aiconfig-create

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Create AI Config

创建AI Config

You're using a skill that will guide you through setting up AI configuration in your application. Your job is to explore the codebase to understand the use case and stack, choose agent vs completion mode, create the config following the right path, and verify it works.

你正在使用一个能引导你在应用中设置AI配置的skill。你的任务是探索代码库以了解使用场景和技术栈，选择Agent模式或Completion模式，遵循正确流程创建配置，并验证其是否可用。

Prerequisites

前提条件

LaunchDarkly API access token with
```
ai-configs:write
```
permission or MCP server
LaunchDarkly project (use
```
aiconfig-projects
```
skill if needed)

拥有
```
ai-configs:write
```
权限的LaunchDarkly API访问令牌，或MCP服务器
LaunchDarkly项目（如有需要，使用
```
aiconfig-projects
```
skill）

Core Principles

核心原则

Understand the Use Case First: Know what you're building before choosing a mode
Choose the Right Mode: Agent mode vs completion mode depends on your framework and needs
Two-Step Creation: Create config first, then create variations (model, prompts, parameters)
Verify via API: The agent fetches the config to confirm it was created correctly

先理解使用场景：在选择模式前，明确你要构建的内容
选择合适的模式：Agent模式与Completion模式的选择取决于你的框架和需求
两步创建法：先创建配置，再创建变体（模型、提示词、参数）
通过API验证：Agent会获取配置以确认其已正确创建

API Key Detection

API密钥检测

Check environment variables —

LAUNCHDARKLY_API_KEY

LAUNCHDARKLY_API_TOKEN

LD_API_KEY

Check MCP config — Claude:

~/.claude/config.json

→

mcpServers.launchdarkly.env.LAUNCHDARKLY_API_KEY

Prompt user — Only if detection fails

检查环境变量 —

LAUNCHDARKLY_API_KEY

、

LAUNCHDARKLY_API_TOKEN

、

LD_API_KEY

检查MCP配置 — Claude:

~/.claude/config.json

→

mcpServers.launchdarkly.env.LAUNCHDARKLY_API_KEY

提示用户 — 仅当检测失败时执行

Workflow

工作流程

Step 1: Understand Your Use Case

步骤1：理解你的使用场景

Before creating, identify what you're building:

What framework? LangGraph, LangChain, CrewAI, OpenAI SDK, Anthropic SDK, custom
What does the AI need? Just text, or tools/function calling?
Agent or completion? See decision below

创建前，明确你要构建的内容：

使用什么框架？ LangGraph、LangChain、CrewAI、OpenAI SDK、Anthropic SDK、自定义框架
AI需要实现什么功能？ 仅生成文本，还是需要工具/函数调用？
选择Agent模式还是Completion模式？ 参考下方决策指南

Step 2: Choose Agent vs Completion Mode

步骤2：选择Agent模式与Completion模式

Your Need	Mode
Persistent instructions across interactions	Agent
LangGraph, CrewAI, AutoGen	Agent
Direct OpenAI/Anthropic API calls	Completion
Full control of message structure	Completion
One-off text generation	Completion

Both modes support tools. Agent mode: single

instructions

string. Completion mode: full

messages

array.

你的需求	模式
交互过程中保留持久化指令	Agent
使用LangGraph、CrewAI、AutoGen	Agent
直接调用OpenAI/Anthropic API	Completion
完全控制消息结构	Completion
一次性文本生成	Completion

两种模式均支持工具调用。Agent模式：使用单个

instructions

字符串；Completion模式：使用完整的

messages

数组。

Step 3: Create the Config

步骤3：创建配置

Follow API Quick Start for curl examples:

Create config —
```
POST /projects/{projectKey}/ai-configs
```
(key, name, mode)
Create variation —
```
POST /projects/{projectKey}/ai-configs/{configKey}/variations
```
(instructions or messages, modelConfigKey, model.parameters)
Attach tools — After creation, PATCH variation to add tools (see
```
aiconfig-tools
```
skill)

参考API快速入门中的curl示例：

创建配置 —
```
POST /projects/{projectKey}/ai-configs
```
（参数包括key、name、mode）
创建变体 —
```
POST /projects/{projectKey}/ai-configs/{configKey}/variations
```
（参数包括instructions或messages、modelConfigKey、model.parameters）
关联工具 — 创建完成后，通过PATCH请求为变体关联工具（参考
```
aiconfig-tools
```
skill）

Step 4: Verify

步骤4：验证

After creation, verify the config:

Fetch via API:

bash

curl -X GET "https://app.launchdarkly.com/api/v2/projects/{projectKey}/ai-configs/{configKey}" \
  -H "Authorization: {api_token}" -H "LD-API-Version: beta"

Confirm:
- Config exists with correct mode
- Variations have model names (not "NO MODEL")
- modelConfigKey is set
- Parameters are present
Report results:
- ✓ Config created with correct structure
- ✓ Variations have models assigned
- ⚠️ Flag any missing model or parameters
- Provide config URL:
```
https://app.launchdarkly.com/projects/{projectKey}/ai-configs/{configKey}
```

创建完成后，验证配置：

通过API获取配置：