AI Skill Hub 强烈推荐:自由LLM API 是一款优质的Agent工作流。已获得 8.4k 颗 GitHub Star,AI 综合评分 8.0 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
集成16家LLM提供商的免费层,实现OpenAI兼容代理
自由LLM API 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
集成16家LLM提供商的免费层,实现OpenAI兼容代理
自由LLM API 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:npm 全局安装 npm install -g freellmapi # 方式二:npx 直接运行(无需安装) npx freellmapi --help # 方式三:项目依赖安装 npm install freellmapi # 方式四:从源码运行 git clone https://github.com/tashfeenahmed/freellmapi cd freellmapi npm install npm start
# 命令行使用
freellmapi --help
# 基本用法
freellmapi [options] <input>
# Node.js 代码中使用
const freellmapi = require('freellmapi');
const result = await freellmapi.run(options);
console.log(result);
# freellmapi 配置说明 # 查看配置选项 freellmapi --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export FREELLMAPI_CONFIG="/path/to/config.yml"

/v1/chat/completions, /v1/responses (what Codex CLI needs), /v1/completions (editor ghost-text autocomplete), /v1/images/generations, /v1/videos/generations, /v1/audio/speech, /v1/audio/transcriptions, /v1/embeddings, and /v1/models — streaming and non-streaming, from the official SDKs or any OpenAI-compatible client. API reference →/v1/messages speaks Anthropic's wire format over the same router, so Claude Code and the official Anthropic SDKs run against your free pool. Details →/v1beta (generateContent, streaming, token counting, models), while opt-in Ollama emulation serves NDJSON chat/generate, tags, metadata, and embeddings for Zed, JetBrains, and other local-model clients.fusion model and the router fans your prompt out to a panel of diverse free models in parallel, then a judge model synthesizes one answer from the drafts. Details →/v1/images/generations, /v1/videos/generations, and /v1/audio/speech route across the providers that serve media models; images and speech also accept custom OpenAI-compatible media endpoints. Video jobs are normalized across synchronous and queued providers and return a completed MP4.tools round-trip across providers (plain-text tool calls are rescued into real tool_calls), plus response_format, seed, logprobs, penalties, and the rest of the sampling params passed through per provider.auto:<profile>.(platform, model, key) that learn providers' reported ceilings, so routing always stays under every cap.freellmapi-… bearer token./mcp; a dependency-free OpenAPI viewer lives at /v1/docs. Coding agents →The scope is deliberately narrow — see what's not supported yet.
One-liner (Docker required — sets up ~/freellmapi, generates an encryption key, pulls the image, and starts the container):
curl -fsSL https://freellmapi.co/install.sh | bash
Prefer to read before you pipe to bash? The script is here. Re-running it is safe: your .env (and encryption key) is preserved and the container updates to :latest.
Open http://localhost:3001, add your provider keys on the Keys page, reorder the Fallback Chain to taste, and grab your unified API key from the Keys page header. That unified key is what you point your OpenAI SDK at.
On Windows, the easiest path is the desktop .exe installer from Releases (below). On Android, see the experimental Termux guide.
Everything else — Docker Compose, local development, declarative startup config, production builds, LAN access, and backups — is in docs/en/install/01-install.md.
7.4 billion tokens per month. 34 free LLM providers. 635 free model endpoints. One OpenAI-compatible endpoint.
Aggregate free tiers from dozens of providers, plus custom OpenAI-compatible chat, embedding, image, and audio endpoints, behind a single /v1 API. Keys are stored encrypted. A router picks the best available model for each request, falls over to the next provider when one is rate-limited, and tracks per-key usage so you stay under every free-tier cap.
freellmapi.co · browse the full catalog: 474 model families, 635 free endpoints
English · 简体中文
<p align="center"> <a href="https://play.google.com/store/apps/details?id=co.freellmapi.app"><img src="repo-assets/badges/play-store.svg" height="60" alt="Get it on Google Play"></a> <a href="https://github.com/tashfeenahmed/freellmapi/releases/latest"><img src="repo-assets/badges/macos.svg" height="60" alt="Download for macOS"></a> <a href="https://github.com/tashfeenahmed/freellmapi/releases/latest"><img src="repo-assets/badges/windows.svg" height="60" alt="Download for Windows"></a> <a href="docs/en/install/01-install.md#docker-compose"><img src="repo-assets/badges/docker.svg" height="60" alt="Self-host with Docker"></a> </p>

Your router updates its own model catalog from a signed feed: new free models, quota changes, and compatibility fixes land without a git pull. Free installs get the monthly snapshot, so a model reaches them 30 days after it joins the live feed; premium routers get it the same day. Go live at freellmapi.co ($19/yr, cancel anytime).
</div>
---
from openai import OpenAI
client = OpenAI(
base_url="http://localhost:3001/v1",
api_key="freellmapi-your-unified-key",
)
resp = client.chat.completions.create(
model="auto", # let the router pick; or "auto:fast", "auto:smart", a profile, or a model id
messages=[{"role": "user", "content": "Summarise the fall of Rome in one sentence."}],
)
print(resp.choices[0].message.content)
print("Routed via:", resp.headers.get("x-routed-via"))
Streaming, the auto:* routing strategies, tool calling, vision input, Gemini Google Search grounding, embeddings, and the Anthropic Messages surface — with curl and Python examples for each — are all in docs/en/api/01-rest-api.md. Every response carries an X-Routed-Via: <platform>/<model> header so you can see which provider actually served it.

Based on public documentation, July 2026 — corrections welcome.
Do I need a password? Not for the desktop app — the dashboard signs itself in with a hidden local account, so there is nothing to set up and nothing to forget. Open it from the tray icon → Open Dashboard. Server installs (Docker, one-liner, npm run dev) do have an email + password account.
I forgot the password on a server install. Click Forgot password? on the login page. There is no email to send a link to, so the one-time code is printed to the server log — read it with docker compose logs -f freellmapi (or in the terminal running the server, or in the desktop log file), then enter it on the reset form. The code lasts 15 minutes.
Where are the logs? In the container log for Docker, in the terminal for a source run, and in <data dir>/logs/freeapi.log for the desktop app — reachable from the tray menu's Open Logs Folder.
How do I uninstall? Remove the app (Trash on macOS, Settings → Apps on Windows, docker compose down -v for Docker), then delete the data directory: %APPDATA%\FreeLLMAPI\, ~/Library/Application Support/FreeLLMAPI/, or ~/.config/FreeLLMAPI/. Uninstalling never touches that folder on its own.
Longer answers, per install method: docs/en/install/01-install.md#faq-passwords-logs-uninstall.
FreeLLMAPI 是一个强大的聚合 API 服务,旨在为开发者提供统一的访问入口。它通过整合全球多家主流 AI 供应商的免费额度,让用户能够以极低的成本甚至零成本调用海量大语言模型。无论是个人开发者还是团队项目,都可以通过 FreeLLMAPI 实现对多种 LLM 资源的无缝切换与高效管理。
本项目具备高度的兼容性与扩展性。首先,它完全兼容 OpenAI 标准��支持 `POST /v1/chat/completions` 和 `GET /v1/models` 接口,这意味着你可以直接在 LangChain、LlamaIndex、Continue 等主流 SDK 或客户端中通过修改 `base_url` 来使用。此外,它还实现了特殊的 `POST /v1/responses` 接口,作为一种翻译层(shim)为 Codex CLI 等特定工具提供流式事件支持。
推荐使用 Docker 进行部署。你可以通过 `docker pull ghcr.io/tashfeenahmed/freellmapi:latest` 获取官方发布的生产级镜像。该镜像支持多架构(`linux/amd64` 和 `linux/arm64`),因此在树莓派(Raspberry Pi)等 ARM 设备上也能完美运行。镜像标签包括 `latest`、版本号(如 `v1.2.3`)以及特定的 `sha-<commit>`,方便进行版本锁定与生产环境部署。
为了实现快速上手,我们提供了“一键安装”脚本。在安装了 Docker 的环境下,只需运行 `curl -fsSL https://freellmapi.co/install.sh | bash`,脚本会自动完成目录创建、加密密钥生成、镜像拉取及容器启动的全过程。该脚本具有幂等性,重复运行不会破坏已有的 `.env` 配置或加密密钥,只会将容器更新至最新版本。
FreeLLMAPI 支持声明式的启动配置,非常适合需要重复部署的 Docker 或服务器环境。你可以通过设置环境变量 `FREEAPI_CONFIG_PATH` 指向一个 JSON 配置文件,或者直接将 JSON 内容填入 `FREEAPI_CONFIG_JSON`。该配置过程是幂等的,系统会自动更新现有的 Key、自定义 Provider、模型编辑、回退路由(fallback rows)及路由设置,而不会产生重复项。
FreeLLMAPI 提供了一个统一的 OpenAI 兼容端点,聚合了包括 Google、Grogro、Cerebras、NVIDIA、Mistral、OpenRouter、GitHub Models、Cohere、Cloudflare、HuggingFace、Z.ai (智谱)、Ollama 等在内的 18 个免费 LLM 供应商,涵盖 161 个免费模型,每月处理 Token 量高达约 17 亿。你可以像使用 OpenAI 一样,通过修改 `base_url` 为本地地址并使用统一的 API Key 来调用这些资源,甚至可以兼容 Anthropic / Claude 的客户端。
高质量的LLM集成项目,值得关注
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建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,自由LLM API 是一款质量优秀的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | freellmapi |
| 原始描述 | 开源AI工作流:OpenAI-compatible proxy that stacks the free tiers of 16 LLM providers (~1.7B to。⭐8.4k · TypeScript |
| Topics | LLMOpenAI代理 |
| GitHub | https://github.com/tashfeenahmed/freellmapi |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-06-07 · 更新时间:2026-06-08 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端