feat(opencode): Add Databricks provider support

packages/opencode/src/cli/cmd/auth.ts

@@ -276,6 +276,7 @@ export const AuthLoginCommand = cmd({
           google: 4,
           openrouter: 5,
           vercel: 6,
+          databricks: 7,
         }
         let provider = await prompts.autocomplete({
           message: "Select provider",
@@ -344,6 +345,19 @@ export const AuthLoginCommand = cmd({
           )
         }
 
+        if (provider === "databricks") {
+          prompts.log.info(
+            "Databricks Foundation Model APIs authentication:\n" +
+              "  Set DATABRICKS_HOST to your workspace URL (e.g., https://dbc-xxx.cloud.databricks.com)\n\n" +
+              "Authentication options (in priority order):\n" +
+              "  1. PAT: Enter your Personal Access Token below, or set DATABRICKS_TOKEN\n" +
+              "     Create at: Workspace > Settings > Developer > Access tokens\n" +
+              "  2. OAuth M2M: Set DATABRICKS_CLIENT_ID + DATABRICKS_CLIENT_SECRET\n" +
+              "  3. Azure AD Service Principal: Set ARM_CLIENT_ID + ARM_CLIENT_SECRET + ARM_TENANT_ID\n" +
+              "  4. Azure CLI (auto): For Azure Databricks, will use 'az account get-access-token' if logged in",
+          )
+        }
+
         if (provider === "opencode") {
           prompts.log.info("Create an api key at https://opencode.ai/auth")
         }

packages/opencode/src/provider/provider.ts

@@ -438,6 +438,344 @@ export namespace Provider {
         },
       }
     },
+    databricks: async (input) => {
+      const config = await Config.get()
+      const providerConfig = config.provider?.["databricks"]
+      const auth = await Auth.get("databricks")
+
+      // Host resolution: 1) config file, 2) env var
+      const configHost = providerConfig?.options?.baseURL ?? providerConfig?.options?.host
+      const envHost = Env.get("DATABRICKS_HOST")
+      const host = configHost ?? envHost
+
+      if (!host) return { autoload: false }
+
+      // Authentication precedence:
+      // 1. PAT token (DATABRICKS_TOKEN or stored auth)
+      // 2. OAuth M2M (DATABRICKS_CLIENT_ID + DATABRICKS_CLIENT_SECRET) for Azure
+      // 3. Azure AD Service Principal (azure_client_id + azure_client_secret + azure_tenant_id)
+      const token = Env.get("DATABRICKS_TOKEN") ?? (auth?.type === "api" ? auth.key : undefined)
+
+      // OAuth M2M credentials for Azure Databricks
+      const clientId =
+        Env.get("DATABRICKS_CLIENT_ID") ??
+        providerConfig?.options?.clientId ??
+        (auth?.type === "oauth" ? (auth as any).clientId : undefined)
+      const clientSecret =
+        Env.get("DATABRICKS_CLIENT_SECRET") ??
+        providerConfig?.options?.clientSecret ??
+        (auth?.type === "oauth" ? (auth as any).clientSecret : undefined)
+
+      // Azure AD Service Principal credentials
+      const azureClientId = Env.get("ARM_CLIENT_ID") ?? providerConfig?.options?.azureClientId
+      const azureClientSecret = Env.get("ARM_CLIENT_SECRET") ?? providerConfig?.options?.azureClientSecret
+      const azureTenantId = Env.get("ARM_TENANT_ID") ?? providerConfig?.options?.azureTenantId
+
+      // Determine which auth method to use
+      const hasOAuthM2M = clientId && clientSecret
+      const hasAzureAD = azureClientId && azureClientSecret && azureTenantId
+      const hasPAT = Boolean(token)
+      // Check if Azure CLI is available for Azure Databricks workspaces
+      const isAzureDatabricks = host.includes("azuredatabricks.net")
+
+      if (!hasPAT && !hasOAuthM2M && !hasAzureAD && !isAzureDatabricks) return { autoload: false }
+
+      // Databricks Foundation Model APIs use OpenAI-compatible endpoints
+      // The base URL format is: https://<workspace-url>/serving-endpoints
+      // If baseURL is already a full path (includes /serving-endpoints), use it as-is
+      const baseURL = host.includes("/serving-endpoints")
+        ? host.replace(/\/$/, "")
+        : host.replace(/\/$/, "") + "/serving-endpoints"
+
+      // For OAuth M2M, we need to fetch an access token
+      let accessToken: string | undefined = token
+      if (!accessToken && hasOAuthM2M) {
+        // Fetch OAuth token from Databricks OIDC endpoint
+        const tokenEndpoint = `${host.replace(/\/$/, "")}/oidc/v1/token`
+        try {
+          const response = await fetch(tokenEndpoint, {
+            method: "POST",
+            headers: {
+              "Content-Type": "application/x-www-form-urlencoded",
+              Authorization: `Basic ${Buffer.from(`${clientId}:${clientSecret}`).toString("base64")}`,
+            },
+            body: "grant_type=client_credentials&scope=all-apis",
+          })
+          if (response.ok) {
+            const data = (await response.json()) as { access_token: string }
+            accessToken = data.access_token
+          }
+        } catch (e) {
+          log.error("Failed to fetch Databricks OAuth token", { error: e })
+        }
+      }
+
+      // For Azure AD Service Principal, we need to fetch an Azure AD token first
+      if (!accessToken && hasAzureAD) {
+        try {
+          // Get Azure AD token for Databricks resource
+          const aadTokenEndpoint = `https://login.microsoftonline.com/${azureTenantId}/oauth2/v2.0/token`
+          const response = await fetch(aadTokenEndpoint, {
+            method: "POST",
+            headers: { "Content-Type": "application/x-www-form-urlencoded" },
+            body: new URLSearchParams({
+              grant_type: "client_credentials",
+              client_id: azureClientId,
+              client_secret: azureClientSecret,
+              scope: "2ff814a6-3304-4ab8-85cb-cd0e6f879c1d/.default", // Azure Databricks resource ID
+            }).toString(),
+          })
+          if (response.ok) {
+            const data = (await response.json()) as { access_token: string }
+            accessToken = data.access_token
+          }
+        } catch (e) {
+          log.error("Failed to fetch Azure AD token for Databricks", { error: e })
+        }
+      }
+
+      // For Azure Databricks, try Azure CLI as a fallback
+      if (!accessToken && isAzureDatabricks) {
+        try {
+          // Try to get token from Azure CLI
+          const proc = Bun.spawn(
+            ["az", "account", "get-access-token", "--resource", "2ff814a6-3304-4ab8-85cb-cd0e6f879c1d", "-o", "json"],
+            { stdout: "pipe", stderr: "pipe" },
+          )
+          const output = await new Response(proc.stdout).text()
+          const exitCode = await proc.exited
+          if (exitCode === 0) {
+            const data = JSON.parse(output) as { accessToken: string }
+            accessToken = data.accessToken
+            log.info("Using Azure CLI token for Databricks authentication")
+          }
+        } catch (e) {
+          log.debug("Azure CLI not available for Databricks auth", { error: e })
+        }
+      }
+
+      if (!accessToken) return { autoload: false }
+
+      // Define default Databricks Foundation Model API endpoints
+      // These are the pay-per-token endpoints available in most workspaces
+      // Users can override or add more models in their opencode.json config
+      const defaultModels: Record<string, ModelsDev.Model> = {
+        "databricks-claude-sonnet-4": {
+          id: "databricks-claude-sonnet-4",
+          name: "Claude Sonnet 4 (Databricks)",
+          family: "claude-sonnet",
+          attachment: true,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-05-22",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 3, output: 15, cache_read: 0.3 },
+          limit: { context: 200000, output: 64000 },
+          options: {},
+        },
+        "databricks-claude-sonnet-4-5": {
+          id: "databricks-claude-sonnet-4-5",
+          name: "Claude Sonnet 4.5 (Databricks)",
+          family: "claude-sonnet",
+          attachment: true,
+          reasoning: true,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-10-22",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 3, output: 15, cache_read: 0.3 },
+          limit: { context: 200000, output: 64000 },
+          options: {},
+        },
+        "databricks-claude-haiku-4-5": {
+          id: "databricks-claude-haiku-4-5",
+          name: "Claude Haiku 4.5 (Databricks)",
+          family: "claude-haiku",
+          attachment: true,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-10-22",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 0.8, output: 4, cache_read: 0.08 },
+          limit: { context: 200000, output: 8192 },
+          options: {},
+        },
+        "databricks-claude-opus-4-5": {
+          id: "databricks-claude-opus-4-5",
+          name: "Claude Opus 4.5 (Databricks)",
+          family: "claude-opus",
+          attachment: true,
+          reasoning: true,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-10-22",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 15, output: 75, cache_read: 1.5 },
+          limit: { context: 200000, output: 32000 },
+          options: {},
+        },
+        "databricks-meta-llama-3-3-70b-instruct": {
+          id: "databricks-meta-llama-3-3-70b-instruct",
+          name: "Meta Llama 3.3 70B Instruct (Databricks)",
+          family: "llama-3.3",
+          attachment: false,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2024-12-06",
+          modalities: { input: ["text"], output: ["text"] },
+          cost: { input: 0.65, output: 2.56 },
+          limit: { context: 128000, output: 4096 },
+          options: {},
+        },
+        "databricks-claude-3-7-sonnet": {
+          id: "databricks-claude-3-7-sonnet",
+          name: "Claude 3.7 Sonnet (Databricks)",
+          family: "claude-sonnet",
+          attachment: true,
+          reasoning: true,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-02-24",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 3, output: 15, cache_read: 0.3 },
+          limit: { context: 200000, output: 64000 },
+          options: {},
+        },
+        "databricks-claude-opus-4-1": {
+          id: "databricks-claude-opus-4-1",
+          name: "Claude Opus 4.1 (Databricks)",
+          family: "claude-opus",
+          attachment: true,
+          reasoning: true,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-04-16",
+          modalities: { input: ["text", "image"], output: ["text"] },
+          cost: { input: 15, output: 75, cache_read: 1.5 },
+          limit: { context: 200000, output: 32000 },
+          options: {},
+        },
+        "databricks-llama-4-maverick": {
+          id: "databricks-llama-4-maverick",
+          name: "Llama 4 Maverick (Databricks)",
+          family: "llama-4",
+          attachment: false,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2025-04-05",
+          modalities: { input: ["text"], output: ["text"] },
+          cost: { input: 0.2, output: 0.6 },
+          limit: { context: 1048576, output: 65536 },
+          options: {},
+        },
+        "databricks-meta-llama-3-1-405b-instruct": {
+          id: "databricks-meta-llama-3-1-405b-instruct",
+          name: "Meta Llama 3.1 405B Instruct (Databricks)",
+          family: "llama-3.1",
+          attachment: false,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2024-07-23",
+          modalities: { input: ["text"], output: ["text"] },
+          cost: { input: 3, output: 3 },
+          limit: { context: 128000, output: 4096 },
+          options: {},
+        },
+        "databricks-meta-llama-3-1-8b-instruct": {
+          id: "databricks-meta-llama-3-1-8b-instruct",
+          name: "Meta Llama 3.1 8B Instruct (Databricks)",
+          family: "llama-3.1",
+          attachment: false,
+          reasoning: false,
+          tool_call: true,
+          temperature: true,
+          release_date: "2024-07-23",
+          modalities: { input: ["text"], output: ["text"] },
+          cost: { input: 0.1, output: 0.1 },
+          limit: { context: 128000, output: 4096 },
+          options: {},
+        },
+      }
+
+      // Transform ModelsDev.Model to Provider.Model format
+      function toProviderModel(model: ModelsDev.Model): Model {
+        return {
+          id: model.id,
+          providerID: "databricks",
+          name: model.name,
+          family: model.family,
+          api: {
+            id: model.id,
+            url: baseURL,
+            npm: "@ai-sdk/openai-compatible",
+          },
+          status: "active",
+          headers: {},
+          options: model.options ?? {},
+          cost: {
+            input: model.cost?.input ?? 0,
+            output: model.cost?.output ?? 0,
+            cache: {
+              read: model.cost?.cache_read ?? 0,
+              write: model.cost?.cache_write ?? 0,
+            },
+          },
+          limit: {
+            context: model.limit.context,
+            output: model.limit.output,
+          },
+          capabilities: {
+            temperature: model.temperature,
+            reasoning: model.reasoning,
+            attachment: model.attachment,
+            toolcall: model.tool_call,
+            input: {
+              text: model.modalities?.input?.includes("text") ?? false,
+              audio: model.modalities?.input?.includes("audio") ?? false,
+              image: model.modalities?.input?.includes("image") ?? false,
+              video: model.modalities?.input?.includes("video") ?? false,
+              pdf: model.modalities?.input?.includes("pdf") ?? false,
+            },
+            output: {
+              text: model.modalities?.output?.includes("text") ?? false,
+              audio: model.modalities?.output?.includes("audio") ?? false,
+              image: model.modalities?.output?.includes("image") ?? false,
+              video: model.modalities?.output?.includes("video") ?? false,
+              pdf: model.modalities?.output?.includes("pdf") ?? false,
+            },
+            interleaved: false,
+          },
+          release_date: model.release_date,
+          variants: {},
+        }
+      }
+
+      // Add default models to the input provider if not already defined
+      for (const [modelID, model] of Object.entries(defaultModels)) {
+        if (!input.models[modelID]) {
+          input.models[modelID] = toProviderModel(model)
+        }
+      }
+
+      return {
+        autoload: true,
+        async getModel(sdk: any, modelID: string, _options?: Record<string, any>) {
+          return sdk.chat(modelID)
+        },
+        options: {
+          baseURL,
+          apiKey: accessToken,
+          headers: {
+            "User-Agent": "opencode",
+          },
+        },
+      }
+    },
   }
 
   export const Model = z
@@ -642,6 +980,19 @@ export namespace Provider {
       }
     }
 
+    // Add Databricks provider for Foundation Model APIs
+    // This provider is not in models.dev so we create it programmatically
+    if (!database["databricks"]) {
+      database["databricks"] = {
+        id: "databricks",
+        name: "Databricks",
+        source: "custom",
+        env: ["DATABRICKS_TOKEN"],
+        options: {},
+        models: {},
+      }
+    }
+
     function mergeProvider(providerID: string, provider: Partial<Info>) {
       const existing = providers[providerID]
       if (existing) {