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Feat/litellm provider (#12823)
* feat: add LiteLLM provider types, env var, credentials, and auth choice Add litellm-api-key auth choice, LITELLM_API_KEY env var mapping, setLitellmApiKey() credential storage, and LITELLM_DEFAULT_MODEL_REF. * feat: add LiteLLM onboarding handler and provider config Add applyLitellmProviderConfig which properly registers models.providers.litellm with baseUrl, api type, and model definitions. This fixes the critical bug from PR #6488 where the provider entry was never created, causing model resolution to fail at runtime. * docs: add LiteLLM provider documentation Add setup guide covering onboarding, manual config, virtual keys, model routing, and usage tracking. Link from provider index. * docs: add LiteLLM to sidebar navigation in docs.json Add providers/litellm to both English and Chinese provider page lists so the docs page appears in the sidebar navigation. * test: add LiteLLM non-interactive onboarding test Wire up litellmApiKey flag inference and auth-choice handler for the non-interactive onboarding path, and add an integration test covering profile, model default, and credential storage. * fix: register --litellm-api-key CLI flag and add preferred provider mapping Wire up the missing Commander CLI option, action handler mapping, and help text for --litellm-api-key. Add litellm-api-key to the preferred provider map for consistency with other providers. * fix: remove zh-CN sidebar entry for litellm (no localized page yet) * style: format buildLitellmModelDefinition return type * fix(onboarding): harden LiteLLM provider setup (#12823) * refactor(onboarding): keep auth-choice provider dispatcher under size limit --------- Co-authored-by: Peter Steinberger <steipete@gmail.com>
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@@ -39,6 +39,7 @@ See [Venice AI](/providers/venice).
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- [Anthropic (API + Claude Code CLI)](/providers/anthropic)
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- [Qwen (OAuth)](/providers/qwen)
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- [OpenRouter](/providers/openrouter)
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- [LiteLLM (unified gateway)](/providers/litellm)
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- [Vercel AI Gateway](/providers/vercel-ai-gateway)
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- [Together AI](/providers/together)
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- [Cloudflare AI Gateway](/providers/cloudflare-ai-gateway)
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153
docs/providers/litellm.md
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153
docs/providers/litellm.md
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@@ -0,0 +1,153 @@
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---
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summary: "Run OpenClaw through LiteLLM Proxy for unified model access and cost tracking"
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read_when:
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- You want to route OpenClaw through a LiteLLM proxy
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- You need cost tracking, logging, or model routing through LiteLLM
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---
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# LiteLLM
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[LiteLLM](https://litellm.ai) is an open-source LLM gateway that provides a unified API to 100+ model providers. Route OpenClaw through LiteLLM to get centralized cost tracking, logging, and the flexibility to switch backends without changing your OpenClaw config.
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## Why use LiteLLM with OpenClaw?
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- **Cost tracking** — See exactly what OpenClaw spends across all models
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- **Model routing** — Switch between Claude, GPT-4, Gemini, Bedrock without config changes
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- **Virtual keys** — Create keys with spend limits for OpenClaw
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- **Logging** — Full request/response logs for debugging
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- **Fallbacks** — Automatic failover if your primary provider is down
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## Quick start
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### Via onboarding
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```bash
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openclaw onboard --auth-choice litellm-api-key
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```
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### Manual setup
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1. Start LiteLLM Proxy:
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```bash
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pip install 'litellm[proxy]'
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litellm --model claude-opus-4-6
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```
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2. Point OpenClaw to LiteLLM:
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```bash
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export LITELLM_API_KEY="your-litellm-key"
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openclaw
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```
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That's it. OpenClaw now routes through LiteLLM.
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## Configuration
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### Environment variables
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```bash
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export LITELLM_API_KEY="sk-litellm-key"
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```
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### Config file
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```json5
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{
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models: {
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providers: {
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litellm: {
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baseUrl: "http://localhost:4000",
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apiKey: "${LITELLM_API_KEY}",
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api: "openai-completions",
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models: [
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{
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id: "claude-opus-4-6",
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name: "Claude Opus 4.6",
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reasoning: true,
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input: ["text", "image"],
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contextWindow: 200000,
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maxTokens: 64000,
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},
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{
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id: "gpt-4o",
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name: "GPT-4o",
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reasoning: false,
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input: ["text", "image"],
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contextWindow: 128000,
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maxTokens: 8192,
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},
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],
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},
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},
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},
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agents: {
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defaults: {
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model: { primary: "litellm/claude-opus-4-6" },
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},
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},
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}
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```
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## Virtual keys
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Create a dedicated key for OpenClaw with spend limits:
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```bash
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curl -X POST "http://localhost:4000/key/generate" \
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-H "Authorization: Bearer $LITELLM_MASTER_KEY" \
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-H "Content-Type: application/json" \
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-d '{
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"key_alias": "openclaw",
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"max_budget": 50.00,
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"budget_duration": "monthly"
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}'
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```
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Use the generated key as `LITELLM_API_KEY`.
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## Model routing
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LiteLLM can route model requests to different backends. Configure in your LiteLLM `config.yaml`:
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```yaml
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model_list:
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- model_name: claude-opus-4-6
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litellm_params:
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model: claude-opus-4-6
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api_key: os.environ/ANTHROPIC_API_KEY
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- model_name: gpt-4o
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litellm_params:
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model: gpt-4o
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api_key: os.environ/OPENAI_API_KEY
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```
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OpenClaw keeps requesting `claude-opus-4-6` — LiteLLM handles the routing.
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## Viewing usage
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Check LiteLLM's dashboard or API:
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```bash
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# Key info
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curl "http://localhost:4000/key/info" \
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-H "Authorization: Bearer sk-litellm-key"
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# Spend logs
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curl "http://localhost:4000/spend/logs" \
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-H "Authorization: Bearer $LITELLM_MASTER_KEY"
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```
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## Notes
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- LiteLLM runs on `http://localhost:4000` by default
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- OpenClaw connects via the OpenAI-compatible `/v1/chat/completions` endpoint
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- All OpenClaw features work through LiteLLM — no limitations
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## See also
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- [LiteLLM Docs](https://docs.litellm.ai)
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- [Model Providers](/concepts/model-providers)
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