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acedatacloud-ai-chatacedatacloudAI 聊天

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

4,480

周安装

183

GitHub Stars

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下载量

1,435
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:acedatacloud-ai-chat(acedatacloudAI 聊天)
来源仓库:https://github.com/germey/acedatacloud-ai-chat
安装命令:
openclaw skills install acedatacloud-ai-chat
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 acedatacloud-ai-chat

简介

通过 AceDataCloud 通过统一的 OpenAI 兼容 API 访问 50 多个 LLM 模型。当您需要 GPT、Claude、Gemini、DeepSeek、Grok 等聊天补全时使用

SKILL.md

name
ai-chat
description
Access 50+ LLM models through a unified OpenAI-compatible API via AceDataCloud. Use when you need chat completions from GPT, Claude, Gemini, DeepSeek, Grok, or other models through a single endpoint. Supports streaming, function calling, and vision.
license
Apache-2.0
metadata
author
acedatacloud
version
1.0
compatibility
Requires ACEDATACLOUD_API_TOKEN environment variable. Works as a drop-in replacement for the OpenAI SDK.

AI Chat — Unified LLM Gateway

Access 50+ language models through a single OpenAI-compatible endpoint via AceDataCloud.

Authentication

export ACEDATACLOUD_API_TOKEN="your-token-here"

Quick Start

curl -X POST https://api.acedata.cloud/v1/chat/completions \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model": "claude-sonnet-4-20250514", "messages": [{"role": "user", "content": "Hello!"}]}'

OpenAI SDK Drop-in

from openai import OpenAI

client = OpenAI(
    api_key="your-token-here",
    base_url="https://api.acedata.cloud/v1"
)

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)
print(response.choices[0].message.content)

Available Models

OpenAI GPT

ModelTypeBest For
gpt-4.1LatestGeneral-purpose, high quality
gpt-4.1-miniSmallFast, cost-effective
gpt-4.1-nanoTinyUltra-fast, lowest cost
gpt-4oMultimodalVision + text
gpt-4o-miniSmall multimodalFast vision tasks
o1ReasoningComplex reasoning tasks
o1-miniSmall reasoningQuick reasoning
o1-proPro reasoningAdvanced reasoning
gpt-5Latest genNext-gen intelligence
gpt-5-miniMini gen 5Fast next-gen

Anthropic Claude

ModelTypeBest For
claude-opus-4-6Latest OpusHighest capability
claude-sonnet-4-6Latest SonnetBalanced quality/speed
claude-opus-4-5-20251101Opus 4.5Premium tasks
claude-sonnet-4-5-20250929Sonnet 4.5High-quality balance
claude-sonnet-4-20250514Sonnet 4Reliable general-purpose
claude-haiku-4-5-20251001Haiku 4.5Fast, efficient
claude-3-5-sonnet-20241022Legacy 3.5Proven track record
claude-3-opus-20240229Legacy OpusMaximum quality (legacy)

Google Gemini

ModelBest For
gemini-1.5-proLong context, complex tasks
gemini-1.5-flashFast, efficient

DeepSeek

ModelBest For
deepseek-r1Deep reasoning
deepseek-r1-0528Latest reasoning
deepseek-v3General-purpose
deepseek-v3-250324Latest general

xAI Grok

ModelBest For
grok-4Latest, highest capability
grok-3General-purpose
grok-3-fastSpeed-optimized
grok-3-miniCompact, efficient

Features

Streaming

POST /v1/chat/completions
{
  "model": "claude-sonnet-4-20250514",
  "messages": [{"role": "user", "content": "Write a story"}],
  "stream": true
}

Function Calling

POST /v1/chat/completions
{
  "model": "gpt-4.1",
  "messages": [{"role": "user", "content": "What's the weather in Tokyo?"}],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "parameters": {"type": "object", "properties": {"location": {"type": "string"}}}
      }
    }
  ]
}

Vision

POST /v1/chat/completions
{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": [
        {"type": "text", "text": "What's in this image?"},
        {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
      ]
    }
  ]
}

Parameters

ParameterTypeDescription
modelstringModel name (see tables above)
messagesarrayArray of {role, content} objects
temperature0–2Randomness (default: 1)
top_p0–1Nucleus sampling
max_tokensintegerMaximum output tokens
streambooleanEnable SSE streaming
toolsarrayFunction calling definitions
tool_choicestring/objectTool selection strategy

Response

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "model": "claude-sonnet-4-20250514",
  "choices": [
    {
      "index": 0,
      "message": {"role": "assistant", "content": "Hello!"},
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 10,
    "completion_tokens": 5,
    "total_tokens": 15
  }
}

Gotchas

  • 100% OpenAI-compatible — use the standard OpenAI SDK with base_url="https://api.acedata.cloud/v1"
  • Billing is token-based with per-model pricing (more expensive models cost more per token)
  • Vision is supported on multimodal models (gpt-4o, gpt-4o-mini, grok-2-vision-*)
  • Function calling works on most modern models (GPT-4+, Claude 3+)
  • Streaming returns chat.completion.chunk objects via SSE
  • finish_reason values: "stop" (complete), "length" (max tokens), "tool_calls" (function call), "content_filter" (filtered)

适合场景

01

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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

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能力 2

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能力 5

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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

96.07%
按下载量换算1,379

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敏感数据

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安装前确认

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来源信息

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