fix(memory): disable score filtering in runtime template defaults

src/assets/templates/a2a-python-strands/README.md

@@ -8,6 +8,13 @@ This agent speaks the A2A protocol. Other agents discover it via its agent card
 `/.well-known/agent-card.json` and invoke it with JSON-RPC (`message/send`, `message/stream`)
 at the server root, matching the AgentCore Runtime A2A service contract.
 
+## Memory
+
+The template provisions semantic and episodic memory. `memory/session.py` retrieves up to three
+semantic facts for the actor and five episodes for the current session. The default
+`relevance_score=0.0` selects results by `top_k` without score filtering. To opt into score
+filtering, increase `relevance_score` in the retrieval configuration.
+
 ## Adding Tools
 
 Define tools with the `@tool` decorator in `main.py` and add them to the `tools` list:

src/assets/templates/a2a-python-strands/memory/session.py

@@ -18,10 +18,8 @@ def get_memory_session_manager(
     session_id = session_id or uuid.uuid4().hex
 
     retrieval_config = {
-        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/users/{actor_id}/preferences": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.5),
-        f"/summaries/{actor_id}": RetrievalConfig(top_k=3, relevance_score=0.5),
+        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0),
+        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0),
     }
 
     return AgentCoreMemorySessionManager(

src/assets/templates/agent-python-strands/README.md

@@ -13,6 +13,13 @@ file defines a Starlette ASGI app with the Strands Agent SDK running within.
 
 `model/load.py` instantiates the chosen model provider.
 
+## Memory
+
+The template provisions semantic and episodic memory. `memory/session.py` retrieves up to three
+semantic facts for the actor and five episodes for the current session. The default
+`relevance_score=0.0` selects results by `top_k` without score filtering. To opt into score
+filtering, increase `relevance_score` in the retrieval configuration.
+
 ## Input Validation
 
 Validate invocation input before forwarding it to Strands. Keep plain prompts typed as strings. If the app accepts a

src/assets/templates/agent-python-strands/memory/session.py

@@ -14,10 +14,8 @@ def get_memory_session_manager(
         return None
 
     retrieval_config = {
-        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/users/{actor_id}/preferences": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.5),
-        f"/summaries/{actor_id}": RetrievalConfig(top_k=3, relevance_score=0.5),
+        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0),
+        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0),
     }
 
     return AgentCoreMemorySessionManager(

src/assets/templates/agent-typescript-strands/README.md

@@ -17,6 +17,11 @@ from `.env.local` under `agentcore dev`; the `openai_compatible` provider is the
 pointed at the base URL you gave the `agentcore create` wizard, baked into `load.ts` as
 `clientConfig.baseURL`.
 
+## Memory
+
+The template provisions semantic and episodic memory. `memory/memory.ts` retrieves semantic
+facts for the actor and episodes for the current session, with score filtering disabled by default.
+
 ## Input Validation
 
 The generated Zod request schema keeps the prompt and actor ID typed as strings before forwarding them to Strands.

src/assets/templates/agent-typescript-strands/memory/memory.ts

@@ -18,9 +18,7 @@ export function getOrCreateMemoryManager(sessionId: string, actorId: string): Me
     sessionId,
     namespaces: [
       { namespace: '/users/{actorId}/facts' },
-      { namespace: '/users/{actorId}/preferences' },
       { namespace: '/episodes/{actorId}/{sessionId}' },
-      { namespace: '/summaries/{actorId}' },
     ],
     // readMode defaults to 'per-namespace' (one retrieve call per namespace).
     // Switch to 'subtree' to consolidate to a single hierarchical recall call.

src/assets/templates/agui-python-strands/README.md

@@ -9,6 +9,13 @@ streams agent-to-UI events over HTTP. It exposes an `/invocations` endpoint that
 an AG-UI `RunAgentInput` body and streams the response back as AG-UI server-sent events,
 matching the AgentCore Runtime HTTP service contract.
 
+## Memory
+
+The template provisions semantic and episodic memory. `memory/session.py` retrieves up to three
+semantic facts for the actor and five episodes for the current session. The default
+`relevance_score=0.0` selects results by `top_k` without score filtering. To opt into score
+filtering, increase `relevance_score` in the retrieval configuration.
+
 ## Adding Tools
 
 Define tools with the `@tool` decorator in `main.py` and add them to the agent's `tools` list:

src/assets/templates/agui-python-strands/memory/session.py

@@ -18,10 +18,8 @@ def get_memory_session_manager(
     session_id = session_id or uuid.uuid4().hex
 
     retrieval_config = {
-        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/users/{actor_id}/preferences": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.5),
-        f"/summaries/{actor_id}": RetrievalConfig(top_k=3, relevance_score=0.5),
+        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0),
+        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0),
     }
 
     return AgentCoreMemorySessionManager(

src/assets/templates/export-harness-python/memory/session.py

@@ -20,16 +20,16 @@ def get_memory_session_manager(
 {{#if memoryStrategies.length}}
     retrieval_config = {
 {{#if (includes memoryStrategies "SEMANTIC")}}
-        f"/users/{actor_id}/facts": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.5{{/if}}),
+        f"/users/{actor_id}/facts": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.0{{/if}}),
 {{/if}}
 {{#if (includes memoryStrategies "USER_PREFERENCE")}}
-        f"/users/{actor_id}/preferences": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.5{{/if}}),
+        f"/users/{actor_id}/preferences": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.0{{/if}}),
 {{/if}}
 {{#if (includes memoryStrategies "EPISODIC")}}
-        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}5{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.5{{/if}}),
+        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}5{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.0{{/if}}),
 {{/if}}
 {{#if (includes memoryStrategies "SUMMARIZATION")}}
-        f"/summaries/{actor_id}": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.5{{/if}}),
+        f"/summaries/{actor_id}": RetrievalConfig(top_k={{#if memoryRetrievalTopK}}{{memoryRetrievalTopK}}{{else}}3{{/if}}, relevance_score={{#if memoryRetrievalRelevanceScore}}{{memoryRetrievalRelevanceScore}}{{else}}0.0{{/if}}),
 {{/if}}
     }
 {{/if}}

src/core/project/__snapshots__/manager.test.ts.snap

@@ -54,18 +54,6 @@ exports[`FsProjectManager.create snapshots the Strands project manifest and runt
           ],
           "type": "SEMANTIC",
         },
-        {
-          "namespaceTemplates": [
-            "/users/{actorId}/preferences",
-          ],
-          "type": "USER_PREFERENCE",
-        },
-        {
-          "namespaceTemplates": [
-            "/summaries/{actorId}/{sessionId}",
-          ],
-          "type": "SUMMARIZATION",
-        },
         {
           "namespaceTemplates": [
             "/episodes/{actorId}/{sessionId}",
@@ -125,18 +113,6 @@ exports[`FsProjectManager.create snapshots the Strands TypeScript project manife
           ],
           "type": "SEMANTIC",
         },
-        {
-          "namespaceTemplates": [
-            "/users/{actorId}/preferences",
-          ],
-          "type": "USER_PREFERENCE",
-        },
-        {
-          "namespaceTemplates": [
-            "/summaries/{actorId}/{sessionId}",
-          ],
-          "type": "SUMMARIZATION",
-        },
         {
           "namespaceTemplates": [
             "/episodes/{actorId}/{sessionId}",
@@ -197,18 +173,6 @@ exports[`FsProjectManager.create snapshots the Strands A2A project manifest and
           ],
           "type": "SEMANTIC",
         },
-        {
-          "namespaceTemplates": [
-            "/users/{actorId}/preferences",
-          ],
-          "type": "USER_PREFERENCE",
-        },
-        {
-          "namespaceTemplates": [
-            "/summaries/{actorId}/{sessionId}",
-          ],
-          "type": "SUMMARIZATION",
-        },
         {
           "namespaceTemplates": [
             "/episodes/{actorId}/{sessionId}",

src/core/project/bedrockAgentImport/strandsTranslator.ts

@@ -248,10 +248,8 @@ function generateStrandsMemoryModule(request: BedrockAgentImportRequest): string
   const retrievalConfig =
     request.memory === "longAndShortTerm"
       ? `    retrieval_config = {
-        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/users/{actor_id}/preferences": RetrievalConfig(top_k=3, relevance_score=0.5),
-        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.5),
-        f"/summaries/{actor_id}": RetrievalConfig(top_k=3, relevance_score=0.5),
+        f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0),
+        f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0),
     }
 `
       : "    retrieval_config = {}\n";

src/core/project/bedrockAgentImport/translator.test.ts

@@ -93,6 +93,22 @@ describe("StrandsBedrockAgentTranslator", () => {
     expect(plan.files["IMPORT_NOTES.md"]).toContain("Strands guardrail");
   });
 
+  test("retrieves semantic and episodic memory without a default score filter", () => {
+    const memory = new StrandsBedrockAgentTranslator(snapshot(), request).translate().files[
+      "memory.py"
+    ]!;
+
+    expect(memory).toContain(
+      'f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0)',
+    );
+    expect(memory).toContain(
+      'f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0)',
+    );
+    expect(memory.match(/RetrievalConfig\(/g)).toHaveLength(2);
+    expect(memory).not.toContain("/preferences");
+    expect(memory).not.toContain("/summaries/");
+  });
+
   test("pins a code-interpreter dependency that can coexist with strands-agents 1.x", () => {
     const pyproject = new StrandsBedrockAgentTranslator(snapshot(), request).translate().files[
       "pyproject.toml"

src/core/project/manager.export.test.ts

@@ -179,7 +179,14 @@ describe("FsProjectManager.exportHarness rendered tree", () => {
         resourceConfig: {
           name: "chat_history",
           eventExpiryDuration: 30,
-          strategies: [{ type: "SEMANTIC" }],
+          strategies: [
+            { type: "SEMANTIC" },
+            {
+              type: "EPISODIC",
+              namespaceTemplates: ["/episodes/{actorId}/{sessionId}"],
+              reflectionNamespaceTemplates: ["/episodes/{actorId}"],
+            },
+          ],
         },
       }),
     );
@@ -188,41 +195,52 @@ describe("FsProjectManager.exportHarness rendered tree", () => {
 
     const session = await Bun.file(join(result.agentPath, "memory", "session.py")).text();
     expect(session).toContain('MEMORY_ID = os.getenv("MEMORY_CHAT_HISTORY_ID")');
+    expect(session).toContain(
+      'f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0)',
+    );
+    expect(session).toContain(
+      'f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0)',
+    );
+    expect(session).not.toContain("/preferences");
+    expect(session).not.toContain("/summaries/");
     expect(await Bun.file(join(result.agentPath, "main.py")).text()).toContain(
       "from memory.session import get_memory_session_manager",
     );
     expect(result.notes).toEqual([]);
   });
 
-  test("renders memory retrieval tuning and notes messagesCount", async () => {
-    const { manager: subject } = manager();
-    let project = await projectWithHarness(subject, {
-      memory: {
-        mode: "existing",
-        name: "chat_history",
-        messagesCount: 12,
-        retrievalConfig: { topK: 8, relevanceScore: 0.7 },
-      },
-    });
-    project = await drain(
-      subject.addResource(project, {
-        resourceType: "memory",
-        resourceConfig: {
+  test.each([0, 0.7])(
+    "renders relevanceScore=%p and notes messagesCount",
+    async (relevanceScore) => {
+      const { manager: subject } = manager();
+      let project = await projectWithHarness(subject, {
+        memory: {
+          mode: "existing",
           name: "chat_history",
-          eventExpiryDuration: 30,
-          strategies: [{ type: "SEMANTIC" }],
+          messagesCount: 12,
+          retrievalConfig: { topK: 8, relevanceScore },
         },
-      }),
-    );
+      });
+      project = await drain(
+        subject.addResource(project, {
+          resourceType: "memory",
+          resourceConfig: {
+            name: "chat_history",
+            eventExpiryDuration: 30,
+            strategies: [{ type: "SEMANTIC" }],
+          },
+        }),
+      );
 
-    const result = await drain(subject.exportHarness(project, exportInput()));
+      const result = await drain(subject.exportHarness(project, exportInput()));
 
-    const session = await Bun.file(join(result.agentPath, "memory", "session.py")).text();
-    expect(session).toContain("RetrievalConfig(top_k=8, relevance_score=0.7)");
-    expect(result.notes.map((note) => note.category)).toContain(
-      "Memory messagesCount is not directly portable to Strands",
-    );
-  });
+      const session = await Bun.file(join(result.agentPath, "memory", "session.py")).text();
+      expect(session).toContain(`RetrievalConfig(top_k=8, relevance_score=${relevanceScore})`);
+      expect(result.notes.map((note) => note.category)).toContain(
+        "Memory messagesCount is not directly portable to Strands",
+      );
+    },
+  );
 
   test("renders OpenAI Responses settings with compatible Strands extras", async () => {
     const { manager: subject } = manager();

src/core/project/templates/runtime.test.ts

@@ -120,17 +120,18 @@ describe("runtime templates", () => {
   });
 
   test.each<[RuntimeTemplateShortcutName, string[]]>([
-    ["agent-python-strands", ["SEMANTIC", "USER_PREFERENCE", "SUMMARIZATION", "EPISODIC"]],
-    ["a2a-python-strands", ["SEMANTIC", "USER_PREFERENCE", "SUMMARIZATION", "EPISODIC"]],
-    ["agent-typescript-strands", ["SEMANTIC", "USER_PREFERENCE", "SUMMARIZATION", "EPISODIC"]],
+    ["agent-python-strands", ["SEMANTIC", "EPISODIC"]],
+    ["agent-python-strands-container", ["SEMANTIC", "EPISODIC"]],
+    ["a2a-python-strands", ["SEMANTIC", "EPISODIC"]],
+    ["agent-typescript-strands", ["SEMANTIC", "EPISODIC"]],
     ["agent-python-minimal", []],
     ["agent-python-langchain", []],
     ["agent-typescript-vercel", []],
     ["mcp-python-fastmcp", []],
-    ["agui-python-strands", ["SEMANTIC", "USER_PREFERENCE", "SUMMARIZATION", "EPISODIC"]],
+    ["agui-python-strands", ["SEMANTIC", "EPISODIC"]],
     ["environment-python-bma", []],
   ])("%s ships with its pre-configured memory", async (template, expectedStrategies) => {
-    const { spec } = await addTemplate("my_agent", template);
+    const { spec, appDir } = await addTemplate("my_agent", template);
     const memory = (spec.memories ?? []).find(
       (candidate: { name: string }) => candidate.name === "my_agentMemory",
     );
@@ -140,6 +141,34 @@ describe("runtime templates", () => {
     }
     expect(memory).toMatchObject({ name: "my_agentMemory", eventExpiryDuration: 30 });
     expect(memory.strategies.map(({ type }: { type: string }) => type)).toEqual(expectedStrategies);
+    expect(memory.strategies).toEqual([
+      { type: "SEMANTIC", namespaceTemplates: ["/users/{actorId}/facts"] },
+      {
+        type: "EPISODIC",
+        namespaceTemplates: ["/episodes/{actorId}/{sessionId}"],
+        reflectionNamespaceTemplates: ["/episodes/{actorId}"],
+      },
+    ]);
+
+    const isTypeScript = template === "agent-typescript-strands";
+    const memoryCode = await Bun.file(
+      join(appDir, "memory", isTypeScript ? "memory.ts" : "session.py"),
+    ).text();
+    expect(memoryCode).not.toContain("/preferences");
+    expect(memoryCode).not.toContain("/summaries/");
+    if (isTypeScript) {
+      expect(memoryCode).toContain("{ namespace: '/users/{actorId}/facts' }");
+      expect(memoryCode).toContain("{ namespace: '/episodes/{actorId}/{sessionId}' }");
+      expect(memoryCode.match(/namespace:/g)).toHaveLength(2);
+    } else {
+      expect(memoryCode).toContain(
+        'f"/users/{actor_id}/facts": RetrievalConfig(top_k=3, relevance_score=0.0)',
+      );
+      expect(memoryCode).toContain(
+        'f"/episodes/{actor_id}/{session_id}": RetrievalConfig(top_k=5, relevance_score=0.0)',
+      );
+      expect(memoryCode.match(/RetrievalConfig\(/g)).toHaveLength(2);
+    }
   });
 
   test.each<[RuntimeTemplateShortcutName, string]>([

src/handlers/project/add/runtime/index.test.ts

@@ -420,8 +420,6 @@ describe("project add runtime --agent-id (Bedrock Agent import)", () => {
     expect(spec.memories).toMatchObject([{ name: "support_proxyMemory" }]);
     expect(spec.memories[0].strategies.map(({ type }: { type: string }) => type)).toEqual([
       "SEMANTIC",
-      "USER_PREFERENCE",
-      "SUMMARIZATION",
       "EPISODIC",
     ]);
   });

src/handlers/project/project.test.ts

@@ -211,8 +211,6 @@ describe("project create", () => {
     expect(memory).toMatchObject({ name: "agentMemory", eventExpiryDuration: 30 });
     expect(memory.strategies.map(({ type }: { type: string }) => type)).toEqual([
       "SEMANTIC",
-      "USER_PREFERENCE",
-      "SUMMARIZATION",
       "EPISODIC",
     ]);
     expect(await Bun.file(join(projectRoot, "app", "agent", "main.py")).exists()).toBe(true);