feat(deepagents): add bedrockPromptCachingMiddleware to default stack (#611)

## Summary

- Adds `bedrockPromptCachingMiddleware` to the default middleware stack
- Adds unit tests for the Bedrock model detection util function covering
the different formats of model strings/`ChatModel`s

.changeset/lemon-roses-tell.md

@@ -0,0 +1,7 @@
+---
+"deepagents": patch
+---
+
+feat(deepagents): add bedrockPromptCachingMiddleware to default stack
+
+Add bedrockPromptCachingMiddleware to default middleware stack. This automatically opts-in to Bedrock prompt caching for Nova and Anthropic models

libs/deepagents/src/agent.ts

@@ -3,6 +3,7 @@ import {
   createMiddleware,
   humanInTheLoopMiddleware,
   anthropicPromptCachingMiddleware,
+  bedrockPromptCachingMiddleware,
   todoListMiddleware,
   SystemMessage,
   type AgentMiddleware,
@@ -61,6 +62,7 @@ import {
   isAnthropicModel,
   getModelProvider,
   getModelIdentifier,
+  isBedrockConverseModel,
 } from "./utils.js";
 
 const BASE_AGENT_PROMPT = context`
@@ -220,15 +222,26 @@ export function createDeepAgent<
       : (tools as StructuredTool[]);
 
   const anthropicModel = isAnthropicModel(model);
-  const cacheMiddleware = anthropicModel
-    ? [
-        anthropicPromptCachingMiddleware({
-          unsupportedModelBehavior: "ignore",
-          minMessagesToCache: 1,
-        }),
-        createCacheBreakpointMiddleware(),
-      ]
-    : [];
+  const bedrockModel = isBedrockConverseModel(model);
+  let cacheMiddleware: AnyAgentMiddleware[] = [];
+
+  if (anthropicModel) {
+    cacheMiddleware = [
+      ...cacheMiddleware,
+      anthropicPromptCachingMiddleware({
+        unsupportedModelBehavior: "ignore",
+        minMessagesToCache: 1,
+      }),
+      createCacheBreakpointMiddleware(),
+    ];
+  }
+
+  if (bedrockModel) {
+    cacheMiddleware = [
+      ...cacheMiddleware,
+      bedrockPromptCachingMiddleware({ unsupportedModelBehavior: "ignore" }),
+    ];
+  }
 
   /**
    * Process subagents to add SkillsMiddleware for those with their own skills.

libs/deepagents/src/utils.test.ts

@@ -0,0 +1,86 @@
+import { describe, it, expect, vi } from "vitest";
+import { FakeListChatModel } from "@langchain/core/utils/testing";
+import { isBedrockConverseModel } from "./utils.js";
+
+describe("isBedrockConverseModel", () => {
+  describe("string inputs", () => {
+    it("should detect bedrock: prefixed model strings", () => {
+      expect(
+        isBedrockConverseModel(
+          "bedrock:anthropic.claude-3-5-sonnet-20240620-v1:0",
+        ),
+      ).toBe(true);
+
+      expect(
+        isBedrockConverseModel(
+          "bedrock:us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+        ),
+      ).toBe(true);
+
+      expect(
+        isBedrockConverseModel("bedrock:meta.llama3-70b-instruct-v1:0"),
+      ).toBe(true);
+    });
+
+    it("should detect aws: prefixed model strings", () => {
+      expect(
+        isBedrockConverseModel("aws:anthropic.claude-3-5-sonnet-20240620-v1:0"),
+      ).toBe(true);
+      expect(isBedrockConverseModel("aws:amazon.nova-pro-v1:0")).toBe(true);
+    });
+
+    it("should detect bare amazon.* model strings (langchain auto-inference)", () => {
+      expect(isBedrockConverseModel("amazon.nova-pro-v1:0")).toBe(true);
+      expect(isBedrockConverseModel("amazon.titan-text-express-v1")).toBe(true);
+    });
+
+    it("should reject non-Bedrock provider-prefixed model strings", () => {
+      expect(isBedrockConverseModel("anthropic:claude-3-opus")).toBe(false);
+      expect(isBedrockConverseModel("openai:gpt-4")).toBe(false);
+      expect(isBedrockConverseModel("google:gemini-pro")).toBe(false);
+    });
+
+    it("should reject bare non-amazon model strings", () => {
+      expect(
+        isBedrockConverseModel("anthropic.claude-3-5-sonnet-20240620-v1:0"),
+      ).toBe(false);
+      expect(isBedrockConverseModel("meta.llama3-70b-instruct-v1:0")).toBe(
+        false,
+      );
+    });
+  });
+
+  describe("model object inputs", () => {
+    it("should detect ChatBedrockConverse model objects", () => {
+      const model = new FakeListChatModel({ responses: [] });
+      vi.spyOn(model, "getName").mockReturnValue("ChatBedrockConverse");
+      expect(isBedrockConverseModel(model)).toBe(true);
+    });
+
+    it("should reject non-Bedrock model objects", () => {
+      const anthropic = new FakeListChatModel({ responses: [] });
+      vi.spyOn(anthropic, "getName").mockReturnValue("ChatAnthropic");
+      expect(isBedrockConverseModel(anthropic)).toBe(false);
+    });
+
+    it("should detect ConfigurableModel wrapping the bedrock provider", () => {
+      const model = new FakeListChatModel({ responses: [] });
+      vi.spyOn(model, "getName").mockReturnValue("ConfigurableModel");
+      (model as any)._defaultConfig = { modelProvider: "bedrock" };
+      expect(isBedrockConverseModel(model)).toBe(true);
+    });
+
+    it("should detect ConfigurableModel wrapping the aws provider alias", () => {
+      const model = new FakeListChatModel({ responses: [] });
+      vi.spyOn(model, "getName").mockReturnValue("ConfigurableModel");
+      (model as any)._defaultConfig = { modelProvider: "aws" };
+      expect(isBedrockConverseModel(model)).toBe(true);
+    });
+
+    it("should reject ConfigurableModel with no _defaultConfig", () => {
+      const model = new FakeListChatModel({ responses: [] });
+      vi.spyOn(model, "getName").mockReturnValue("ConfigurableModel");
+      expect(isBedrockConverseModel(model)).toBe(false);
+    });
+  });
+});

libs/deepagents/src/utils.ts

@@ -26,6 +26,36 @@ export function isAnthropicModel(
   return model.getName() === "ChatAnthropic";
 }
 
+/**
+ * Detect whether a model is an AWS Bedrock Converse model.
+ *
+ * Accepts the wider `RunnableInterface` shape (the type of `request.model`
+ * inside `wrapModelCall`, aliased as `AgentLanguageModelLike` in langchain)
+ * because the function only depends on `.getName()`, which is part of the
+ * Runnable contract. `BaseLanguageModel` extends `Runnable`, so existing
+ * call sites still type-check.
+ */
+export function isBedrockConverseModel(
+  model: BaseLanguageModel | RunnableInterface<unknown, unknown> | string,
+): boolean {
+  if (typeof model === "string") {
+    // Explicit provider prefix (`bedrock:` or `aws:`) — both map to
+    // ChatBedrockConverse in langchain's initChatModel.
+    const colonIdx = model.indexOf(":");
+    if (colonIdx !== -1) {
+      const prefix = model.slice(0, colonIdx);
+      if (prefix === "bedrock" || prefix === "aws") return true;
+    }
+
+    return model.startsWith("amazon.");
+  }
+  if (model.getName() === "ConfigurableModel") {
+    const provider = (model as any)._defaultConfig?.modelProvider;
+    return provider === "bedrock" || provider === "aws";
+  }
+  return model.getName() === "ChatBedrockConverse";
+}
+
 /**
  * Extract the provider name from a model instance for profile lookup.
  *