
AIClient-2-API
AIClient2API:模拟Gemini CLI,Qwen Code和Kiro 客户端请求,兼容OpenAI API。可每日千次Gemini模型请求, 免费使用Kiro内置Claude模型。通过API轻松接入任何客户端,让AI开发更高效!
Stars: 950

AIClient-2-API is a versatile and lightweight API proxy designed for developers, providing ample free API request quotas and comprehensive support for various mainstream large models like Gemini, Qwen Code, Claude, etc. It converts multiple backend APIs into standard OpenAI format interfaces through a Node.js HTTP server. The project adopts a modern modular architecture, supports strategy and adapter patterns, comes with complete test coverage and health check mechanisms, and is ready to use after 'npm install'. By easily switching model service providers in the configuration file, any OpenAI-compatible client or application can seamlessly access different large model capabilities through the same API address, eliminating the hassle of maintaining multiple sets of configurations for different services and dealing with incompatible interfaces.
README:
一个能将多种仅客户端内使用的大模型 API(Gemini CLI, Qwen Code Plus, Kiro Claude...),模拟请求,统一封装为本地 OpenAI 兼容接口的强大代理。
AIClient2API
是一个专为开发者打造的多功能、轻量化 API 代理,旨在提供大量免费的 API 请求额度,全面支持 Gemini、Qwen Code、Claude 等主流大模型。通过一个 Node.js HTTP 服务器,它将多种后端 API 统一转换为标准的 OpenAI 格式接口。项目采用现代化的模块化架构,支持策略模式和适配器模式,具备完整的测试覆盖和健康检查机制,开箱即用,npm install
后即可直接运行。您只需在配置文件中轻松切换模型服务商,就能让任何兼容 OpenAI 的客户端或应用,通过同一个 API 地址,无缝地使用不同的大模型能力,彻底摆脱为不同服务维护多套配置和处理接口不兼容问题的烦恼。
[!NOTE] 感谢阮一峰老师在周刊359期的推荐。
8.29 新增账号池模式,可支持所有provider配置多个账号,自带轮询,故障转移(需要客户端重试)和配置降级。需要在 config 新增配置 PROVIDER_POOLS_FILE_PATH , 详见配置文件:provider_pools.json
8.30 最新消息,kiro可免费使用至9.15
9.1 偷摸的新增 Qwen Code CLI 支持,可使用 qwen3-coder-plus 模型
- ✅ 多模型统一接入:一个接口,通吃 Gemini、OpenAI、Claude、Kimi K2、GLM-4.5、Qwen Code 等多种最新模型。通过简单的启动参数或请求头,即可在不同模型服务商之间自由切换。
- ✅ 突破官方限制:通过支持 Gemini CLI 的 OAuth 授权方式,有效绕过官方免费 API 的速率和配额限制,让您享受更高的请求额度和使用频率。
- ✅ 突破客户端限制:Kiro API 模式下支持免费使用Claude Sonnet 4 模型。
- ✅ 无缝兼容 OpenAI:提供与 OpenAI API 完全兼容的接口,让您现有的工具链和客户端(如 LobeChat, NextChat 等)可以零成本接入所有支持的模型。
- ✅ 账号池智能管理:支持多账号轮询、故障转移和配置降级,确保服务高可用性,有效避免单一账号的限制问题。
- ✅ 增强的可控性:通过强大的日志功能,可以捕获并记录所有请求的提示词(Prompts),便于审计、调试和构建私有数据集。
- ✅ 极易扩展:得益于全新的模块化和策略模式设计,添加一个新的模型服务商变得前所未有的简单。
- ✅ 完整测试覆盖:提供全面的集成测试和单元测试,确保各个API端点和功能的稳定性和可靠性。
- ✅ Docker支持:提供完整的Docker容器化支持,支持快速部署和环境隔离。
-
OpenAI 协议 (P_OPENAI): 支持所有 MODEL_PROVIDER,包括 openai-custom、gemini-cli-oauth、claude-custom、 claude-kiro-oauth 和 openai-qwen-oauth。
-
Claude 协议 (P_CLAUDE): 支持 claude-custom、claude-kiro-oauth、gemini-cli-oauth、openai-custom和 openai-qwen-oauth。
-
Gemini 协议 (P_GEMINI): 支持 gemini-cli-oauth。
graph TD subgraph Core_Protocols["核心协议"] P_OPENAI[OpenAI Protocol] P_GEMINI[Gemini Protocol] P_CLAUDE[Claude Protocol] end subgraph Supported_Model_Providers["支持的模型提供商"] MP_OPENAI[openai-custom] MP_GEMINI[gemini-cli-oauth] MP_CLAUDE_C[claude-custom] MP_CLAUDE_K[claude-kiro-oauth] MP_QWEN[openai-qwen-oauth] end P_OPENAI ---|支持| MP_OPENAI P_OPENAI ---|支持| MP_QWEN P_OPENAI ---|支持| MP_GEMINI P_OPENAI ---|支持| MP_CLAUDE_C P_OPENAI ---|支持| MP_CLAUDE_K P_GEMINI ---|支持| MP_GEMINI P_CLAUDE ---|支持| MP_CLAUDE_C P_CLAUDE ---|支持| MP_CLAUDE_K P_CLAUDE ---|支持| MP_GEMINI P_CLAUDE ---|支持| MP_OPENAI P_CLAUDE ---|支持| MP_QWEN style P_OPENAI fill:#f9f,stroke:#333,stroke-width:2px style P_GEMINI fill:#ccf,stroke:#333,stroke-width:2px style P_CLAUDE fill:#cfc,stroke:#333,stroke-width:2px
-
MCP 支持: 虽然原版 Gemini CLI 的内置命令功能不可用,但本项目完美支持 MCP (Model Context Protocol),可配合支持 MCP 的客户端实现更强大的功能扩展。
-
多模态能力: 支持图片、文档等多模态输入,为您提供更丰富的交互体验。
-
最新模型支持: 支持最新的 Kimi K2、GLM-4.5 和 Qwen Code 模型,只需在
config.json
中配置相应的 OpenAI 或 Claude 兼容接口即可使用。 -
Qwen Code 支持: 使用 Qwen Code 会自动在浏览器打开授权页面,完成授权后会在
~/.qwen
目录下生成oauth_creds.json
文件。请使用官方默认参数 temperature=0 , top_p=1。 -
Kiro API: 使用 Kiro API 需要下载kiro客户端并完成授权登录生成 kiro-auth-token.json。推荐配合 Claude Code 使用以获得最佳体验。注意:Kiro服务政策已调整,具体使用限制请查看官方公告。
-
Claude Code 中使用不同供应商: 通过 Path 路由或环境变量,您可以在 Claude 相关的 API 调用中使用不同的供应商:
-
http://localhost:3000/claude-custom
- 使用配置文件中定义的 Claude API 供应商 -
http://localhost:3000/claude-kiro-oauth
- 使用 Kiro OAuth 认证方式访问 Claude API -
http://localhost:3000/openai-custom
- 使用 OpenAI 自定义供应商处理 Claude 请求 -
http://localhost:3000/gemini-cli-oauth
- 使用 Gemini CLI OAuth 供应商处理 Claude 请求 -
http://localhost:3000/openai-qwen-oauth
- 使用 Qwen OAuth 供应商处理 Claude 请求 - 每个供应商可以配置不同的 API 密钥、基础 URL 和其他参数,实现灵活的供应商切换
这些 Path 路由不仅可以在直接 API 调用中使用,也可以在 Cline、Kilo 等编程 agent 中使用,通过指定不同的路径来调用相应的模型。例如,在编程 agent 中配置 API 端点时,可以使用
http://localhost:3000/claude-kiro-oauth
来调用通过 Kiro OAuth 认证的 Claude 模型,或使用http://localhost:3000/gemini-cli-oauth
来调用 Gemini 模型。除了通过 Path 路由切换供应商外,您还可以通过设置环境变量来配置 Claude 参数。可以通过以下环境变量进行配置:
-
ANTHROPIC_BASE_URL
: 设置 Claude API 的基础 URL 路径 -
ANTHROPIC_AUTH_TOKEN
: 设置 Claude 服务的认证密钥 -
ANTHROPIC_MODEL
: 设置需要使用的 Claude 模型
当使用
http://localhost:3000/claude-custom
路径时,可以通过以下方式设置环境变量:export ANTHROPIC_BASE_URL="http://localhost:3000/claude-custom" export ANTHROPIC_AUTH_TOKEN="your-auth-token-here" export ANTHROPIC_MODEL="your-model-name"
set ANTHROPIC_BASE_URL=http://localhost:3000/claude-custom set ANTHROPIC_AUTH_TOKEN=your-auth-token-here set ANTHROPIC_MODEL=your-model-name
$env:ANTHROPIC_BASE_URL="http://localhost:3000/claude-custom" $env:ANTHROPIC_AUTH_TOKEN="your-auth-token-here" $env:ANTHROPIC_MODEL="your-model-name"
-
以下是各服务授权文件的默认存储路径:
-
Gemini:
~/.gemini/oauth_creds.json
-
Kiro:
~/.aws/sso/cache/kiro-auth-token.json
-
Qwen:
~/.qwen/oauth_creds.json
其中 ~
代表用户主目录。如果需要自定义路径,可以通过配置文件或环境变量进行设置。
提示: 如果您在无法直接访问 Google/OpenAI/Claude/Kiro 服务的环境中使用,请先为您的终端设置 HTTP代理,不要设置 HTTPS代理。
为了确保 AIClient2API
能够正常访问外部 AI 服务(如 Google、OpenAI、Claude、Kiro 等),您可能需要在您的终端环境中设置 HTTP 代理。以下是针对不同操作系统的代理设置命令:
export HTTP_PROXY="http://your_proxy_address:port"
# 如果代理需要认证
# export HTTP_PROXY="http://username:password@your_proxy_address:port"
要使这些设置永久生效,您可以将它们添加到您的 shell 配置文件中(例如 ~/.bashrc
, ~/.zshrc
或 ~/.profile
)。
set HTTP_PROXY=http://your_proxy_address:port
:: 如果代理需要认证
:: set HTTP_PROXY=http://username:password@your_proxy_address:port
这些设置只对当前 CMD 会话有效。如需永久设置,您可以通过系统环境变量进行配置。
$env:HTTP_PROXY="http://your_proxy_address:port"
# 如果代理需要认证
# $env:HTTP_PROXY="http://username:password@your_proxy_address:port"
这些设置只对当前 PowerShell 会话有效。如需永久设置,您可以将它们添加到您的 PowerShell 配置文件中 ($PROFILE
) 或通过系统环境变量进行配置。
请务必将 your_proxy_address
和 port
替换为您的实际代理地址和端口。
-
🔌 对接任意 OpenAI 客户端: 这是本项目的基本功能。将任何支持 OpenAI 的应用(如 LobeChat, NextChat, VS Code 插件等)的 API 地址指向本服务 (
http://localhost:3000
),即可无缝使用所有已配置的模型。 -
🔍 中心化请求监控与审计: 在
config.json
中设置"PROMPT_LOG_MODE": "file"
来捕获所有请求和响应,并保存到本地日志文件。这对于分析、调试和优化提示词,甚至构建私有数据集都至关重要。 -
💡 动态系统提示词:
- 通过在
config.json
中设置SYSTEM_PROMPT_FILE_PATH
和SYSTEM_PROMPT_MODE
,您可以更灵活地控制系统提示词的行为。 -
支持的模式:
-
override
: 完全忽略客户端的系统提示词,强制使用文件中的内容。 -
append
: 在客户端系统提示词的末尾追加文件中的内容,实现规则的补充。
-
- 这使得您可以为不同的客户端设置统一的基础指令,同时允许单个应用进行个性化扩展。
- 通过在
-
🛠️ 作为二次开发基石:
-
添加新模型: 只需在
src
目录下创建一个新的提供商目录,实现ApiServiceAdapter
接口和相应的策略,然后在adapter.js
和common.js
中注册即可。 - 响应缓存: 对高频重复问题添加缓存逻辑,降低 API 调用,提升响应速度。
- 自定义内容过滤: 在请求发送或返回前增加关键词过滤或内容审查逻辑,满足合规要求。
-
添加新模型: 只需在
-
🎯 账号池高级配置:
-
多账号管理: 通过配置
provider_pools.json
文件,可以为每个提供商配置多个账号,实现智能轮询。 - 故障转移: 当某个账号失效时,系统会自动切换到下一个可用账号,确保服务连续性。
- 配置降级: 支持根据账号状态动态调整配置参数,优化资源使用效率。
-
使用示例: 参考项目中的
provider_pools.json
配置文件,轻松设置多账号环境。
-
多账号管理: 通过配置
本项目支持丰富的命令行参数配置,可以根据需要灵活调整服务行为。以下是对所有启动参数的详细说明,按功能分组展示:
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--host |
string | localhost | 服务器监听地址 |
--port |
number | 3000 | 服务器监听端口 |
--api-key |
string | 123456 | 身份验证所需的 API 密钥 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--model-provider |
string | gemini-cli-oauth | AI 模型提供商,可选值:openai-custom, claude-custom, gemini-cli-oauth, claude-kiro-oauth, openai-qwen-oauth |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--openai-api-key |
string | null | OpenAI API 密钥 (用于 openai-custom 提供商) |
--openai-base-url |
string | null | OpenAI API 基础 URL (用于 openai-custom 提供商) |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--claude-api-key |
string | null | Claude API 密钥 (用于 claude-custom 提供商) |
--claude-base-url |
string | null | Claude API 基础 URL (用于 claude-custom 提供商) |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--gemini-oauth-creds-base64 |
string | null | Gemini OAuth 凭据的 Base64 字符串 |
--gemini-oauth-creds-file |
string | null | Gemini OAuth 凭据 JSON 文件路径 |
--project-id |
string | null | Google Cloud 项目 ID (用于 gemini-cli 提供商) |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--kiro-oauth-creds-base64 |
string | null | Kiro OAuth 凭据的 Base64 字符串 |
--kiro-oauth-creds-file |
string | null | Kiro OAuth 凭据 JSON 文件路径 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--qwen-oauth-creds-file |
string | null | Qwen OAuth 凭据 JSON 文件路径 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--system-prompt-file |
string | input_system_prompt.txt | 系统提示文件路径 |
--system-prompt-mode |
string | overwrite | 系统提示模式,可选值:overwrite(覆盖), append(追加) |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--log-prompts |
string | none | 提示日志模式,可选值:console(控制台), file(文件), none(无) |
--prompt-log-base-name |
string | prompt_log | 提示日志文件基础名称 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--request-max-retries |
number | 3 | API 请求失败时,自动重试的最大次数 |
--request-base-delay |
number | 1000 | 自动重试之间的基础延迟时间(毫秒),每次重试后延迟会增加 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--cron-near-minutes |
number | 15 | OAuth 令牌刷新任务计划的间隔时间(分钟) |
--cron-refresh-token |
boolean | true | 是否开启 OAuth 令牌自动刷新任务 |
参数 | 类型 | 默认值 | 说明 |
---|---|---|---|
--provider-pools-file |
string | null | 提供商号池配置文件路径 |
# 基本用法
node src/api-server.js
# 指定端口和API密钥
node src/api-server.js --port 8080 --api-key my-secret-key
# 使用OpenAI提供商
node src/api-server.js --model-provider openai-custom --openai-api-key sk-xxx --openai-base-url https://api.openai.com/v1
# 使用Claude提供商
node src/api-server.js --model-provider claude-custom --claude-api-key sk-ant-xxx --claude-base-url https://api.anthropic.com
# 使用Gemini提供商(Base64凭据)
node src/api-server.js --model-provider gemini-cli-oauth --gemini-oauth-creds-base64 eyJ0eXBlIjoi... --project-id your-project-id
# 使用Gemini提供商(凭据文件)
node src/api-server.js --model-provider gemini-cli-oauth --gemini-oauth-creds-file /path/to/credentials.json --project-id your-project-id
# 配置系统提示
node src/api-server.js --system-prompt-file custom-prompt.txt --system-prompt-mode append
# 配置日志
node src/api-server.js --log-prompts console
node src/api-server.js --log-prompts file --prompt-log-base-name my-logs
# 完整示例
node src/api-server.js \
--host 0.0.0.0 \
--port 3000 \
--api-key my-secret-key \
--model-provider gemini-cli-oauth \
--project-id my-gcp-project \
--gemini-oauth-creds-file ./credentials.json \
--system-prompt-file ./custom-system-prompt.txt \
--system-prompt-mode overwrite \
--log-prompts file \
--prompt-log-base-name api-logs
本项目遵循 GNU General Public License v3 (GPLv3) 开源许可。详情请查看根目录下的 LICENSE
文件。
本项目的开发受到了官方 Google Gemini CLI 的极大启发,并参考了Cline 3.18.0 版本 gemini-cli.ts
的部分代码实现。在此对 Google 官方团队和 Cline 开发团队的卓越工作表示衷心的感谢!
本项目(AIClient-2-API)仅供学习和研究使用。用户在使用本项目时,应自行承担所有风险。作者不对因使用本项目而导致的任何直接、间接或 consequential 损失承担责任。
本项目是一个API代理工具,不提供任何AI模型服务。所有AI模型服务由相应的第三方提供商(如Google、OpenAI、Anthropic等)提供。用户在使用本项目访问这些第三方服务时,应遵守各第三方服务的使用条款和政策。作者不对第三方服务的可用性、质量、安全性或合法性承担责任。
本项目在本地运行,不会收集或上传用户的任何数据。但用户在使用本项目时,应注意保护自己的API密钥和其他敏感信息。建议用户定期检查和更新自己的API密钥,并避免在不安全的网络环境中使用本项目。
用户在使用本项目时,应遵守所在国家/地区的法律法规。严禁将本项目用于任何非法用途。如因用户违反法律法规而导致的任何后果,由用户自行承担全部责任。
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for AIClient-2-API
Similar Open Source Tools

AIClient-2-API
AIClient-2-API is a versatile and lightweight API proxy designed for developers, providing ample free API request quotas and comprehensive support for various mainstream large models like Gemini, Qwen Code, Claude, etc. It converts multiple backend APIs into standard OpenAI format interfaces through a Node.js HTTP server. The project adopts a modern modular architecture, supports strategy and adapter patterns, comes with complete test coverage and health check mechanisms, and is ready to use after 'npm install'. By easily switching model service providers in the configuration file, any OpenAI-compatible client or application can seamlessly access different large model capabilities through the same API address, eliminating the hassle of maintaining multiple sets of configurations for different services and dealing with incompatible interfaces.

LLM-TPU
LLM-TPU project aims to deploy various open-source generative AI models on the BM1684X chip, with a focus on LLM. Models are converted to bmodel using TPU-MLIR compiler and deployed to PCIe or SoC environments using C++ code. The project has deployed various open-source models such as Baichuan2-7B, ChatGLM3-6B, CodeFuse-7B, DeepSeek-6.7B, Falcon-40B, Phi-3-mini-4k, Qwen-7B, Qwen-14B, Qwen-72B, Qwen1.5-0.5B, Qwen1.5-1.8B, Llama2-7B, Llama2-13B, LWM-Text-Chat, Mistral-7B-Instruct, Stable Diffusion, Stable Diffusion XL, WizardCoder-15B, Yi-6B-chat, Yi-34B-chat. Detailed model deployment information can be found in the 'models' subdirectory of the project. For demonstrations, users can follow the 'Quick Start' section. For inquiries about the chip, users can contact SOPHGO via the official website.

Element-Plus-X
Element-Plus-X is an out-of-the-box enterprise-level AI component library based on Vue 3 + Element-Plus. It features built-in scenario components such as chatbots and voice interactions, seamless integration with zero configuration based on Element-Plus design system, and support for on-demand loading with Tree Shaking optimization.

Langchain-Chatchat
LangChain-Chatchat is an open-source, offline-deployable retrieval-enhanced generation (RAG) large model knowledge base project based on large language models such as ChatGLM and application frameworks such as Langchain. It aims to establish a knowledge base Q&A solution that is friendly to Chinese scenarios, supports open-source models, and can run offline.

ChuanhuChatGPT
Chuanhu Chat is a user-friendly web graphical interface that provides various additional features for ChatGPT and other language models. It supports GPT-4, file-based question answering, local deployment of language models, online search, agent assistant, and fine-tuning. The tool offers a range of functionalities including auto-solving questions, online searching with network support, knowledge base for quick reading, local deployment of language models, GPT 3.5 fine-tuning, and custom model integration. It also features system prompts for effective role-playing, basic conversation capabilities with options to regenerate or delete dialogues, conversation history management with auto-saving and search functionalities, and a visually appealing user experience with themes, dark mode, LaTeX rendering, and PWA application support.

Awesome-ChatTTS
Awesome-ChatTTS is an official recommended guide for ChatTTS beginners, compiling common questions and related resources. It provides a comprehensive overview of the project, including official introduction, quick experience options, popular branches, parameter explanations, voice seed details, installation guides, FAQs, and error troubleshooting. The repository also includes video tutorials, discussion community links, and project trends analysis. Users can explore various branches for different functionalities and enhancements related to ChatTTS.

Speech-AI-Forge
Speech-AI-Forge is a project developed around TTS generation models, implementing an API Server and a WebUI based on Gradio. The project offers various ways to experience and deploy Speech-AI-Forge, including online experience on HuggingFace Spaces, one-click launch on Colab, container deployment with Docker, and local deployment. The WebUI features include TTS model functionality, speaker switch for changing voices, style control, long text support with automatic text segmentation, refiner for ChatTTS native text refinement, various tools for voice control and enhancement, support for multiple TTS models, SSML synthesis control, podcast creation tools, voice creation, voice testing, ASR tools, and post-processing tools. The API Server can be launched separately for higher API throughput. The project roadmap includes support for various TTS models, ASR models, voice clone models, and enhancer models. Model downloads can be manually initiated using provided scripts. The project aims to provide inference services and may include training-related functionalities in the future.

HivisionIDPhotos
HivisionIDPhoto is a practical algorithm for intelligent ID photo creation. It utilizes a comprehensive model workflow to recognize, cut out, and generate ID photos for various user photo scenarios. The tool offers lightweight cutting, standard ID photo generation based on different size specifications, six-inch layout photo generation, beauty enhancement (waiting), and intelligent outfit swapping (waiting). It aims to solve emergency ID photo creation issues.

build_MiniLLM_from_scratch
This repository aims to build a low-parameter LLM model through pretraining, fine-tuning, model rewarding, and reinforcement learning stages to create a chat model capable of simple conversation tasks. It features using the bert4torch training framework, seamless integration with transformers package for inference, optimized file reading during training to reduce memory usage, providing complete training logs for reproducibility, and the ability to customize robot attributes. The chat model supports multi-turn conversations. The trained model currently only supports basic chat functionality due to limitations in corpus size, model scale, SFT corpus size, and quality.

BlueLM
BlueLM is a large-scale pre-trained language model developed by vivo AI Global Research Institute, featuring 7B base and chat models. It includes high-quality training data with a token scale of 26 trillion, supporting both Chinese and English languages. BlueLM-7B-Chat excels in C-Eval and CMMLU evaluations, providing strong competition among open-source models of similar size. The models support 32K long texts for better context understanding while maintaining base capabilities. BlueLM welcomes developers for academic research and commercial applications.

agentica
Agentica is a human-centric framework for building large language model agents. It provides functionalities for planning, memory management, tool usage, and supports features like reflection, planning and execution, RAG, multi-agent, multi-role, and workflow. The tool allows users to quickly code and orchestrate agents, customize prompts, and make API calls to various services. It supports API calls to OpenAI, Azure, Deepseek, Moonshot, Claude, Ollama, and Together. Agentica aims to simplify the process of building AI agents by providing a user-friendly interface and a range of functionalities for agent development.

chats
Sdcb Chats is a powerful and flexible frontend for large language models, supporting multiple functions and platforms. Whether you want to manage multiple model interfaces or need a simple deployment process, Sdcb Chats can meet your needs. It supports dynamic management of multiple large language model interfaces, integrates visual models to enhance user interaction experience, provides fine-grained user permission settings for security, real-time tracking and management of user account balances, easy addition, deletion, and configuration of models, transparently forwards user chat requests based on the OpenAI protocol, supports multiple databases including SQLite, SQL Server, and PostgreSQL, compatible with various file services such as local files, AWS S3, Minio, Aliyun OSS, Azure Blob Storage, and supports multiple login methods including Keycloak SSO and phone SMS verification.

XianyuAutoAgent
Xianyu AutoAgent is an AI customer service robot system specifically designed for the Xianyu platform, providing 24/7 automated customer service, supporting multi-expert collaborative decision-making, intelligent bargaining, and context-aware conversations. The system includes intelligent conversation engine with features like context awareness and expert routing, business function matrix with modules like core engine, bargaining system, technical support, and operation monitoring. It requires Python 3.8+ and NodeJS 18+ for installation and operation. Users can customize prompts for different experts and contribute to the project through issues or pull requests.

ChatTTS-Forge
ChatTTS-Forge is a powerful text-to-speech generation tool that supports generating rich audio long texts using a SSML-like syntax and provides comprehensive API services, suitable for various scenarios. It offers features such as batch generation, support for generating super long texts, style prompt injection, full API services, user-friendly debugging GUI, OpenAI-style API, Google-style API, support for SSML-like syntax, speaker management, style management, independent refine API, text normalization optimized for ChatTTS, and automatic detection and processing of markdown format text. The tool can be experienced and deployed online through HuggingFace Spaces, launched with one click on Colab, deployed using containers, or locally deployed after cloning the project, preparing models, and installing necessary dependencies.

AI-Guide-and-Demos-zh_CN
This is a Chinese AI/LLM introductory project that aims to help students overcome the initial difficulties of accessing foreign large models' APIs. The project uses the OpenAI SDK to provide a more compatible learning experience. It covers topics such as AI video summarization, LLM fine-tuning, and AI image generation. The project also offers a CodePlayground for easy setup and one-line script execution to experience the charm of AI. It includes guides on API usage, LLM configuration, building AI applications with Gradio, customizing prompts for better model performance, understanding LoRA, and more.

DeepAI
DeepAI is a proxy server that enhances the interaction experience of large language models (LLMs) by integrating the 'thinking chain' process. It acts as an intermediary layer, receiving standard OpenAI API compatible requests, using independent 'thinking services' to generate reasoning processes, and then forwarding the enhanced requests to the LLM backend of your choice. This ensures that responses are not only generated by the LLM but also based on pre-inference analysis, resulting in more insightful and coherent answers. DeepAI supports seamless integration with applications designed for the OpenAI API, providing endpoints for '/v1/chat/completions' and '/v1/models', making it easy to integrate into existing applications. It offers features such as reasoning chain enhancement, flexible backend support, API key routing, weighted random selection, proxy support, comprehensive logging, and graceful shutdown.
For similar tasks

hCaptcha-Solver
hCaptcha-Solver is an AI-based hcaptcha text challenge solver that utilizes the playwright module to generate the hsw N data. It can solve any text challenge without any problem, but may be flagged on some websites like Discord. The tool requires proxies since hCaptcha also rate limits. Users can run the 'hsw_api.py' before running anything and then integrate the usage shown in 'main.py' into their projects that require hCaptcha solving. Please note that this tool only works on sites that support hCaptcha text challenge.

AIClient-2-API
AIClient-2-API is a versatile and lightweight API proxy designed for developers, providing ample free API request quotas and comprehensive support for various mainstream large models like Gemini, Qwen Code, Claude, etc. It converts multiple backend APIs into standard OpenAI format interfaces through a Node.js HTTP server. The project adopts a modern modular architecture, supports strategy and adapter patterns, comes with complete test coverage and health check mechanisms, and is ready to use after 'npm install'. By easily switching model service providers in the configuration file, any OpenAI-compatible client or application can seamlessly access different large model capabilities through the same API address, eliminating the hassle of maintaining multiple sets of configurations for different services and dealing with incompatible interfaces.

Helios
Helios is a powerful open-source tool for managing and monitoring your Kubernetes clusters. It provides a user-friendly interface to easily visualize and control your cluster resources, including pods, deployments, services, and more. With Helios, you can efficiently manage your containerized applications and ensure high availability and performance of your Kubernetes infrastructure.

agentica
Agentica is a specialized Agentic AI library focused on LLM Function Calling. Users can provide Swagger/OpenAPI documents or TypeScript class types to Agentica for seamless functionality. The library simplifies AI development by handling various tasks effortlessly.
For similar jobs

sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.