genai-hub-foundation-models
List and explore foundation models available in SAP AI Core GenAI Hub: browse supported providers, model names, versions, capabilities, and executable IDs needed to create deployments. WHEN: user wants to see what models are available, find an executable-id or model-name for deployment, browse providers (Azure OpenAI, Anthropic, Google, Mistral, Cohere, etc.), check model capabilities or context length, get the correct model-name to pass to createllmdeployment, or get curl inference examples for a deployed model (chat completions, Responses API, embeddings, image generation, etc.). DO NOT USE FOR: creating or managing deployments — use aicore-lifecycle-management.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/sap/ai-skills-library --skill genai-hub-foundation-models- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads genai-hub-foundation-models automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Rules
- Fetch the live model list when the model name is unknown or unconfirmed — skip if the user already named a specific model.
executable-idandmodel-namevalues from this skill are the inputs needed byaicore-lifecycle-managementto create a deployment.- If credentials are not configured, invoke
aicore-admin-resourcesfirst. - Before executing any curl example, get a Bearer token with:
Never add
export TOKEN=$(uv run skills/aicore-admin-resources/scripts/get_token.py)2>&1or pipe the command — that prints the raw JWT into the conversation.
List Available Models
# Show all options and examples:
uv run scripts/list_foundation_models.py --help
# One provider only (e.g. Azure OpenAI):
uv run scripts/list_foundation_models.py --executable-id azure-openai
# Detailed view (versions, capabilities, context length, streaming support):
uv run scripts/list_foundation_models.py --response-format detailed
# Machine-readable JSON for scripting:
uv run scripts/list_foundation_models.py --json | jq '.[].model'
uv run scripts/list_foundation_models.py --response-format detailed --json | jq '.[] | select(.model == "gpt-4o") | .versions'
# Models supported by the Orchestration service only:
uv run scripts/list_foundation_models.py --scenario-id orchestration
Provider → Executable ID Mapping
| Provider | --executable-id |
|---|---|
| Azure OpenAI | azure-openai |
| Anthropic | aws-bedrock |
gcp-vertexai | |
| Amazon Bedrock | aws-bedrock |
| Mistral AI | aicore-mistralai |
| Cohere | aicore-cohere |
| Perplexity | perplexity-ai |
| NVIDIA | aicore-nvidia |
| Open Source | aicore-opensource |
| SAP | aicore-sap |
Supported models in your instance may differ from this table — use the script to get the live list.
Create a Deployment
Once you have the executable-id and model-name, check whether a RUNNING deployment for that model already exists:
uv run skills/aicore-lifecycle-management/scripts/get_deployments.py \
--scenario foundation-models --status RUNNING --json
If one is found, use AskUserQuestion to ask whether to reuse it or create a new one. Then invoke aicore-lifecycle-management with both values.
The modelName value must exactly match the catalog output — a mismatch causes an "Invalid Configuration" error at deployment time, not at configuration creation.
When to Load Reference Files
| Trigger | Load |
|---|---|
| Curl inference examples, provider-specific endpoint paths, or about to call a deployed model | references/MODELS.md |
Finding the Deployment URL for a Curl Call
-
Get the
executable-id— look it up in the Provider → Executable ID table above. -
Find the running deployment:
uv run skills/aicore-lifecycle-management/scripts/get_deployments.py \ --scenario foundation-models --executable-id <executable-id> --status RUNNING --json # use .deployment_url and .resource_group from the matching entry -
See
references/MODELS.mdfor export setup and curl examples per provider.
Handoffs
- Credential/auth error? → invoke
aicore-admin-resources - Ready to create a deployment with the model you found? → invoke
aicore-lifecycle-management
FAQ
What does the genai-hub-foundation-models skill do?
List and explore foundation models available in SAP AI Core GenAI Hub: browse supported providers, model names, versions, capabilities, and executable IDs needed to create deployments. WHEN: user wants to see what models are available, find an executable-id or model-name for deployment, browse providers (Azure OpenAI, Anthropic, Google, Mistral, Cohere, etc.), check model capabilities or context length, get the correct model-name to pass to createllmdeployment, or get curl inference examples for a deployed model (chat completions, Responses API, embeddings, image generation, etc.). DO NOT USE FOR: creating or managing deployments — use aicore-lifecycle-management.
How do I install genai-hub-foundation-models?
Run npx skills add https://github.com/sap/ai-skills-library --skill genai-hub-foundation-models in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/genai-hub-foundation-models/ (personal) or .claude/skills/genai-hub-foundation-models/ (project).
Which AI agents can use genai-hub-foundation-models?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is genai-hub-foundation-models safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains genai-hub-foundation-models?
It is published by sap in sap/ai-skills-library. It has 87 recorded installs.
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