docs: update READMEs for baseURL support and local model examples
- Add Ollama/local model agent example in multi-model teams section - Update "Model Agnostic" description to mention local models and baseURL - Update contributing section to reflect built-in OpenAI-compatible support - Add author block with Xiaohongshu link in Chinese README
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JackChen
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README.md
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README.md
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@ -12,7 +12,7 @@ Build AI agent teams that work together. One agent plans, another implements, a
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- **Multi-Agent Teams** — Define agents with different roles, tools, and even different models. They collaborate through a message bus and shared memory.
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- **Task DAG Scheduling** — Tasks have dependencies. The framework resolves them topologically — dependent tasks wait, independent tasks run in parallel.
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- **Model Agnostic** — Claude and GPT in the same team. Swap models per agent. Bring your own adapter for any LLM.
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- **Model Agnostic** — Claude, GPT, and local models (Ollama, vLLM, LM Studio) in the same team. Swap models per agent via `baseURL`.
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- **In-Process Execution** — No subprocess overhead. Everything runs in one Node.js process. Deploy to serverless, Docker, CI/CD.
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## Quick Start
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@ -160,7 +160,7 @@ const result = await agent.run('Find the three most recent TypeScript releases.'
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</details>
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<details>
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<summary><b>Multi-Model Teams</b> — mix Claude, GPT, and Copilot in one workflow</summary>
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<summary><b>Multi-Model Teams</b> — mix Claude, GPT, and local models in one workflow</summary>
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```typescript
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const claudeAgent: AgentConfig = {
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@ -179,9 +179,20 @@ const gptAgent: AgentConfig = {
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tools: ['bash', 'file_read', 'file_write'],
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}
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// Any OpenAI-compatible API — Ollama, vLLM, LM Studio, etc.
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const localAgent: AgentConfig = {
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name: 'reviewer',
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model: 'llama3.1',
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provider: 'openai',
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baseURL: 'http://localhost:11434/v1',
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apiKey: 'ollama',
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systemPrompt: 'You review code for correctness and clarity.',
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tools: ['file_read', 'grep'],
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}
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const team = orchestrator.createTeam('mixed-team', {
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name: 'mixed-team',
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agents: [claudeAgent, gptAgent],
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agents: [claudeAgent, gptAgent, localAgent],
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sharedMemory: true,
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})
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@ -270,7 +281,7 @@ for await (const event of agent.stream('Explain monads in two sentences.')) {
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Issues, feature requests, and PRs are welcome. Some areas where contributions would be especially valuable:
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- **LLM Adapters** — Copilot is now supported out of the box. Additional adapters for Ollama, llama.cpp, vLLM, and Gemini are welcome. The `LLMAdapter` interface requires just two methods: `chat()` and `stream()`.
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- **LLM Adapters** — Anthropic, OpenAI, and Copilot are supported out of the box. Any OpenAI-compatible API (Ollama, vLLM, LM Studio, etc.) works via `baseURL`. Additional adapters for Gemini and other providers are welcome. The `LLMAdapter` interface requires just two methods: `chat()` and `stream()`.
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- **Examples** — Real-world workflows and use cases.
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- **Documentation** — Guides, tutorials, and API docs.
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README_zh.md
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README_zh.md
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@ -12,7 +12,7 @@
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- **多智能体团队** — 定义不同角色、工具甚至不同模型的智能体。它们通过消息总线和共享内存协作。
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- **任务 DAG 调度** — 任务之间存在依赖关系。框架进行拓扑排序——有依赖的任务等待，无依赖的任务并行执行。
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- **模型无关** — Claude 和 GPT 可以在同一个团队中使用。每个智能体可以单独配置模型。你也可以为任何 LLM 编写自己的适配器。
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- **模型无关** — Claude、GPT 和本地模型（Ollama、vLLM、LM Studio）可以在同一个团队中使用。通过 `baseURL` 即可接入任何 OpenAI 兼容服务。
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- **进程内执行** — 没有子进程开销。所有内容在一个 Node.js 进程中运行。可部署到 Serverless、Docker、CI/CD。
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## 快速开始
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@ -41,6 +41,10 @@ const result = await orchestrator.runAgent(
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console.log(result.output)
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```
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## 作者
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> JackChen — 前 WPS 产品经理，现独立创业者。关注小红书[「杰克西｜硅基杠杆」](https://www.xiaohongshu.com/user/profile/5a1bdc1e4eacab4aa39ea6d6)，持续获取我的 AI Agent 观点和思考。
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## 多智能体团队
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这才是有意思的地方。三个智能体，一个目标：
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@ -160,7 +164,7 @@ const result = await agent.run('Find the three most recent TypeScript releases.'
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</details>
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<details>
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<summary><b>多模型团队</b> — 在一个工作流中混合使用 Claude、GPT 和 Copilot</summary>
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<summary><b>多模型团队</b> — 在一个工作流中混合使用 Claude、GPT 和本地模型</summary>
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```typescript
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const claudeAgent: AgentConfig = {
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@ -179,9 +183,20 @@ const gptAgent: AgentConfig = {
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tools: ['bash', 'file_read', 'file_write'],
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}
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// 任何 OpenAI 兼容 API — Ollama、vLLM、LM Studio 等
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const localAgent: AgentConfig = {
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name: 'reviewer',
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model: 'llama3.1',
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provider: 'openai',
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baseURL: 'http://localhost:11434/v1',
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apiKey: 'ollama',
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systemPrompt: 'You review code for correctness and clarity.',
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tools: ['file_read', 'grep'],
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}
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const team = orchestrator.createTeam('mixed-team', {
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name: 'mixed-team',
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agents: [claudeAgent, gptAgent],
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agents: [claudeAgent, gptAgent, localAgent],
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sharedMemory: true,
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})
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@ -270,7 +285,7 @@ for await (const event of agent.stream('Explain monads in two sentences.')) {
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欢迎提 Issue、功能需求和 PR。以下方向的贡献尤其有价值：
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- **LLM 适配器** — Copilot 已原生支持。欢迎继续贡献 Ollama、llama.cpp、vLLM、Gemini 等适配器。`LLMAdapter` 接口只需实现两个方法：`chat()` 和 `stream()`。
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- **LLM 适配器** — Anthropic、OpenAI、Copilot 已原生支持。任何 OpenAI 兼容 API（Ollama、vLLM、LM Studio 等）可通过 `baseURL` 直接使用。欢迎贡献 Gemini 等其他适配器。`LLMAdapter` 接口只需实现两个方法：`chat()` 和 `stream()`。
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- **示例** — 真实场景的工作流和用例。
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- **文档** — 指南、教程和 API 文档。
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