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Initial commit: skills library

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- 70 skills with code and documentation
- Add .gitignore (ignore __pycache__, output/, temp/, venv/)
- Clean up test intermediates and caches
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hmo
2026-04-26 19:27:40 +08:00
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llm-hub/.env.example
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# LLM Hub 环境变量配置
# 复制此文件为 .env 并填入实际API Key
# 火山方舟 (https://console.volcengine.com/ark)
VOLCENGINE_API_KEY=your_volcengine_api_key_here
# OpenRouter (https://openrouter.ai/)
OPENROUTER_API_KEY=sk-your-key-here
# Groq (https://console.groq.com/)
GROQ_API_KEY=gsk_your-key-here
# DeepSeek (https://platform.deepseek.com/)
DEEPSEEK_API_KEY=sk-your-key-here
# 硅基流动 (https://siliconflow.cn/)
SILICONFLOW_API_KEY=sk-your-key-here
# 阶跃星辰 (https://platform.stepfun.com/)
STEPFUN_API_KEY=sk-your-key-here
llm-hub/SKILL.md
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---
name: llm-hub
description: LLM资源中心。管理多供应商大模型API、本地Ollama模型、额度监控、自动切换配置。当用户需要查询模型、切换API、管理额度时使用此技能。
---
# LLM Hub - 大模型资源管理中心
## 概述
此技能用于统一管理多供应商的大模型API和本地Ollama模型，提供额度监控、自动切换、账号管理等功能。
## 触发场景
当用户提及以下内容时激活此技能：
- "查一下额度"、"看看各平台剩余"
- "切换模型"、"换一个API"
- "本地有什么模型"、"Ollama在跑什么"
- "帮我注册"、"申请新账号"
- "API配置"、"模型对比"
## 功能模块
### 1. 模型发现
#### 本地模型（Ollama）
```bash
# 列出本地模型
ollama list
# 查看运行状态
ollama ps
# 拉取模型
ollama pull <model-name>
```
**配置文件位置**: `%USERPROFILE%\.ollama\models`
#### 云端模型
支持的供应商和免费额度：
| 供应商 | 特点 | 推荐模型 | API端点 |
|-------|------|---------|---------|
| **火山方舟** | Coding Plan ¥7.9/月 | doubao-seed-2.0-pro, doubao-seed-code (视觉) | `https://ark.cn-beijing.volces.com/api/coding/v3` |
| DeepSeek | 价格屠夫 | deepseek-v3, deepseek-coder | `https://api.deepseek.com/v1` |
| Groq | 免费额度充足 | mixtral-8x7b-32768, llama-3.1-70b | `https://api.groq.com/openai/v1` |
| OpenRouter | 有限免费 | deepseek/deepseek-r1 | `https://openrouter.ai/api/v1` |
### 2. 额度监控
#### 检查各平台额度
```bash
# 火山方舟 - 通过API查询
curl -H "Authorization: Bearer $VOLCENGINE_API_KEY" \
https://ark.cn-beijing.volces.com/api/coding/v3/usage
# OpenRouter - 通过API查询
curl -H "Authorization: Bearer $OPENROUTER_API_KEY" \
https://openrouter.ai/api/v1/credits
# DeepSeek - 通过API查询
curl -H "Authorization: Bearer $DEEPSEEK_API_KEY" \
https://api.deepseek.com/v1/remaining_quota
```
#### 额度记录
每次使用后更新 `references/usage_records.md`，记录：
- 日期时间
- 供应商
- 模型
- 消耗token数
- 剩余额度
### 3. 自动切换配置
#### 配置文件
配置文件: `config/providers.json`
```json
{
"providers": [
{
"name": "volcengine",
"priority": 1,
"api_key_env": "VOLCENGINE_API_KEY",
"base_url": "https://ark.cn-beijing.volces.com/api/coding/v3",
"models": ["doubao-seed-2.0-pro", "doubao-seed-code"],
"enabled": true
},
{
"name": "deepseek",
"priority": 2,
"api_key_env": "DEEPSEEK_API_KEY",
"base_url": "https://api.deepseek.com/v1",
"models": ["deepseek-v3", "deepseek-coder"],
"enabled": true
},
{
"name": "groq",
"priority": 3,
"api_key_env": "GROQ_API_KEY",
"base_url": "https://api.groq.com/openai/v1",
"models": ["mixtral-8x7b-32768", "llama-3.1-70b"],
"enabled": true
}
],
"current_provider": "volcengine",
"fallback_enabled": true
}
```
#### 切换逻辑
当检测到当前供应商额度不足或API报错时：
1. 自动切换到下一个可用的provider
2. 记录切换事件到日志
3. 发送通知（可选）
### 4. 账号管理
#### 火山方舟账号
当前使用火山方舟 Coding Plan：
```bash
VOLCENGINE_API_KEY=b0359bed-09f2-49e2-a53c-32ba057412e3
```
**账号记录**: `references/accounts.md`
| 账号 | API Key | 套餐 | 状态 |
|-----|---------|------|------|
| Coding Plan | b0359...412e3 | ¥7.9/月 | 正常 |
#### 新账号注册指引
**火山方舟 Coding Plan**:
1. 访问 https://console.volcengine.com/ark/
2. 注册/登录账号
3. 开通 Coding Plan 套餐
4. 获取 API Key
### 5. 模型对比
| 场景 | 推荐模型 | 原因 |
|-----|---------|------|
| 代码生成 | doubao-seed-code, deepseek-coder | 专用模型 |
| 中文对话 | doubao-pro, deepseek-v3 | 中文优化 |
| 快速响应 | groq+mixtral, llama-3.1-8b | 延迟低 |
| 多模态/视觉 | doubao-seed-code | Coding Plan唯一视觉模型 |
| 免费优先 | groq, openrouter免费层 | 成本最低 |
## 使用流程
### 首次使用
1. 配置环境变量（见下方）
2. 运行 `python scripts/init_config.py` 初始化配置
3. 查询各平台额度：`python scripts/check_quotas.py`
### 日常使用
1. 查询额度: "帮我查一下各平台额度"
2. 切换模型: "切换到Groq"
3. 添加账号: "添加一个新的阿里云账号"
## 环境变量配置
在系统环境变量或 `.env` 文件中配置：
```bash
# 火山方舟 (Coding Plan)
VOLCENGINE_API_KEY=b0359bed-09f2-49e2-a53c-32ba057412e3
# DeepSeek
DEEPSEEK_API_KEY=sk-xxx
# Groq
GROQ_API_KEY=gsk_xxx
# OpenRouter
OPENROUTER_API_KEY=sk-xxx
```
## OpenCode 配置
要在 OpenCode 的 /models 中添加火山方舟：
### 方法1：使用环境变量
```bash
# 在系统环境变量中设置
VOLCENGINE_API_KEY=b0359bed-09f2-49e2-a53c-32ba057412e3
```
### 方法2：配置文件（推荐）
火山方舟已在 `~/.config/opencode/config.json` 中配置：
```jsonc
{
"provider": {
"volcengine": {
"npm": "@ai-sdk/openai-compatible",
"options": {
"baseURL": "https://ark.cn-beijing.volces.com/api/coding/v3",
"apiKey": "b0359bed-09f2-49e2-a53c-32ba057412e3"
},
"models": {
"doubao-seed-2.0-pro": {},
"doubao-seed-2.0-code": {},
"doubao-seed-2.0-lite": {},
"doubao-seed-code": {}
}
},
"deepseek": {
"npm": "@ai-sdk/openai-compatible",
"options": {
"baseURL": "https://api.deepseek.com/v1"
},
"models": {
"deepseek-chat": {},
"deepseek-coder": {}
}
}
}
}
```
### 配置步骤
1. 创建/编辑配置文件：
```bash
# Windows
notepad %USERPROFILE%\.config\opencode\opencode.json
# 或用 VS Code
code %USERPROFILE%\.config\opencode\opencode.json
```
2. 添加 API Key（两种方式）：
**方式A：写到配置里（不安全）**
```jsonc
{
"provider": {
"dashscope": {
"options": {
"apiKey": "sk-56a8e427c3f7403a90e2cf22f1b9d842"
}
}
}
}
```
**方式B：用环境变量（推荐）**
- 设置系统环境变量 `DASHSCOPE_API_KEY`
3. 重启 OpenCode，运行 `/models` 刷新模型列表
## 文件结构
```
llm-hub/
├── SKILL.md # 本文件
├── config/
│ └── providers.json # 供应商配置
├── references/
│ ├── usage_records.md # 使用记录
│ ├── accounts.md # 账号管理
│ └── model_comparison.md # 模型对比表
├── scripts/
│ ├── check_quotas.py # 查询额度
│ ├── switch_provider.py # 切换供应商
│ ├── add_account.py # 添加账号
│ └── init_config.py # 初始化配置
└── .env.example # 环境变量示例
```
## 注意事项
1. **火山方舟 Coding Plan** - 主要供应商，视觉模型用 `doubao-seed-code`
2. API Key 安全 - 不要提交到Git
3. 额度告警 - 低于10%时提醒切换
4. 轮询机制 - 多个账号时轮换使用
llm-hub/assets/.gitkeep
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llm-hub/config/providers.json
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{
"providers": [
{
"name": "volcengine",
"priority": 1,
"api_key_env": "VOLCENGINE_API_KEY",
"base_url": "https://ark.cn-beijing.volces.com/api/coding/v3",
"models": ["doubao-seed-2.0-pro", "doubao-seed-2.0-code", "doubao-seed-2.0-lite", "doubao-seed-code", "doubao-1.5-pro-32k-250115", "doubao-1.5-lite-32k-250115"],
"enabled": true
},
{
"name": "deepseek",
"priority": 2,
"api_key_env": "DEEPSEEK_API_KEY",
"base_url": "https://api.deepseek.com/v1",
"models": ["deepseek-chat", "deepseek-coder", "deepseek-v3", "deepseek-v3.2"],
"enabled": true
},
{
"name": "groq",
"priority": 3,
"api_key_env": "GROQ_API_KEY",
"base_url": "https://api.groq.com/openai/v1",
"models": ["mixtral-8x7b-32768", "llama-3.1-70b-versatile", "llama-3.1-8b-instant"],
"enabled": true
},
{
"name": "openrouter",
"priority": 4,
"api_key_env": "OPENROUTER_API_KEY",
"base_url": "https://openrouter.ai/api/v1",
"models": ["deepseek/deepseek-r1", "mistralai/mistral-small-3", "meta-llama/llama-3.1-8b-instruct"],
"enabled": true
}
],
"current_provider": "volcengine",
"fallback_enabled": true,
"alert_threshold": 0.1,
"vision_config": {
"default_model": "doubao-seed-code",
"note": "火山方舟Coding Plan唯一支持的视觉模型",
"auto_switch": false,
"ask_before_switch": true
}
}
llm-hub/references/accounts.md
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# 账号管理
## 阿里云百炼账号
| 账号 | API Key | 剩余额度 | 状态 | 备注 |
|-----|---------|---------|------|------|
| 账号1 | sk-xxx | | | |
| 账号2 | sk-xxx | | | |
| 账号3 | sk-xxx | | | |
## 其他平台
| 平台 | API Key | 状态 |
|-----|---------|------|
| OpenRouter | sk-xxx | |
| Groq | gsk_xxx | |
| DeepSeek | sk-xxx | |
| 硅基流动 | sk-xxx | |
| 阶跃星辰 | sk-xxx | |
llm-hub/references/example.md
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# Example Reference
This is an example reference file. Delete if not needed.
llm-hub/references/model_comparison.md
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# 模型对比表
## 按场景推荐
| 场景 | 推荐模型 | 供应商 | 特点 | 适合 |
|-----|---------|-------|------|------|
| 👑 **最新最强** | qwen3.5-plus | 阿里云 | 2026.2.16发布，超GPT-5.2，0.8元/百万Token | 所有场景 |
| 👑 **最新最强** | qwen3.5-397b-a17b | 阿里云 | 3970亿参数激活170亿，旗舰开源 | 复杂推理 |
| 代码生成 | deepseek-coder | DeepSeek | 专用代码模型 | 编程任务 |
| 代码生成 | codeqwen:7b | Ollama | 本地可跑 | 低延迟 |
| 中文对话 | qwen-plus | 阿里云 | 中文优化 | 日常对话 |
| 中文对话 | deepseek-chat | DeepSeek | 性价比高 | 日常对话 |
| 快速响应 | mixtral-8x7b-32768 | Groq | 超低延迟 | 实时交互 |
| 快速响应 | llama-3.1-8b-instruct | Ollama | 本地快速 | 离线使用 |
| 多模态 | qwen2.5vl:7b | Ollama | 看图理解 | 图像分析 |
| 多模态 | llama3.2-vision:11b | Ollama | 图像理解强 | 复杂图像 |
| 免费优先 | mistral-small-3 | OpenRouter | 免费层可用 | 预算有限 |
| 推理能力 | deepseek-r1 | OpenRouter | 推理能力强 | 复杂逻辑 |
## Qwen3.5 新模型（2026.2.16发布）
| 模型 | 参数 | 激活参数 | 特点 | API价格 |
|-----|------|---------|------|-------|
| qwen3.5-plus | 3970亿 | 170亿 | 最强开源，超越GPT-5.2 | 0.8元/百万Token |
| qwen3.5-397b-a17b | 3970亿 | 170亿 | 旗舰开源，支持多模态 | 参考plus |
**新用户福利**: 阿里云百炼新用户送 **100万免费Token**
## 按硬件选择
### 16GB VRAM (RTX 3080)
| 模型 | 量化 | 内存需求 | 速度 |
|-----|-----|---------|------|
| llama3.1:8b | Q4_K_M | ~5GB | 快 |
| qwen2.5:7b | Q4_K_M | ~4.5GB | 快 |
| mistral:7b | Q4_K_M | ~4.5GB | 极快 |
| phi4:14b | Q4_K_M | ~9GB | 中 |
| llama3.2-vision:11b | Q4_K_M | ~7GB | 中 |
| qwen2.5vl:7b | Q4_K_M | ~5GB | 中 |
### 24GB+ VRAM
| 模型 | 量化 | 内存需求 | 速度 |
|-----|-----|---------|------|
| qwen2.5:14b | Q4_K_M | ~9GB | 中 |
| deepseek-r1:8b | Q4_K_M | ~5GB | 快 |
| llama3.3:70b | Q4_K_M | ~40GB | 慢 |
llm-hub/references/usage_records.md
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# 使用记录
## 2026-02-17
| 时间 | 供应商 | 模型 | 消耗Token | 剩余额度 |
|-----|-------|------|----------|---------|
| | | | | |
llm-hub/requirements.txt
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# llm-hub - dependencies
requests>=0.0.1
llm-hub/scripts/add_account.py
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#!/usr/bin/env python3
"""
添加新账号
"""
import os
import sys
ACCOUNTS_FILE = os.path.join(os.path.dirname(__file__), "../references/accounts.md")
def add_aliyun_account(key, label=None):
"""添加阿里云账号"""
if not label:
# 自动生成标签
with open(ACCOUNTS_FILE, "r", encoding="utf-8") as f:
content = f.read()
count = content.count("| 账号") - 1 # 减去表头
label = f"账号{count + 1}"
# 读取现有内容
with open(ACCOUNTS_FILE, "r", encoding="utf-8") as f:
lines = f.readlines()
# 找到表格最后一行
insert_idx = len(lines)
for i, line in enumerate(lines):
if line.startswith("| ---"):
insert_idx = i
break
new_row = f"| {label} | {key} | | 正常 |\n"
lines.insert(insert_idx, new_row)
with open(ACCOUNTS_FILE, "w", encoding="utf-8") as f:
f.writelines(lines)
print(f"已添加阿里云账号: {label}")
print(f"API Key: {key[:10]}...")
def main():
if len(sys.argv) < 2:
print("用法:")
print(" python add_account.py aliyun <api_key> [标签]")
print(" python add_account.py openrouter <api_key>")
print(" python add_account.py groq <api_key>")
print(" python add_account.py deepseek <api_key>")
return
platform = sys.argv[1]
api_key = sys.argv[2] if len(sys.argv) > 2 else input("请输入API Key: ")
label = sys.argv[3] if len(sys.argv) > 3 else None
if platform == "aliyun":
add_aliyun_account(api_key, label)
else:
print(f"暂不支持平台: {platform}")
if __name__ == "__main__":
main()
llm-hub/scripts/check_quotas.py
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#!/usr/bin/env python3
"""
查询各平台API额度
"""
import os
import json
import requests
from datetime import datetime
def check_aliyun_quota():
"""查询阿里云百炼额度"""
api_key = os.getenv("DASHSCOPE_API_KEY")
if not api_key:
return {"error": "DASHSCOPE_API_KEY not set"}
try:
url = "https://dashscope.aliyuncs.com/compatible-mode/v1/usage"
headers = {"Authorization": f"Bearer {api_key}"}
resp = requests.get(url, headers=headers, timeout=10)
if resp.status_code == 200:
data = resp.json()
return {"provider": "aliyun", "status": "ok", "data": data}
else:
return {"provider": "aliyun", "error": resp.text}
except Exception as e:
return {"provider": "aliyun", "error": str(e)}
def check_openrouter_quota():
"""查询OpenRouter额度"""
api_key = os.getenv("OPENROUTER_API_KEY")
if not api_key:
return {"error": "OPENROUTER_API_KEY not set"}
try:
url = "https://openrouter.ai/api/v1/credits"
headers = {"Authorization": f"Bearer {api_key}"}
resp = requests.get(url, headers=headers, timeout=10)
if resp.status_code == 200:
data = resp.json()
return {"provider": "openrouter", "status": "ok", "data": data}
else:
return {"provider": "openrouter", "error": resp.text}
except Exception as e:
return {"provider": "openrouter", "error": str(e)}
def check_deepseek_quota():
"""查询DeepSeek额度"""
api_key = os.getenv("DEEPSEEK_API_KEY")
if not api_key:
return {"error": "DEEPSEEK_API_KEY not set"}
try:
url = "https://api.deepseek.com/v1/remaining_quota"
headers = {"Authorization": f"Bearer {api_key}"}
resp = requests.get(url, headers=headers, timeout=10)
if resp.status_code == 200:
data = resp.json()
return {"provider": "deepseek", "status": "ok", "data": data}
else:
return {"provider": "deepseek", "error": resp.text}
except Exception as e:
return {"provider": "deepseek", "error": str(e)}
def check_groq_quota():
"""查询Groq额度（通过OpenAI兼容接口）"""
api_key = os.getenv("GROQ_API_KEY")
if not api_key:
return {"error": "GROQ_API_KEY not set"}
try:
# Groq没有直接的额度查询API，返回提示
return {
"provider": "groq",
"status": "no_api",
"message": "Groq无公开额度查询API，请登录Groq Dashboard查看",
}
except Exception as e:
return {"provider": "groq", "error": str(e)}
def main():
print(f"=== LLM额度查询 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} ===\n")
results = []
# 阿里云
print("[1/4] 阿里云百炼...")
result = check_aliyun_quota()
results.append(result)
if "error" in result:
print(f" 错误: {result.get('error')}")
else:
print(f" OK")
# OpenRouter
print("[2/4] OpenRouter...")
result = check_openrouter_quota()
results.append(result)
if "error" in result:
print(f" 错误: {result.get('error')}")
elif result.get("status") == "no_api":
print(f" {result.get('message')}")
else:
print(f" OK")
# DeepSeek
print("[3/4] DeepSeek...")
result = check_deepseek_quota()
results.append(result)
if "error" in result:
print(f" 错误: {result.get('error')}")
else:
print(f" OK")
# Groq
print("[4/4] Groq...")
result = check_groq_quota()
results.append(result)
if "error" in result:
print(f" 错误: {result.get('error')}")
else:
print(f" {result.get('message', 'OK')}")
print("\n=== 详细结果 ===")
print(json.dumps(results, indent=2, ensure_ascii=False))
if __name__ == "__main__":
main()
llm-hub/scripts/example.py
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#!/usr/bin/env python3
"""Example script - delete if not needed."""
print("Hello from skill!")
llm-hub/scripts/init_config.py
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#!/usr/bin/env python3
"""
初始化LLM Hub配置
"""
import os
def create_env_example():
content = """# LLM Hub 环境变量配置
# 复制此文件为 .env 并填入实际API Key
# 阿里云百炼 (https://dashscope.console.aliyun.com/)
DASHSCOPE_API_KEY=sk-your-key-here
# OpenRouter (https://openrouter.ai/)
OPENROUTER_API_KEY=sk-your-key-here
# Groq (https://console.groq.com/)
GROQ_API_KEY=gsk_your-key-here
# DeepSeek (https://platform.deepseek.com/)
DEEPSEEK_API_KEY=sk-your-key-here
# 硅基流动 (https://siliconflow.cn/)
SILICONFLOW_API_KEY=sk-your-key-here
# 阶跃星辰 (https://platform.stepfun.com/)
STEPFUN_API_KEY=sk-your-key-here
"""
env_file = os.path.join(os.path.dirname(__file__), "../.env.example")
with open(env_file, "w", encoding="utf-8") as f:
f.write(content)
print(f"已变量示例文件创建环境: {env_file}")
print("请复制为 .env 并填入实际的API Key")
def main():
print("=== LLM Hub 配置初始化 ===\n")
# 创建环境变量示例
create_env_example()
print("\n=== 下一步 ===")
print("1. 复制 .env.example 为 .env")
print("2. 填入各平台的API Key")
print("3. 运行 python scripts/check_quotas.py 查询额度")
if __name__ == "__main__":
main()
llm-hub/scripts/switch_provider.py
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#!/usr/bin/env python3
"""
切换供应商
"""
import os
import json
import sys
CONFIG_FILE = os.path.join(os.path.dirname(__file__), "../config/providers.json")
def load_config():
with open(CONFIG_FILE, "r", encoding="utf-8") as f:
return json.load(f)
def save_config(config):
with open(CONFIG_FILE, "w", encoding="utf-8") as f:
json.dump(config, f, indent=2, ensure_ascii=False)
def list_providers(config):
print("可用供应商:")
for p in config["providers"]:
status = "✓" if p["enabled"] else "✗"
current = " ← 当前" if p["name"] == config.get("current_provider") else ""
print(f" {status} {p['name']}{current}")
print(f" 模型: {', '.join(p['models'])}")
def switch_provider(target_name):
config = load_config()
# 查找目标供应商
target = None
for p in config["providers"]:
if p["name"] == target_name:
target = p
break
if not target:
print(f"错误: 未找到供应商 '{target_name}'")
return
if not target["enabled"]:
print(f"警告: 供应商 '{target_name}' 当前未启用")
config["current_provider"] = target_name
save_config(config)
print(f"已切换到供应商: {target_name}")
def main():
config = load_config()
if len(sys.argv) < 2:
list_providers(config)
print("\n用法:")
print(" python switch_provider.py list # 列出所有供应商")
print(" python switch_provider.py <provider> # 切换到指定供应商")
return
action = sys.argv[1]
if action == "list":
list_providers(config)
else:
switch_provider(action)
if __name__ == "__main__":
main()