* ✨ feat: add NewAPI as a router provider for multi-model aggregation
* Update packages/model-runtime/src/newapi/index.ts
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update packages/model-runtime/src/newapi/index.ts
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update packages/model-runtime/src/newapi/index.ts
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update packages/model-runtime/src/newapi/index.ts
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* 🐛 fix: correct baseURL configuration and add comprehensive tests for NewAPI
- Fix baseURL handling to avoid double /v1 path
- Add url-join for proper URL concatenation
- Simplify router models functions using Array.from and filter
- Add comprehensive test coverage with 100% branch coverage
- Fix TypeScript type issues in tests
* 🧪 test: implement 100% branch coverage for NewAPI runtime
- Add comprehensive test suite with 44 test cases
- Achieve 100% branch coverage for all conditional logic
- Test all provider detection, pricing calculation, and data handling branches
- Fix TypeScript type errors with proper type annotations
- Maintain all 44 tests passing with zero errors
- Cover handlePayload, getProviderFromOwnedBy, and models function branches
- No business code modifications - test-only changes
* 🔨 fix: adjust for review comment https://github.com/lobehub/lobe-chat/pull/9041#pullrequestreview-3183464594
* 🐛 fix: resolve NewAPI baseURL transmission issue with dynamic routers configuration
- Extend RouterRuntime to support dynamic routers: RouterInstance[] | ((options) => RouterInstance[])
- Refactor NewAPI from IIFE closure to dynamic configuration function
- Fix timing issue where routers were configured before baseURL was available
- Add comprehensive tests for dynamic routers functionality
- Resolve 'Invalid URL input: v1/models' error by ensuring user baseURL propagates correctly
- Maintain backward compatibility with static routers arrays
Tests: NewAPI (44→45), RouterRuntime (15→17), all passing
- Add 'lmstudio' to providerWhitelist in both user and aiInfra store selectors
- Fix issue where LMStudio's client fetch mode toggle was non-functional
- Users can now properly control client/server request mode for LMStudio
- Resolves forced client mode when only baseURL is configured
Fixes client request mode control for LMStudio provider
* 👷 build: add docker compose to setup local services for development
* 👷 build: setup dotenv-expand for all the npm scripts
* 🐛 fix: remove useless comments
* 📚 docs: add server-side database setup guide with i18n support
- Add comprehensive server-side database setup documentation
- Include step-by-step Docker service configuration
- Add Chinese localization for better developer experience
- Cover environment setup, database migration, and verification steps
* 🐛 fix: adjust ControlsForm component to use responsive widths for descriptions
* 🐛 fix: update ControlsForm component for responsive description widths on narrow screens
* feat: add Nebius model support and configuration
* feat(nebius): enhance model definitions and add support for image and embedding models
* Implement code changes to enhance functionality and improve performance
* feat(nebius): remove 'created' field from model standardization
* feat(novita): format model pricing and enhance model data structure
* feat: 更新模型处理逻辑,优化模型字段和定价格式
* feat(openrouter): 更新模型接口,优化价格格式和上下文窗口大小
* feat: 添加定价格式化功能,更新模型接口以支持新的定价结构
* fix test
* feat: 添加Hermes-4-70B和Hermes-4-405B模型,更新定价结构
* feat: add functionCall, reasoning, and vision properties to model list
* 拆分 pr
* Delete src/config/aiModels/nebius.ts
* Delete src/config/aiModels/index.ts
* Delete src/config/aiModels/openrouter.ts
* add change
* 添加 nebius 模型的导出路径
* Update providers.tsx
* 更新 Gemini 2.5 Flash Image Preview 模型名称为 "Nano Banana"
* fix
---------
Co-authored-by: Arvin Xu <arvinx@foxmail.com>
* move
* refactor with model banks
* refactor with model banks
* refactor @/config/aiModels to model-bank
* refactor @/config/aiModels to model-bank
* fix model bank exports
* clean
* add test workflow
* try again
* fix
* add exports tests
* fix model bank alias
* Update tsconfig.json
* fix import issue
* clean unused code
* fix tests
* 🔨 chore: add image generation development environment setup
- Add setup-image-generation-dev.sh script for automated environment configuration
- Add English and Chinese documentation for image generation development setup
- Configure PostgreSQL and MinIO for local development with automatic bucket creation
- Include database migration and S3 environment variable configuration
* Update scripts/setup-image-generation-dev.sh
✨ feat(desktop): add comprehensive Linux package format support
- Add rpm and tar.gz targets to electron-builder configuration
- Update GitHub Actions workflows to upload all Linux package formats
- Support for Ubuntu/Debian (.deb), Snap (.snap), RPM-based distributions (.rpm)
- Include universal tar.gz archives for maximum Linux distribution compatibility
- Ensure proper artifact collection and release publishing for all formats
This enables desktop app distribution across major Linux ecosystems including
Ubuntu, CentOS, openSUSE, Arch Linux, and Chinese domestic OS like UOS and Kylin.
* test workflow
* test workflow
* add test workflow
* add test workflow
* add test config
* add test config
* add test config
* add test config
* add test config
* update
* refactor tests
* fix tests
* fix tests
* exclude packages
* improve test
* fix test
* add a new package
- Add tmp, temp, .temp directories to .eslintignore
- Add .local, .cache, .claude, .serena directories to .eslintignore
- Create .stylelintignore with same ignore patterns
- Update tsconfig.json to exclude temporary directories from type checking
- Prevents linting and type checking of temporary and AI tool directories
* ♻️ refactor(utils): extract args parsing logic from ArgsInput component
- Extract parseArgs and argsToString functions to src/utils/args.ts
- Add comprehensive test suite with 19 test cases covering edge cases
- Fix escaped quote handling in parseArgs function
- Replace String.replace() with String.replaceAll() for better readability
- Improve code reusability and maintainability following project best practices
* 📝 docs(utils): improve JSDoc comments and clean up redundant comments
- Add comprehensive JSDoc with @param and @returns for args functions
- Translate inline comments to English for consistency
- Remove redundant comments in ArgsInput component
- Keep only essential comments and improve code clarity
- Improve code documentation quality and IDE support
* ♻️ refactor(ArgsInput): completely redesign as array editor
- Replace single input with individual argument inputs
- Add visual array structure with add/remove buttons
- Support keyboard shortcuts (Enter to add, Backspace to delete)
- Improve UX with proper array operations and indexing
- Remove dependency on args parsing utils for better performance
* 🌐 i18n: add ArgsInput internationalization support
- Add ArgsInput translations for en-US and zh-CN
- Add TypeScript type definitions for new translation keys
- Support dynamic placeholder with argument index
- Fix TypeScript error for missing translation keys
* Update anthropic.ts
* Update anthropic.ts
* Update aihubmix.ts
* fix: `temperature` and `top_p` cannot both be specified for this model. Please use only one.
* update
* 更新 Groq 模型
* 🐛 fix: settings window can't exit when fullscreen
* 🐛 fix: refactor macOS fullscreen hide to prevent black screen
- Unified fullscreen handling in Browser.hide() method
- Fixed black screen issue when hiding fullscreen windows on macOS
- Simplified close event handler by removing duplicate logic
- Updated toggleVisible() to use consistent hide() method
- Added platform check to only apply fix on macOS
Fixes: https://github.com/electron/electron/issues/20263🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
Reverted a micro-change which was changed during some testing (back to original)
Removed Okta Test
Removed deprecated env variables
Add Okta support to auth config and tests
* Add Okta support to auth config and tests
* Added documentation
* Removed deprecated env variables
* Added Okta as SSO Provider
* Removed Okta Test
* Reverted a micro-change which was changed during some testing (back to original)
* Added Okta to SSO providers list
* ✨ feat: Implement API Key management functionality
- Added new components for API Key management including creation, deletion, and display.
- Introduced a new database schema for storing API Keys.
- Implemented server and client services for API Key operations.
- Integrated API Key management into the profile section with appropriate routing and feature flags.
- Enhanced localization support for API Key related UI elements.
This commit lays the groundwork for managing API Keys within the application, allowing users to create, view, and manage their keys effectively.
* fix: server config unit test
* ✨ feat(database): Create api_keys table with conditional existence check
- Added a conditional check to create the "api_keys" table only if it does not already exist.
- Ensured the foreign key constraint for "user_id" references the "users" table remains intact.
This change enhances the migration process by preventing errors during table creation if the table already exists.
* feat: Implement API Key management interface
- Introduced a new Client component for managing API keys, including creation, updating, and deletion functionalities.
- Replaced the previous page component with the new Client component in the API key management page.
- Removed obsolete client and server service files related to API key management, streamlining the service layer.
This update enhances the user experience by providing a dedicated interface for API key operations.
* Update test data for plugin action to use avatar icon path (rather than hard coded)
* Update tests to use BRANDING_NAME constant instead of hardcoded 'LobeChat' and update avatar icon path in chat message tests
* Update tests to replace hardcoded avatar paths with constants for inbox and user avatars
* Update plugin action tests to use DEFAULT_INBOX_AVATAR constant instead of hardcoded path
description: Complete guide for adding a new AI provider documentation to LobeChat
alwaysApply: false
---
# Adding New AI Provider Documentation
This document provides a step-by-step guide for adding documentation for a new AI provider to LobeChat, based on the complete workflow used for adding providers like BFL (Black Forest Labs) and FAL.
## Overview
Adding a new provider requires creating both user-facing documentation and technical configuration files. The process involves:
1. Creating usage documentation (EN + CN)
2. Adding environment variable documentation (EN + CN)
3. Updating Docker configuration files
4. Updating .env.example file
5. Preparing image resources
## Step 1: Create Provider Usage Documentation
Create user-facing documentation that explains how to use the new provider.
- Description: This is the API key you applied for in the {Provider Name} service.
- Default: -
- Example: `{api-key-format-example}`
### `{PROVIDER}_MODEL_LIST`
- Type: Optional
- Description: Used to control the {Provider Name} model list. Use `+` to add a model, `-` to hide a model, and `model_name=display_name` to customize the display name of a model. Separate multiple entries with commas. The definition syntax follows the same rules as other providers' model lists.
@@ -26,26 +26,11 @@ Gather the modified code and context. Please strictly follow the process below:
### Code Style
- Ensure JSDoc comments accurately reflect the implementation; update them when needed.
- Look for opportunities to simplify or modernize code with the latest JavaScript/TypeScript features.
- Prefer `async`/`await` over callbacks or chained `.then` promises.
- Use consistent, descriptive naming—avoid obscure abbreviations.
- Replace magic numbers or strings with well-named constants.
- Use semantically meaningful variable, function, and class names.
- Ignore purely formatting issues and other autofixable lint problems.
read [typescript.mdc](mdc:.cursor/rules/typescript.mdc) for the consolidated project code style and optimization rules.
### Code Optimization
- Prefer `for…of` loops to index-based `for` loops when feasible.
- Decide whether callbacks should be **debounced** or **throttled**.
- Use components from `@lobehub/ui`, Ant Design, or the existing design system instead of raw HTML tags (e.g., `Button` vs. `button`).
- reuse npm packages already installed (e.g., `lodash/omit`) rather than reinventing the wheel.
- Design for dark mode and mobile responsiveness:
- Use the `antd-style` token system instead of hard-coded colors.
- Select the proper component variants.
- Performance considerations:
- Where safe, convert sequential async flows to concurrent ones with `Promise.all`, `Promise.race`, etc.
- Query only the required columns from a database rather than selecting entire rows.
The optimization checklist has been consolidated into [typescript.mdc](mdc:.cursor/rules/typescript.mdc): loops, debouncing/throttling, design system components, theming tokens, concurrency with `Promise.*`, minimal DB column selection, and package reuse.
Before producing any Mermaid diagram, you **must** compare your final code line-by-line against every rule in the following checklist to ensure 100% compliance. **This is a hard requirement and takes precedence over other stylistic suggestions.** Please follow these action steps:
1. Plan the Mermaid diagram logic in your mind.
2. Write the Mermaid code.
3. **Carefully review your code line-by-line against the entire checklist below.**
4. Fix any aspect of your code that doesn't comply.
5. Use the `validateMermaid` tool to check your code for syntax errors. Only proceed if validation passes.
6. Output the final, compliant, and copy-ready Mermaid code block.
7. Immediately after the Mermaid code block, output:
I have checked that the Mermaid syntax fully complies with the validation checklist.
---
### Checklist Details
#### Rule 1: Edge Labels – Must Be Plain Text Only
> **Essence:** Anything inside `|...|` must contain pure, unformatted text. Absolutely NO Markdown, list markers, or parentheses/brackets allowed—these often cause rendering failures.
- **✅ Do:** `A -->|Process plain text data| B`
- **❌ Don't:** `A -->|1. Ordered list item| B` (No numbered lists)
- **❌ Don't:** `CC --"1. fetch('/api/...')"--> API` (No square brackets)
- **❌ Don't:** `A -->|- Unordered list item| B` (No hyphen lists)
- **❌ Don't:** `A -->|Transform (important)| B` (No parentheses)
- **❌ Don't:** `A -->|Transform [important]| B` (No square brackets)
#### Rule 2: Node Definition – Handle Special Characters with Care
> **Essence:** When node text or subgraph titles contain special characters like `()` or `[]`, wrap the text in quotes to avoid conflicts with Mermaid shape syntax.
- **When your node text includes parentheses (e.g., 'React (JSX)'):**
- **✅ Do:** `I_REACT["<b>React component (JSX)</b>"]` (Quotes wrap all text)
- **❌ Don't:** `I_REACT(<b>React component (JSX)</b>)` (Wrong, Mermaid parses this as a shape)
- **❌ Don't:** `subgraph Plugin Features (Plugins)` (Wrong, subgraph titles with parentheses must also be wrapped in quotes)
#### Rule 3: Double Quotes in Text – Must Be Escaped
> **Essence:** Use `"` for double quotes **inside node text**.
read [package.json](mdc:package.json) to know all npm packages you can use. read [folder-structure.mdx](mdc:docs/development/basic/folder-structure.mdx) to learn project structure.
read [package.json](mdc:package.json) to know all npm packages you can use.
The project uses the following technologies:
@@ -42,17 +42,3 @@ The project uses the following technologies:
- Cursor AI for code editing and AI coding assistance
Note: All tools and libraries used are the latest versions. The application only needs to be compatible with the latest browsers;
## Often used npm scripts
```bash
# type check
bun type-check
# install dependencies
pnpm install
# !: don't any build script to check weather code can work after modify
```
check [testing guide](./testing-guide/testing-guide.mdc) to learn test scripts.
- Add server service: `src/server/services/<domain>`
- Add a new model/provider: `src/config/modelProviders/<provider>.ts` + `packages/model-bank/src/aiModels/<provider>.ts` + `packages/model-runtime/src/<provider>/index.ts`
- Add DB schema/model/repository: `packages/database/src/{schemas|models|repositories}`
- Add Zustand slice: `src/store/<domain>/slices`
## Env Modes
- `NEXT_PUBLIC_CLIENT_DB`: selects client DB mode (e.g., `pglite`) vs server-backed
- `NEXT_PUBLIC_IS_DESKTOP_APP`: enables desktop-specific routes and behavior
- `NEXT_PUBLIC_SERVICE_MODE`: controls service routing preference (client/server)
## Boundaries
- Keep client logic in `src/services`; server-only logic stays in `src/server/services`
- Don’t mix Web API (`webapi/`) with tRPC (`src/server/routers/`)
- Place business UI under `src/features`, global reusable UI under `src/components`
This document explains how the LobeChat project's Cursor rules system works and serves as an index for manually accessible rules.
## 🎯 Core Principle
**All rules are equal** - there are no priorities or "recommendations" between different rule sources. You should follow all applicable rules simultaneously.
### 4. **Manual Rules Index** - This file + `read_file`
- **What**: Additional rules not covered by the above mechanisms
- **Why needed**: Cursor's rule system only supports "agent request" or "auto attach" modes
- **Access**: Use `read_file` tool to read specific `.mdc` files
## 🔧 When to Use `read_file` for Rules
Use `read_file` to access rules from the index below when:
1. **Gap identification**: You determine a rule is needed for the current task
2. **No auto-trigger**: The rule isn't provided in `cursor_rules_context` (because relevant files weren't @ mentioned)
3. **Not agent-requestable**: The rule isn't available via `fetch_rules`
## 📋 Available Rules Index
# 📋 Available Rules Index
The following rules are available via `read_file` from the `.cursor/rules/` directory:
## General
- `project-introduce.mdc` – Project description and tech stack
- `cursor-rules.mdc` – Cursor rules authoring and optimization guide
- `code-review.mdc` – How to code review
## Backend
- `backend-architecture.mdc` – Backend layer architecture and design guidelines
- `define-database-model.mdc` – Database model definition guidelines
- `drizzle-schema-style-guide.mdc` – Style guide for defining Drizzle ORM schemas
## Frontend
- `react-component.mdc` – React component style guide and conventions
- `testing-guide.mdc` – Comprehensive testing guide for Vitest environment
- `i18n.mdc` – Internationalization guide using react-i18next
- `typescript.mdc` – TypeScript code style guide
- `packages/react-layout-kit.mdc` – Usage guide for react-layout-kit
## State Management
- `zustand-action-patterns.mdc` – Recommended patterns for organizing Zustand actions
- `zustand-slice-organization.mdc` – Best practices for structuring Zustand slices
## ❌ Common Misunderstandings to Avoid
## Desktop (Electron)
1. **"Priority confusion"**: There's no hierarchy between rule sources - they're complementary, not competitive
2. **"Dynamic expectations"**: `cursor_rules_context` only updates when you @ files - it won't automatically include rules for tasks you're thinking about
3. **"Tool redundancy"**: Each access method serves a different purpose - they're not alternatives to choose from
- `desktop-feature-implementation.mdc` – Implementing new Electron desktop features
- `desktop-controller-tests.mdc` – Desktop controller unit testing guide
- `desktop-local-tools-implement.mdc` – Workflow to add new desktop local tools
- `desktop-menu-configuration.mdc` – Desktop menu configuration guide
You are an expert in full-stack Web development, proficient in JavaScript, TypeScript, CSS, React, Node.js, Next.js, Postgresql, all kinds of network protocols.
You are an expert in full-stack Web development, proficient in JavaScript, TypeScript, CSS, React, Node.js, Next.js, Postgresql, Redis, S3, all kinds of network protocols.
You are an expert in LLM and Ai art. In Ai image generation, you are proficient in Stable Diffusion and ComfyUI's architectural principles, workflows, model structures, parameter configurations, training methods, and inference optimization.
You are an LLM expert, you are familiar with all kinds of LLM models, ai agents, ai workflow, prompt engineering and context engineering.
You are an expert in Ai art. In Ai image generation, you are proficient in Stable Diffusion and ComfyUI's architectural principles, workflows, model structures, parameter configurations, training methods, and inference optimization.
You are an expert in UI/UX design, proficient in web interaction patterns, responsive design, accessibility, and user behavior optimization. You excel at improving user retention and paid conversion rates through various interaction details.
## Problem Solving
- Before formulating any response, you must first gather context by using tools like codebase_search, grep_search, file_search, web_search, fetch_rules, context7, and read_file to avoid making assumptions.
- When modifying existing code, clearly describe the differences and reasons for the changes
- Provide alternative solutions that may be better overall or superior in specific aspects
- Provide optimization suggestions for deprecated API usage
- Cite sources whenever possible at the end, not inline
- When you provide multiple solutions, provide the recommended solution first, and note it as `Recommended`
- Express uncertainty when there might not be a correct answer
- Admit when you don't know something instead of guessing
- Express uncertainty when there might not be a correct answer, instead of take action by guessing and assuming
- First, think step-by-step: describe your plan in detailed pseudocode before implementation
- Confirm the plan before writing code
- Focus on maintainable over being performant
- Leave NO TODOs, placeholders, or missing pieces
- Be sure to reference file names
- When you notice I have manually modified the code, that was definitely on purpose and do not revert them
- If documentation links or required files are missing, ask for them before proceeding with the task rather than making assumptions
- If you're unable to access or retrieve content from websites, please inform me immediately and request the specific information needed rather than making assumptions
- You can use emojis, npm packages like `chalk`/`chalk-animation`/`terminal-link`/`gradient-string`/`log-symbols`/`boxen`/`consola`/`@clack/prompts` to create beautiful terminal output
- Don't run `tsc --noEmit` to check ts syntax error, because our project is very large and the validate very slow
## Some logging rules
- Never log user private information like api key, etc
- Don't use `import { log } from 'debug'` to log messages, because it will directly log the message to the console.
- Be sure to reference file path
- If doc links or required files are missing, ask for them before proceeding with the task rather than making assumptions
- If you're unable to get valid result when using tools, please clearly state in the output
- wrapped the file path in single quotes to avoid shell expansion
- Never run `bun run test` etc to run tests, this will run all tests and cost about 10mins
- If try to fix the same test twice, but still failed, stop and ask for help.
### Typecheck
- use `bun run type-check` to check type errors.
### i18n
- **Keys**: Add to `src/locales/default/namespace.ts`
- **Dev**: Translate `locales/zh-CN/namespace.json` locale file only for preview
- DON'T run `pnpm i18n`, let CI auto handle it
## Rules Index
Some useful rules of this project. Read them when needed.
**IMPORTANT**: All rule files referenced in this document are located in the `.cursor/rules/` directory. Throughout this document, rule files are referenced by their filename only for brevity.
### 📋 Complete Rule Files
**Core Development**
-`backend-architecture.mdc` - Three-layer architecture, data flow
@@ -150,7 +150,7 @@ From productivity tools to development environments, discover new ways to extend
**Peak Performance, Zero Distractions**
Get the full LobeChat experience without browser limitations—lightweight, focused, and always ready to go. Our desktop application provides a dedicated environment for your AI interactions, ensuring optimal performance and minimal distractions.
Get the full LobeChat experience without browser limitations—comprehensive, focused, and always ready to go. Our desktop application provides a dedicated environment for your AI interactions, ensuring optimal performance and minimal distractions.
Experience faster response times, better resource management, and a more stable connection to your AI assistant. The desktop app is designed for users who demand the best performance from their AI tools.
@@ -245,15 +245,17 @@ We have implemented support for the following model service providers:
- **[Bedrock](https://lobechat.com/discover/provider/bedrock)**: Bedrock is a service provided by Amazon AWS, focusing on delivering advanced AI language and visual models for enterprises. Its model family includes Anthropic's Claude series, Meta's Llama 3.1 series, and more, offering a range of options from lightweight to high-performance, supporting tasks such as text generation, conversation, and image processing for businesses of varying scales and needs.
- **[Google](https://lobechat.com/discover/provider/google)**: Google's Gemini series represents its most advanced, versatile AI models, developed by Google DeepMind, designed for multimodal capabilities, supporting seamless understanding and processing of text, code, images, audio, and video. Suitable for various environments from data centers to mobile devices, it significantly enhances the efficiency and applicability of AI models.
- **[DeepSeek](https://lobechat.com/discover/provider/deepseek)**: DeepSeek is a company focused on AI technology research and application, with its latest model DeepSeek-V2.5 integrating general dialogue and code processing capabilities, achieving significant improvements in human preference alignment, writing tasks, and instruction following.
- **[HuggingFace](https://lobechat.com/discover/provider/huggingface)**: The HuggingFace Inference API provides a fast and free way for you to explore thousands of models for various tasks. Whether you are prototyping for a new application or experimenting with the capabilities of machine learning, this API gives you instant access to high-performance models across multiple domains.
- **[Moonshot](https://lobechat.com/discover/provider/moonshot)**: Moonshot is an open-source platform launched by Beijing Dark Side Technology Co., Ltd., providing various natural language processing models with a wide range of applications, including but not limited to content creation, academic research, intelligent recommendations, and medical diagnosis, supporting long text processing and complex generation tasks.
- **[OpenRouter](https://lobechat.com/discover/provider/openrouter)**: OpenRouter is a service platform providing access to various cutting-edge large model interfaces, supporting OpenAI, Anthropic, LLaMA, and more, suitable for diverse development and application needs. Users can flexibly choose the optimal model and pricing based on their requirements, enhancing the AI experience.
- **[HuggingFace](https://lobechat.com/discover/provider/huggingface)**: The HuggingFace Inference API provides a fast and free way for you to explore thousands of models for various tasks. Whether you are prototyping for a new application or experimenting with the capabilities of machine learning, this API gives you instant access to high-performance models across multiple domains.
- **[Cloudflare Workers AI](https://lobechat.com/discover/provider/cloudflare)**: Run serverless GPU-powered machine learning models on Cloudflare's global network.
<details><summary><kbd>See more providers (+32)</kbd></summary>
- **[GitHub](https://lobechat.com/discover/provider/github)**: With GitHub Models, developers can become AI engineers and leverage the industry's leading AI models.
<details><summary><kbd>See more providers (+31)</kbd></summary>
- **[Novita](https://lobechat.com/discover/provider/novita)**: Novita AI is a platform providing a variety of large language models and AI image generation API services, flexible, reliable, and cost-effective. It supports the latest open-source models like Llama3 and Mistral, offering a comprehensive, user-friendly, and auto-scaling API solution for generative AI application development, suitable for the rapid growth of AI startups.
- **[PPIO](https://lobechat.com/discover/provider/ppio)**: PPIO supports stable and cost-efficient open-source LLM APIs, such as DeepSeek, Llama, Qwen etc.
- **[302.AI](https://lobechat.com/discover/provider/ai302)**: 302.AI is an on-demand AI application platform offering the most comprehensive AI APIs and online AI applications available on the market.
- **[Together AI](https://lobechat.com/discover/provider/togetherai)**: Together AI is dedicated to achieving leading performance through innovative AI models, offering extensive customization capabilities, including rapid scaling support and intuitive deployment processes to meet various enterprise needs.
- **[Fireworks AI](https://lobechat.com/discover/provider/fireworksai)**: Fireworks AI is a leading provider of advanced language model services, focusing on functional calling and multimodal processing. Its latest model, Firefunction V2, is based on Llama-3, optimized for function calling, conversation, and instruction following. The visual language model FireLLaVA-13B supports mixed input of images and text. Other notable models include the Llama series and Mixtral series, providing efficient multilingual instruction following and generation support.
- **[Groq](https://lobechat.com/discover/provider/groq)**: Groq's LPU inference engine has excelled in the latest independent large language model (LLM) benchmarks, redefining the standards for AI solutions with its remarkable speed and efficiency. Groq represents instant inference speed, demonstrating strong performance in cloud-based deployments.
@@ -272,7 +274,6 @@ We have implemented support for the following model service providers:
- **[Spark](https://lobechat.com/discover/provider/spark)**: iFlytek's Spark model provides powerful AI capabilities across multiple domains and languages, utilizing advanced natural language processing technology to build innovative applications suitable for smart hardware, smart healthcare, smart finance, and other vertical scenarios.
- **[SenseNova](https://lobechat.com/discover/provider/sensenova)**: SenseNova, backed by SenseTime's robust infrastructure, offers efficient and user-friendly full-stack large model services.
- **[Stepfun](https://lobechat.com/discover/provider/stepfun)**: StepFun's large model possesses industry-leading multimodal and complex reasoning capabilities, supporting ultra-long text understanding and powerful autonomous scheduling search engine functions.
- **[Moonshot](https://lobechat.com/discover/provider/moonshot)**: Moonshot is an open-source platform launched by Beijing Dark Side Technology Co., Ltd., providing various natural language processing models with a wide range of applications, including but not limited to content creation, academic research, intelligent recommendations, and medical diagnosis, supporting long text processing and complex generation tasks.
- **[Baichuan](https://lobechat.com/discover/provider/baichuan)**: Baichuan Intelligence is a company focused on the research and development of large AI models, with its models excelling in domestic knowledge encyclopedias, long text processing, and generative creation tasks in Chinese, surpassing mainstream foreign models. Baichuan Intelligence also possesses industry-leading multimodal capabilities, performing excellently in multiple authoritative evaluations. Its models include Baichuan 4, Baichuan 3 Turbo, and Baichuan 3 Turbo 128k, each optimized for different application scenarios, providing cost-effective solutions.
- **[Minimax](https://lobechat.com/discover/provider/minimax)**: MiniMax is a general artificial intelligence technology company established in 2021, dedicated to co-creating intelligence with users. MiniMax has independently developed general large models of different modalities, including trillion-parameter MoE text models, voice models, and image models, and has launched applications such as Conch AI.
- **[InternLM](https://lobechat.com/discover/provider/internlm)**: An open-source organization dedicated to the research and development of large model toolchains. It provides an efficient and user-friendly open-source platform for all AI developers, making cutting-edge large models and algorithm technologies easily accessible.
@@ -286,7 +287,7 @@ We have implemented support for the following model service providers:
</details>
> 📊 Total providers: [<kbd>**41**</kbd>](https://lobechat.com/discover/providers)
> 📊 Total providers: [<kbd>**42**</kbd>](https://lobechat.com/discover/providers)
<!-- PROVIDER LIST -->
@@ -383,12 +384,12 @@ In addition, these plugins are not limited to news aggregation, but can also ext
| [Speak](https://lobechat.com/discover/plugin/speak)<br/><sup>By **speak** on **2025-07-18**</sup> | Learn how to say anything in another language with Speak, your AI-powered language tutor.<br/>`education``language` |
| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-05-27**</sup> | Analyze stocks and get comprehensive real-time investment data and analytics.<br/>`stock` |
| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-07-21**</sup> | Analyze stocks and get comprehensive real-time investment data and analytics.<br/>`stock` |
| [Web](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup> | Smart web search that reads and analyzes pages to deliver comprehensive answers from Google results.<br/>`web``search` |
| [Bing_websearch](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup> | Search for information from the internet base BingApi<br/>`bingsearch` |
| [Google CSE](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup> | Searches Google through their official CSE API.<br/>`web``search` |
> 📊 Total plugins: [<kbd>**43**</kbd>](https://lobechat.com/discover/plugins)
> 📊 Total plugins: [<kbd>**42**</kbd>](https://lobechat.com/discover/plugins)
<!-- PLUGIN LIST -->
@@ -480,7 +481,7 @@ We deeply understand the importance of providing a seamless experience for users
Therefore, we have adopted Progressive Web Application ([PWA](https://support.google.com/chrome/answer/9658361)) technology,
a modern web technology that elevates web applications to an experience close to that of native apps.
Through PWA, LobeChat can offer a highly optimized user experience on both desktop and mobile devices while maintaining its lightweight and high-performance characteristics.
Through PWA, LobeChat can offer a highly optimized user experience on both desktop and mobile devices while maintaining high-performance characteristics.
Visually and in terms of feel, we have also meticulously designed the interface to ensure it is indistinguishable from native apps,
providing smooth animations, responsive layouts, and adapting to different device screen resolutions.
- **[Bedrock](https://lobechat.com/discover/provider/bedrock)**: Bedrock 是亚马逊 AWS 提供的一项服务,专注于为企业提供先进的 AI 语言模型和视觉模型。其模型家族包括 Anthropic 的 Claude 系列、Meta 的 Llama 3.1 系列等,涵盖从轻量级到高性能的多种选择,支持文本生成、对话、图像处理等多种任务,适用于不同规模和需求的企业应用。
- **[Google](https://lobechat.com/discover/provider/google)**: Google 的 Gemini 系列是其最先进、通用的 AI 模型,由 Google DeepMind 打造,专为多模态设计,支持文本、代码、图像、音频和视频的无缝理解与处理。适用于从数据中心到移动设备的多种环境,极大提升了 AI 模型的效率与应用广泛性。
- **[HuggingFace](https://lobechat.com/discover/provider/huggingface)**: HuggingFace Inference API 提供了一种快速且免费的方式,让您可以探索成千上万种模型,适用于各种任务。无论您是在为新应用程序进行原型设计,还是在尝试机器学习的功能,这个 API 都能让您即时访问多个领域的高性能模型。
- **[OpenRouter](https://lobechat.com/discover/provider/openrouter)**: OpenRouter 是一个提供多种前沿大模型接口的服务平台,支持 OpenAI、Anthropic、LLaMA 及更多,适合多样化的开发和应用需求。用户可根据自身需求灵活选择最优的模型和价格,助力 AI 体验的提升。
- **[HuggingFace](https://lobechat.com/discover/provider/huggingface)**: HuggingFace Inference API 提供了一种快速且免费的方式,让您可以探索成千上万种模型,适用于各种任务。无论您是在为新应用程序进行原型设计,还是在尝试机器学习的功能,这个 API 都能让您即时访问多个领域的高性能模型。
<details><summary><kbd>See more providers (+32)</kbd></summary>
- **[GitHub](https://lobechat.com/discover/provider/github)**: 通过 GitHub 模型,开发人员可以成为 AI 工程师,并使用行业领先的 AI 模型进行构建。
<details><summary><kbd>See more providers (+31)</kbd></summary>
- **[Novita](https://lobechat.com/discover/provider/novita)**: Novita AI 是一个提供多种大语言模型与 AI 图像生成的 API 服务的平台,灵活、可靠且具有成本效益。它支持 Llama3、Mistral 等最新的开源模型,并为生成式 AI 应用开发提供了全面、用户友好且自动扩展的 API 解决方案,适合 AI 初创公司的快速发展。
- **[PPIO](https://lobechat.com/discover/provider/ppio)**: PPIO 派欧云提供稳定、高性价比的开源模型 API 服务,支持 DeepSeek 全系列、Llama、Qwen 等行业领先大模型。
- **[302.AI](https://lobechat.com/discover/provider/ai302)**: 302.AI 是一个按需付费的 AI 应用平台,提供市面上最全的 AI API 和 AI 在线应用
- **[Together AI](https://lobechat.com/discover/provider/togetherai)**: Together AI 致力于通过创新的 AI 模型实现领先的性能,提供广泛的自定义能力,包括快速扩展支持和直观的部署流程,满足企业的各种需求。
| [Speak](https://lobechat.com/discover/plugin/speak)<br/><sup>By **speak** on **2025-07-18**</sup> | 使用 Speak,您的 AI 语言导师,学习如何用另一种语言说任何事情。<br/>`教育``语言` |
| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-05-27**</sup> | 分析股票并获取全面的实时投资数据和分析。<br/>`股票` |
| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-07-21**</sup> | 分析股票并获取全面的实时投资数据和分析。<br/>`股票` |
| [网页](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup> | 智能网页搜索,读取和分析页面,以提供来自 Google 结果的全面答案。<br/>`网页``搜索` |
| [必应网页搜索](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup> | 通过 BingApi 搜索互联网上的信息<br/>`bingsearch` |
| [谷歌自定义搜索引擎](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup> | 通过他们的官方自定义搜索引擎 API 搜索谷歌。<br/>`网络``搜索` |
> 📊 Total plugins: [<kbd>**43**</kbd>](https://lobechat.com/discover/plugins)
> 📊 Total plugins: [<kbd>**42**</kbd>](https://lobechat.com/discover/plugins)
LobeHub Desktop 是 [LobeChat](https://github.com/lobehub/lobe-chat) 的跨平台桌面应用程序,使用 Electron 构建,提供了更加原生的桌面体验和功能。
LobeHub Desktop is a cross-platform desktop application for [LobeChat](https://github.com/lobehub/lobe-chat), built with Electron, providing a more native desktop experience and functionality.
## 功能特点
## ✨ Features
- **跨平台支持**:支持 macOS (Intel/Apple Silicon)、Windows 和 Linux 系统
- **自动更新**:内置更新机制,确保您始终使用最新版本
- **多语言支持**:完整的国际化支持,包括中文、英文等多种语言
- **原生集成**:与操作系统深度集成,提供原生菜单、快捷键和通知
- **安全可靠**:macOS 版本经过公证,确保安全性
- **多渠道发布**:提供稳定版、测试版和每日构建版本
- **🌍 Cross-platform Support**: Supports macOS (Intel/Apple Silicon), Windows, and Linux systems
- **🔄 Auto Updates**: Built-in update mechanism ensures you always have the latest version
- **🌐 Multi-language Support**: Complete i18n support for 18+ languages with lazy loading
- **🎨 Native Integration**: Deep OS integration with native menus, shortcuts, and notifications
- **Request Filtering** - Security controls for external requests
### Data Protection
- **Encrypted Configuration** - Sensitive data encrypted at rest
- **Secure IPC** - Type-safe communication channels
- **Path Validation** - Secure file system access controls
- **Network Security** - HTTPS enforcement and proxy support
## 🤝 Contribution
Desktop application development involves complex cross-platform considerations and native integrations. We welcome community contributions to improve functionality, performance, and user experience. You can participate in improvements through:
### How to Contribute
1.**Platform Support**: Enhance cross-platform compatibility and native integrations
2.**Performance Optimization**: Improve application startup time, memory usage, and responsiveness
3.**Feature Development**: Add new desktop-specific features and capabilities
4.**Bug Fixes**: Fix platform-specific issues and edge cases
5.**Security Improvements**: Enhance security measures and authentication flows
6.**UI/UX Enhancements**: Improve desktop user interface and experience
### Contribution Process
1. Fork the [LobeChat repository](https://github.com/lobehub/lobe-chat)
2. Set up the desktop development environment following our setup guide
3. Make your changes to the desktop application
4. Submit a Pull Request describing:
- Platform compatibility testing results
- Performance impact analysis
- Security considerations
- User experience improvements
- Breaking changes (if any)
### Development Areas
- **Core Architecture**: Dependency injection, event system, and lifecycle management
- **Window Management**: Multi-window support, theme synchronization, and state persistence
- **IPC Communication**: Type-safe inter-process communication between main and renderer
- **Platform Integration**: Native menus, shortcuts, notifications, and system tray
- **Security Features**: OAuth flows, token encryption, and secure storage
- **Auto-Update System**: Multi-channel updates and rollback mechanisms
## 📚 Additional Resources
- **Development Guide**: [`Development.md`](./Development.md) - Comprehensive development documentation
Some files were not shown because too many files have changed in this diff
Show More
Reference in New Issue
Block a user
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.