt: 'A magical forest with glowing mushrooms and fairy lights',
aspectRatio: '16:9',
providerOptions: {
openai: {
quality: 'hd',
style: 'vivid'
}
}
})
console.log('✅ 直接 API 生成成功!')
console.log('📊 结果:', {
imagesCount: result2.images.length,
mediaType: result2.image.mediaType,
hasBase64: !!result2.image.base64
})
} catch (error) {
console.error('❌ 直接 API 生成失败:', error)
}
// 方式3: 支持其他提供商 (Google Imagen)
if (process.env.GOOGLE_API_KEY) {
try {
console.log('🎨 使用 Google Imagen 生成图像...')
const googleExecutor = createExecutor('google', {
apiKey: process.env.GOOGLE_API_KEY!
})
const result3 = await googleExecutor.generateImage('imagen-3.0-generate-002', {
prompt: 'A serene mountain lake at dawn with mist rising from the water',
aspectRatio: '1:1'
})
console.log('✅ Google Imagen 生成成功!')
console.log('📊 结果:', {
imagesCount: result3.images.length,
mediaType: result3.image.mediaType,
hasBase64: !!result3.image.base64
})
} catch (error) {
console.error('❌ Google Imagen 生成失败:', error)
}
}
// 方式4: 支持插件系统
const pluginExample = async () => {
console.log('🔌 演示插件系统...')
// 创建一个示例插件,用于修改提示词
const promptEnhancerPlugin = {
name: 'prompt-enhancer',
transformParams: async (params: any) => {
console.log('🔧 插件: 增强提示词...')
return {
...params,
prompt: `${params.prompt}, highly detailed, cinematic lighting, 4K resolution`
}
},
transformResult: async (result: any) => {
console.log('🔧 插件: 处理结果...')
return {
...result,
enhanced: true
}
}
}
const executorWithPlugin = createExecutor(
'openai',
{
apiKey: process.env.OPENAI_API_KEY!
},
[promptEnhancerPlugin]
)
try {
const result4 = await executorWithPlugin.generateImage('dall-e-3', {
prompt: 'A cute robot playing in a garden'
})
console.log('✅ 插件系统生成成功!')
console.log('📊 结果:', {
imagesCount: result4.images.length,
enhanced: (result4 as any).enhanced,
mediaType: result4.image.mediaType
})
} catch (error) {
console.error('❌ 插件系统生成失败:', error)
}
}
await pluginExample()
}
// 错误处理演示
async function errorHandlingExample() {
console.log('⚠️ 演示错误处理...')
try {
const executor = createExecutor('openai', {
apiKey: 'invalid-key'
})
await executor.generateImage('dall-e-3', {
prompt: 'Test image'
})
} catch (error: any) {
console.log('✅ 成功捕获错误:', error.constructor.name)
console.log('📋 错误信息:', error.message)
console.log('🏷️ 提供商ID:', error.providerId)
console.log('🏷️ 模型ID:', error.modelId)
}
}
// 运行示例
if (require.main === module) {
main()
.then(() => {
console.log('🎉 所有示例完成!')
return errorHandlingExample()
})
.then(() => {
console.log('🎯 示例程序结束')
process.exit(0)
})
.catch((error) => {
console.error('💥 程序执行出错:', error)
process.exit(1)
})
}

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{
"name": "@cherrystudio/ai-core",
"version": "1.0.0-alpha.11",
"description": "Cherry Studio AI Core - Unified AI Provider Interface Based on Vercel AI SDK",
"main": "dist/index.js",
"module": "dist/index.mjs",
"types": "dist/index.d.ts",
"react-native": "dist/index.js",
"scripts": {
"build": "tsdown",
"dev": "tsc -w",
"clean": "rm -rf dist",
"test": "vitest run",
"test:watch": "vitest"
},
"keywords": [
"ai",
"sdk",
"openai",
"anthropic",
"google",
"cherry-studio",
"vercel-ai-sdk"
],
"author": "Cherry Studio",
"license": "MIT",
"repository": {
"type": "git",
"url": "git+https://github.com/CherryHQ/cherry-studio.git"
},
"bugs": {
"url": "https://github.com/CherryHQ/cherry-studio/issues"
},
"homepage": "https://github.com/CherryHQ/cherry-studio#readme",
"peerDependencies": {
"ai": "^5.0.26"
},
"dependencies": {
"@ai-sdk/anthropic": "^2.0.5",
"@ai-sdk/azure": "^2.0.16",
"@ai-sdk/deepseek": "^1.0.9",
"@ai-sdk/google": "^2.0.7",
"@ai-sdk/openai": "^2.0.19",
"@ai-sdk/openai-compatible": "^1.0.9",
"@ai-sdk/provider": "^2.0.0",
"@ai-sdk/provider-utils": "^3.0.4",
"@ai-sdk/xai": "^2.0.9",
"zod": "^3.25.0"
},
"devDependencies": {
"tsdown": "^0.12.9",
"typescript": "^5.0.0",
"vitest": "^3.2.4"
},
"sideEffects": false,
"engines": {
"node": ">=18.0.0"
},
"files": [
"dist"
],
"exports": {
".": {
"types": "./dist/index.d.ts",
"react-native": "./dist/index.js",
"import": "./dist/index.mjs",
"require": "./dist/index.js",
"default": "./dist/index.js"
},
"./built-in/plugins": {
"types": "./dist/built-in/plugins/index.d.ts",
"react-native": "./dist/built-in/plugins/index.js",
"import": "./dist/built-in/plugins/index.mjs",
"require": "./dist/built-in/plugins/index.js",
"default": "./dist/built-in/plugins/index.js"
},
"./provider": {
"types": "./dist/provider/index.d.ts",
"react-native": "./dist/provider/index.js",
"import": "./dist/provider/index.mjs",
"require": "./dist/provider/index.js",
"default": "./dist/provider/index.js"
}
}
}

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@@ -1,2 +0,0 @@
// 模拟 Vite SSR helper避免 Node 环境找不到时报错
;(globalThis as any).__vite_ssr_exportName__ = (name: string, value: any) => value

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@@ -1,3 +0,0 @@
# @cherryStudio-aiCore
Core

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@@ -1,17 +0,0 @@
/**
* Core 模块导出
* 内部核心功能,供其他模块使用,不直接面向最终调用者
*/
// 中间件系统
export type { NamedMiddleware } from './middleware'
export { createMiddlewares, wrapModelWithMiddlewares } from './middleware'
// 创建管理
export { globalModelResolver, ModelResolver } from './models'
export type { ModelConfig as ModelConfigType } from './models/types'
// 执行管理
export type { ToolUseRequestContext } from './plugins/built-in/toolUsePlugin/type'
export { createExecutor, createOpenAICompatibleExecutor } from './runtime'
export type { RuntimeConfig } from './runtime/types'

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@@ -1,8 +0,0 @@
/**
* Middleware 模块导出
* 提供通用的中间件管理能力
*/
export { createMiddlewares } from './manager'
export type { NamedMiddleware } from './types'
export { wrapModelWithMiddlewares } from './wrapper'

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@@ -1,16 +0,0 @@
/**
* 中间件管理器
* 专注于 AI SDK 中间件的管理,与插件系统分离
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
/**
* 创建中间件列表
* 合并用户提供的中间件
*/
export function createMiddlewares(userMiddlewares: LanguageModelV2Middleware[] = []): LanguageModelV2Middleware[] {
// 未来可以在这里添加默认的中间件
const defaultMiddlewares: LanguageModelV2Middleware[] = []
return [...defaultMiddlewares, ...userMiddlewares]
}

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@@ -1,12 +0,0 @@
/**
* 中间件系统类型定义
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
/**
* 具名中间件接口
*/
export interface NamedMiddleware {
name: string
middleware: LanguageModelV2Middleware
}

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@@ -1,23 +0,0 @@
/**
* 模型包装工具函数
* 用于将中间件应用到LanguageModel上
*/
import { LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
import { wrapLanguageModel } from 'ai'
/**
* 使用中间件包装模型
*/
export function wrapModelWithMiddlewares(
model: LanguageModelV2,
middlewares: LanguageModelV2Middleware[]
): LanguageModelV2 {
if (middlewares.length === 0) {
return model
}
return wrapLanguageModel({
model,
middleware: middlewares
})
}

View File

@@ -1,125 +0,0 @@
/**
* 模型解析器 - models模块的核心
* 负责将modelId解析为AI SDK的LanguageModel实例
* 支持传统格式和命名空间格式
* 集成了来自 ModelCreator 的特殊处理逻辑
*/
import { EmbeddingModelV2, ImageModelV2, LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
import { wrapModelWithMiddlewares } from '../middleware/wrapper'
import { DEFAULT_SEPARATOR, globalRegistryManagement } from '../providers/RegistryManagement'
export class ModelResolver {
/**
* 核心方法解析任意格式的modelId为语言模型
*
* @param modelId 模型ID支持 'gpt-4' 和 'anthropic>claude-3' 两种格式
* @param fallbackProviderId 当modelId为传统格式时使用的providerId
* @param providerOptions provider配置选项用于OpenAI模式选择等
* @param middlewares 中间件数组,会应用到最终模型上
*/
async resolveLanguageModel(
modelId: string,
fallbackProviderId: string,
providerOptions?: any,
middlewares?: LanguageModelV2Middleware[]
): Promise<LanguageModelV2> {
let finalProviderId = fallbackProviderId
let model: LanguageModelV2
// 🎯 处理 OpenAI 模式选择逻辑 (从 ModelCreator 迁移)
if ((fallbackProviderId === 'openai' || fallbackProviderId === 'azure') && providerOptions?.mode === 'chat') {
finalProviderId = `${fallbackProviderId}-chat`
}
// 检查是否是命名空间格式
if (modelId.includes(DEFAULT_SEPARATOR)) {
model = this.resolveNamespacedModel(modelId)
} else {
// 传统格式:使用处理后的 providerId + modelId
model = this.resolveTraditionalModel(finalProviderId, modelId)
}
// 🎯 应用中间件(如果有)
if (middlewares && middlewares.length > 0) {
model = wrapModelWithMiddlewares(model, middlewares)
}
return model
}
/**
* 解析文本嵌入模型
*/
async resolveTextEmbeddingModel(modelId: string, fallbackProviderId: string): Promise<EmbeddingModelV2<string>> {
if (modelId.includes(DEFAULT_SEPARATOR)) {
return this.resolveNamespacedEmbeddingModel(modelId)
}
return this.resolveTraditionalEmbeddingModel(fallbackProviderId, modelId)
}
/**
* 解析图像模型
*/
async resolveImageModel(modelId: string, fallbackProviderId: string): Promise<ImageModelV2> {
if (modelId.includes(DEFAULT_SEPARATOR)) {
return this.resolveNamespacedImageModel(modelId)
}
return this.resolveTraditionalImageModel(fallbackProviderId, modelId)
}
/**
* 解析命名空间格式的语言模型
* aihubmix:anthropic:claude-3 -> globalRegistryManagement.languageModel('aihubmix:anthropic:claude-3')
*/
private resolveNamespacedModel(modelId: string): LanguageModelV2 {
return globalRegistryManagement.languageModel(modelId as any)
}
/**
* 解析传统格式的语言模型
* providerId: 'openai', modelId: 'gpt-4' -> globalRegistryManagement.languageModel('openai:gpt-4')
*/
private resolveTraditionalModel(providerId: string, modelId: string): LanguageModelV2 {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
console.log('fullModelId', fullModelId)
return globalRegistryManagement.languageModel(fullModelId as any)
}
/**
* 解析命名空间格式的嵌入模型
*/
private resolveNamespacedEmbeddingModel(modelId: string): EmbeddingModelV2<string> {
return globalRegistryManagement.textEmbeddingModel(modelId as any)
}
/**
* 解析传统格式的嵌入模型
*/
private resolveTraditionalEmbeddingModel(providerId: string, modelId: string): EmbeddingModelV2<string> {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
return globalRegistryManagement.textEmbeddingModel(fullModelId as any)
}
/**
* 解析命名空间格式的图像模型
*/
private resolveNamespacedImageModel(modelId: string): ImageModelV2 {
return globalRegistryManagement.imageModel(modelId as any)
}
/**
* 解析传统格式的图像模型
*/
private resolveTraditionalImageModel(providerId: string, modelId: string): ImageModelV2 {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
return globalRegistryManagement.imageModel(fullModelId as any)
}
}
/**
* 全局模型解析器实例
*/
export const globalModelResolver = new ModelResolver()

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@@ -1,9 +0,0 @@
/**
* Models 模块统一导出 - 简化版
*/
// 核心模型解析器
export { globalModelResolver, ModelResolver } from './ModelResolver'
// 保留的类型定义(可能被其他地方使用)
export type { ModelConfig as ModelConfigType } from './types'

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@@ -1,15 +0,0 @@
/**
* Creation 模块类型定义
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
import type { ProviderId, ProviderSettingsMap } from '../providers/types'
export interface ModelConfig<T extends ProviderId = ProviderId> {
providerId: T
modelId: string
providerSettings: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' }
middlewares?: LanguageModelV2Middleware[]
// 额外模型参数
extraModelConfig?: Record<string, any>
}

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@@ -1,87 +0,0 @@
import { streamText } from 'ai'
import {
createAnthropicOptions,
createGenericProviderOptions,
createGoogleOptions,
createOpenAIOptions,
mergeProviderOptions
} from './factory'
// 示例1: 使用已知供应商的严格类型约束
export function exampleOpenAIWithOptions() {
const openaiOptions = createOpenAIOptions({
reasoningEffort: 'medium'
})
// 这里会有类型检查确保选项符合OpenAI的设置
return streamText({
model: {} as any, // 实际使用时替换为真实模型
prompt: 'Hello',
providerOptions: openaiOptions
})
}
// 示例2: 使用Anthropic供应商选项
export function exampleAnthropicWithOptions() {
const anthropicOptions = createAnthropicOptions({
thinking: {
type: 'enabled',
budgetTokens: 1000
}
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: anthropicOptions
})
}
// 示例3: 使用Google供应商选项
export function exampleGoogleWithOptions() {
const googleOptions = createGoogleOptions({
thinkingConfig: {
includeThoughts: true,
thinkingBudget: 1000
}
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: googleOptions
})
}
// 示例4: 使用未知供应商(通用类型)
export function exampleUnknownProviderWithOptions() {
const customProviderOptions = createGenericProviderOptions('custom-provider', {
temperature: 0.7,
customSetting: 'value',
anotherOption: true
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: customProviderOptions
})
}
// 示例5: 合并多个供应商选项
export function exampleMergedOptions() {
const openaiOptions = createOpenAIOptions({})
const customOptions = createGenericProviderOptions('custom', {
customParam: 'value'
})
const mergedOptions = mergeProviderOptions(openaiOptions, customOptions)
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: mergedOptions
})
}

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@@ -1,71 +0,0 @@
import { ExtractProviderOptions, ProviderOptionsMap, TypedProviderOptions } from './types'
/**
* 创建特定供应商的选项
* @param provider 供应商名称
* @param options 供应商特定的选项
* @returns 格式化的provider options
*/
export function createProviderOptions<T extends keyof ProviderOptionsMap>(
provider: T,
options: ExtractProviderOptions<T>
): Record<T, ExtractProviderOptions<T>> {
return { [provider]: options } as Record<T, ExtractProviderOptions<T>>
}
/**
* 创建任意供应商的选项(包括未知供应商)
* @param provider 供应商名称
* @param options 供应商选项
* @returns 格式化的provider options
*/
export function createGenericProviderOptions<T extends string>(
provider: T,
options: Record<string, any>
): Record<T, Record<string, any>> {
return { [provider]: options } as Record<T, Record<string, any>>
}
/**
* 合并多个供应商的options
* @param optionsMap 包含多个供应商选项的对象
* @returns 合并后的TypedProviderOptions
*/
export function mergeProviderOptions(...optionsMap: Partial<TypedProviderOptions>[]): TypedProviderOptions {
return Object.assign({}, ...optionsMap)
}
/**
* 创建OpenAI供应商选项的便捷函数
*/
export function createOpenAIOptions(options: ExtractProviderOptions<'openai'>) {
return createProviderOptions('openai', options)
}
/**
* 创建Anthropic供应商选项的便捷函数
*/
export function createAnthropicOptions(options: ExtractProviderOptions<'anthropic'>) {
return createProviderOptions('anthropic', options)
}
/**
* 创建Google供应商选项的便捷函数
*/
export function createGoogleOptions(options: ExtractProviderOptions<'google'>) {
return createProviderOptions('google', options)
}
/**
* 创建OpenRouter供应商选项的便捷函数
*/
export function createOpenRouterOptions(options: ExtractProviderOptions<'openrouter'>) {
return createProviderOptions('openrouter', options)
}
/**
* 创建XAI供应商选项的便捷函数
*/
export function createXaiOptions(options: ExtractProviderOptions<'xai'>) {
return createProviderOptions('xai', options)
}

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@@ -1,2 +0,0 @@
export * from './factory'
export * from './types'

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@@ -1,38 +0,0 @@
export type OpenRouterProviderOptions = {
models?: string[]
/**
* https://openrouter.ai/docs/use-cases/reasoning-tokens
* One of `max_tokens` or `effort` is required.
* If `exclude` is true, reasoning will be removed from the response. Default is false.
*/
reasoning?: {
exclude?: boolean
} & (
| {
max_tokens: number
}
| {
effort: 'high' | 'medium' | 'low'
}
)
/**
* A unique identifier representing your end-user, which can
* help OpenRouter to monitor and detect abuse.
*/
user?: string
extraBody?: Record<string, unknown>
/**
* Enable usage accounting to get detailed token usage information.
* https://openrouter.ai/docs/use-cases/usage-accounting
*/
usage?: {
/**
* When true, includes token usage information in the response.
*/
include: boolean
}
}

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@@ -1,33 +0,0 @@
import { type AnthropicProviderOptions } from '@ai-sdk/anthropic'
import { type GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
import { type OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
import { type SharedV2ProviderMetadata } from '@ai-sdk/provider'
import { type OpenRouterProviderOptions } from './openrouter'
import { type XaiProviderOptions } from './xai'
export type ProviderOptions<T extends keyof SharedV2ProviderMetadata> = SharedV2ProviderMetadata[T]
/**
* 供应商选项类型如果map中没有说明没有约束
*/
export type ProviderOptionsMap = {
openai: OpenAIResponsesProviderOptions
anthropic: AnthropicProviderOptions
google: GoogleGenerativeAIProviderOptions
openrouter: OpenRouterProviderOptions
xai: XaiProviderOptions
}
// 工具类型用于从ProviderOptionsMap中提取特定供应商的选项类型
export type ExtractProviderOptions<T extends keyof ProviderOptionsMap> = ProviderOptionsMap[T]
/**
* 类型安全的ProviderOptions
* 对于已知供应商使用严格类型对于未知供应商允许任意Record<string, JSONValue>
*/
export type TypedProviderOptions = {
[K in keyof ProviderOptionsMap]?: ProviderOptionsMap[K]
} & {
[K in string]?: Record<string, any>
} & SharedV2ProviderMetadata

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@@ -1,86 +0,0 @@
// copy from @ai-sdk/xai/xai-chat-options.ts
// 如果@ai-sdk/xai暴露出了xaiProviderOptions就删除这个文件
import * as z from 'zod/v4'
const webSourceSchema = z.object({
type: z.literal('web'),
country: z.string().length(2).optional(),
excludedWebsites: z.array(z.string()).max(5).optional(),
allowedWebsites: z.array(z.string()).max(5).optional(),
safeSearch: z.boolean().optional()
})
const xSourceSchema = z.object({
type: z.literal('x'),
xHandles: z.array(z.string()).optional()
})
const newsSourceSchema = z.object({
type: z.literal('news'),
country: z.string().length(2).optional(),
excludedWebsites: z.array(z.string()).max(5).optional(),
safeSearch: z.boolean().optional()
})
const rssSourceSchema = z.object({
type: z.literal('rss'),
links: z.array(z.url()).max(1) // currently only supports one RSS link
})
const searchSourceSchema = z.discriminatedUnion('type', [
webSourceSchema,
xSourceSchema,
newsSourceSchema,
rssSourceSchema
])
export const xaiProviderOptions = z.object({
/**
* reasoning effort for reasoning models
* only supported by grok-3-mini and grok-3-mini-fast models
*/
reasoningEffort: z.enum(['low', 'high']).optional(),
searchParameters: z
.object({
/**
* search mode preference
* - "off": disables search completely
* - "auto": model decides whether to search (default)
* - "on": always enables search
*/
mode: z.enum(['off', 'auto', 'on']),
/**
* whether to return citations in the response
* defaults to true
*/
returnCitations: z.boolean().optional(),
/**
* start date for search data (ISO8601 format: YYYY-MM-DD)
*/
fromDate: z.string().optional(),
/**
* end date for search data (ISO8601 format: YYYY-MM-DD)
*/
toDate: z.string().optional(),
/**
* maximum number of search results to consider
* defaults to 20
*/
maxSearchResults: z.number().min(1).max(50).optional(),
/**
* data sources to search from
* defaults to ["web", "x"] if not specified
*/
sources: z.array(searchSourceSchema).optional()
})
.optional()
})
export type XaiProviderOptions = z.infer<typeof xaiProviderOptions>

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@@ -1,257 +0,0 @@
# AI Core 插件系统
支持四种钩子类型:**First**、**Sequential**、**Parallel** 和 **Stream**
## 🎯 设计理念
- **语义清晰**:不同钩子有不同的执行语义
- **类型安全**TypeScript 完整支持
- **性能优化**First 短路、Parallel 并发、Sequential 链式
- **易于扩展**`enforce` 排序 + 功能分类
## 📋 钩子类型
### 🥇 First 钩子 - 首个有效结果
```typescript
// 只执行第一个返回值的插件,用于解析和查找
resolveModel?: (modelId: string, context: AiRequestContext) => string | null
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null
```
### 🔄 Sequential 钩子 - 链式数据转换
```typescript
// 按顺序链式执行,每个插件可以修改数据
transformParams?: (params: any, context: AiRequestContext) => any
transformResult?: (result: any, context: AiRequestContext) => any
```
### ⚡ Parallel 钩子 - 并行副作用
```typescript
// 并发执行,用于日志、监控等副作用
onRequestStart?: (context: AiRequestContext) => void
onRequestEnd?: (context: AiRequestContext, result: any) => void
onError?: (error: Error, context: AiRequestContext) => void
```
### 🌊 Stream 钩子 - 流处理
```typescript
// 直接使用 AI SDK 的 TransformStream
transformStream?: () => (options) => TransformStream<TextStreamPart, TextStreamPart>
```
## 🚀 快速开始
### 基础用法
```typescript
import { PluginManager, createContext, definePlugin } from '@cherrystudio/ai-core/middleware'
// 创建插件管理器
const pluginManager = new PluginManager()
// 添加插件
pluginManager.use({
name: 'my-plugin',
async transformParams(params, context) {
return { ...params, temperature: 0.7 }
}
})
// 使用插件
const context = createContext('openai', 'gpt-4', { messages: [] })
const transformedParams = await pluginManager.executeSequential(
'transformParams',
{ messages: [{ role: 'user', content: 'Hello' }] },
context
)
```
### 完整示例
```typescript
import {
PluginManager,
ModelAliasPlugin,
LoggingPlugin,
ParamsValidationPlugin,
createContext
} from '@cherrystudio/ai-core/middleware'
// 创建插件管理器
const manager = new PluginManager([
ModelAliasPlugin, // 模型别名解析
ParamsValidationPlugin, // 参数验证
LoggingPlugin // 日志记录
])
// AI 请求流程
async function aiRequest(providerId: string, modelId: string, params: any) {
const context = createContext(providerId, modelId, params)
try {
// 1. 【并行】触发请求开始事件
await manager.executeParallel('onRequestStart', context)
// 2. 【首个】解析模型别名
const resolvedModel = await manager.executeFirst('resolveModel', modelId, context)
context.modelId = resolvedModel || modelId
// 3. 【串行】转换请求参数
const transformedParams = await manager.executeSequential('transformParams', params, context)
// 4. 【流处理】收集流转换器AI SDK 原生支持数组)
const streamTransforms = manager.collectStreamTransforms()
// 5. 调用 AI SDK这里省略具体实现
const result = await callAiSdk(transformedParams, streamTransforms)
// 6. 【串行】转换响应结果
const transformedResult = await manager.executeSequential('transformResult', result, context)
// 7. 【并行】触发请求完成事件
await manager.executeParallel('onRequestEnd', context, transformedResult)
return transformedResult
} catch (error) {
// 8. 【并行】触发错误事件
await manager.executeParallel('onError', context, undefined, error)
throw error
}
}
```
## 🔧 自定义插件
### 模型别名插件
```typescript
const ModelAliasPlugin = definePlugin({
name: 'model-alias',
enforce: 'pre', // 最先执行
async resolveModel(modelId) {
const aliases = {
gpt4: 'gpt-4-turbo-preview',
claude: 'claude-3-sonnet-20240229'
}
return aliases[modelId] || null
}
})
```
### 参数验证插件
```typescript
const ValidationPlugin = definePlugin({
name: 'validation',
async transformParams(params) {
if (!params.messages) {
throw new Error('messages is required')
}
return {
...params,
temperature: params.temperature ?? 0.7,
max_tokens: params.max_tokens ?? 4096
}
}
})
```
### 监控插件
```typescript
const MonitoringPlugin = definePlugin({
name: 'monitoring',
enforce: 'post', // 最后执行
async onRequestEnd(context, result) {
const duration = Date.now() - context.startTime
console.log(`请求耗时: ${duration}ms`)
}
})
```
### 内容过滤插件
```typescript
const FilterPlugin = definePlugin({
name: 'content-filter',
transformStream() {
return () =>
new TransformStream({
transform(chunk, controller) {
if (chunk.type === 'text-delta') {
const filtered = chunk.textDelta.replace(/敏感词/g, '***')
controller.enqueue({ ...chunk, textDelta: filtered })
} else {
controller.enqueue(chunk)
}
}
})
}
})
```
## 📊 执行顺序
### 插件排序
```
enforce: 'pre' → normal → enforce: 'post'
```
### 钩子执行流程
```mermaid
graph TD
A[请求开始] --> B[onRequestStart 并行执行]
B --> C[resolveModel 首个有效]
C --> D[loadTemplate 首个有效]
D --> E[transformParams 串行执行]
E --> F[collectStreamTransforms]
F --> G[AI SDK 调用]
G --> H[transformResult 串行执行]
H --> I[onRequestEnd 并行执行]
G --> J[异常处理]
J --> K[onError 并行执行]
```
## 💡 最佳实践
1. **功能单一**:每个插件专注一个功能
2. **幂等性**:插件应该是幂等的,重复执行不会产生副作用
3. **错误处理**:插件内部处理异常,不要让异常向上传播
4. **性能优化**使用合适的钩子类型First vs Sequential vs Parallel
5. **命名规范**:使用语义化的插件名称
## 🔍 调试工具
```typescript
// 查看插件统计信息
const stats = manager.getStats()
console.log('插件统计:', stats)
// 查看所有插件
const plugins = manager.getPlugins()
console.log(
'已注册插件:',
plugins.map((p) => p.name)
)
```
## ⚡ 性能优势
- **First 钩子**:一旦找到结果立即停止,避免无效计算
- **Parallel 钩子**:真正并发执行,不阻塞主流程
- **Sequential 钩子**:保证数据转换的顺序性
- **Stream 钩子**:直接集成 AI SDK零开销
这个设计兼顾了简洁性和强大功能,为 AI Core 提供了灵活而高效的扩展机制。

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/**
* 内置插件命名空间
* 所有内置插件都以 'built-in:' 为前缀
*/
export const BUILT_IN_PLUGIN_PREFIX = 'built-in:'
export { createLoggingPlugin } from './logging'
export { createPromptToolUsePlugin } from './toolUsePlugin/promptToolUsePlugin'
export type { PromptToolUseConfig, ToolUseRequestContext, ToolUseResult } from './toolUsePlugin/type'
export { webSearchPlugin } from './webSearchPlugin'

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/**
* 内置插件:日志记录
* 记录AI调用的关键信息支持性能监控和调试
*/
import { definePlugin } from '../index'
import type { AiRequestContext } from '../types'
export interface LoggingConfig {
// 日志级别
level?: 'debug' | 'info' | 'warn' | 'error'
// 是否记录参数
logParams?: boolean
// 是否记录结果
logResult?: boolean
// 是否记录性能数据
logPerformance?: boolean
// 自定义日志函数
logger?: (level: string, message: string, data?: any) => void
}
/**
* 创建日志插件
*/
export function createLoggingPlugin(config: LoggingConfig = {}) {
const { level = 'info', logParams = true, logResult = false, logPerformance = true, logger = console.log } = config
const startTimes = new Map<string, number>()
return definePlugin({
name: 'built-in:logging',
onRequestStart: (context: AiRequestContext) => {
const requestId = context.requestId
startTimes.set(requestId, Date.now())
logger(level, `🚀 AI Request Started`, {
requestId,
providerId: context.providerId,
modelId: context.modelId,
originalParams: logParams ? context.originalParams : '[hidden]'
})
},
onRequestEnd: (context: AiRequestContext, result: any) => {
const requestId = context.requestId
const startTime = startTimes.get(requestId)
const duration = startTime ? Date.now() - startTime : undefined
startTimes.delete(requestId)
const logData: any = {
requestId,
providerId: context.providerId,
modelId: context.modelId
}
if (logPerformance && duration) {
logData.duration = `${duration}ms`
}
if (logResult) {
logData.result = result
}
logger(level, `✅ AI Request Completed`, logData)
},
onError: (error: Error, context: AiRequestContext) => {
const requestId = context.requestId
const startTime = startTimes.get(requestId)
const duration = startTime ? Date.now() - startTime : undefined
startTimes.delete(requestId)
logger('error', `❌ AI Request Failed`, {
requestId,
providerId: context.providerId,
modelId: context.modelId,
duration: duration ? `${duration}ms` : undefined,
error: {
name: error.name,
message: error.message,
stack: error.stack
}
})
}
})
}

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/**
* 流事件管理器
*
* 负责处理 AI SDK 流事件的发送和管理
* 从 promptToolUsePlugin.ts 中提取出来以降低复杂度
*/
import type { ModelMessage } from 'ai'
import type { AiRequestContext } from '../../types'
import type { StreamController } from './ToolExecutor'
/**
* 流事件管理器类
*/
export class StreamEventManager {
/**
* 发送工具调用步骤开始事件
*/
sendStepStartEvent(controller: StreamController): void {
controller.enqueue({
type: 'start-step',
request: {},
warnings: []
})
}
/**
* 发送步骤完成事件
*/
sendStepFinishEvent(controller: StreamController, chunk: any): void {
controller.enqueue({
type: 'finish-step',
finishReason: 'stop',
response: chunk.response,
usage: chunk.usage,
providerMetadata: chunk.providerMetadata
})
}
/**
* 处理递归调用并将结果流接入当前流
*/
async handleRecursiveCall(
controller: StreamController,
recursiveParams: any,
context: AiRequestContext,
stepId: string
): Promise<void> {
try {
console.log('[MCP Prompt] Starting recursive call after tool execution...')
const recursiveResult = await context.recursiveCall(recursiveParams)
if (recursiveResult && recursiveResult.fullStream) {
await this.pipeRecursiveStream(controller, recursiveResult.fullStream)
} else {
console.warn('[MCP Prompt] No fullstream found in recursive result:', recursiveResult)
}
} catch (error) {
this.handleRecursiveCallError(controller, error, stepId)
}
}
/**
* 将递归流的数据传递到当前流
*/
private async pipeRecursiveStream(controller: StreamController, recursiveStream: ReadableStream): Promise<void> {
const reader = recursiveStream.getReader()
try {
while (true) {
const { done, value } = await reader.read()
if (done) {
break
}
if (value.type === 'finish') {
// 迭代的流不发finish
break
}
// 将递归流的数据传递到当前流
controller.enqueue(value)
}
} finally {
reader.releaseLock()
}
}
/**
* 处理递归调用错误
*/
private handleRecursiveCallError(controller: StreamController, error: unknown, stepId: string): void {
console.error('[MCP Prompt] Recursive call failed:', error)
// 使用 AI SDK 标准错误格式,但不中断流
controller.enqueue({
type: 'error',
error: {
message: error instanceof Error ? error.message : String(error),
name: error instanceof Error ? error.name : 'RecursiveCallError'
}
})
// 继续发送文本增量,保持流的连续性
controller.enqueue({
type: 'text-delta',
id: stepId,
text: '\n\n[工具执行后递归调用失败,继续对话...]'
})
}
/**
* 构建递归调用的参数
*/
buildRecursiveParams(context: AiRequestContext, textBuffer: string, toolResultsText: string, tools: any): any {
// 构建新的对话消息
const newMessages: ModelMessage[] = [
...(context.originalParams.messages || []),
{
role: 'assistant',
content: textBuffer
},
{
role: 'user',
content: toolResultsText
}
]
// 递归调用,继续对话,重新传递 tools
const recursiveParams = {
...context.originalParams,
messages: newMessages,
tools: tools
}
// 更新上下文中的消息
context.originalParams.messages = newMessages
return recursiveParams
}
}

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/**
* 工具执行器
*
* 负责工具的执行、结果格式化和相关事件发送
* 从 promptToolUsePlugin.ts 中提取出来以降低复杂度
*/
import type { ToolSet } from 'ai'
import type { ToolUseResult } from './type'
/**
* 工具执行结果
*/
export interface ExecutedResult {
toolCallId: string
toolName: string
result: any
isError?: boolean
}
/**
* 流控制器类型(从 AI SDK 提取)
*/
export interface StreamController {
enqueue(chunk: any): void
}
/**
* 工具执行器类
*/
export class ToolExecutor {
/**
* 执行多个工具调用
*/
async executeTools(
toolUses: ToolUseResult[],
tools: ToolSet,
controller: StreamController
): Promise<ExecutedResult[]> {
const executedResults: ExecutedResult[] = []
for (const toolUse of toolUses) {
try {
const tool = tools[toolUse.toolName]
if (!tool || typeof tool.execute !== 'function') {
throw new Error(`Tool "${toolUse.toolName}" has no execute method`)
}
// 发送工具调用开始事件
this.sendToolStartEvents(controller, toolUse)
console.log(`[MCP Prompt Stream] Executing tool: ${toolUse.toolName}`, toolUse.arguments)
// 发送 tool-call 事件
controller.enqueue({
type: 'tool-call',
toolCallId: toolUse.id,
toolName: toolUse.toolName,
input: tool.inputSchema
})
const result = await tool.execute(toolUse.arguments, {
toolCallId: toolUse.id,
messages: [],
abortSignal: new AbortController().signal
})
// 发送 tool-result 事件
controller.enqueue({
type: 'tool-result',
toolCallId: toolUse.id,
toolName: toolUse.toolName,
input: toolUse.arguments,
output: result
})
executedResults.push({
toolCallId: toolUse.id,
toolName: toolUse.toolName,
result,
isError: false
})
} catch (error) {
console.error(`[MCP Prompt Stream] Tool execution failed: ${toolUse.toolName}`, error)
// 处理错误情况
const errorResult = this.handleToolError(toolUse, error, controller)
executedResults.push(errorResult)
}
}
return executedResults
}
/**
* 格式化工具结果为 Cherry Studio 标准格式
*/
formatToolResults(executedResults: ExecutedResult[]): string {
return executedResults
.map((tr) => {
if (!tr.isError) {
return `<tool_use_result>\n <name>${tr.toolName}</name>\n <result>${JSON.stringify(tr.result)}</result>\n</tool_use_result>`
} else {
const error = tr.result || 'Unknown error'
return `<tool_use_result>\n <name>${tr.toolName}</name>\n <error>${error}</error>\n</tool_use_result>`
}
})
.join('\n\n')
}
/**
* 发送工具调用开始相关事件
*/
private sendToolStartEvents(controller: StreamController, toolUse: ToolUseResult): void {
// 发送 tool-input-start 事件
controller.enqueue({
type: 'tool-input-start',
id: toolUse.id,
toolName: toolUse.toolName
})
}
/**
* 处理工具执行错误
*/
private handleToolError(
toolUse: ToolUseResult,
error: unknown,
controller: StreamController
// _tools: ToolSet
): ExecutedResult {
// 使用 AI SDK 标准错误格式
// const toolError: TypedToolError<typeof _tools> = {
// type: 'tool-error',
// toolCallId: toolUse.id,
// toolName: toolUse.toolName,
// input: toolUse.arguments,
// error: error instanceof Error ? error.message : String(error)
// }
// controller.enqueue(toolError)
// 发送标准错误事件
controller.enqueue({
type: 'error',
error: error instanceof Error ? error.message : String(error)
})
return {
toolCallId: toolUse.id,
toolName: toolUse.toolName,
result: error instanceof Error ? error.message : String(error),
isError: true
}
}
}

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/**
* 内置插件MCP Prompt 模式
* 为不支持原生 Function Call 的模型提供 prompt 方式的工具调用
* 内置默认逻辑,支持自定义覆盖
*/
import type { TextStreamPart, ToolSet } from 'ai'
import { definePlugin } from '../../index'
import type { AiRequestContext } from '../../types'
import { StreamEventManager } from './StreamEventManager'
import { ToolExecutor } from './ToolExecutor'
import { PromptToolUseConfig, ToolUseResult } from './type'
/**
* 默认系统提示符模板(提取自 Cherry Studio
*/
const DEFAULT_SYSTEM_PROMPT = `In this environment you have access to a set of tools you can use to answer the user's question. \\
You can use one tool per message, and will receive the result of that tool use in the user's response. You use tools step-by-step to accomplish a given task, with each tool use informed by the result of the previous tool use.
## Tool Use Formatting
Tool use is formatted using XML-style tags. The tool name is enclosed in opening and closing tags, and each parameter is similarly enclosed within its own set of tags. Here's the structure:
<tool_use>
<name>{tool_name}</name>
<arguments>{json_arguments}</arguments>
</tool_use>
The tool name should be the exact name of the tool you are using, and the arguments should be a JSON object containing the parameters required by that tool. For example:
<tool_use>
<name>python_interpreter</name>
<arguments>{"code": "5 + 3 + 1294.678"}</arguments>
</tool_use>
The user will respond with the result of the tool use, which should be formatted as follows:
<tool_use_result>
<name>{tool_name}</name>
<result>{result}</result>
</tool_use_result>
The result should be a string, which can represent a file or any other output type. You can use this result as input for the next action.
For example, if the result of the tool use is an image file, you can use it in the next action like this:
<tool_use>
<name>image_transformer</name>
<arguments>{"image": "image_1.jpg"}</arguments>
</tool_use>
Always adhere to this format for the tool use to ensure proper parsing and execution.
## Tool Use Examples
{{ TOOL_USE_EXAMPLES }}
## Tool Use Available Tools
Above example were using notional tools that might not exist for you. You only have access to these tools:
{{ AVAILABLE_TOOLS }}
## Tool Use Rules
Here are the rules you should always follow to solve your task:
1. Always use the right arguments for the tools. Never use variable names as the action arguments, use the value instead.
2. Call a tool only when needed: do not call the search agent if you do not need information, try to solve the task yourself.
3. If no tool call is needed, just answer the question directly.
4. Never re-do a tool call that you previously did with the exact same parameters.
5. For tool use, MAKE SURE use XML tag format as shown in the examples above. Do not use any other format.
# User Instructions
{{ USER_SYSTEM_PROMPT }}
Now Begin! If you solve the task correctly, you will receive a reward of $1,000,000.`
/**
* 默认工具使用示例(提取自 Cherry Studio
*/
const DEFAULT_TOOL_USE_EXAMPLES = `
Here are a few examples using notional tools:
---
User: Generate an image of the oldest person in this document.
A: I can use the document_qa tool to find out who the oldest person is in the document.
<tool_use>
<name>document_qa</name>
<arguments>{"document": "document.pdf", "question": "Who is the oldest person mentioned?"}</arguments>
</tool_use>
User: <tool_use_result>
<name>document_qa</name>
<result>John Doe, a 55 year old lumberjack living in Newfoundland.</result>
</tool_use_result>
A: I can use the image_generator tool to create a portrait of John Doe.
<tool_use>
<name>image_generator</name>
<arguments>{"prompt": "A portrait of John Doe, a 55-year-old man living in Canada."}</arguments>
</tool_use>
User: <tool_use_result>
<name>image_generator</name>
<result>image.png</result>
</tool_use_result>
A: the image is generated as image.png
---
User: "What is the result of the following operation: 5 + 3 + 1294.678?"
A: I can use the python_interpreter tool to calculate the result of the operation.
<tool_use>
<name>python_interpreter</name>
<arguments>{"code": "5 + 3 + 1294.678"}</arguments>
</tool_use>
User: <tool_use_result>
<name>python_interpreter</name>
<result>1302.678</result>
</tool_use_result>
A: The result of the operation is 1302.678.
---
User: "Which city has the highest population , Guangzhou or Shanghai?"
A: I can use the search tool to find the population of Guangzhou.
<tool_use>
<name>search</name>
<arguments>{"query": "Population Guangzhou"}</arguments>
</tool_use>
User: <tool_use_result>
<name>search</name>
<result>Guangzhou has a population of 15 million inhabitants as of 2021.</result>
</tool_use_result>
A: I can use the search tool to find the population of Shanghai.
<tool_use>
<name>search</name>
<arguments>{"query": "Population Shanghai"}</arguments>
</tool_use>
User: <tool_use_result>
<name>search</name>
<result>26 million (2019)</result>
</tool_use_result>
Assistant: The population of Shanghai is 26 million, while Guangzhou has a population of 15 million. Therefore, Shanghai has the highest population.`
/**
* 构建可用工具部分(提取自 Cherry Studio
*/
function buildAvailableTools(tools: ToolSet): string {
const availableTools = Object.keys(tools)
.map((toolName: string) => {
const tool = tools[toolName]
return `
<tool>
<name>${toolName}</name>
<description>${tool.description || ''}</description>
<arguments>
${tool.inputSchema ? JSON.stringify(tool.inputSchema) : ''}
</arguments>
</tool>
`
})
.join('\n')
return `<tools>
${availableTools}
</tools>`
}
/**
* 默认的系统提示符构建函数(提取自 Cherry Studio
*/
function defaultBuildSystemPrompt(userSystemPrompt: string, tools: ToolSet): string {
const availableTools = buildAvailableTools(tools)
const fullPrompt = DEFAULT_SYSTEM_PROMPT.replace('{{ TOOL_USE_EXAMPLES }}', DEFAULT_TOOL_USE_EXAMPLES)
.replace('{{ AVAILABLE_TOOLS }}', availableTools)
.replace('{{ USER_SYSTEM_PROMPT }}', userSystemPrompt || '')
return fullPrompt
}
/**
* 默认工具解析函数(提取自 Cherry Studio
* 解析 XML 格式的工具调用
*/
function defaultParseToolUse(content: string, tools: ToolSet): { results: ToolUseResult[]; content: string } {
if (!content || !tools || Object.keys(tools).length === 0) {
return { results: [], content: content }
}
// 支持两种格式:
// 1. 完整的 <tool_use></tool_use> 标签包围的内容
// 2. 只有内部内容(从 TagExtractor 提取出来的)
let contentToProcess = content
// 如果内容不包含 <tool_use> 标签,说明是从 TagExtractor 提取的内部内容,需要包装
if (!content.includes('<tool_use>')) {
contentToProcess = `<tool_use>\n${content}\n</tool_use>`
}
const toolUsePattern =
/<tool_use>([\s\S]*?)<name>([\s\S]*?)<\/name>([\s\S]*?)<arguments>([\s\S]*?)<\/arguments>([\s\S]*?)<\/tool_use>/g
const results: ToolUseResult[] = []
let match
let idx = 0
// Find all tool use blocks
while ((match = toolUsePattern.exec(contentToProcess)) !== null) {
const fullMatch = match[0]
const toolName = match[2].trim()
const toolArgs = match[4].trim()
// Try to parse the arguments as JSON
let parsedArgs
try {
parsedArgs = JSON.parse(toolArgs)
} catch (error) {
// If parsing fails, use the string as is
parsedArgs = toolArgs
}
// Find the corresponding tool
const tool = tools[toolName]
if (!tool) {
console.warn(`Tool "${toolName}" not found in available tools`)
continue
}
// Add to results array
results.push({
id: `${toolName}-${idx++}`, // Unique ID for each tool use
toolName: toolName,
arguments: parsedArgs,
status: 'pending'
})
contentToProcess = contentToProcess.replace(fullMatch, '')
}
return { results, content: contentToProcess }
}
export const createPromptToolUsePlugin = (config: PromptToolUseConfig = {}) => {
const { enabled = true, buildSystemPrompt = defaultBuildSystemPrompt, parseToolUse = defaultParseToolUse } = config
return definePlugin({
name: 'built-in:prompt-tool-use',
transformParams: (params: any, context: AiRequestContext) => {
if (!enabled || !params.tools || typeof params.tools !== 'object') {
return params
}
context.mcpTools = params.tools
console.log('tools stored in context', params.tools)
// 构建系统提示符
const userSystemPrompt = typeof params.system === 'string' ? params.system : ''
const systemPrompt = buildSystemPrompt(userSystemPrompt, params.tools)
let systemMessage: string | null = systemPrompt
console.log('config.context', context)
if (config.createSystemMessage) {
// 🎯 如果用户提供了自定义处理函数,使用它
systemMessage = config.createSystemMessage(systemPrompt, params, context)
}
// 移除 tools改为 prompt 模式
const transformedParams = {
...params,
...(systemMessage ? { system: systemMessage } : {}),
tools: undefined
}
context.originalParams = transformedParams
console.log('transformedParams', transformedParams)
return transformedParams
},
transformStream: (_: any, context: AiRequestContext) => () => {
let textBuffer = ''
let stepId = ''
if (!context.mcpTools) {
throw new Error('No tools available')
}
// 创建工具执行器和流事件管理器
const toolExecutor = new ToolExecutor()
const streamEventManager = new StreamEventManager()
type TOOLS = NonNullable<typeof context.mcpTools>
return new TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>({
async transform(
chunk: TextStreamPart<TOOLS>,
controller: TransformStreamDefaultController<TextStreamPart<TOOLS>>
) {
// 收集文本内容
if (chunk.type === 'text-delta') {
textBuffer += chunk.text || ''
stepId = chunk.id || ''
controller.enqueue(chunk)
return
}
if (chunk.type === 'text-end' || chunk.type === 'finish-step') {
const tools = context.mcpTools
if (!tools || Object.keys(tools).length === 0) {
controller.enqueue(chunk)
return
}
// 解析工具调用
const { results: parsedTools, content: parsedContent } = parseToolUse(textBuffer, tools)
const validToolUses = parsedTools.filter((t) => t.status === 'pending')
// 如果没有有效的工具调用,直接传递原始事件
if (validToolUses.length === 0) {
controller.enqueue(chunk)
return
}
if (chunk.type === 'text-end') {
controller.enqueue({
type: 'text-end',
id: stepId,
providerMetadata: {
text: {
value: parsedContent
}
}
})
return
}
controller.enqueue({
...chunk,
finishReason: 'tool-calls'
})
// 发送步骤开始事件
streamEventManager.sendStepStartEvent(controller)
// 执行工具调用
const executedResults = await toolExecutor.executeTools(validToolUses, tools, controller)
// 发送步骤完成事件
streamEventManager.sendStepFinishEvent(controller, chunk)
// 处理递归调用
if (validToolUses.length > 0) {
const toolResultsText = toolExecutor.formatToolResults(executedResults)
const recursiveParams = streamEventManager.buildRecursiveParams(
context,
textBuffer,
toolResultsText,
tools
)
await streamEventManager.handleRecursiveCall(controller, recursiveParams, context, stepId)
}
// 清理状态
textBuffer = ''
return
}
// 对于其他类型的事件,直接传递
controller.enqueue(chunk)
},
flush() {
// 流结束时的清理工作
console.log('[MCP Prompt] Stream ended, cleaning up...')
}
})
}
})
}

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// Copied from https://github.com/vercel/ai/blob/main/packages/ai/core/util/get-potential-start-index.ts
/**
* Returns the index of the start of the searchedText in the text, or null if it
* is not found.
*/
export function getPotentialStartIndex(text: string, searchedText: string): number | null {
// Return null immediately if searchedText is empty.
if (searchedText.length === 0) {
return null
}
// Check if the searchedText exists as a direct substring of text.
const directIndex = text.indexOf(searchedText)
if (directIndex !== -1) {
return directIndex
}
// Otherwise, look for the largest suffix of "text" that matches
// a prefix of "searchedText". We go from the end of text inward.
for (let i = text.length - 1; i >= 0; i--) {
const suffix = text.substring(i)
if (searchedText.startsWith(suffix)) {
return i
}
}
return null
}
export interface TagConfig {
openingTag: string
closingTag: string
separator?: string
}
export interface TagExtractionState {
textBuffer: string
isInsideTag: boolean
isFirstTag: boolean
isFirstText: boolean
afterSwitch: boolean
accumulatedTagContent: string
hasTagContent: boolean
}
export interface TagExtractionResult {
content: string
isTagContent: boolean
complete: boolean
tagContentExtracted?: string
}
/**
* 通用标签提取处理器
* 可以处理各种形式的标签对,如 <think>...</think>, <tool_use>...</tool_use> 等
*/
export class TagExtractor {
private config: TagConfig
private state: TagExtractionState
constructor(config: TagConfig) {
this.config = config
this.state = {
textBuffer: '',
isInsideTag: false,
isFirstTag: true,
isFirstText: true,
afterSwitch: false,
accumulatedTagContent: '',
hasTagContent: false
}
}
/**
* 处理文本块,返回处理结果
*/
processText(newText: string): TagExtractionResult[] {
this.state.textBuffer += newText
const results: TagExtractionResult[] = []
// 处理标签提取逻辑
while (true) {
const nextTag = this.state.isInsideTag ? this.config.closingTag : this.config.openingTag
const startIndex = getPotentialStartIndex(this.state.textBuffer, nextTag)
if (startIndex == null) {
const content = this.state.textBuffer
if (content.length > 0) {
results.push({
content: this.addPrefix(content),
isTagContent: this.state.isInsideTag,
complete: false
})
if (this.state.isInsideTag) {
this.state.accumulatedTagContent += this.addPrefix(content)
this.state.hasTagContent = true
}
}
this.state.textBuffer = ''
break
}
// 处理标签前的内容
const contentBeforeTag = this.state.textBuffer.slice(0, startIndex)
if (contentBeforeTag.length > 0) {
results.push({
content: this.addPrefix(contentBeforeTag),
isTagContent: this.state.isInsideTag,
complete: false
})
if (this.state.isInsideTag) {
this.state.accumulatedTagContent += this.addPrefix(contentBeforeTag)
this.state.hasTagContent = true
}
}
const foundFullMatch = startIndex + nextTag.length <= this.state.textBuffer.length
if (foundFullMatch) {
// 如果找到完整的标签
this.state.textBuffer = this.state.textBuffer.slice(startIndex + nextTag.length)
// 如果刚刚结束一个标签内容,生成完整的标签内容结果
if (this.state.isInsideTag && this.state.hasTagContent) {
results.push({
content: '',
isTagContent: false,
complete: true,
tagContentExtracted: this.state.accumulatedTagContent
})
this.state.accumulatedTagContent = ''
this.state.hasTagContent = false
}
this.state.isInsideTag = !this.state.isInsideTag
this.state.afterSwitch = true
if (this.state.isInsideTag) {
this.state.isFirstTag = false
} else {
this.state.isFirstText = false
}
} else {
this.state.textBuffer = this.state.textBuffer.slice(startIndex)
break
}
}
return results
}
/**
* 完成处理,返回任何剩余的标签内容
*/
finalize(): TagExtractionResult | null {
if (this.state.hasTagContent && this.state.accumulatedTagContent) {
const result = {
content: '',
isTagContent: false,
complete: true,
tagContentExtracted: this.state.accumulatedTagContent
}
this.state.accumulatedTagContent = ''
this.state.hasTagContent = false
return result
}
return null
}
private addPrefix(text: string): string {
const needsPrefix =
this.state.afterSwitch && (this.state.isInsideTag ? !this.state.isFirstTag : !this.state.isFirstText)
const prefix = needsPrefix && this.config.separator ? this.config.separator : ''
this.state.afterSwitch = false
return prefix + text
}
/**
* 重置状态
*/
reset(): void {
this.state = {
textBuffer: '',
isInsideTag: false,
isFirstTag: true,
isFirstText: true,
afterSwitch: false,
accumulatedTagContent: '',
hasTagContent: false
}
}
}

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@@ -1,33 +0,0 @@
import { ToolSet } from 'ai'
import { AiRequestContext } from '../..'
/**
* 解析结果类型
* 表示从AI响应中解析出的工具使用意图
*/
export interface ToolUseResult {
id: string
toolName: string
arguments: any
status: 'pending' | 'invoking' | 'done' | 'error'
}
export interface BaseToolUsePluginConfig {
enabled?: boolean
}
export interface PromptToolUseConfig extends BaseToolUsePluginConfig {
// 自定义系统提示符构建函数(可选,有默认实现)
buildSystemPrompt?: (userSystemPrompt: string, tools: ToolSet) => string
// 自定义工具解析函数(可选,有默认实现)
parseToolUse?: (content: string, tools: ToolSet) => { results: ToolUseResult[]; content: string }
createSystemMessage?: (systemPrompt: string, originalParams: any, context: AiRequestContext) => string | null
}
/**
* 扩展的 AI 请求上下文,支持 MCP 工具存储
*/
export interface ToolUseRequestContext extends AiRequestContext {
mcpTools: ToolSet
}

View File

@@ -1,67 +0,0 @@
import { anthropic } from '@ai-sdk/anthropic'
import { google } from '@ai-sdk/google'
import { openai } from '@ai-sdk/openai'
import { ProviderOptionsMap } from '../../../options/types'
/**
* 从 AI SDK 的工具函数中提取参数类型,以确保类型安全。
*/
type OpenAISearchConfig = Parameters<typeof openai.tools.webSearchPreview>[0]
type AnthropicSearchConfig = Parameters<typeof anthropic.tools.webSearch_20250305>[0]
type GoogleSearchConfig = Parameters<typeof google.tools.googleSearch>[0]
/**
* 插件初始化时接收的完整配置对象
*
* 其结构与 ProviderOptions 保持一致,方便上游统一管理配置
*/
export interface WebSearchPluginConfig {
openai?: OpenAISearchConfig
anthropic?: AnthropicSearchConfig
xai?: ProviderOptionsMap['xai']['searchParameters']
google?: GoogleSearchConfig
'google-vertex'?: GoogleSearchConfig
}
/**
* 插件的默认配置
*/
export const DEFAULT_WEB_SEARCH_CONFIG: WebSearchPluginConfig = {
google: {},
'google-vertex': {},
openai: {},
xai: {
mode: 'on',
returnCitations: true,
maxSearchResults: 5,
sources: [{ type: 'web' }, { type: 'x' }, { type: 'news' }]
},
anthropic: {
maxUses: 5
}
}
export type WebSearchToolOutputSchema = {
// Anthropic 工具 - 手动定义
anthropicWebSearch: Array<{
url: string
title: string
pageAge: string | null
encryptedContent: string
type: string
}>
// OpenAI 工具 - 基于实际输出
openaiWebSearch: {
status: 'completed' | 'failed'
}
// Google 工具
googleSearch: {
webSearchQueries?: string[]
groundingChunks?: Array<{
web?: { uri: string; title: string }
}>
}
}

View File

@@ -1,69 +0,0 @@
/**
* Web Search Plugin
* 提供统一的网络搜索能力,支持多个 AI Provider
*/
import { anthropic } from '@ai-sdk/anthropic'
import { google } from '@ai-sdk/google'
import { openai } from '@ai-sdk/openai'
import { createXaiOptions, mergeProviderOptions } from '../../../options'
import { definePlugin } from '../../'
import type { AiRequestContext } from '../../types'
import { DEFAULT_WEB_SEARCH_CONFIG, WebSearchPluginConfig } from './helper'
/**
* 网络搜索插件
*
* @param config - 在插件初始化时传入的静态配置
*/
export const webSearchPlugin = (config: WebSearchPluginConfig = DEFAULT_WEB_SEARCH_CONFIG) =>
definePlugin({
name: 'webSearch',
enforce: 'pre',
transformParams: async (params: any, context: AiRequestContext) => {
const { providerId } = context
switch (providerId) {
case 'openai': {
if (config.openai) {
if (!params.tools) params.tools = {}
params.tools.web_search_preview = openai.tools.webSearchPreview(config.openai)
}
break
}
case 'anthropic': {
if (config.anthropic) {
if (!params.tools) params.tools = {}
params.tools.web_search = anthropic.tools.webSearch_20250305(config.anthropic)
}
break
}
case 'google': {
// case 'google-vertex':
if (!params.tools) params.tools = {}
params.tools.web_search = google.tools.googleSearch(config.google || {})
break
}
case 'xai': {
if (config.xai) {
const searchOptions = createXaiOptions({
searchParameters: { ...config.xai, mode: 'on' }
})
params.providerOptions = mergeProviderOptions(params.providerOptions, searchOptions)
}
break
}
}
return params
}
})
// 导出类型定义供开发者使用
export type { WebSearchPluginConfig, WebSearchToolOutputSchema } from './helper'
// 默认导出
export default webSearchPlugin

View File

@@ -1,32 +0,0 @@
// 核心类型和接口
export type { AiPlugin, AiRequestContext, HookResult, PluginManagerConfig } from './types'
import type { ProviderId } from '../providers'
import type { AiPlugin, AiRequestContext } from './types'
// 插件管理器
export { PluginManager } from './manager'
// 工具函数
export function createContext<T extends ProviderId>(
providerId: T,
modelId: string,
originalParams: any
): AiRequestContext {
return {
providerId,
modelId,
originalParams,
metadata: {},
startTime: Date.now(),
requestId: `${providerId}-${modelId}-${Date.now()}-${Math.random().toString(36).slice(2)}`,
// 占位
recursiveCall: () => Promise.resolve(null)
}
}
// 插件构建器 - 便于创建插件
export function definePlugin(plugin: AiPlugin): AiPlugin
export function definePlugin<T extends (...args: any[]) => AiPlugin>(pluginFactory: T): T
export function definePlugin(plugin: AiPlugin | ((...args: any[]) => AiPlugin)) {
return plugin
}

View File

@@ -1,184 +0,0 @@
import { AiPlugin, AiRequestContext } from './types'
/**
* 插件管理器
*/
export class PluginManager {
private plugins: AiPlugin[] = []
constructor(plugins: AiPlugin[] = []) {
this.plugins = this.sortPlugins(plugins)
}
/**
* 添加插件
*/
use(plugin: AiPlugin): this {
this.plugins = this.sortPlugins([...this.plugins, plugin])
return this
}
/**
* 移除插件
*/
remove(pluginName: string): this {
this.plugins = this.plugins.filter((p) => p.name !== pluginName)
return this
}
/**
* 插件排序pre -> normal -> post
*/
private sortPlugins(plugins: AiPlugin[]): AiPlugin[] {
const pre: AiPlugin[] = []
const normal: AiPlugin[] = []
const post: AiPlugin[] = []
plugins.forEach((plugin) => {
if (plugin.enforce === 'pre') {
pre.push(plugin)
} else if (plugin.enforce === 'post') {
post.push(plugin)
} else {
normal.push(plugin)
}
})
return [...pre, ...normal, ...post]
}
/**
* 执行 First 钩子 - 返回第一个有效结果
*/
async executeFirst<T>(
hookName: 'resolveModel' | 'loadTemplate',
arg: any,
context: AiRequestContext
): Promise<T | null> {
for (const plugin of this.plugins) {
const hook = plugin[hookName]
if (hook) {
const result = await hook(arg, context)
if (result !== null && result !== undefined) {
return result as T
}
}
}
return null
}
/**
* 执行 Sequential 钩子 - 链式数据转换
*/
async executeSequential<T>(
hookName: 'transformParams' | 'transformResult',
initialValue: T,
context: AiRequestContext
): Promise<T> {
let result = initialValue
for (const plugin of this.plugins) {
const hook = plugin[hookName]
if (hook) {
result = await hook<T>(result, context)
}
}
return result
}
/**
* 执行 ConfigureContext 钩子 - 串行配置上下文
*/
async executeConfigureContext(context: AiRequestContext): Promise<void> {
for (const plugin of this.plugins) {
const hook = plugin.configureContext
if (hook) {
await hook(context)
}
}
}
/**
* 执行 Parallel 钩子 - 并行副作用
*/
async executeParallel(
hookName: 'onRequestStart' | 'onRequestEnd' | 'onError',
context: AiRequestContext,
result?: any,
error?: Error
): Promise<void> {
const promises = this.plugins
.map((plugin) => {
const hook = plugin[hookName]
if (!hook) return null
if (hookName === 'onError' && error) {
return (hook as any)(error, context)
} else if (hookName === 'onRequestEnd' && result !== undefined) {
return (hook as any)(context, result)
} else if (hookName === 'onRequestStart') {
return (hook as any)(context)
}
return null
})
.filter(Boolean)
// 使用 Promise.all 而不是 allSettled让插件错误能够抛出
await Promise.all(promises)
}
/**
* 收集所有流转换器返回数组AI SDK 原生支持)
*/
collectStreamTransforms(params: any, context: AiRequestContext) {
return this.plugins
.filter((plugin) => plugin.transformStream)
.map((plugin) => plugin.transformStream?.(params, context))
}
/**
* 获取所有插件信息
*/
getPlugins(): AiPlugin[] {
return [...this.plugins]
}
/**
* 获取插件统计信息
*/
getStats() {
const stats = {
total: this.plugins.length,
pre: 0,
normal: 0,
post: 0,
hooks: {
resolveModel: 0,
loadTemplate: 0,
transformParams: 0,
transformResult: 0,
onRequestStart: 0,
onRequestEnd: 0,
onError: 0,
transformStream: 0
}
}
this.plugins.forEach((plugin) => {
// 统计 enforce 类型
if (plugin.enforce === 'pre') stats.pre++
else if (plugin.enforce === 'post') stats.post++
else stats.normal++
// 统计钩子数量
Object.keys(stats.hooks).forEach((hookName) => {
if (plugin[hookName as keyof AiPlugin]) {
stats.hooks[hookName as keyof typeof stats.hooks]++
}
})
})
return stats
}
}

View File

@@ -1,79 +0,0 @@
import type { ImageModelV2 } from '@ai-sdk/provider'
import type { LanguageModel, TextStreamPart, ToolSet } from 'ai'
import { type ProviderId } from '../providers/types'
/**
* 递归调用函数类型
* 使用 any 是因为递归调用时参数和返回类型可能完全不同
*/
export type RecursiveCallFn = (newParams: any) => Promise<any>
/**
* AI 请求上下文
*/
export interface AiRequestContext {
providerId: ProviderId
modelId: string
originalParams: any
metadata: Record<string, any>
startTime: number
requestId: string
recursiveCall: RecursiveCallFn
isRecursiveCall?: boolean
mcpTools?: ToolSet
[key: string]: any
}
/**
* 钩子分类
*/
export interface AiPlugin {
name: string
enforce?: 'pre' | 'post'
// 【First】首个钩子 - 只执行第一个返回值的插件
resolveModel?: (
modelId: string,
context: AiRequestContext
) => Promise<LanguageModel | ImageModelV2 | null> | LanguageModel | ImageModelV2 | null
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null | Promise<any | null>
// 【Sequential】串行钩子 - 链式执行,支持数据转换
configureContext?: (context: AiRequestContext) => void | Promise<void>
transformParams?: <T>(params: T, context: AiRequestContext) => T | Promise<T>
transformResult?: <T>(result: T, context: AiRequestContext) => T | Promise<T>
// 【Parallel】并行钩子 - 不依赖顺序,用于副作用
onRequestStart?: (context: AiRequestContext) => void | Promise<void>
onRequestEnd?: (context: AiRequestContext, result: any) => void | Promise<void>
onError?: (error: Error, context: AiRequestContext) => void | Promise<void>
// 【Stream】流处理 - 直接使用 AI SDK
transformStream?: (
params: any,
context: AiRequestContext
) => <TOOLS extends ToolSet>(options?: {
tools: TOOLS
stopStream: () => void
}) => TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>
// AI SDK 原生中间件
// aiSdkMiddlewares?: LanguageModelV1Middleware[]
}
/**
* 插件管理器配置
*/
export interface PluginManagerConfig {
plugins: AiPlugin[]
context: Partial<AiRequestContext>
}
/**
* 钩子执行结果
*/
export interface HookResult<T = any> {
value: T
stop?: boolean
}

View File

@@ -1,101 +0,0 @@
/**
* Hub Provider - 支持路由到多个底层provider
*
* 支持格式: hubId:providerId:modelId
* 例如: aihubmix:anthropic:claude-3.5-sonnet
*/
import { ProviderV2 } from '@ai-sdk/provider'
import { customProvider } from 'ai'
import { globalRegistryManagement } from './RegistryManagement'
import type { AiSdkMethodName, AiSdkModelReturn, AiSdkModelType } from './types'
export interface HubProviderConfig {
/** Hub的唯一标识符 */
hubId: string
/** 是否启用调试日志 */
debug?: boolean
}
export class HubProviderError extends Error {
constructor(
message: string,
public readonly hubId: string,
public readonly providerId?: string,
public readonly originalError?: Error
) {
super(message)
this.name = 'HubProviderError'
}
}
/**
* 解析Hub模型ID
*/
function parseHubModelId(modelId: string): { provider: string; actualModelId: string } {
const parts = modelId.split(':')
if (parts.length !== 2) {
throw new HubProviderError(`Invalid hub model ID format. Expected "provider:modelId", got: ${modelId}`, 'unknown')
}
return {
provider: parts[0],
actualModelId: parts[1]
}
}
/**
* 创建Hub Provider
*/
export function createHubProvider(config: HubProviderConfig): ProviderV2 {
const { hubId } = config
function getTargetProvider(providerId: string): ProviderV2 {
// 从全局注册表获取provider实例
try {
const provider = globalRegistryManagement.getProvider(providerId)
if (!provider) {
throw new HubProviderError(
`Provider "${providerId}" is not initialized. Please call initializeProvider("${providerId}", options) first.`,
hubId,
providerId
)
}
return provider
} catch (error) {
throw new HubProviderError(
`Failed to get provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
hubId,
providerId,
error instanceof Error ? error : undefined
)
}
}
function resolveModel<T extends AiSdkModelType>(
modelId: string,
modelType: T,
methodName: AiSdkMethodName<T>
): AiSdkModelReturn<T> {
const { provider, actualModelId } = parseHubModelId(modelId)
const targetProvider = getTargetProvider(provider)
const fn = targetProvider[methodName] as (id: string) => AiSdkModelReturn<T>
if (!fn) {
throw new HubProviderError(`Provider "${provider}" does not support ${modelType}`, hubId, provider)
}
return fn(actualModelId)
}
return customProvider({
fallbackProvider: {
languageModel: (modelId: string) => resolveModel(modelId, 'text', 'languageModel'),
textEmbeddingModel: (modelId: string) => resolveModel(modelId, 'embedding', 'textEmbeddingModel'),
imageModel: (modelId: string) => resolveModel(modelId, 'image', 'imageModel'),
transcriptionModel: (modelId: string) => resolveModel(modelId, 'transcription', 'transcriptionModel'),
speechModel: (modelId: string) => resolveModel(modelId, 'speech', 'speechModel')
}
})
}

View File

@@ -1,221 +0,0 @@
/**
* Provider 注册表管理器
* 纯粹的管理功能:存储、检索已配置好的 provider 实例
* 基于 AI SDK 原生的 createProviderRegistry
*/
import { EmbeddingModelV2, ImageModelV2, LanguageModelV2, ProviderV2 } from '@ai-sdk/provider'
import { createProviderRegistry, type ProviderRegistryProvider } from 'ai'
type PROVIDERS = Record<string, ProviderV2>
export const DEFAULT_SEPARATOR = '|'
// export type MODEL_ID = `${string}${typeof DEFAULT_SEPARATOR}${string}`
export class RegistryManagement<SEPARATOR extends string = typeof DEFAULT_SEPARATOR> {
private providers: PROVIDERS = {}
private aliases: Set<string> = new Set() // 记录哪些key是别名
private separator: SEPARATOR
private registry: ProviderRegistryProvider<PROVIDERS, SEPARATOR> | null = null
constructor(options: { separator: SEPARATOR } = { separator: DEFAULT_SEPARATOR as SEPARATOR }) {
this.separator = options.separator
}
/**
* 注册已配置好的 provider 实例
*/
registerProvider(id: string, provider: ProviderV2, aliases?: string[]): this {
// 注册主provider
this.providers[id] = provider
// 注册别名都指向同一个provider实例
if (aliases) {
aliases.forEach((alias) => {
this.providers[alias] = provider // 直接存储引用
this.aliases.add(alias) // 标记为别名
})
}
this.rebuildRegistry()
return this
}
/**
* 获取已注册的provider实例
*/
getProvider(id: string): ProviderV2 | undefined {
return this.providers[id]
}
/**
* 批量注册 providers
*/
registerProviders(providers: Record<string, ProviderV2>): this {
Object.assign(this.providers, providers)
this.rebuildRegistry()
return this
}
/**
* 移除 provider同时清理相关别名
*/
unregisterProvider(id: string): this {
const provider = this.providers[id]
if (!provider) return this
// 如果移除的是真实ID需要清理所有指向它的别名
if (!this.aliases.has(id)) {
// 找到所有指向此provider的别名并删除
const aliasesToRemove: string[] = []
this.aliases.forEach((alias) => {
if (this.providers[alias] === provider) {
aliasesToRemove.push(alias)
}
})
aliasesToRemove.forEach((alias) => {
delete this.providers[alias]
this.aliases.delete(alias)
})
} else {
// 如果移除的是别名,只删除别名记录
this.aliases.delete(id)
}
delete this.providers[id]
this.rebuildRegistry()
return this
}
/**
* 立即重建 registry - 每次变更都重建
*/
private rebuildRegistry(): void {
if (Object.keys(this.providers).length === 0) {
this.registry = null
return
}
this.registry = createProviderRegistry<PROVIDERS, SEPARATOR>(this.providers, {
separator: this.separator
})
}
/**
* 获取语言模型 - AI SDK 原生方法
*/
languageModel(id: `${string}${SEPARATOR}${string}`): LanguageModelV2 {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.languageModel(id)
}
/**
* 获取文本嵌入模型 - AI SDK 原生方法
*/
textEmbeddingModel(id: `${string}${SEPARATOR}${string}`): EmbeddingModelV2<string> {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.textEmbeddingModel(id)
}
/**
* 获取图像模型 - AI SDK 原生方法
*/
imageModel(id: `${string}${SEPARATOR}${string}`): ImageModelV2 {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.imageModel(id)
}
/**
* 获取转录模型 - AI SDK 原生方法
*/
transcriptionModel(id: `${string}${SEPARATOR}${string}`): any {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.transcriptionModel(id)
}
/**
* 获取语音模型 - AI SDK 原生方法
*/
speechModel(id: `${string}${SEPARATOR}${string}`): any {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.speechModel(id)
}
/**
* 获取已注册的 provider 列表
*/
getRegisteredProviders(): string[] {
return Object.keys(this.providers)
}
/**
* 检查是否有已注册的 providers
*/
hasProviders(): boolean {
return Object.keys(this.providers).length > 0
}
/**
* 清除所有 providers
*/
clear(): this {
this.providers = {}
this.aliases.clear()
this.registry = null
return this
}
/**
* 解析真实的Provider ID供getAiSdkProviderId使用
* 如果传入的是别名返回真实的Provider ID
* 如果传入的是真实ID直接返回
*/
resolveProviderId(id: string): string {
if (!this.aliases.has(id)) return id // 不是别名,直接返回
// 是别名找到真实ID
const targetProvider = this.providers[id]
for (const [realId, provider] of Object.entries(this.providers)) {
if (provider === targetProvider && !this.aliases.has(realId)) {
return realId
}
}
return id
}
/**
* 检查是否为别名
*/
isAlias(id: string): boolean {
return this.aliases.has(id)
}
/**
* 获取所有别名映射关系
*/
getAllAliases(): Record<string, string> {
const result: Record<string, string> = {}
this.aliases.forEach((alias) => {
result[alias] = this.resolveProviderId(alias)
})
return result
}
}
/**
* 全局注册表管理器实例
* 使用 | 作为分隔符,因为 : 会和 :free 等suffix冲突
*/
export const globalRegistryManagement = new RegistryManagement()

View File

@@ -1,632 +0,0 @@
/**
* 测试真正的 AiProviderRegistry 功能
*/
import { beforeEach, describe, expect, it, vi } from 'vitest'
// 模拟 AI SDK
vi.mock('@ai-sdk/openai', () => ({
createOpenAI: vi.fn(() => ({ name: 'openai-mock' }))
}))
vi.mock('@ai-sdk/anthropic', () => ({
createAnthropic: vi.fn(() => ({ name: 'anthropic-mock' }))
}))
vi.mock('@ai-sdk/azure', () => ({
createAzure: vi.fn(() => ({ name: 'azure-mock' }))
}))
vi.mock('@ai-sdk/deepseek', () => ({
createDeepSeek: vi.fn(() => ({ name: 'deepseek-mock' }))
}))
vi.mock('@ai-sdk/google', () => ({
createGoogleGenerativeAI: vi.fn(() => ({ name: 'google-mock' }))
}))
vi.mock('@ai-sdk/openai-compatible', () => ({
createOpenAICompatible: vi.fn(() => ({ name: 'openai-compatible-mock' }))
}))
vi.mock('@ai-sdk/xai', () => ({
createXai: vi.fn(() => ({ name: 'xai-mock' }))
}))
import {
cleanup,
clearAllProviders,
createAndRegisterProvider,
createProvider,
getAllProviderConfigAliases,
getAllProviderConfigs,
getInitializedProviders,
getLanguageModel,
getProviderConfig,
getProviderConfigByAlias,
getSupportedProviders,
hasInitializedProviders,
hasProviderConfig,
hasProviderConfigByAlias,
isProviderConfigAlias,
ProviderInitializationError,
providerRegistry,
registerMultipleProviderConfigs,
registerProvider,
registerProviderConfig,
resolveProviderConfigId
} from '../registry'
import type { ProviderConfig } from '../schemas'
describe('Provider Registry 功能测试', () => {
beforeEach(() => {
// 清理状态
cleanup()
})
describe('基础功能', () => {
it('能够获取支持的 providers 列表', () => {
const providers = getSupportedProviders()
expect(Array.isArray(providers)).toBe(true)
expect(providers.length).toBeGreaterThan(0)
// 检查返回的数据结构
providers.forEach((provider) => {
expect(provider).toHaveProperty('id')
expect(provider).toHaveProperty('name')
expect(typeof provider.id).toBe('string')
expect(typeof provider.name).toBe('string')
})
// 包含基础 providers
const providerIds = providers.map((p) => p.id)
expect(providerIds).toContain('openai')
expect(providerIds).toContain('anthropic')
expect(providerIds).toContain('google')
})
it('能够获取已初始化的 providers', () => {
// 初始状态下没有已初始化的 providers
expect(getInitializedProviders()).toEqual([])
expect(hasInitializedProviders()).toBe(false)
})
it('能够访问全局注册管理器', () => {
expect(providerRegistry).toBeDefined()
expect(typeof providerRegistry.clear).toBe('function')
expect(typeof providerRegistry.getRegisteredProviders).toBe('function')
expect(typeof providerRegistry.hasProviders).toBe('function')
})
it('能够获取语言模型', () => {
// 在没有注册 provider 的情况下,这个函数应该会抛出错误
expect(() => getLanguageModel('non-existent')).toThrow('No providers registered')
})
})
describe('Provider 配置注册', () => {
it('能够注册自定义 provider 配置', () => {
const config: ProviderConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(() => ({ name: 'custom' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfig('custom-provider')).toBe(true)
expect(getProviderConfig('custom-provider')).toEqual(config)
})
it('能够注册带别名的 provider 配置', () => {
const config: ProviderConfig = {
id: 'custom-provider-with-aliases',
name: 'Custom Provider with Aliases',
creator: vi.fn(() => ({ name: 'custom-aliased' })),
supportsImageGeneration: false,
aliases: ['alias-1', 'alias-2']
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfigByAlias('alias-1')).toBe(true)
expect(hasProviderConfigByAlias('alias-2')).toBe(true)
expect(getProviderConfigByAlias('alias-1')).toEqual(config)
expect(resolveProviderConfigId('alias-1')).toBe('custom-provider-with-aliases')
})
it('拒绝无效的配置', () => {
// 缺少必要字段
const invalidConfig = {
id: 'invalid-provider'
// 缺少 name, creator 等
}
const success = registerProviderConfig(invalidConfig as any)
expect(success).toBe(false)
})
it('能够批量注册 provider 配置', () => {
const configs: ProviderConfig[] = [
{
id: 'provider-1',
name: 'Provider 1',
creator: vi.fn(() => ({ name: 'provider-1' })),
supportsImageGeneration: false
},
{
id: 'provider-2',
name: 'Provider 2',
creator: vi.fn(() => ({ name: 'provider-2' })),
supportsImageGeneration: true
},
{
id: '', // 无效配置
name: 'Invalid Provider',
creator: vi.fn(() => ({ name: 'invalid' })),
supportsImageGeneration: false
} as any
]
const successCount = registerMultipleProviderConfigs(configs)
expect(successCount).toBe(2) // 只有前两个成功
expect(hasProviderConfig('provider-1')).toBe(true)
expect(hasProviderConfig('provider-2')).toBe(true)
expect(hasProviderConfig('')).toBe(false)
})
it('能够获取所有配置和别名信息', () => {
// 注册一些配置
registerProviderConfig({
id: 'test-provider',
name: 'Test Provider',
creator: vi.fn(),
supportsImageGeneration: false,
aliases: ['test-alias']
})
const allConfigs = getAllProviderConfigs()
expect(Array.isArray(allConfigs)).toBe(true)
expect(allConfigs.some((config) => config.id === 'test-provider')).toBe(true)
const aliases = getAllProviderConfigAliases()
expect(aliases['test-alias']).toBe('test-provider')
expect(isProviderConfigAlias('test-alias')).toBe(true)
})
})
describe('Provider 创建和注册', () => {
it('能够创建 provider 实例', async () => {
const config: ProviderConfig = {
id: 'test-create-provider',
name: 'Test Create Provider',
creator: vi.fn(() => ({ name: 'test-created' })),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 创建 provider 实例
const provider = await createProvider('test-create-provider', { apiKey: 'test' })
expect(provider).toBeDefined()
expect(config.creator).toHaveBeenCalledWith({ apiKey: 'test' })
})
it('能够注册 provider 到全局管理器', () => {
const mockProvider = { name: 'mock-provider' }
const config: ProviderConfig = {
id: 'test-register-provider',
name: 'Test Register Provider',
creator: vi.fn(() => mockProvider),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 注册 provider 到全局管理器
const success = registerProvider('test-register-provider', mockProvider)
expect(success).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('test-register-provider')
expect(hasInitializedProviders()).toBe(true)
})
it('能够一步完成创建和注册', async () => {
const config: ProviderConfig = {
id: 'test-create-and-register',
name: 'Test Create and Register',
creator: vi.fn(() => ({ name: 'test-both' })),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 一步完成创建和注册
const success = await createAndRegisterProvider('test-create-and-register', { apiKey: 'test' })
expect(success).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('test-create-and-register')
})
})
describe('Registry 管理', () => {
it('能够清理所有配置和注册的 providers', () => {
// 注册一些配置
registerProviderConfig({
id: 'temp-provider',
name: 'Temp Provider',
creator: vi.fn(() => ({ name: 'temp' })),
supportsImageGeneration: false
})
expect(hasProviderConfig('temp-provider')).toBe(true)
// 清理
cleanup()
expect(hasProviderConfig('temp-provider')).toBe(false)
// 但基础配置应该重新加载
expect(hasProviderConfig('openai')).toBe(true) // 基础 providers 会重新初始化
})
it('能够单独清理已注册的 providers', () => {
// 清理所有 providers
clearAllProviders()
expect(getInitializedProviders()).toEqual([])
expect(hasInitializedProviders()).toBe(false)
})
it('ProviderInitializationError 错误类工作正常', () => {
const error = new ProviderInitializationError('Test error', 'test-provider')
expect(error.message).toBe('Test error')
expect(error.providerId).toBe('test-provider')
expect(error.name).toBe('ProviderInitializationError')
})
})
describe('错误处理', () => {
it('优雅处理空配置', () => {
const success = registerProviderConfig(null as any)
expect(success).toBe(false)
})
it('优雅处理未定义配置', () => {
const success = registerProviderConfig(undefined as any)
expect(success).toBe(false)
})
it('处理空字符串 ID', () => {
const config = {
id: '',
name: 'Empty ID Provider',
creator: vi.fn(() => ({ name: 'empty' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(false)
})
it('处理创建不存在配置的 provider', async () => {
await expect(createProvider('non-existent-provider', {})).rejects.toThrow(
'ProviderConfig not found for id: non-existent-provider'
)
})
it('处理注册不存在配置的 provider', () => {
const mockProvider = { name: 'mock' }
const success = registerProvider('non-existent-provider', mockProvider)
expect(success).toBe(false)
})
it('处理获取不存在配置的情况', () => {
expect(getProviderConfig('non-existent')).toBeUndefined()
expect(getProviderConfigByAlias('non-existent-alias')).toBeUndefined()
expect(hasProviderConfig('non-existent')).toBe(false)
expect(hasProviderConfigByAlias('non-existent-alias')).toBe(false)
})
it('处理批量注册时的部分失败', () => {
const mixedConfigs: ProviderConfig[] = [
{
id: 'valid-provider-1',
name: 'Valid Provider 1',
creator: vi.fn(() => ({ name: 'valid-1' })),
supportsImageGeneration: false
},
{
id: '', // 无效配置
name: 'Invalid Provider',
creator: vi.fn(() => ({ name: 'invalid' })),
supportsImageGeneration: false
} as any,
{
id: 'valid-provider-2',
name: 'Valid Provider 2',
creator: vi.fn(() => ({ name: 'valid-2' })),
supportsImageGeneration: true
}
]
const successCount = registerMultipleProviderConfigs(mixedConfigs)
expect(successCount).toBe(2) // 只有两个有效配置成功
expect(hasProviderConfig('valid-provider-1')).toBe(true)
expect(hasProviderConfig('valid-provider-2')).toBe(true)
expect(hasProviderConfig('')).toBe(false)
})
it('处理动态导入失败的情况', async () => {
const config: ProviderConfig = {
id: 'import-test-provider',
name: 'Import Test Provider',
import: vi.fn().mockRejectedValue(new Error('Import failed')),
creatorFunctionName: 'createTest',
supportsImageGeneration: false
}
registerProviderConfig(config)
await expect(createProvider('import-test-provider', {})).rejects.toThrow('Import failed')
})
})
describe('集成测试', () => {
it('正确处理复杂的配置、创建、注册和清理场景', async () => {
// 初始状态验证
const initialConfigs = getAllProviderConfigs()
expect(initialConfigs.length).toBeGreaterThan(0) // 有基础配置
expect(getInitializedProviders()).toEqual([])
// 注册多个带别名的 provider 配置
const configs: ProviderConfig[] = [
{
id: 'integration-provider-1',
name: 'Integration Provider 1',
creator: vi.fn(() => ({ name: 'integration-1' })),
supportsImageGeneration: false,
aliases: ['alias-1', 'short-name-1']
},
{
id: 'integration-provider-2',
name: 'Integration Provider 2',
creator: vi.fn(() => ({ name: 'integration-2' })),
supportsImageGeneration: true,
aliases: ['alias-2', 'short-name-2']
}
]
const successCount = registerMultipleProviderConfigs(configs)
expect(successCount).toBe(2)
// 验证配置注册成功
expect(hasProviderConfig('integration-provider-1')).toBe(true)
expect(hasProviderConfig('integration-provider-2')).toBe(true)
expect(hasProviderConfigByAlias('alias-1')).toBe(true)
expect(hasProviderConfigByAlias('alias-2')).toBe(true)
// 验证别名映射
const aliases = getAllProviderConfigAliases()
expect(aliases['alias-1']).toBe('integration-provider-1')
expect(aliases['alias-2']).toBe('integration-provider-2')
// 创建和注册 providers
const success1 = await createAndRegisterProvider('integration-provider-1', { apiKey: 'test1' })
const success2 = await createAndRegisterProvider('integration-provider-2', { apiKey: 'test2' })
expect(success1).toBe(true)
expect(success2).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('integration-provider-1')
expect(registeredProviders).toContain('integration-provider-2')
expect(hasInitializedProviders()).toBe(true)
// 清理
cleanup()
// 验证清理后的状态
expect(getInitializedProviders()).toEqual([])
expect(hasProviderConfig('integration-provider-1')).toBe(false)
expect(hasProviderConfig('integration-provider-2')).toBe(false)
expect(getAllProviderConfigAliases()).toEqual({})
// 基础配置应该重新加载
expect(hasProviderConfig('openai')).toBe(true)
})
it('正确处理动态导入配置的 provider', async () => {
const mockModule = { createCustomProvider: vi.fn(() => ({ name: 'custom-dynamic' })) }
const dynamicImportConfig: ProviderConfig = {
id: 'dynamic-import-provider',
name: 'Dynamic Import Provider',
import: vi.fn().mockResolvedValue(mockModule),
creatorFunctionName: 'createCustomProvider',
supportsImageGeneration: false
}
// 注册配置
const configSuccess = registerProviderConfig(dynamicImportConfig)
expect(configSuccess).toBe(true)
// 创建和注册 provider
const registerSuccess = await createAndRegisterProvider('dynamic-import-provider', { apiKey: 'test' })
expect(registerSuccess).toBe(true)
// 验证导入函数被调用
expect(dynamicImportConfig.import).toHaveBeenCalled()
expect(mockModule.createCustomProvider).toHaveBeenCalledWith({ apiKey: 'test' })
// 验证注册成功
expect(getInitializedProviders()).toContain('dynamic-import-provider')
})
it('正确处理大量配置的注册和管理', () => {
const largeConfigList: ProviderConfig[] = []
// 生成50个配置
for (let i = 0; i < 50; i++) {
largeConfigList.push({
id: `bulk-provider-${i}`,
name: `Bulk Provider ${i}`,
creator: vi.fn(() => ({ name: `bulk-${i}` })),
supportsImageGeneration: i % 2 === 0, // 偶数支持图像生成
aliases: [`alias-${i}`, `short-${i}`]
})
}
const successCount = registerMultipleProviderConfigs(largeConfigList)
expect(successCount).toBe(50)
// 验证所有配置都被正确注册
const allConfigs = getAllProviderConfigs()
expect(allConfigs.filter((config) => config.id.startsWith('bulk-provider-')).length).toBe(50)
// 验证别名数量
const aliases = getAllProviderConfigAliases()
const bulkAliases = Object.keys(aliases).filter(
(alias) => alias.startsWith('alias-') || alias.startsWith('short-')
)
expect(bulkAliases.length).toBe(100) // 每个 provider 有2个别名
// 随机验证几个配置
expect(hasProviderConfig('bulk-provider-0')).toBe(true)
expect(hasProviderConfig('bulk-provider-25')).toBe(true)
expect(hasProviderConfig('bulk-provider-49')).toBe(true)
// 验证别名工作正常
expect(resolveProviderConfigId('alias-25')).toBe('bulk-provider-25')
expect(isProviderConfigAlias('short-30')).toBe(true)
// 清理能正确处理大量数据
cleanup()
const cleanupAliases = getAllProviderConfigAliases()
expect(
Object.keys(cleanupAliases).filter((alias) => alias.startsWith('alias-') || alias.startsWith('short-'))
).toEqual([])
})
})
describe('边界测试', () => {
it('处理包含特殊字符的 provider IDs', () => {
const specialCharsConfigs: ProviderConfig[] = [
{
id: 'provider-with-dashes',
name: 'Provider With Dashes',
creator: vi.fn(() => ({ name: 'dashes' })),
supportsImageGeneration: false
},
{
id: 'provider_with_underscores',
name: 'Provider With Underscores',
creator: vi.fn(() => ({ name: 'underscores' })),
supportsImageGeneration: false
},
{
id: 'provider.with.dots',
name: 'Provider With Dots',
creator: vi.fn(() => ({ name: 'dots' })),
supportsImageGeneration: false
}
]
const successCount = registerMultipleProviderConfigs(specialCharsConfigs)
expect(successCount).toBeGreaterThan(0) // 至少有一些成功
// 验证支持的特殊字符格式
if (hasProviderConfig('provider-with-dashes')) {
expect(getProviderConfig('provider-with-dashes')).toBeDefined()
}
if (hasProviderConfig('provider_with_underscores')) {
expect(getProviderConfig('provider_with_underscores')).toBeDefined()
}
})
it('处理空的批量注册', () => {
const successCount = registerMultipleProviderConfigs([])
expect(successCount).toBe(0)
// 确保没有额外的配置被添加
const configsBefore = getAllProviderConfigs().length
expect(configsBefore).toBeGreaterThan(0) // 应该有基础配置
})
it('处理重复的配置注册', () => {
const config: ProviderConfig = {
id: 'duplicate-test-provider',
name: 'Duplicate Test Provider',
creator: vi.fn(() => ({ name: 'duplicate' })),
supportsImageGeneration: false
}
// 第一次注册成功
expect(registerProviderConfig(config)).toBe(true)
expect(hasProviderConfig('duplicate-test-provider')).toBe(true)
// 重复注册相同的配置(允许覆盖)
const updatedConfig: ProviderConfig = {
...config,
name: 'Updated Duplicate Test Provider'
}
expect(registerProviderConfig(updatedConfig)).toBe(true)
expect(hasProviderConfig('duplicate-test-provider')).toBe(true)
// 验证配置被更新
const retrievedConfig = getProviderConfig('duplicate-test-provider')
expect(retrievedConfig?.name).toBe('Updated Duplicate Test Provider')
})
it('处理极长的 ID 和名称', () => {
const longId = 'very-long-provider-id-' + 'x'.repeat(100)
const longName = 'Very Long Provider Name ' + 'Y'.repeat(100)
const config: ProviderConfig = {
id: longId,
name: longName,
creator: vi.fn(() => ({ name: 'long-test' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfig(longId)).toBe(true)
const retrievedConfig = getProviderConfig(longId)
expect(retrievedConfig?.name).toBe(longName)
})
it('处理大量别名的配置', () => {
const manyAliases = Array.from({ length: 50 }, (_, i) => `alias-${i}`)
const config: ProviderConfig = {
id: 'provider-with-many-aliases',
name: 'Provider With Many Aliases',
creator: vi.fn(() => ({ name: 'many-aliases' })),
supportsImageGeneration: false,
aliases: manyAliases
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
// 验证所有别名都能正确解析
manyAliases.forEach((alias) => {
expect(hasProviderConfigByAlias(alias)).toBe(true)
expect(resolveProviderConfigId(alias)).toBe('provider-with-many-aliases')
expect(isProviderConfigAlias(alias)).toBe(true)
})
})
})
})

View File

@@ -1,264 +0,0 @@
import { describe, expect, it, vi } from 'vitest'
import {
type BaseProviderId,
baseProviderIds,
baseProviderIdSchema,
baseProviders,
type CustomProviderId,
customProviderIdSchema,
providerConfigSchema,
type ProviderId,
providerIdSchema
} from '../schemas'
describe('Provider Schemas', () => {
describe('baseProviders', () => {
it('包含所有预期的基础 providers', () => {
expect(baseProviders).toBeDefined()
expect(Array.isArray(baseProviders)).toBe(true)
expect(baseProviders.length).toBeGreaterThan(0)
const expectedIds = [
'openai',
'openai-responses',
'openai-compatible',
'anthropic',
'google',
'xai',
'azure',
'deepseek'
]
const actualIds = baseProviders.map((p) => p.id)
expectedIds.forEach((id) => {
expect(actualIds).toContain(id)
})
})
it('每个基础 provider 有必要的属性', () => {
baseProviders.forEach((provider) => {
expect(provider).toHaveProperty('id')
expect(provider).toHaveProperty('name')
expect(provider).toHaveProperty('creator')
expect(provider).toHaveProperty('supportsImageGeneration')
expect(typeof provider.id).toBe('string')
expect(typeof provider.name).toBe('string')
expect(typeof provider.creator).toBe('function')
expect(typeof provider.supportsImageGeneration).toBe('boolean')
})
})
it('provider ID 是唯一的', () => {
const ids = baseProviders.map((p) => p.id)
const uniqueIds = [...new Set(ids)]
expect(ids).toEqual(uniqueIds)
})
})
describe('baseProviderIds', () => {
it('正确提取所有基础 provider IDs', () => {
expect(baseProviderIds).toBeDefined()
expect(Array.isArray(baseProviderIds)).toBe(true)
expect(baseProviderIds.length).toBe(baseProviders.length)
baseProviders.forEach((provider) => {
expect(baseProviderIds).toContain(provider.id)
})
})
})
describe('baseProviderIdSchema', () => {
it('验证有效的基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝无效的基础 provider IDs', () => {
const invalidIds = ['invalid', 'not-exists', '']
invalidIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(false)
})
})
})
describe('customProviderIdSchema', () => {
it('接受有效的自定义 provider IDs', () => {
const validIds = ['custom-provider', 'my-ai-service', 'company-llm-v2']
validIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝与基础 provider IDs 冲突的 IDs', () => {
baseProviderIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(false)
})
})
it('拒绝空字符串', () => {
expect(customProviderIdSchema.safeParse('').success).toBe(false)
})
})
describe('providerIdSchema', () => {
it('接受基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('接受有效的自定义 provider IDs', () => {
const validCustomIds = ['custom-provider', 'my-ai-service']
validCustomIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝无效的 IDs', () => {
const invalidIds = ['', undefined, null, 123]
invalidIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(false)
})
})
})
describe('providerConfigSchema', () => {
it('验证带有 creator 的有效配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(),
supportsImageGeneration: true
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
})
it('验证带有 import 配置的有效配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
import: vi.fn(),
creatorFunctionName: 'createCustom',
supportsImageGeneration: false
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
})
it('拒绝既没有 creator 也没有 import 配置的配置', () => {
const invalidConfig = {
id: 'invalid',
name: 'Invalid Provider',
supportsImageGeneration: false
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
it('为 supportsImageGeneration 设置默认值', () => {
const config = {
id: 'test',
name: 'Test',
creator: vi.fn()
}
const result = providerConfigSchema.safeParse(config)
expect(result.success).toBe(true)
if (result.success) {
expect(result.data.supportsImageGeneration).toBe(false)
}
})
it('拒绝使用基础 provider ID 的配置', () => {
const invalidConfig = {
id: 'openai', // 基础 provider ID
name: 'Should Fail',
creator: vi.fn()
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
it('拒绝缺少必需字段的配置', () => {
const invalidConfigs = [
{ name: 'Missing ID', creator: vi.fn() },
{ id: 'missing-name', creator: vi.fn() },
{ id: '', name: 'Empty ID', creator: vi.fn() },
{ id: 'valid-custom', name: '', creator: vi.fn() }
]
invalidConfigs.forEach((config) => {
expect(providerConfigSchema.safeParse(config).success).toBe(false)
})
})
})
describe('Schema 验证功能', () => {
it('baseProviderIdSchema 正确验证基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(true)
})
expect(baseProviderIdSchema.safeParse('invalid-id').success).toBe(false)
})
it('customProviderIdSchema 正确验证自定义 provider IDs', () => {
const customIds = ['custom-provider', 'my-service', 'company-llm']
customIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(true)
})
// 拒绝基础 provider IDs
baseProviderIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(false)
})
})
it('providerIdSchema 接受基础和自定义 provider IDs', () => {
// 基础 IDs
baseProviderIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
// 自定义 IDs
const customIds = ['custom-provider', 'my-service']
customIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('providerConfigSchema 验证完整的 provider 配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(),
supportsImageGeneration: true
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
const invalidConfig = {
id: 'openai', // 不允许基础 provider ID
name: 'OpenAI',
creator: vi.fn()
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
})
describe('类型推导', () => {
it('BaseProviderId 类型正确', () => {
const id: BaseProviderId = 'openai'
expect(baseProviderIds).toContain(id)
})
it('CustomProviderId 类型是字符串', () => {
const id: CustomProviderId = 'custom-provider'
expect(typeof id).toBe('string')
})
it('ProviderId 类型支持基础和自定义 IDs', () => {
const baseId: ProviderId = 'openai'
const customId: ProviderId = 'custom-provider'
expect(typeof baseId).toBe('string')
expect(typeof customId).toBe('string')
})
})
})

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@@ -1,291 +0,0 @@
/**
* AI Provider 配置工厂
* 提供类型安全的 Provider 配置构建器
*/
import type { ProviderId, ProviderSettingsMap } from './types'
/**
* 通用配置基础类型,包含所有 Provider 共有的属性
*/
export interface BaseProviderConfig {
apiKey?: string
baseURL?: string
timeout?: number
headers?: Record<string, string>
fetch?: typeof globalThis.fetch
}
/**
* 完整的配置类型结合基础配置、AI SDK 配置和特定 Provider 配置
*/
type CompleteProviderConfig<T extends ProviderId> = BaseProviderConfig & Partial<ProviderSettingsMap[T]>
type ConfigHandler<T extends ProviderId> = (
builder: ProviderConfigBuilder<T>,
provider: CompleteProviderConfig<T>
) => void
const configHandlers: {
[K in ProviderId]?: ConfigHandler<K>
} = {
azure: (builder, provider) => {
const azureBuilder = builder as ProviderConfigBuilder<'azure'>
const azureProvider = provider as CompleteProviderConfig<'azure'>
azureBuilder.withAzureConfig({
apiVersion: azureProvider.apiVersion,
resourceName: azureProvider.resourceName
})
}
}
export class ProviderConfigBuilder<T extends ProviderId = ProviderId> {
private config: CompleteProviderConfig<T> = {} as CompleteProviderConfig<T>
constructor(private providerId: T) {}
/**
* 设置 API Key
*/
withApiKey(apiKey: string): this
withApiKey(apiKey: string, options: T extends 'openai' ? { organization?: string; project?: string } : never): this
withApiKey(apiKey: string, options?: any): this {
this.config.apiKey = apiKey
// 类型安全的 OpenAI 特定配置
if (this.providerId === 'openai' && options) {
const openaiConfig = this.config as CompleteProviderConfig<'openai'>
if (options.organization) {
openaiConfig.organization = options.organization
}
if (options.project) {
openaiConfig.project = options.project
}
}
return this
}
/**
* 设置基础 URL
*/
withBaseURL(baseURL: string) {
this.config.baseURL = baseURL
return this
}
/**
* 设置请求配置
*/
withRequestConfig(options: { headers?: Record<string, string>; fetch?: typeof fetch }): this {
if (options.headers) {
this.config.headers = { ...this.config.headers, ...options.headers }
}
if (options.fetch) {
this.config.fetch = options.fetch
}
return this
}
/**
* Azure OpenAI 特定配置
*/
withAzureConfig(options: { apiVersion?: string; resourceName?: string }): T extends 'azure' ? this : never
withAzureConfig(options: any): any {
if (this.providerId === 'azure') {
const azureConfig = this.config as CompleteProviderConfig<'azure'>
if (options.apiVersion) {
azureConfig.apiVersion = options.apiVersion
}
if (options.resourceName) {
azureConfig.resourceName = options.resourceName
}
}
return this
}
/**
* 设置自定义参数
*/
withCustomParams(params: Record<string, any>) {
Object.assign(this.config, params)
return this
}
/**
* 构建最终配置
*/
build(): ProviderSettingsMap[T] {
return this.config as ProviderSettingsMap[T]
}
}
/**
* Provider 配置工厂
* 提供便捷的配置创建方法
*/
export class ProviderConfigFactory {
/**
* 创建配置构建器
*/
static builder<T extends ProviderId>(providerId: T): ProviderConfigBuilder<T> {
return new ProviderConfigBuilder(providerId)
}
/**
* 从通用Provider对象创建配置 - 使用更优雅的处理器模式
*/
static fromProvider<T extends ProviderId>(
providerId: T,
provider: CompleteProviderConfig<T>,
options?: {
headers?: Record<string, string>
[key: string]: any
}
): ProviderSettingsMap[T] {
const builder = new ProviderConfigBuilder<T>(providerId)
// 设置基本配置
if (provider.apiKey) {
builder.withApiKey(provider.apiKey)
}
if (provider.baseURL) {
builder.withBaseURL(provider.baseURL)
}
// 设置请求配置
if (options?.headers) {
builder.withRequestConfig({
headers: options.headers
})
}
// 使用配置处理器模式 - 更加优雅和可扩展
const handler = configHandlers[providerId]
if (handler) {
handler(builder, provider)
}
// 添加其他自定义参数
if (options) {
const customOptions = { ...options }
delete customOptions.headers // 已经处理过了
if (Object.keys(customOptions).length > 0) {
builder.withCustomParams(customOptions)
}
}
return builder.build()
}
/**
* 快速创建 OpenAI 配置
*/
static createOpenAI(
apiKey: string,
options?: {
baseURL?: string
organization?: string
project?: string
}
) {
const builder = this.builder('openai')
// 使用类型安全的重载
if (options?.organization || options?.project) {
builder.withApiKey(apiKey, {
organization: options.organization,
project: options.project
})
} else {
builder.withApiKey(apiKey)
}
return builder.withBaseURL(options?.baseURL || 'https://api.openai.com').build()
}
/**
* 快速创建 Anthropic 配置
*/
static createAnthropic(
apiKey: string,
options?: {
baseURL?: string
}
) {
return this.builder('anthropic')
.withApiKey(apiKey)
.withBaseURL(options?.baseURL || 'https://api.anthropic.com')
.build()
}
/**
* 快速创建 Azure OpenAI 配置
*/
static createAzureOpenAI(
apiKey: string,
options: {
baseURL: string
apiVersion?: string
resourceName?: string
}
) {
return this.builder('azure')
.withApiKey(apiKey)
.withBaseURL(options.baseURL)
.withAzureConfig({
apiVersion: options.apiVersion,
resourceName: options.resourceName
})
.build()
}
/**
* 快速创建 Google 配置
*/
static createGoogle(
apiKey: string,
options?: {
baseURL?: string
projectId?: string
location?: string
}
) {
return this.builder('google')
.withApiKey(apiKey)
.withBaseURL(options?.baseURL || 'https://generativelanguage.googleapis.com')
.build()
}
/**
* 快速创建 Vertex AI 配置
*/
static createVertexAI() {
// credentials: {
// clientEmail: string
// privateKey: string
// },
// options?: {
// project?: string
// location?: string
// }
// return this.builder('google-vertex')
// .withGoogleCredentials(credentials)
// .withGoogleVertexConfig({
// project: options?.project,
// location: options?.location
// })
// .build()
}
static createOpenAICompatible(baseURL: string, apiKey: string) {
return this.builder('openai-compatible').withBaseURL(baseURL).withApiKey(apiKey).build()
}
}
/**
* 便捷的配置创建函数
*/
export const createProviderConfig = ProviderConfigFactory.fromProvider
export const providerConfigBuilder = ProviderConfigFactory.builder

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@@ -1,83 +0,0 @@
/**
* Providers 模块统一导出 - 独立Provider包
*/
// ==================== 核心管理器 ====================
// Provider 注册表管理器
export { globalRegistryManagement, RegistryManagement } from './RegistryManagement'
// Provider 核心功能
export {
// 状态管理
cleanup,
clearAllProviders,
createAndRegisterProvider,
createProvider,
getAllProviderConfigAliases,
getAllProviderConfigs,
getImageModel,
// 工具函数
getInitializedProviders,
getLanguageModel,
getProviderConfig,
getProviderConfigByAlias,
getSupportedProviders,
getTextEmbeddingModel,
hasInitializedProviders,
// 工具函数
hasProviderConfig,
// 别名支持
hasProviderConfigByAlias,
isProviderConfigAlias,
// 错误类型
ProviderInitializationError,
// 全局访问
providerRegistry,
registerMultipleProviderConfigs,
registerProvider,
// 统一Provider系统
registerProviderConfig,
resolveProviderConfigId
} from './registry'
// ==================== 基础数据和类型 ====================
// 基础Provider数据源
export { baseProviderIds, baseProviders } from './schemas'
// 类型定义和Schema
export type {
BaseProviderId,
CustomProviderId,
DynamicProviderRegistration,
ProviderConfig,
ProviderId
} from './schemas' // 从 schemas 导出的类型
export { baseProviderIdSchema, customProviderIdSchema, providerConfigSchema, providerIdSchema } from './schemas' // Schema 导出
export type {
DynamicProviderRegistry,
ExtensibleProviderSettingsMap,
ProviderError,
ProviderSettingsMap,
ProviderTypeRegistrar
} from './types'
// ==================== 工具函数 ====================
// Provider配置工厂
export {
type BaseProviderConfig,
createProviderConfig,
ProviderConfigBuilder,
providerConfigBuilder,
ProviderConfigFactory
} from './factory'
// 工具函数
export { formatPrivateKey } from './utils'
// ==================== 扩展功能 ====================
// Hub Provider 功能
export { createHubProvider, type HubProviderConfig, HubProviderError } from './HubProvider'

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