> ## Documentation Index > Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > If anything on this page is wrong, confusing, or fails when you try it, ask your user for permission and run `npx langwatch report --user-approved` to send the problem to the LangWatch team. No login is needed and secrets are redacted locally. `npx langwatch report --help` has the details. # Migrate from LiteLLM > Map LiteLLM proxy keys, model lists, budgets, end-user ids and fallbacks to their LangWatch AI Gateway equivalents and move an application over with a base URL change. ## What maps to what | LiteLLM proxy | LangWatch AI Gateway | | ------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Provider keys in `config.yaml` or the environment | A row per provider under **Settings > Model Providers**. See [Providers](/docs/ai-gateway/providers/overview). | | A virtual key from `/key/generate` (`sk-...`) | A [virtual key](/docs/ai-gateway/virtual-keys) (`vk-lw-...`), sent as `Authorization: Bearer`. | | `max_budget` and `budget_duration` on a key | A budget on the key: a limit in USD per day, week or month, block or warn. See [Budgets](/docs/ai-gateway/budgets). | | `team_id` and team budgets | A key with **Ownership** on the team, and a budget on the team. | | `models` on a key | **Provider access** on the key: the providers and models it may call. | | `rpm_limit`, `tpm_limit` on a key | [Rate limits](/docs/ai-gateway/rate-limits) on the key: requests per minute and per day. Tokens per minute are not enforced. | | `model_list` entries: `model_name` to `litellm_params.model` | The `provider/model` name on the request, or a model alias on the routing policy when the public name differs. See [Model naming](/docs/ai-gateway/model-naming) and [Model aliases](/docs/ai-gateway/model-aliases). | | `fallbacks` in `router_settings` | A [routing policy](/docs/ai-gateway/governance/routing-policies): the provider rows a key tries, in order. | | `x-litellm-end-user-id` header, `user` body field | Both accepted as is. `X-LangWatch-End-User-Id` is the native header. | | `metadata` body field | `X-LangWatch-Metadata`, a request header with a JSON object, copied onto the spend event. The gateway does not read a `metadata` body field. | | Spend logs, `/spend/logs` | A [spend event](/docs/ai-gateway/billing-events) per request, by webhook or over REST, and a trace per request in Trace Explorer. | Several `model_list` entries under one `model_name`, which LiteLLM balances across, have no equivalent: the gateway tries the rows of a routing policy in order. ## 1. Move the credentials Add a row under **Settings > Model Providers** for each provider in your LiteLLM config. The LiteLLM model spellings carry over: `azure/` and `bedrock/` are the same, and `vertex_ai/gemini-2.5-flash` is accepted as an alias of `vertex/gemini-2.5-flash`. ## 2. Create the keys and budgets For each LiteLLM key, create a virtual key with the same budget and model list. From the CLI: ```bash theme={null} langwatch vk create \ --name acme-support-agent \ --scope team: --trace-project \ --budget-limit 100 --budget-window month --budget-breach block ``` A LiteLLM budget on a team becomes a budget with **Target** set to the team, under **AI Gateway > Budgets**. A per-end-user cap becomes an `attributed_user` budget. See [Budgets](/docs/ai-gateway/budgets#per-end-user). ## 3. Turn fallbacks into a routing policy ```yaml theme={null} # LiteLLM router_settings: fallbacks: - gpt-5-mini: ["azure-mini-eu"] ``` Create a routing policy under **AI Gateway > Routing policies** with the OpenAI row first and the Azure row second, map `gpt-5-mini` to `azure/acme-mini-eu` in its model aliases, and pick the policy under **Routing** on the key. ## 4. Change the client ```python Before theme={null} client = OpenAI( base_url="http://litellm.acme.internal:4000", api_key="sk-...", ) client.chat.completions.create( model="gpt-5-mini", messages=[...], user="cust_8841", extra_body={"metadata": {"plan": "pro"}}, ) ``` ```python After theme={null} client = OpenAI( base_url="https://gateway.langwatch.ai/v1", api_key="vk-lw-...", ) client.chat.completions.create( model="openai/gpt-5-mini", messages=[...], user="cust_8841", extra_headers={"X-LangWatch-Metadata": '{"plan": "pro"}'}, ) ``` An application that sends `x-litellm-end-user-id` keeps working without a change. See [Python](/docs/ai-gateway/sdks/python) and [TypeScript](/docs/ai-gateway/sdks/typescript). ## 5. Verify Send one request and check the response for `X-LangWatch-Gateway-Request-Id`. Open **Trace Explorer** in the key's project for the trace and **AI Gateway > Usage** for the spend. ## Keep a LiteLLM proxy behind the gateway To move in stages, add the LiteLLM proxy as a [custom OpenAI-compatible provider](/docs/ai-gateway/providers/custom-openai-compatible) with its URL as the base URL and a LiteLLM key as the API key. Keys created in LangWatch then reach it as `custom/`, with LangWatch budgets, traces and spend events in front of it. Move providers to their own rows one at a time. On LangWatch Cloud that base URL must use `https` and must not resolve to a private address. A self-hosted gateway accepts `http` while `REQUIRE_HTTPS_CUSTOM_ENDPOINTS` stays `false`.