Add Siliconflow Provider 1

为 OpenClaw 配置硅基流动 (SiliconFlow) 作为模型源。SiliconFlow 是国内领先的 AI 模型推理平台，提供 98+ 个 chat 模型，包含多个免费模型（Qwen3-8B、DeepSeek-R1-8B 等）。使用标准 OpenAI 协议（openai-completions）。包含 provider 注册、模型定义、别名配置、fallback 链接入和验证的完整流程。当管理员说想"加硅基流动"、"配 SiliconFlow"、"接入 SF 模型"、"加 Kimi"、"加 Qwen3"、"加免费模型"、"接入 DeepSeek V3.2"时使用此 skill。

Security Scan

This is an instruction-only skill that coherently documents how to add SiliconFlow as an OpenClaw provider; it requests no unrelated credentials or installs, but it will ask the administrator to place an API key into OpenClaw config (so treat that secret carefully).

Purpose & Capability

The skill's name/description match its contents: a step-by-step guide to register a SiliconFlow provider, define models, add aliases, and validate an API key. Required binaries/env/configs declared are none, which fits an instruction-only guide. No unrelated services or credentials are requested.

Instruction Scope

Instructions explicitly tell the operator to back up and edit the OpenClaw config (~/.openclaw/openclaw.json), run a curl against SiliconFlow's API for key validation, and apply a gateway config.patch to add providers/models/aliases. All actions are within the scope of configuring a model provider, but the skill tells the admin to store the provider API key directly in the OpenClaw config — this is expected for provider registration but has security implications (see guidance).

Install Mechanism

No install spec or code files are included; the skill is purely documentation/instructions. This is the lowest-risk install posture.

Credentials

The skill declares no required environment variables or credentials, and does not attempt to access unrelated secrets. However, it instructs administrators to place a SiliconFlow API key (format sk-xxx) into OpenClaw's config JSON. Storing an API key in a plaintext config file may expose it to others with access to the host — this is proportional to the task but worth protecting.

Persistence & Privilege

The skill is not always-enabled and does not request autonomous privileges. It instructs modifying the OpenClaw configuration (provider/models/aliases), which is a normal administrative operation for this purpose and requires admin rights on the host — no elevated or unexpected platform-wide privileges are requested by the skill itself.

Assessment

This skill is a coherent how-to for adding SiliconFlow to OpenClaw. Before applying: 1) Verify you trust the SiliconFlow endpoints and the invite link; cross-check with official docs (links are provided in README/SKILL.md). 2) Backup and inspect the config backup before and after applying the patch (the SKILL.md shows a cp backup step). 3) Treat the SiliconFlow API key as a secret: avoid committing it to shared repos or exposing it in logs; if your deployment supports a secrets store or environment variable for provider credentials, prefer that over plaintext config. 4) Confirm the gateway config.patch operation is executed by an administrator and review the resulting ~/.openclaw/openclaw.json to ensure only the intended entries were added. 5) Note the skill source/homepage is unknown — if you need higher assurance, obtain the same steps directly from OpenClaw or SiliconFlow official docs rather than third-party instructions.

配置 SiliconFlow Provider（硅基流动模型推理平台）

SiliconFlow（硅基流动）是国内领先的 AI 模型推理平台，提供 98+ 个 chat 模型，涵盖 Qwen、DeepSeek、Kimi、GLM、MiniMax 等主流系列。

核心优势：

• 🆓 多个免费模型：Qwen3-8B、DeepSeek-R1-8B 等完全免费
• 💰 价格极低：旗舰模型价格仅为官方的 30-50%
• 🔌 OpenAI 兼容：标准 openai-completions 协议，即插即用
• 📦 模型丰富：一个 API Key 访问所有模型

如果还没有 SiliconFlow 账号，请通过邀请链接注册（双方均获赠额度）： 👉 https://cloud.siliconflow.cn/i/ihj5inat

项目	值
Provider 名称	siliconflow
API 协议	openai-completions
Base URL	https://api.siliconflow.cn/v1
认证方式	Bearer Token (API Key)

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前置条件

项目	说明
API Key	在 控制台 创建，格式 sk-xxx
余额	免费模型无需余额；付费模型需充值（新用户注册送 ¥14）

获取 API Key

1. 注册：https://cloud.siliconflow.cn/i/ihj5inat
2. 进入控制台 → API 密钥 → 创建
3. 复制 sk-xxx 格式的密钥

验证 API Key

curl -s 'https://api.siliconflow.cn/v1/user/info' \
  -H 'Authorization: Bearer <YOUR_API_KEY>' | python3 -m json.tool

期望返回 "status": "normal" 和余额信息。

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推荐模型

🆓 免费模型（无限使用）

模型 ID	说明	推荐别名
Qwen/Qwen3-8B	通义千问 3 代 8B，综合能力强	sf-qwen3-8b
deepseek-ai/DeepSeek-R1-0528-Qwen3-8B	DeepSeek R1 推理蒸馏版	sf-r1-8b
THUDM/glm-4-9b-chat	智谱 GLM-4 9B	sf-glm4
Qwen/Qwen2.5-7B-Instruct	Qwen 2.5 7B	sf-qwen25-7b
Qwen/Qwen2.5-Coder-7B-Instruct	Qwen 2.5 编码专用	sf-qwen-coder-7b

💰 性价比模型（便宜好用）

模型 ID	输入/输出 (¥/M tokens)	说明	推荐别名
Qwen/Qwen3-30B-A3B	0.7 / 2.8	MoE 架构，性价比极高	sf-qwen3-30b
Qwen/Qwen3-Coder-30B-A3B-Instruct	0.7 / 2.8	编码专用 30B	sf-coder-30b
deepseek-ai/DeepSeek-V3.2	2.0 / 3.0	DeepSeek 最新版	sf-dsv3
Pro/deepseek-ai/DeepSeek-V3.2	2.0 / 3.0	Pro 加速版	sf-dsv3-pro

🚀 旗舰模型（重要任务）

模型 ID	输入/输出 (¥/M tokens)	说明	推荐别名
deepseek-ai/DeepSeek-R1	4.0 / 16.0	推理模型	sf-r1
Pro/moonshotai/Kimi-K2.5	4.0 / 21.0	月之暗面最强模型	sf-kimi
Qwen/Qwen3-Coder-480B-A35B-Instruct	8.0 / 16.0	编码旗舰 480B MoE	sf-coder-480b

---

配置步骤

Step 1: 备份配置

cp ~/.openclaw/openclaw.json ~/.openclaw/openclaw.json.backup.$(date +%Y%m%d_%H%M%S)

Step 2: 添加 Provider

通过 gateway config.patch 添加 SiliconFlow provider。以下为推荐配置（8 个精选模型）：

{
  "models": {
    "providers": {
      "siliconflow": {
        "baseUrl": "https://api.siliconflow.cn/v1",
        "apiKey": "<YOUR_API_KEY>",
        "api": "openai-completions",
        "models": [
          {
            "id": "Qwen/Qwen3-8B",
            "name": "Qwen3 8B (Free)",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 32768,
            "maxTokens": 8192
          },
          {
            "id": "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
            "name": "DeepSeek R1 Qwen3 8B (Free)",
            "reasoning": true,
            "input": ["text"],
            "cost": {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 32768,
            "maxTokens": 8192
          },
          {
            "id": "Qwen/Qwen3-30B-A3B",
            "name": "Qwen3 30B MoE",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 0.7, "output": 2.8, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 32768,
            "maxTokens": 8192
          },
          {
            "id": "Qwen/Qwen3-Coder-30B-A3B-Instruct",
            "name": "Qwen3 Coder 30B",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 0.7, "output": 2.8, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 32768,
            "maxTokens": 8192
          },
          {
            "id": "deepseek-ai/DeepSeek-V3.2",
            "name": "DeepSeek V3.2",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 2.0, "output": 3.0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 128000,
            "maxTokens": 8192
          },
          {
            "id": "deepseek-ai/DeepSeek-R1",
            "name": "DeepSeek R1",
            "reasoning": true,
            "input": ["text"],
            "cost": {"input": 4.0, "output": 16.0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 128000,
            "maxTokens": 8192
          },
          {
            "id": "Pro/moonshotai/Kimi-K2.5",
            "name": "Kimi K2.5",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 4.0, "output": 21.0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 128000,
            "maxTokens": 8192
          },
          {
            "id": "Qwen/Qwen3-Coder-480B-A35B-Instruct",
            "name": "Qwen3 Coder 480B",
            "reasoning": false,
            "input": ["text"],
            "cost": {"input": 8.0, "output": 16.0, "cacheRead": 0, "cacheWrite": 0},
            "contextWindow": 32768,
            "maxTokens": 8192
          }
        ]
      }
    }
  }
}

Step 3: 添加别名

在同一个 patch 中添加别名映射：

{
  "agents": {
    "defaults": {
      "models": {
        "siliconflow/Qwen/Qwen3-8B": {"alias": "sf-qwen3-8b"},
        "siliconflow/deepseek-ai/DeepSeek-R1-0528-Qwen3-8B": {"alias": "sf-r1-8b"},
        "siliconflow/Qwen/Qwen3-30B-A3B": {"alias": "sf-qwen3-30b"},
        "siliconflow/Qwen/Qwen3-Coder-30B-A3B-Instruct": {"alias": "sf-coder-30b"},
        "siliconflow/deepseek-ai/DeepSeek-V3.2": {"alias": "sf-dsv3"},
        "siliconflow/deepseek-ai/DeepSeek-R1": {"alias": "sf-r1"},
        "siliconflow/Pro/moonshotai/Kimi-K2.5": {"alias": "sf-kimi"},
        "siliconflow/Qwen/Qwen3-Coder-480B-A35B-Instruct": {"alias": "sf-coder-480b"}
      }
    }
  }
}

⚠️ agents.defaults.models.<id> 只允许 alias 字段！ 其他字段会导致 Gateway 崩溃。

Step 4: 接入 Fallback 链

将免费模型加入 fallback 链作为兜底：

{
  "agents": {
    "defaults": {
      "model": {
        "fallbacks": [
          "...(现有 fallbacks)...",
          "siliconflow/Qwen/Qwen3-8B",
          "siliconflow/Qwen/Qwen3-30B-A3B"
        ]
      }
    }
  }
}

推荐 fallback 策略：优先放免费模型 (Qwen3-8B)，然后放便宜模型 (Qwen3-30B)。

Step 5: 验证

# 1. 配置校验
openclaw doctor

# 2. 重启生效
openclaw gateway restart

# 3. 确认状态
openclaw gateway status

# 4. 测试模型切换
# 在聊天中输入: /model sf-kimi

---

实用 API

查询余额

curl -s 'https://api.siliconflow.cn/v1/user/info' \
  -H 'Authorization: Bearer <API_KEY>' | python3 -c "
import json,sys; d=json.load(sys.stdin)['data']
print(f'充值余额: ¥{d[\"chargeBalance\"]}')
print(f'赠送余额: ¥{d[\"balance\"]}')
print(f'总余额: ¥{d[\"totalBalance\"]}')
"

查看可用模型

# 所有 chat 模型
curl -s 'https://api.siliconflow.cn/v1/models?sub_type=chat' \
  -H 'Authorization: Bearer <API_KEY>' | python3 -c "
import json,sys
models = json.load(sys.stdin)['data']
print(f'共 {len(models)} 个 chat 模型')
for m in sorted(models, key=lambda x: x['id']):
    print(f'  {m[\"id\"]}')
"

测试模型

curl -s 'https://api.siliconflow.cn/v1/chat/completions' \
  -H 'Authorization: Bearer <API_KEY>' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "Qwen/Qwen3-8B",
    "messages": [{"role":"user","content":"说OK"}],
    "max_tokens": 5
  }'

---

添加更多模型

SiliconFlow 有 98+ 个 chat 模型。如需添加更多，先用模型列表 API 查询可用模型，然后按 Step 2 的格式添加到 provider 的 models 数组中。

热门模型速查

模型	输入/输出 (¥/M tokens)	特点
zai-org/GLM-4.6	3.5 / 14.0	智谱最新旗舰
Pro/deepseek-ai/DeepSeek-R1	4.0 / 16.0	Pro 加速推理
moonshotai/Kimi-K2-Thinking	4.0 / 16.0	Kimi 思考模型
Qwen/Qwen3-235B-A22B-Instruct-2507	2.5 / 10.0	Qwen3 指令模型
baidu/ERNIE-4.5-300B-A47B	2.0 / 8.0	百度文心
stepfun-ai/step3	4.0 / 10.0	阶跃星辰 Step3

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注意事项

1. 免费模型有 QPS 限制：免费模型的并发数可能受限，适合 fallback 和低频任务
2. Pro 版本 vs 普通版本：Pro/ 前缀的模型使用专用推理集群，速度更快但价格略高
3. 模型 ID 区分大小写：必须严格匹配，如 Qwen/Qwen3-8B 不能写成 qwen/qwen3-8b
4. cost 字段单位：¥/百万 tokens (1M tokens)

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注册链接：https://cloud.siliconflow.cn/i/ihj5inat （邀请注册双方均获赠额度）