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sber-gigachatsber 千兆聊天室

Agent Skill

sber-gigachat 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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周安装

471

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下载量

3,693
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:sber-gigachat(sber 千兆聊天室)
来源仓库:https://github.com/smvlx/sber-gigachat
安装命令:
openclaw skills install sber-gigachat
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install sber-gigachat

简介

通过 gpt2giga 代理将 GigaChat (Sber AI) 与 OpenClaw 集成

SKILL.md

name
gigachat
description
Integrate GigaChat (Sber AI) with OpenClaw via gpt2giga proxy
version
1.2.0
metadata
{"openclaw":{"emoji":"🤖","homepage":"https://github.com/smvlx/openclaw-ru-skills","os":["darwin","linux"],"requires":{"bins":["python3","curl"],"env":["GIGACHAT_CREDENTIALS","GIGACHAT_SCOPE"]},"primaryEnv":"GIGACHAT_CREDENTIALS","configPaths":["~/.openclaw/gigachat-new.env","~/.openclaw/openclaw.json"],"install":[{"type":"uv","package":"gpt2giga"}]}}

GigaChat Skill

Integrate GigaChat (Sber AI) with OpenClaw via gpt2giga proxy.

Features

  • Three models: GigaChat, GigaChat-Pro, GigaChat-Max
  • OpenAI API compatibility via gpt2giga proxy
  • Automatic token management (gpt2giga handles OAuth internally)
  • Credentials passed via environment variables only (never on CLI)

Prerequisites

  1. GigaChat API Access:

- Register at https://developers.sber.ru/ - Create a GigaChat API application - Note your Client ID and Client Secret - Choose scope: GIGACHAT_API_PERS (free tier) or GIGACHAT_API_CORP (paid)

  1. Python & gpt2giga:
   pip3 install gpt2giga
  1. Environment File:

Create ~/.openclaw/gigachat-new.env:

   CLIENT_ID="your-client-id-here"
   CLIENT_SECRET="your-client-secret-here"

   # Auto-generate credentials (base64 of CLIENT_ID:CLIENT_SECRET)
   GIGACHAT_CREDENTIALS=$(echo -n "$CLIENT_ID:$CLIENT_SECRET" | base64)
   GIGACHAT_SCOPE="GIGACHAT_API_PERS"

Quick Start

1. Start the proxy

/openclaw/skills/gigachat/scripts/start-proxy.sh

Output:

Starting gpt2giga proxy on port 8443...
✅ gpt2giga started successfully (PID: 12345)
   Log: ~/.openclaw/gpt2giga.log
   Endpoint: http://localhost:8443/v1/chat/completions

gpt2giga handles OAuth token generation and refresh internally using the GIGACHAT_CREDENTIALS environment variable.

2. Configure OpenClaw

Run the patch script (backs up your config first):

/openclaw/skills/gigachat/scripts/patch-config.sh

Or add manually to openclaw.json:

{
  "models": {
    "providers": {
      "gigachat": {
        "baseUrl": "http://127.0.0.1:8443",
        "apiKey": "not-needed",
        "api": "openai-completions",
        "models": [
          {
            "id": "GigaChat-Max",
            "name": "GigaChat MAX",
            "contextWindow": 32768,
            "maxTokens": 8192
          },
          {
            "id": "GigaChat-Pro",
            "name": "GigaChat Pro",
            "contextWindow": 32768,
            "maxTokens": 4096
          },
          {
            "id": "GigaChat",
            "name": "GigaChat Lite",
            "contextWindow": 8192,
            "maxTokens": 2048
          }
        ]
      }
    }
  }
}

3. Test

curl -s -X POST http://localhost:8443/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "GigaChat-Max",
    "messages": [{"role": "user", "content": "Привет!"}]
  }' | jq -r '.choices[0].message.content'

Expected output:

Привет! Как дела?

Creating an Agent

Add a GigaChat-powered agent to openclaw.json:

{
  "agents": {
    "list": [
      {
        "id": "ruslan",
        "name": "Ruslan",
        "emoji": "🐻",
        "model": "gigachat/GigaChat-Pro",
        "workspace": "/root/.openclaw/agents/ruslan/workspace"
      }
    ]
  }
}

Create agent workspace:

mkdir -p /root/.openclaw/agents/ruslan/workspace

IDENTITY.md:

# IDENTITY.md

- Name: Ruslan
- Creature: Российский AI-ассистент
- Vibe: Дружелюбный, знает русский контекст
- Emoji: 🐻

SOUL.md:

# SOUL.md — Кто ты

Ты Руслан. Российский AI-ассистент на базе GigaChat.

Говоришь на русском, знаешь русский контекст (кухня, культура, реалии).
Отвечаешь кратко и по делу. Без лишней вежливости.

Token Management

gpt2giga handles OAuth token generation and refresh automatically using the GIGACHAT_CREDENTIALS environment variable. No manual token management is needed.

If the proxy loses its token (e.g. after a long idle period), restart it:

/openclaw/skills/gigachat/scripts/start-proxy.sh

Troubleshooting

Issue: 401 Unauthorized

Cause: Token expired or invalid credentials Fix: Restart proxy script (generates fresh token)

Issue: 402 Payment Required

Cause: Quota exhausted for that model Fix: Try a different model or wait for quota reset

  • Free tier: Limits per model
  • Strategy: Rotate between Max → Pro → Lite

Issue: Process defunct / zombie

Cause: gpt2giga crashes but holds port Fix:

fuser -k 8443/tcp
/openclaw/skills/gigachat/scripts/start-proxy.sh

Architecture

OpenClaw → http://localhost:8443/v1/chat/completions
           ↓
       gpt2giga (proxy, env-var auth)
           ↓
   Sber GigaChat API (OAuth token auto-managed)

Flow:

  1. Startup script exports credentials as environment variables
  2. gpt2giga starts and handles OAuth token generation internally
  3. OpenClaw sends OpenAI-format requests to localhost:8443
  4. gpt2giga translates to GigaChat format and manages auth
  5. Responses translated back to OpenAI format

Files

  • scripts/start-proxy.sh — Start proxy with env-var credentials
  • scripts/start.sh — Alternative start (nohup)
  • scripts/stop.sh — Stop proxy
  • scripts/status.sh — Check proxy status
  • scripts/setup.sh — Install gpt2giga from PyPI
  • scripts/patch-config.sh — Add GigaChat provider to openclaw.json (backs up config first)
  • SKILL.md — This file

Limitations

  • Free Tier Quotas: Limited tokens per model
  • SSL Verification: Disabled by default due to Sber's custom CA; install Sber root CA to /etc/ssl/certs/sber-ca.crt to enable
  • Credentials: Passed via environment variables only (never on the command line); protect ~/.openclaw/gigachat-new.env with chmod 600

References

  • GigaChat Docs: https://developers.sber.ru/docs/ru/gigachat/overview
  • gpt2giga: https://pypi.org/project/gpt2giga/
  • OpenClaw: https://openclaw.ai

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

74.64%
按下载量换算2,756

安全审计

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可疑

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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