aicore-lifecycle-management

规则

1. 所有脚本都必须从技能根目录运行，并使用 uv run scripts/<name>.py。
2. 切勿打印或记录凭证值——SDK 会从环境中读取这些值。
3. 删除或修改状态的脚本需要使用 --confirm。务必显式传入；切勿绕过此要求。
4. 用户未指定资源组时，省略 --resource-group，以便 SDK 使用其配置的默认值。
5. 对于大模型部署：场景 ID、可执行文件 ID 和模型参数名称来自 genai-hub-foundation-models——如果这些值未知，请先调用它。
6. 部署配置命名约定：大模型部署使用 {executable_id}--{model_name}（例如 azure-openai--gpt-4o-mini）。创建配置前，使用 get_configurations.py --scenario-id <id> 检查是否已存在同名配置，并重复使用该配置以避免重复创建。

---

列出 / 检查场景

# List all scenarios
uv run scripts/get_scenarios.py

# Inspect a specific scenario and its versions
uv run scripts/get_scenarios.py --scenario-id <id>
uv run scripts/get_scenarios.py --scenario-id <id> --response-format detailed

# JSON output for piping
uv run scripts/get_scenarios.py --json

---

列出可执行文件

# List executables for a scenario
uv run scripts/get_executables.py --scenario-id <id>

# Inspect a specific executable (includes parameters and input artifacts)
uv run scripts/get_executables.py --scenario-id <id> --executable-id <id>
uv run scripts/get_executables.py --scenario-id <id> --executable-id <id> --response-format detailed

# JSON output
uv run scripts/get_executables.py --scenario-id <id> --json

只有检查单个可执行文件（--executable-id）时才会返回参数。列表视图仅返回 ID、名称和描述。

---

配置

# List configurations
uv run scripts/get_configurations.py
uv run scripts/get_configurations.py --scenario-id <id>
uv run scripts/get_configurations.py --response-format detailed
uv run scripts/get_configurations.py --json

# Inspect a specific configuration
uv run scripts/get_configurations.py --configuration-id <id>

# Create a configuration (binds parameters to an executable)
uv run scripts/create_configuration.py \
  --name my-config \
  --scenario-id <id> \
  --executable-id <id> \
  --param modelName=gpt-4o \
  --param temperature=0.7

如果部署失败，或在几分钟后仍处于 PENDING 状态，请根据可执行文件声明的参数检查参数名称和值：

uv run scripts/get_executables.py --scenario-id <id> --executable-id <id> --response-format detailed

---

部署

部署用于提供推理端点。标准流程是：创建（或重复使用）配置，然后根据该配置创建部署。

配置命名约定

创建配置前，务必检查是否已存在匹配的配置，以避免重复创建：

# Check existing configurations before creating
uv run scripts/get_configurations.py --scenario-id <scenario-id> --json | jq '.[] | select(.name == "<expected-name>")'

命名约定：

• 大模型：{executable_id}--{model_name} — 例如 azure-openai--gpt-4o-mini
• 编排：orchestration
• 自定义：选择一个描述性名称

大模型部署（来自 genai-hub-foundation-models 的交接信息）

# 1. Create configuration (skip if one with this name already exists):
uv run scripts/create_configuration.py \
  --name azure-openai--gpt-4o-mini \
  --scenario-id foundation-models \
  --executable-id azure-openai \
  --param modelName=gpt-4o-mini \
  --param modelVersion=latest

# 2. Deploy:
uv run scripts/create_deployment.py --configuration-id <config-id> --wait

编排部署

# 1. Create configuration (skip if "orchestration" config already exists):
uv run scripts/create_configuration.py \
  --name orchestration \
  --scenario-id orchestration \
  --executable-id orchestration

# 2. Deploy:
uv run scripts/create_deployment.py --configuration-id <config-id> --wait --timeout 600

列出和检查部署

# List all deployments
uv run scripts/get_deployments.py

# Filter by status or scenario or executable
uv run scripts/get_deployments.py --status RUNNING
uv run scripts/get_deployments.py --scenario orchestration
uv run scripts/get_deployments.py --executable-id azure-openai --status RUNNING
uv run scripts/get_deployments.py --executable-id azure-openai --status RUNNING --json

# Inspect one deployment
uv run scripts/get_deployments.py --deployment-id <id>
uv run scripts/get_deployments.py --deployment-id <id> --response-format detailed
uv run scripts/get_deployments.py --deployment-id <id> --json

停止、修补、删除、查看日志

# Stop a deployment
uv run scripts/stop_deployment.py --deployment-id <id> --confirm
uv run scripts/stop_deployment.py --deployment-id <id> --confirm --wait

# Patch (swap configuration on a running deployment)
uv run scripts/patch_deployment.py --deployment-id <id> --configuration-id <new-config-id>

# Delete (must be STOPPED or DEAD first)
uv run scripts/delete_deployment.py --deployment-id <id> --confirm
# Stop and delete in one step:
uv run scripts/delete_deployment.py --deployment-id <id> --confirm --auto-stop

# Deployment logs
uv run scripts/get_deployment_logs.py --deployment-id <id>
uv run scripts/get_deployment_logs.py --deployment-id <id> --tail 50
uv run scripts/get_deployment_logs.py --deployment-id <id> --order asc
uv run scripts/get_deployment_logs.py --deployment-id <id> --json

# Remove duplicate LLM deployments (only affects LLM deployments with a model name)
uv run scripts/dedup_deployments.py --dry-run
uv run scripts/dedup_deployments.py

---

交接

• 需要 Bearer 令牌或凭证设置？ → 调用 aicore-admin-resources
• 需要可执行文件 ID、模型名称或模型能力？ → 调用 genai-hub-foundation-models
• 想列出可用模型或提供商？ → 调用 genai-hub-foundation-models