browser-use-bridge 1.0.0

AI browser automation bridge for Chinese LLMs, custom model providers, and OpenAI-compatible endpoints

Browser Use Bridge

English | 中文

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AI browser automation bridge with first-class support for Chinese LLMs, custom model providers, and any OpenAI-compatible endpoint.

Built on top of browser-use — extending it with Chinese LLM adapters, vision understanding, memory, checkpointing, and more.

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What's Different from browser-use

browser-use-bridge is a fork of browser-use with the following additions and changes:

Added

Feature	Details
Chinese LLM adapters	Native support for Kimi (Moonshot), Qwen (DashScope), GLM (Zhipu), MiniMax, DeepSeek — no LangChain required
Custom model provider	ChatCustom: point at any OpenAI-compatible endpoint with base_url + api_key
Ollama local models	ChatOllama with health checking, model discovery, streaming, and vision model support
Vision understanding	VisionService: screenshot → annotated image → Vision LLM analysis; automatic fallback when DOM is sparse
Planner / Controller separation	Two-agent architecture: Planner decomposes tasks into sub-goals; Controller executes and verifies each step
Memory store	BM25 keyword retrieval (zero deps) or ChromaDB vector backend; injected into Agent context automatically
Checkpoint / Resume	CheckpointManager: save task state at any step, resume after interruption
History export	HistoryExporter: export completed runs as JSON, self-contained HTML timeline, or animated GIF
Structured retry	RetryController: exponential backoff, error classification, loop detection with page fingerprinting
Updated default models	Kimi kimi-2.6, Qwen qwen3.6-plus, GLM glm-5.1, MiniMax MiniMax-M2.7, DeepSeek deepseek-v4-pro
Independent packaging	Published as browser-use-bridge on PyPI with optional dependency groups per provider

Changed

Aspect	browser-use	browser-use-bridge
Package name	browser_use	browser_use_bridge
CLI command	browser-use	browser-use-bridge
LLM base class	LangChain BaseChatModel	Lightweight custom BaseChatModel (no LangChain dependency)
Provider auto-detection	—	Detects Chinese gateways from base_url pattern

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Installation

pip install browser-use-bridge

Install with Chinese LLM SDKs:

pip install "browser-use-bridge[cn]"        # Qwen (DashScope) + GLM (Zhipu) + Anthropic
pip install "browser-use-bridge[kimi]"       # Moonshot Kimi
pip install "browser-use-bridge[deepseek]"   # DeepSeek
pip install "browser-use-bridge[minimax]"    # MiniMax
pip install "browser-use-bridge[ollama]"     # Ollama local models
pip install "browser-use-bridge[all]"        # Everything

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Quick Start

Python API

import asyncio

from browser_use_bridge import Agent, BrowserSession
from browser_use_bridge.llm import ChatKimi

async def main():
    session = BrowserSession()
    try:
        await session.start()
        agent = Agent(
            task="Search for the latest AI news and summarize the top 3 results",
            llm=ChatKimi(model="kimi-2.6", api_key="your-key"),
            browser_session=session,
        )
        history = await agent.run()
        return history
    finally:
        await session.close()

history = asyncio.run(main())

With Memory and Checkpoint

import asyncio

from browser_use_bridge import Agent
from browser_use_bridge.browser import BrowserSession
from browser_use_bridge.llm import ChatQwen
from browser_use_bridge.memory import MemoryStore
from browser_use_bridge.checkpoint import CheckpointManager

async def main():
    session = BrowserSession()
    checkpoint_manager = CheckpointManager(autosave_every_steps=5)
    try:
        await session.start()
        agent = Agent(
            task="Fill in the registration form at example.com",
            llm=ChatQwen(model="qwen3.6-plus"),
            browser_session=session,
            memory_store=MemoryStore(),
        )
        history = await agent.run()
        checkpoint_manager.save(
            task_id="registration-form",
            step_counter=len(history.histories),
            current_url=await session.get_current_url(),
            agent_history=history.model_dump(mode="json"),
            label="completed",
        )
        return history
    finally:
        await session.close()

history = asyncio.run(main())

CLI

# Run a task
browser-use-bridge run --task "Open baidu.com and search for Python" --provider kimi

# List all registered tools
browser-use-bridge list-tools

# Start MCP server for Claude Desktop
browser-use-bridge mcp --stdio

# Resume an interrupted task
browser-use-bridge resume <checkpoint_id>

# List saved checkpoints
browser-use-bridge checkpoint list

Export History

from browser_use_bridge.history import HistoryExporter

exporter = HistoryExporter(output_dir="history-exports")
artifacts = exporter.export("<checkpoint_id>", format="html")
print(artifacts["html"])

Custom / Local Model

from browser_use_bridge.llm import ChatCustom

# Any OpenAI-compatible endpoint
llm = ChatCustom(
    model="my-model",
    base_url="http://localhost:8080/v1",
    api_key="optional",
)

---

Supported Providers

Provider	Class	Default Model	Install
OpenAI	ChatOpenAI	gpt-4o	built-in
Anthropic	ChatAnthropic	claude-sonnet-4-20250514	[cn]
Google Gemini	ChatGoogle	gemini-2.0-flash	built-in
Kimi (Moonshot)	ChatKimi	kimi-2.6	built-in
Qwen (DashScope)	ChatQwen	qwen3.6-plus	[cn]
GLM (Zhipu)	ChatGLM	glm-5.1	[cn]
MiniMax	ChatMiniMax	MiniMax-M2.7	built-in
DeepSeek	ChatDeepSeek	deepseek-v4-pro	built-in
Ollama (local)	ChatOllama	llama3	[ollama]
Custom endpoint	ChatCustom	configurable	built-in

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Environment Variables

Create a .env file in your project root:

MOONSHOT_API_KEY=your-kimi-key
DASHSCOPE_API_KEY=your-qwen-key
ZHIPU_API_KEY=your-glm-key
MINIMAX_API_KEY=your-minimax-key
DEEPSEEK_API_KEY=your-deepseek-key
OPENAI_API_KEY=your-openai-key

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License

MIT — see LICENSE.

Original browser-use is also MIT licensed.

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中文说明

English | 中文

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基于 browser-use 构建的 AI 浏览器自动化框架，新增国产大模型支持、视觉理解、记忆存储、断点续传等能力。

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相比 browser-use 的改动说明

browser-use-bridge 是 browser-use 的 Fork 版本，主要改动如下：

新增功能

功能	说明
国产大模型适配器	原生支持 Kimi（月之暗面）、通义千问（DashScope）、智谱 GLM、MiniMax、DeepSeek，无需 LangChain
自定义模型提供商	ChatCustom：通过 base_url + api_key 接入任意 OpenAI 兼容接口
Ollama 本地模型	ChatOllama：含健康检查、模型发现、流式输出、视觉模型支持
视觉理解模块	VisionService：截图 → 标注图像 → Vision LLM 分析；DOM 稀少时自动降级到视觉模式
Planner / Controller 分离	双 Agent 架构：Planner 将任务分解为子目标，Controller 逐步执行并验证
记忆存储	BM25 关键词检索（零依赖）或 ChromaDB 向量后端；自动注入 Agent 上下文
断点续传	CheckpointManager：任意步骤保存任务状态，中断后可恢复
历史回放导出	HistoryExporter：导出为 JSON、自包含 HTML 时间线、或 GIF 动画
结构化重试	RetryController：指数退避、错误分级、基于页面指纹的循环检测
最新默认模型	Kimi kimi-2.6、千问 qwen3.6-plus、GLM glm-5.1、MiniMax MiniMax-M2.7、DeepSeek deepseek-v4-pro
独立 PyPI 发布	以 browser-use-bridge 发布，各模型 SDK 按需安装

变更对比

方面	browser-use	browser-use-bridge
包名	browser_use	browser_use_bridge
CLI 命令	browser-use	browser-use-bridge
LLM 基类	LangChain BaseChatModel	轻量自研 BaseChatModel（无 LangChain 依赖）
国产模型接入	不支持	原生支持，含 API Key 自动读取

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安装

pip install browser-use-bridge

安装国产模型 SDK：

pip install "browser-use-bridge[cn]"        # 千问 + GLM + Anthropic
pip install "browser-use-bridge[kimi]"       # Kimi（月之暗面）
pip install "browser-use-bridge[deepseek]"   # DeepSeek
pip install "browser-use-bridge[minimax]"    # MiniMax
pip install "browser-use-bridge[ollama]"     # Ollama 本地模型
pip install "browser-use-bridge[all]"        # 全部安装

---

快速开始

Python API

import asyncio

from browser_use_bridge import Agent
from browser_use_bridge.browser import BrowserSession
from browser_use_bridge.llm import ChatKimi

async def main():
    session = BrowserSession()
    try:
        await session.start()
        agent = Agent(
            task="搜索最新的 AI 新闻，总结前 3 条结果",
            llm=ChatKimi(model="kimi-2.6", api_key="your-key"),
            browser_session=session,
        )
        history = await agent.run()
        return history
    finally:
        await session.close()

history = asyncio.run(main())

带记忆和断点续传

import asyncio

from browser_use_bridge import Agent
from browser_use_bridge.browser import BrowserSession
from browser_use_bridge.llm import ChatQwen
from browser_use_bridge.memory import MemoryStore
from browser_use_bridge.checkpoint import CheckpointManager

async def main():
    session = BrowserSession()
    checkpoint_manager = CheckpointManager(autosave_every_steps=5)
    try:
        await session.start()
        agent = Agent(
            task="填写 example.com 的注册表单",
            llm=ChatQwen(model="qwen3.6-plus"),
            browser_session=session,
            memory_store=MemoryStore(),
        )
        history = await agent.run()
        checkpoint_manager.save(
            task_id="registration-form",
            step_counter=len(history.histories),
            current_url=await session.get_current_url(),
            agent_history=history.model_dump(mode="json"),
            label="completed",
        )
        return history
    finally:
        await session.close()

history = asyncio.run(main())

CLI

# 执行任务
browser-use-bridge run --task "打开百度搜索 Python" --provider kimi

# 列出所有工具
browser-use-bridge list-tools

# 启动 MCP 服务（供 Claude Desktop 使用）
browser-use-bridge mcp --stdio

# 恢复中断的任务
browser-use-bridge resume <checkpoint_id>

# 列出已保存的断点
browser-use-bridge checkpoint list

导出历史

from browser_use_bridge.history import HistoryExporter

exporter = HistoryExporter(output_dir="history-exports")
artifacts = exporter.export("<checkpoint_id>", format="html")
print(artifacts["html"])

自定义 / 本地模型

from browser_use_bridge.llm import ChatCustom

# 任意 OpenAI 兼容接口
llm = ChatCustom(
    model="my-model",
    base_url="http://localhost:8080/v1",
    api_key="optional",
)

---

支持的模型提供商

提供商	类名	默认模型	安装方式
OpenAI	ChatOpenAI	gpt-4o	内置
Anthropic	ChatAnthropic	claude-sonnet-4-20250514	[cn]
Google Gemini	ChatGoogle	gemini-2.0-flash	内置
Kimi（月之暗面）	ChatKimi	kimi-2.6	内置
通义千问（DashScope）	ChatQwen	qwen3.6-plus	[cn]
智谱 GLM	ChatGLM	glm-5.1	[cn]
MiniMax	ChatMiniMax	MiniMax-M2.7	内置
DeepSeek	ChatDeepSeek	deepseek-v4-pro	内置
Ollama（本地）	ChatOllama	llama3	[ollama]
自定义接口	ChatCustom	可配置	内置

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环境变量

在项目根目录创建 .env 文件：

MOONSHOT_API_KEY=your-kimi-key
DASHSCOPE_API_KEY=your-qwen-key
ZHIPU_API_KEY=your-glm-key
MINIMAX_API_KEY=your-minimax-key
DEEPSEEK_API_KEY=your-deepseek-key
OPENAI_API_KEY=your-openai-key

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开源协议

MIT — 详见 LICENSE。

原项目 browser-use 同样采用 MIT 协议。