> For the complete documentation index, see [llms.txt](https://docs.otari.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.otari.ai/otari/for-operators/gemini.md). # Gemini provider guide Route requests to Google's Gemini models through Otari, using a Gemini API key from Google AI Studio. For Gemini on Google Cloud, use the `vertex` provider instead. See any-llm's [supported providers](https://docs.mozilla.ai/any-llm/providers/) for the current provider list and [Models](/otari/for-operators/models.md) for Otari's model-name format. ## What you'll set up A Gemini provider entry in your `config.yml` that reads your key from `GEMINI_API_KEY` (or the key stored on the dashboard's Providers page), then a first request that Otari routes to Gemini. ## Prerequisites * Otari running locally (see the [Quickstart](/otari/start-here/quickstart.md)) * A Gemini API key from ## Configure Add Gemini under `providers:` in your `config.yml`: ```yaml providers: gemini: api_key: "AIza..." # your Gemini API key ``` To keep your provider key out of the file with environment interpolation: ```yaml providers: gemini: api_key: ${GEMINI_API_KEY} ``` ...then export it before starting Otari: ```bash export GEMINI_API_KEY=AIza... ``` > `GEMINI_API_KEY` alone is not enough, and neither is a bare `gemini:` entry: Otari reads the variable only where an entry names it, as the `api_key: ${GEMINI_API_KEY}` line above does. The dashboard's Providers page and an organization's own key work too. ## Choose a model Models are addressed as `gemini:`: ``` gemini:gemini-3-flash-preview gemini:gemini-3.1-flash-lite ``` Everything after the colon is passed straight to Gemini, so any model your key can access works. Google retires older models for new keys, so check the [model list](https://ai.google.dev/gemini-api/docs/models) if a name is rejected. Chat completions take only text-generation models. Embedding models such as `gemini-embedding-001` do not work there; send them to `POST /api/v1/embeddings` instead (see the [API reference](/otari/for-integrators/api-reference.md)). ## Verify If you have not already started Otari and created a client key, follow the [Quickstart](/otari/start-here/quickstart.md) first. Then make a request with the Otari Python SDK (`pip install otari`; any OpenAI-compatible client also works), using a `gemini:` selector: ```python from otari import OtariClient client = OtariClient(api_base="http://localhost:8000", api_key="tk-...") resp = client.completion( model="gemini:gemini-3-flash-preview", messages=[{"role": "user", "content": "Say hello in five words."}], ) print(resp.choices[0].message.content) ``` Expected (sample) output: ``` Hello there, how are you? ``` ## Troubleshooting | Symptom | Likely cause | | ------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | HTTP 400 `API key not valid. Please pass a valid API key.` | Gemini rejected the `api_key` Otari sent. Check the `api_key` (or `GEMINI_API_KEY`) configured on the gateway. | | HTTP 404 `This model ... is no longer available to new users` | Google has retired that model for new keys. Use the model the message suggests. | | HTTP 429 `You exceeded your current quota` (code `upstream_rate_limited`) | Your key's quota for that model is used up or is zero, which is common for Pro models on the free tier. Wait, pick another model, or enable billing in Google AI Studio. | | HTTP 502 `The provider failed the request with HTTP 503` | Gemini is overloaded or failed on its side. These are retryable. | | HTTP 402 `No pricing configured for model ...` | Otari could not resolve pricing for that model and `require_pricing` rejected the request. Add a `pricing:` entry, enable `default_pricing: true` for bundled fallback pricing, or use a model that already has pricing coverage. | --- # Agent Instructions This documentation is published with GitBook. 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