feat: add DigitalOcean Gradient AI components

docs/components/DigitalOcean.mdx

@@ -15,6 +15,7 @@ import { CardGrid, LinkCard } from "@astrojs/starlight/components";
   <LinkCard title="Create App" href="#create-app" description="Create a new DigitalOcean App Platform application with services, static sites, workers, or jobs" />
   <LinkCard title="Create DNS Record" href="#create-dns-record" description="Create a DNS record for a DigitalOcean domain" />
   <LinkCard title="Create Droplet" href="#create-droplet" description="Create a new DigitalOcean Droplet" />
+  <LinkCard title="Create Knowledge Base" href="#create-knowledge-base" description="Create a DigitalOcean Gradient AI knowledge base with one or more data sources" />
   <LinkCard title="Create Load Balancer" href="#create-load-balancer" description="Create a DigitalOcean Load Balancer with forwarding rules and targets" />
   <LinkCard title="Create Snapshot" href="#create-snapshot" description="Create a snapshot of a DigitalOcean Droplet" />
   <LinkCard title="Delete Alert Policy" href="#delete-alert-policy" description="Delete a DigitalOcean monitoring alert policy" />
@@ -472,6 +473,71 @@ Returns the created droplet object including:
 }
 ```
 
+<a id="create-knowledge-base"></a>
+
+## Create Knowledge Base
+
+The Create Knowledge Base component creates a new knowledge base on the DigitalOcean Gradient AI Platform, ready for use with AI agents via retrieval-augmented generation (RAG).
+
+### How it works
+
+A knowledge base converts your data sources into vector embeddings using the selected embedding model. Those embeddings are stored in an OpenSearch database — either a newly provisioned one or one you already have. Once created, the knowledge base can be attached to any Gradient AI agent.
+
+### Data Sources
+
+You can add multiple data sources of different types:
+
+- **Spaces Bucket or Folder** — indexes all supported files in a DigitalOcean Spaces bucket or folder
+- **Web or Sitemap URL** — crawls a public website (seed URL) or a list of URLs from a sitemap
+
+Each data source has its own independent chunking strategy.
+
+### Chunking Strategies
+
+- **Section-based** (default) — splits on structural elements like headings and paragraphs; fast and low-cost
+- **Semantic** — groups sentences by meaning; slower but context-aware
+- **Hierarchical** — creates parent (context) and child (retrieval) chunk pairs
+- **Fixed-length** — splits strictly by token count; best for logs and unstructured text
+
+### OpenSearch Database
+
+The knowledge base requires an OpenSearch database to store the vector embeddings:
+- **Create new** — provisions a new database automatically sized to your data
+- **Use existing** — connects to a database you already have by providing its ID
+
+### Output
+
+Returns the created knowledge base including:
+- **uuid**: Knowledge base UUID for use in downstream components
+- **name**: Name of the knowledge base
+- **region**: Datacenter region
+- **embeddingModelUUID**: UUID of the embedding model used
+- **projectId**: Associated project ID
+- **databaseId**: UUID of the OpenSearch database (empty when creating new)
+- **createdAt**: Creation timestamp
+
+### Example Output
+
+```json
+{
+  "data": {
+    "createdAt": "2025-01-01T00:00:00Z",
+    "databaseId": "abf1055a-745d-4c24-a1db-1959ea819264",
+    "embeddingModelUUID": "05700391-7aa8-11ef-bf8f-4e013e2ddde4",
+    "name": "my-knowledge-base",
+    "projectId": "37455431-84bd-4fa2-94cf-e8486f8f8c5e",
+    "region": "tor1",
+    "tags": [
+      "docs",
+      "production"
+    ],
+    "uuid": "20cd8434-6ea1-11f0-bf8f-4e013e2ddde4"
+  },
+  "timestamp": "2025-01-01T00:00:00Z",
+  "type": "digitalocean.knowledge_base.created"
+}
+```
+
 <a id="create-load-balancer"></a>
 
 ## Create Load Balancer

pkg/integrations/digitalocean/client.go

@@ -2289,6 +2289,189 @@ func (c *Client) ListApps() ([]App, error) {
 	return response.Apps, nil
 }
 
+// EmbeddingModel represents a DigitalOcean Gradient AI embedding model
+type EmbeddingModel struct {
+	UUID               string `json:"uuid"`
+	Name               string `json:"name"`
+	Description        string `json:"description"`
+	KBMinChunkSize     int    `json:"kb_min_chunk_size"`
+	KBMaxChunkSize     int    `json:"kb_max_chunk_size"`
+	KBDefaultChunkSize int    `json:"kb_default_chunk_size"`
+}
+
+// ListEmbeddingModels retrieves all embedding models available for knowledge base vectorization
+func (c *Client) ListEmbeddingModels() ([]EmbeddingModel, error) {
+	url := fmt.Sprintf("%s/gen-ai/models?usecases=MODEL_USECASE_KNOWLEDGEBASE&per_page=200", c.BaseURL)
+	responseBody, err := c.execRequest(http.MethodGet, url, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	var response struct {
+		Models []EmbeddingModel `json:"models"`
+	}
+
+	if err := json.Unmarshal(responseBody, &response); err != nil {
+		return nil, fmt.Errorf("error parsing response: %v", err)
+	}
+
+	return response.Models, nil
+}
+
+// Project represents a DigitalOcean project
+type Project struct {
+	ID          string `json:"id"`
+	Name        string `json:"name"`
+	Description string `json:"description"`
+	Purpose     string `json:"purpose"`
+	Environment string `json:"environment"`
+	IsDefault   bool   `json:"is_default"`
+}
+
+// ListProjects retrieves all projects in the account
+func (c *Client) ListProjects() ([]Project, error) {
+	url := fmt.Sprintf("%s/projects?per_page=200", c.BaseURL)
+	responseBody, err := c.execRequest(http.MethodGet, url, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	var response struct {
+		Projects []Project `json:"projects"`
+	}
+
+	if err := json.Unmarshal(responseBody, &response); err != nil {
+		return nil, fmt.Errorf("error parsing response: %v", err)
+	}
+
+	return response.Projects, nil
+}
+
+// Database represents a DigitalOcean managed database cluster
+type Database struct {
+	ID     string `json:"id"`
+	Name   string `json:"name"`
+	Engine string `json:"engine"`
+	Status string `json:"status"`
+}
+
+// ListDatabasesByEngine retrieves all managed database clusters filtered by engine
+func (c *Client) ListDatabasesByEngine(engine string) ([]Database, error) {
+	url := fmt.Sprintf("%s/databases?engine=%s&per_page=200", c.BaseURL, engine)
+	responseBody, err := c.execRequest(http.MethodGet, url, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	var response struct {
+		Databases []Database `json:"databases"`
+	}
+
+	if err := json.Unmarshal(responseBody, &response); err != nil {
+		return nil, fmt.Errorf("error parsing response: %v", err)
+	}
+
+	return response.Databases, nil
+}
+
+// KnowledgeBase represents a DigitalOcean Gradient AI knowledge base
+type KnowledgeBase struct {
+	UUID               string   `json:"uuid"`
+	Name               string   `json:"name"`
+	EmbeddingModelUUID string   `json:"embedding_model_uuid"`
+	Region             string   `json:"region"`
+	ProjectID          string   `json:"project_id"`
+	Tags               []string `json:"tags"`
+	DatabaseID         string   `json:"database_id"`
+	CreatedAt          string   `json:"created_at"`
+	UpdatedAt          string   `json:"updated_at"`
+}
+
+// KBSpacesDataSource defines a Spaces bucket data source for a knowledge base
+type KBSpacesDataSource struct {
+	BucketName string `json:"bucket_name"`
+	Region     string `json:"region"`
+}
+
+// KBWebCrawlerDataSource defines a web crawler data source for a knowledge base
+type KBWebCrawlerDataSource struct {
+	BaseURL        string   `json:"base_url"`
+	CrawlingOption string   `json:"crawling_option,omitempty"`
+	EmbedMedia     bool     `json:"embed_media"`
+	ExcludeTags    []string `json:"exclude_tags,omitempty"`
+}
+
+// KBChunkingOptions defines chunking configuration for a knowledge base data source
+type KBChunkingOptions struct {
+	MaxChunkSize      int     `json:"max_chunk_size,omitempty"`
+	SemanticThreshold float64 `json:"semantic_threshold,omitempty"`
+	ParentChunkSize   int     `json:"parent_chunk_size,omitempty"`
+	ChildChunkSize    int     `json:"child_chunk_size,omitempty"`
+}
+
+// KBDataSource represents a single data source in a knowledge base
+type KBDataSource struct {
+	SpacesDataSource     *KBSpacesDataSource     `json:"spaces_data_source,omitempty"`
+	WebCrawlerDataSource *KBWebCrawlerDataSource `json:"web_crawler_data_source,omitempty"`
+	ChunkingAlgorithm    string                  `json:"chunking_algorithm,omitempty"`
+	ChunkingOptions      *KBChunkingOptions      `json:"chunking_options,omitempty"`
+}
+
+// CreateKnowledgeBaseRequest is the payload for POST /v2/gen-ai/knowledge_bases
+type CreateKnowledgeBaseRequest struct {
+	Name               string         `json:"name"`
+	EmbeddingModelUUID string         `json:"embedding_model_uuid"`
+	Region             string         `json:"region"`
+	ProjectID          string         `json:"project_id"`
+	Tags               []string       `json:"tags,omitempty"`
+	DatabaseID         string         `json:"database_id,omitempty"`
+	DataSources        []KBDataSource `json:"datasources,omitempty"`
+}
+
+// CreateKnowledgeBase creates a new Gradient AI knowledge base
+func (c *Client) CreateKnowledgeBase(req CreateKnowledgeBaseRequest) (*KnowledgeBase, error) {
+	url := fmt.Sprintf("%s/gen-ai/knowledge_bases", c.BaseURL)
+
+	body, err := json.Marshal(req)
+	if err != nil {
+		return nil, fmt.Errorf("error marshaling request: %v", err)
+	}
+
+	responseBody, err := c.execRequest(http.MethodPost, url, bytes.NewReader(body))
+	if err != nil {
+		return nil, err
+	}
+
+	var response struct {
+		KnowledgeBase KnowledgeBase `json:"knowledge_base"`
+	}
+
+	if err := json.Unmarshal(responseBody, &response); err != nil {
+		return nil, fmt.Errorf("error parsing response: %v", err)
+	}
+
+	return &response.KnowledgeBase, nil
+}
+
+// ListKnowledgeBases retrieves all knowledge bases in the account
+func (c *Client) ListKnowledgeBases() ([]KnowledgeBase, error) {
+	url := fmt.Sprintf("%s/gen-ai/knowledge_bases?per_page=200", c.BaseURL)
+	responseBody, err := c.execRequest(http.MethodGet, url, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	var response struct {
+		KnowledgeBases []KnowledgeBase `json:"knowledge_bases"`
+	}
+
+	if err := json.Unmarshal(responseBody, &response); err != nil {
+		return nil, fmt.Errorf("error parsing response: %v", err)
+	}
+
+	return response.KnowledgeBases, nil
+}
+
 // AppNodeMetadata stores metadata about an app for display in the UI
 type AppNodeMetadata struct {
 	AppID   string `json:"appId" mapstructure:"appId"`