Weaviate's integration with [DigitalOcean's Serverless Inference](https://docs.digitalocean.com/products/inference/how-to/use-serverless-inference/) allows you to access their generative models' capabilities directly from Weaviate. [Configure a Weaviate collection](#configure-collection) to use a generative AI model with DigitalOcean. Weaviate will perform retrieval augmented generation (RAG) using the specified model and your DigitalOcean API key. More specifically, Weaviate will perform a search, retrieve the most relevant objects, and then pass them to the DigitalOcean generative model to generate outputs. ![RAG integration illustration](/assets/docs/weaviate/model-providers/_includes/integration_digitalocean_rag.png) :::callout{intent="info" title="Code examples are Python-only for now"} Examples for the other client languages will follow. ::: ## Requirements ### Weaviate configuration Your Weaviate instance must be configured with the DigitalOcean generative AI integration (`generative-digitalocean`) module. :::callout{intent="info" title="Added in `v1.37.15`, `v1.38.13`, and `v1.39.2`"} ::: :::accordion{title="For Weaviate Cloud (WCD) users"} This integration is enabled by default on Weaviate Cloud (WCD) instances. ::: :::accordion{title="For self-hosted users"} - Check the [cluster metadata](../monitoring-and-logging/status.md#cluster-metadata) to verify if the module is enabled. - Follow the [how-to configure modules](../how-to-configure-weaviate/modules.md) guide to enable the module in Weaviate. ::: ### API credentials You must provide a valid DigitalOcean API key to Weaviate for this integration. Generate one in the [DigitalOcean Cloud console](https://cloud.digitalocean.com/) and supply it via one of: - Set the `DIGITALOCEAN_APIKEY` environment variable on the Weaviate server. - Provide the `X-Digitalocean-Api-Key` header at request time, as shown below. ```python # Recommended: save sensitive data as environment variables digitalocean_key = os.getenv("DIGITALOCEAN_APIKEY") ``` ## Configure collection :::callout{intent="info" title="Generative model integration mutability"} A collection's `generative` model integration configuration is mutable from `v1.25.23`, `v1.26.8` and `v1.27.1`. See [this section](../how-to-manage-collections/generative-reranker-models.md#update-the-generative-model-integration) for details on how to update the collection configuration. ::: [Configure a Weaviate index](../how-to-manage-collections/generative-reranker-models.md#specify-a-generative-model-integration) as follows to use a DigitalOcean generative model: ```python {5-7} from weaviate.classes.config import Configure client.collections.create( "DemoCollection", generative_config=Configure.Generative.digitalocean( model="llama-4-maverick" ) # Additional parameters not shown ) ``` ### Select a model Set `model` to any model that DigitalOcean Serverless Inference serves for your account. See [Available models](#available-models) for where to find the current names, and [Generative parameters](#generative-parameters) for the other settings you can configure alongside it. You can also [override the model at query time](#select-a-model-at-runtime). ### Generative parameters Configure the following generative parameters to customize the model behavior. ```python {5-15} from weaviate.classes.config import Configure client.collections.create( "DemoCollection", generative_config=Configure.Generative.digitalocean( model="llama-4-maverick", # # These parameters are optional # temperature=0.7, # top_p=0.9, # max_tokens=500, # frequency_penalty=0.0, # presence_penalty=0.0, # stop=["\n\n"], # base_url="https://inference.do-ai.run", ) ) ``` For further details on model parameters, see the [DigitalOcean chat completions documentation](https://docs.digitalocean.com/products/inference/how-to/use-chat-completions-api/). ## Select a model at runtime Aside from setting the default model provider when creating the collection, you can also override it at query time. ```python {8-19} from weaviate.classes.generate import GenerativeConfig collection = client.collections.use("DemoCollection") response = collection.generate.near_text( query="A holiday film", limit=2, grouped_task="Write a tweet promoting these two movies", generative_provider=GenerativeConfig.digitalocean( model="llama-4-maverick", # Any model your DigitalOcean account can serve # # These parameters are optional # temperature=0.7, # top_p=0.9, # max_tokens=500, # frequency_penalty=0.0, # presence_penalty=0.0, # stop=["\n\n"], # base_url="https://inference.do-ai.run", ), # Additional parameters not shown ) ``` ## Header parameters You can provide the API key as well as some optional parameters at runtime through additional headers in the request. The following headers are available: - `X-Digitalocean-Api-Key`: The DigitalOcean API key. - `X-Digitalocean-Baseurl`: The base URL to use (e.g. a proxy) instead of the default DigitalOcean URL. `X-Digitalocean-Api-Key` takes precedence over the `DIGITALOCEAN_APIKEY` environment variable. The API key is never part of the collection configuration, so if neither the header nor the environment variable is set, the request fails with `api key: no api key found`. `X-Digitalocean-Baseurl` takes precedence over a `baseURL` set at query time, which in turn takes precedence over the `baseURL` in the collection configuration. If none of them are set, Weaviate uses `https://inference.do-ai.run`. Provide an API root rather than a full endpoint path, because Weaviate appends `/v1/chat/completions` to it. Provide the headers as shown in the [API credentials examples](#api-credentials) above. ## Retrieval augmented generation After configuring the generative AI integration, perform RAG operations, either with the [single prompt](#single-prompt) or [grouped task](#grouped-task) method. ### Single prompt ![Single prompt RAG integration generates individual outputs per search result](/assets/docs/weaviate/model-providers/_includes/integration_digitalocean_rag_single.png) To generate text for each object in the search results, use the single prompt method. The example below generates outputs for each of the `n` search results, where `n` is specified by the `limit` parameter. When creating a single prompt query, use braces `{}` to interpolate the object properties you want Weaviate to pass on to the language model. For example, to pass on the object's `title` property, include `{title}` in the query. ```python {5-6} collection = client.collections.use("DemoCollection") response = collection.generate.near_text( query="A holiday film", # The model provider integration will automatically vectorize the query single_prompt="Translate this into French: {title}", limit=2 ) for obj in response.objects: print(obj.properties["title"]) print(f"Generated output: {obj.generated}") # Note that the generated output is per object ``` ### Grouped task ![Grouped task RAG integration generates one output for the set of search results](/assets/docs/weaviate/model-providers/_includes/integration_digitalocean_rag_grouped.png) To generate one text for the entire set of search results, use the grouped task method. In other words, when you have `n` search results, the generative model generates one output for the entire group. ```python {5-6} collection = client.collections.use("DemoCollection") response = collection.generate.near_text( query="A holiday film", # The model provider integration will automatically vectorize the query grouped_task="Write a fun tweet to promote readers to check out these films.", limit=2 ) print(f"Generated output: {response.generative.text}") # Note that the generated output is per query for obj in response.objects: print(obj.properties["title"]) ``` ## References ### Available models Weaviate forwards the configured model name to DigitalOcean as-is. The `generative-digitalocean` module keeps no list of model names and does not check the name, so a name that DigitalOcean does not serve is accepted when you create the collection and fails later, as an error from DigitalOcean at query time. For the models available to your account, query `GET /v1/models` on the inference endpoint, or see the [DigitalOcean Serverless Inference docs](https://docs.digitalocean.com/products/inference/how-to/use-serverless-inference/) for the live list, as model availability can change. ## Further resources ### Other integrations - [DigitalOcean embedding models + Weaviate](digitalocean-embeddings.md) - [Weaviate model providers overview](index.md) ### Code examples Once the integration is configured at the collection, the data management and search operations in Weaviate work identically to any other collection. See the following model-agnostic examples: - The [How-to: Manage collections](../how-to-manage-collections/index.md) and [How-to: Manage objects](../how-to-manage-objects/index.md) guides show how to perform data operations (i.e. create, read, update, delete collections and objects within them). - The [How-to: Query & Search](../how-to-query-search/index.md) guides show how to perform search operations (i.e. vector, keyword, hybrid) as well as retrieval augmented generation. ### References - [DigitalOcean Serverless Inference documentation](https://docs.digitalocean.com/products/inference/how-to/use-serverless-inference/) - [DigitalOcean chat completions API](https://docs.digitalocean.com/products/inference/how-to/use-chat-completions-api/) ## Questions and feedback Have a question or feedback? Here's how to reach us. ::::card-grid :::card{title="Community Forum" href="https://forum.weaviate.io/c/support" icon="messages-square"} Ask questions and connect with other developers on our **Community forum**. ::: :::card{title="Support" href="/guides/support-overview" icon="life-buoy"} Weaviate Cloud user or customer? Find the right channel on the **Support page**. ::: :::: ## Related pages - [Agents](./agents-index.md) - [AI-assisted Weaviate code generation](./ai-assisted-vibe-coding-index.md) - [APIs](./apis-index.md) - [Authorization and authentication](./authorization-and-authentication-index.md) - [Benchmarks](./benchmarks-index.md) - [Best practices](./best-practices-index.md) - [Client libraries](./clients-index.md) - [Client Libraries / SDKs](./client-libraries-index.md) - [Cloud](./cloud-index.md) - [Cloud account management](./cloud-account-management-index.md) # Agent Instructions This portal answers questions programmatically. To receive a synthesized, source-cited answer instead of crawling page by page, append the `?ask=` query parameter to any page URL on this site: /guides/quickstart?ask=how+do+I+authenticate Optional parameters: - `&goal=` steers the answer toward your objective (e.g. `&goal=write+a+python+client`). - `&version=