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许可证:MIT-0
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版本:v1.0.0
统计:⭐ 0 · 32 · 1 current installs · 1 all-time installs
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安装量(当前) 1
🛡 VirusTotal :可疑 · OpenClaw :可疑
Package:adisinghstudent/open-autoglm-phone-agent
安全扫描(ClawHub)
- VirusTotal :可疑
- OpenClaw :可疑
OpenClaw 评估
The skill's runtime instructions require API keys and server configuration options that are not declared in the metadata and include over-broad recommendations (e.g., allowing model servers to read '/' and sending screenshots to 3rd‑party model APIs), so the package is internally inconsistent and raises privacy/exposure concerns.
目的
The described purpose (phone agent controlling Android/HarmonyOS/iOS via ADB/HDC/WebDriverAgent and a VLM) matches the commands and tools in SKILL.md (git clone, ADB/HDC, model servers). However the skill metadata declares no required environment variables or credentials while the instructions repeatedly reference multiple API keys and env vars (BIGMODEL_API_KEY, MODELSCOPE_API_KEY, MODEL_BASE_URL, MODEL_API_KEY, etc.). That mismatch is incohe…
说明范围
The instructions legitimately require screenshots and device control, but they also recommend running model servers with --allowed-local-media-path / which grants the model server access to the entire filesystem, and they show example calls that send screenshots and inputs to third‑party APIs (BigModel/ModelScope). Those are reasonable for functionality but create a significant privacy/data-exfiltration risk that is not documented or constrain…
安装机制
This is an instruction-only skill (no install spec, no code files in the bundle), so nothing is written by the skill package itself. The instructions pull a GitHub repo and recommend public Docker images and pip installs (vLLM, SGLang), which are normal; no obscure download URLs are present in the visible text.
证书
The skill metadata lists no required env vars/credentials, yet the instructions require multiple API keys and expect environment variables (e.g., BIGMODEL_API_KEY, MODELSCOPE_API_KEY, MODEL_BASE_URL, MODEL_API_KEY). Requesting API keys for model hosting is reasonable given the purpose, but the omission from metadata is an incoherence and increases risk because users may not realize which secrets will be used or transmitted.
持久
The skill does not request persistent privileges and 'always' is false. However the recommended model-server configuration (--allowed-local-media-path /) effectively grants the model process broad local file access while it's running; this is a operational privilege granted by following the instructions, not by the skill metadata. That operational recommendation should be treated as a high-risk configuration option.
安装(复制给龙虾 AI)
将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「open-autoglm-phone-agent」。简介:Expert skill for Open-AutoGLM, an AI phone agent framework that controls Androi…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/adisinghstudent/open-autoglm-phone-agent/SKILL.md
(来源:yingzhi8.cn 技能库)
SKILL.md
---
name: open-autoglm-phone-agent
description: Expert skill for Open-AutoGLM, an AI phone agent framework that controls Android/HarmonyOS/iOS devices via natural language using the AutoGLM vision-language model
triggers:
- set up AutoGLM phone agent
- control android phone with AI
- automate phone tasks with natural language
- deploy AutoGLM model for phone automation
- configure ADB phone agent
- run phone agent with AutoGLM
- phone use agent python setup
- automate mobile device with vision model
---
# Open-AutoGLM Phone Agent
> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.
Open-AutoGLM is an open-source AI phone agent framework that enables natural language control of Android, HarmonyOS NEXT, and iOS devices. It uses the AutoGLM vision-language model (9B parameters) to perceive screen content and execute multi-step tasks like "open Meituan and search for nearby hot pot restaurants."
## Architecture Overview
```
User Natural Language → AutoGLM VLM → Screen Perception → ADB/HDC/WebDriverAgent → Device Actions
```
- **Model**: AutoGLM-Phone-9B (Chinese-optimized) or AutoGLM-Phone-9B-Multilingual
- **Device control**: ADB (Android), HDC (HarmonyOS NEXT), WebDriverAgent (iOS)
- **Model serving**: vLLM or SGLang (self-hosted) or BigModel/ModelScope API
- **Input**: Screenshot + task description → Output: structured action commands
## Installation
### Prerequisites
- Python 3.10+
- ADB installed and in PATH (Android) or HDC (HarmonyOS) or WebDriverAgent (iOS)
- Android device with Developer Mode + USB Debugging enabled
- ADB Keyboard APK installed on Android device (for text input)
### Install the framework
```bash
git clone https://github.com/zai-org/Open-AutoGLM.git
cd Open-AutoGLM
pip install -r requirements.txt
pip install -e .
```
### Verify ADB connection
```bash
# Android
adb devices
# Expected: emulator-5554 device
# HarmonyOS NEXT
hdc list targets
# Expected: 7001005458323933328a01bce01c2500
```
## Model Deployment Options
### Option A: Third-party API (Recommended for quick start)
**BigModel (ZhipuAI)**
```bash
export BIGMODEL_API_KEY="your-bigmodel-api-key"
python main.py
--base-url https://open.bigmodel.cn/api/paas/v4
--model "autoglm-phone"
--apikey $BIGMODEL_API_KEY
"打开美团搜索附近的火锅店"
```
**ModelScope**
```bash
export MODELSCOPE_API_KEY="your-modelscope-api-key"
python main.py
--base-url https://api-inference.modelscope.cn/v1
--model "ZhipuAI/AutoGLM-Phone-9B"
--apikey $MODELSCOPE_API_KEY
"open Meituan and find nearby hotpot"
```
### Option B: Self-hosted with vLLM
```bash
# Install vLLM (or use official Docker: docker pull vllm/vllm-openai:v0.12.0)
pip install vllm
# Start model server (strictly follow these parameters)
python3 -m vllm.entrypoints.openai.api_server
--served-model-name autoglm-phone-9b
--allowed-local-media-path /
--mm-encoder-tp-mode data
--mm_processor_cache_type shm
--mm_processor_kwargs '{"max_pixels":5000000}'
--max-model-len 25480
--chat-template-content-format string
--limit-mm-per-prompt '{"image":10}'
--model zai-org/AutoGLM-Phone-9B
--port 8000
```
### Option C: Self-hosted with SGLang
```bash
# Install SGLang or use: docker pull lmsysorg/sglang:v0.5.6.post1
# Inside container: pip install nvidia-cudnn-cu12==9.16.0.29
python3 -m sglang.launch_server
--model-path zai-org/AutoGLM-Phone-9B
--served-model-name autoglm-phone-9b
--context-length 25480
--mm-enable-dp-encoder
--mm-process-config '{"image":{"max_pixels":5000000}}'
--port 8000
```
### Verify deployment
```bash
python scripts/check_deployment_cn.py
--base-url http://localhost:8000/v1
--model autoglm-phone-9b
```
Expected output includes a `<think>...</think>` block followed by `<answer>do(action="Launch", app="...")`. **If the chain-of-thought is very short or garbled, the model deployment has failed.**
## Running the Agent
### Basic CLI usage
```bash
# Android device (default)
python main.py
--base-url http://localhost:8000/v1
--model autoglm-phone-9b
"打开小红书搜索美食"
# HarmonyOS device
python main.py
--base-url http://localhost:8000/v1
--model autoglm-phone-9b
--device-type hdc
"打开设置查看WiFi"
# Multilingual model for English apps
python main.py
--base-url http://localhost:8000/v1
--model autoglm-phone-9b-multilingual
"Open Instagram and search for travel photos"
```
### Key CLI parameters
| Parameter | Description | Default |
|-----------|-------------|---------|
| `--base-url` | Model service endpoint | Required |
| `--model` | Model name on server | Required |
| `--apikey` | API key for third-party services | None |
| `--device-type` | `adb` (Android) or `hdc` (HarmonyOS) | `adb` |
| `--device-id` | Specific device serial number | Auto-detect |
## Python API Usage
### Basic agent invocation
```python
from phone_agent import PhoneAgent
from phone_agent.config import AgentConfig
config = AgentConfig(
base_url="http://localhost:8000/v1",
model="autoglm-phone-9b",
device_type="adb", # or "hdc" for HarmonyOS
)
agent = PhoneAgent(config)
# Run a task
result = agent.run("打开淘宝搜索蓝牙耳机")
print(result)
```
### Custom task with device selection
```python
from phone_agent import PhoneAgent
from phone_agent.config import AgentConfig
import os
config = AgentConfig(
base_url=os.environ["MODEL_BASE_URL"],
model=os.environ["MODEL_NAME"],
apikey=os.environ.get("MODEL_API_KEY"),
device_type="adb",
device_id="emulator-5554", # specific device
)
agent = PhoneAgent(config)
# Task with sensitive operation confirmation
result = agent.run(
"在京东购买最便宜的蓝牙耳机",
confirm_sensitive=True # prompt user before purchase actions
)
```
### Direct model API call (for testing/integration)
```python
import openai
import base64
import os
from pathlib import Path
client = openai.OpenAI(
base_url=os.environ["MODEL_BASE_URL"],
api_key=os.environ.get("MODEL_API_KEY", "dummy"),
)
# Load screenshot
screenshot_path = "screenshot.png"
with open(screenshot_path, "rb") as f:
image_b64 = base64.b64encode(f.read()).decode()
response = client.chat.completions.create(
model="autoglm-phone-9b",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {"url": f"data:image/png;base64,{image_b64}"},
},
{
"type": "text",
"text": "Task: 搜索附近的咖啡店nCurrent step: Navigate to search",
},
],
}
],
)
print(response.choices[0].message.content)
# Output format: <think>...</think>n<answer>do(action="...", ...)
```
### Parsing model action output
```python
import re
def parse_action(model_output: str) -> dict:
"""Parse AutoGLM model output into structured action."""
# Extract answer block
answer_match = re.search(r'<answer>(.*?)(?:</answer>|$)', model_output, re.DOTALL)
if not answer_match:
return {"action": "unknown"}
answer = answer_match.group(1).strip()
# Parse do() call
# Format: do(action="ActionName", param1="value1", param2="value2")
action_match = re.search(r'do(action="([^"]+)"(.*?))', answer, re.DOTALL)
if not action_match:
return {"action": "unknown", "raw": answer}
action_name = action_match.group(1)
params_str = action_match.group(2)
# Parse parameters
params = {}
for param_match in re.finditer(r'(w+)="([^"]*)"', params_str):
params[param_match.group(1)] = param_match.group(2)
return {"action": action_name, **params}
# Example usage
output = '<think>需要启动京东</think>n<answer>do(action="Launch", app="京东")'
action = parse_action(output)
# {"action": "Launch", "app": "京东"}
```
## ADB Device Control Patterns
### Common ADB operations used by the agent
```python
import subprocess
def take_screenshot(device_id: str = None) -> bytes:
"""Capture current device screen."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
cmd.extend(["exec-out", "screencap", "-p"])
result = subprocess.run(cmd, capture_output=True)
return result.stdout
def send_tap(x: int, y: int, device_id: str = None):
"""Tap at screen coordinates."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
cmd.extend(["shell", "input", "tap", str(x), str(y)])
subprocess.run(cmd)
def send_text_adb_keyboard(text: str, device_id: str = None):
"""Send text via ADB Keyboard (must be installed and enabled)."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
# Enable ADB keyboard first
cmd_enable = cmd + ["shell", "ime", "set", "com.android.adbkeyboard/.AdbIME"]
subprocess.run(cmd_enable)
# Send text
cmd_text = cmd + ["shell", "am", "broadcast", "-a", "ADB_INPUT_TEXT",
"--es", "msg", text]
subprocess.run(cmd_text)
def swipe(x1: int, y1: int, x2: int, y2: int, duration_ms: int = 300, device_id: str = None):
"""Swipe gesture on screen."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
cmd.extend(["shell", "input", "swipe",
str(x1), str(y1), str(x2), str(y2), str(duration_ms)])
subprocess.run(cmd)
def press_back(device_id: str = None):
"""Press Android back button."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
cmd.extend(["shell", "input", "keyevent", "KEYCODE_BACK"])
subprocess.run(cmd)
def launch_app(package_name: str, device_id: str = None):
"""Launch app by package name."""
cmd = ["adb"]
if device_id:
cmd.extend(["-s", device_id])
cmd.extend(["shell", "monkey", "-p", package_name, "-c",
"android.intent.category.LAUNCHER", "1"])
subprocess.run(cmd)
```
## Midscene.js Integration
For JavaScript/TypeScript automation using AutoGLM:
```javascript
// .env configuration
// MIDSCENE_MODEL_NAME=autoglm-phone
// MIDSCENE_OPENAI_BASE_URL=https://open.bigmodel.cn/api/paas/v4
// MIDSCENE_OPENAI_API_KEY=your-api-key
import { AndroidAgent } from "@midscene/android";
const agent = new AndroidAgent();
await agent.aiAction("打开微信发送消息给张三");
await agent.aiQuery("当前页面显示的消息内容是什么?");
```
## Remote ADB (WiFi Debugging)
```bash
# Connect device via USB first, then enable TCP/IP mode
adb tcpip 5555
# Get device IP address
adb shell ip addr show wlan0
# Connect wirelessly (disconnect USB after this)
adb connect 192.168.1.100:5555
# Verify connection
adb devices
# 192.168.1.100:5555 device
# Use with agent
python main.py
--base-url http://model-server:8000/v1
--model autoglm-phone-9b
--device-id "192.168.1.100:5555"
"打开支付宝查看余额"
```
## Common Action Types
The AutoGLM model outputs structured actions:
| Action | Description | Example |
|--------|-------------|---------|
| `Launch` | Open an app | `do(action="Launch", app="微信")` |
| `Tap` | Tap screen element | `do(action="Tap", element="搜索框")` |
| `Type` | Input text | `do(action="Type", text="火锅")` |
| `Swipe` | Scroll/swipe | `do(action="Swipe", direction="up")` |
| `Back` | Press back button | `do(action="Back")` |
| `Home` | Go to home screen | `do(action="Home")` |
| `Finish` | Task complete | `do(action="Finish", result="已完成搜索")` |
## Model Selection Guide
| Model | Use Case | Languages |
|-------|----------|-----------|
| `AutoGLM-Phone-9B` | Chinese apps (WeChat, Taobao, Meituan) | Chinese-optimized |
| `AutoGLM-Phone-9B-Multilingual` | International apps, mixed content | Chinese + English + others |
- HuggingFace: `zai-org/AutoGLM-Phone-9B` / `zai-org/AutoGLM-Phone-9B-Multilingual`
- ModelScope: `ZhipuAI/AutoGLM-Phone-9B` / `ZhipuAI/AutoGLM-Phone-9B-Multilingual`
## Environment Variables Reference
```bash
# Model service
export MODEL_BASE_URL="http://localhost:8000/v1"
export MODEL_NAME="autoglm-phone-9b"
export MODEL_API_KEY="" # Required for BigModel/ModelScope APIs
# BigModel API
export BIGMODEL_API_KEY=""
export BIGMODEL_BASE_URL="https://open.bigmodel.cn/api/paas/v4"
# ModelScope API
export MODELSCOPE_API_KEY=""
export MODELSCOPE_BASE_URL="https://api-inference.modelscope.cn/v1"
# Device configuration
export ADB_DEVICE_ID="" # Leave empty for auto-detect
export HDC_DEVICE_ID="" # HarmonyOS device ID
```
## Troubleshooting
### Model output is garbled or very short chain-of-thought
**Cause**: Incorrect vLLM/SGLang startup parameters.
**Fix**: Ensure `--chat-template-content-format string` (vLLM) and `--mm-process-config` with `max_pixels:5000000` are set. Check transformers version compatibility.
### `adb devices` shows no devices
**Fix**:
1. Verify USB cable supports data transfer (not charge-only)
2. Accept "Allow USB debugging" dialog on phone
3. Try `adb kill-server && adb start-server`
4. Some devices require reboot after enabling developer options
### Text input not working on Android
**Fix**: ADB Keyboard must be installed AND enabled:
```bash
adb shell ime enable com.android.adbkeyboard/.AdbIME
adb shell ime set com.android.adbkeyboard/.AdbIME
```
### Agent stuck in a loop
**Cause**: Model cannot identify a path to complete the task.
**Fix**: The framework includes sensitive operation confirmation — ensure `confirm_sensitive=True` for purchase/delete tasks. For login/CAPTCHA screens, the agent supports human takeover.
### vLLM CUDA out of memory
**Fix**: AutoGLM-Phone-9B requires ~20GB VRAM. Use `--tensor-parallel-size 2` for multi-GPU, or use the API service instead.
### Connection refused to model server
**Fix**: Check firewall rules. For remote server:
```bash
# Test connectivity
curl http://YOUR_SERVER_IP:8000/v1/models
# Should return model list JSON
```
### HDC device not recognized (HarmonyOS)
**Fix**: HarmonyOS NEXT (not earlier versions) is required. Enable developer mode in Settings → About → Version Number (tap 10 times rapidly).
## iOS Setup
For iPhone automation, see the dedicated setup guide:
```bash
# After configuring WebDriverAgent per docs/ios_setup/ios_setup.md
python main.py
--base-url http://localhost:8000/v1
--model autoglm-phone-9b-multilingual
--device-type ios
"Open Maps and navigate to Central Park"
```