Agent Skills
› NeverSight/learn-skills.dev
› ai-chat
ai-chat
GitHub通过AceDataCloud统一网关访问50+主流LLM模型（如GPT、Claude、Gemini等）。提供OpenAI兼容API，支持流式传输、函数调用及多模态功能，适用于各类对话与推理任务。
Trigger Scenarios
需要调用大语言模型进行对话生成
请求使用特定LLM模型（如GPT、Claude）
需要执行复杂推理或多模态任务
Install
npx skills add NeverSight/learn-skills.dev --skill ai-chat -g -y
SKILL.md
Frontmatter
{
"name": "ai-chat",
"license": "Apache-2.0",
"metadata": {
"author": "acedatacloud",
"version": "1.0"
},
"description": "Access 50+ LLM models through a unified OpenAI-compatible API via AceDataCloud. Use when you need chat completions from GPT, Claude, Gemini, Kimi, Grok, or other models through a single endpoint. Supports streaming, function calling, and vision.",
"compatibility": "Requires ACEDATACLOUD_API_TOKEN in .env file (see _shared\/authentication.md). 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.
Setup: See authentication for token setup.
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
| Model | Type | Best For |
|---|---|---|
gpt-4.1 |
Latest | General-purpose, high quality |
gpt-4.1-mini |
Small | Fast, cost-effective |
gpt-4.1-nano |
Tiny | Ultra-fast, lowest cost |
gpt-4o |
Multimodal | Vision + text |
gpt-4o-mini |
Small multimodal | Fast vision tasks |
o1 |
Reasoning | Complex reasoning tasks |
o1-mini |
Small reasoning | Quick reasoning |
o1-pro |
Pro reasoning | Advanced reasoning |
gpt-5 |
Latest gen | Next-gen intelligence |
gpt-5.4 |
Gen 5.4 | High-performance next-gen |
gpt-5-mini |
Mini gen 5 | Fast next-gen |
Anthropic Claude
| Model | Type | Best For |
|---|---|---|
claude-opus-4-8 |
Latest Opus | Highest capability |
claude-opus-4-6 |
Latest Opus | Highest capability |
claude-sonnet-4-6 |
Latest Sonnet | Balanced quality/speed |
claude-opus-4-5-20251101 |
Opus 4.5 | Premium tasks |
claude-sonnet-4-5-20250929 |
Sonnet 4.5 | High-quality balance |
claude-sonnet-4-20250514 |
Sonnet 4 | Reliable general-purpose |
claude-haiku-4-5-20251001 |
Haiku 4.5 | Fast, efficient |
claude-3-5-sonnet-20241022 |
Legacy 3.5 | Proven track record |
claude-3-opus-20240229 |
Legacy Opus | Maximum quality (legacy) |
Google Gemini
| Model | Best For |
|---|---|
gemini-1.5-pro |
Long context, complex tasks |
gemini-1.5-flash |
Fast, efficient |
xAI Grok
| Model | Best For |
|---|---|
grok-4 |
Latest, highest capability |
grok-3 |
General-purpose |
grok-3-fast |
Speed-optimized |
grok-3-mini |
Compact, 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
| Parameter | Type | Description |
|---|---|---|
model |
string | Model name (see tables above) |
messages |
array | Array of {role, content} objects |
temperature |
0–2 | Randomness (default: 1) |
top_p |
0–1 | Nucleus sampling |
max_tokens |
integer | Maximum output tokens |
stream |
boolean | Enable SSE streaming |
tools |
array | Function calling definitions |
tool_choice |
string/object | Tool 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.chunkobjects via SSE finish_reasonvalues:"stop"(complete),"length"(max tokens),"tool_calls"(function call),"content_filter"(filtered)
Stateful Conversations Endpoint
For stateful, session-based chat (no need to send the full history each time), use POST /aichat2/conversations (recommended). POST /aichat/conversations remains available for legacy compatibility.
curl -X POST https://api.acedata.cloud/aichat2/conversations \
-H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"model": "gpt-4.1", "question": "What is quantum computing?", "stateful": true}'
| Parameter | Type | Description |
|---|---|---|
model |
string | Model name (see Available Models above) |
question |
string | The prompt or question to answer |
id |
string | Conversation ID — pass the same ID to continue a session |
preset |
string | Preset/system prompt for the conversation |
stateful |
boolean | Enable stateful conversation (maintains history server-side) |
references |
array | Additional context documents to include |
Version History
- e0220ca Current 2026-07-05 22:52
