Fix: AgentCore prompt cache support via environment variable

Load SUPPORTED_CACHE_FIELDS from environment variable to maintain
single source of truth in TypeScript (packages/common/model.ts).

This follows the same pattern as MCP_SERVERS configuration:
- CDK injects SUPPORTED_CACHE_FIELDS via environment variable
- Python runtime reads from environment
- Claude models: cache_prompt + cache_tools enabled
- Nova models: cache_prompt only (no cache_tools)
- Other models: no caching (safe default)

Changes:
- generic-agent-core.ts: Pass SUPPORTED_CACHE_FIELDS as env var
- config.py: Load from env var with standard Python style
- agent.py: Conditional BedrockModel initialization

Fixes: ValidationException when using Nova models with AgentCore

Author: keykbd

packages/cdk/lambda-python/generic-agent-core-runtime/src/agent.py

@@ -9,7 +9,7 @@
 from strands import Agent as StrandsAgent
 from strands.models import BedrockModel
 
-from .config import extract_model_info, get_max_iterations, get_system_prompt
+from .config import extract_model_info, get_max_iterations, get_system_prompt, supports_prompt_cache, supports_tools_cache
 from .tools import ToolManager
 from .types import Message, ModelInfo
 from .utils import (
@@ -81,12 +81,21 @@ async def process_request_streaming(
 
             # Create boto3 session and Bedrock model
             session = boto3.Session(region_name=region)
-            bedrock_model = BedrockModel(
-                model_id=model_id,
-                boto_session=session,
-                cache_prompt="default",
-                cache_tools="default",
-            )
+
+            # Configure caching based on model support (loaded from environment variable)
+            bedrock_model_params = {
+                "model_id": model_id,
+                "boto_session": session,
+            }
+
+            # Only enable caching for officially supported models
+            if supports_prompt_cache(model_id):
+                bedrock_model_params["cache_prompt"] = "default"
+
+                if supports_tools_cache(model_id):
+                    bedrock_model_params["cache_tools"] = "default"
+
+            bedrock_model = BedrockModel(**bedrock_model_params)
 
             # Process messages and prompt using utility functions
             processed_messages = process_messages(messages)

packages/cdk/lambda-python/generic-agent-core-runtime/src/config.py

@@ -1,7 +1,9 @@
 """Configuration and environment setup for the agent core runtime."""
 
+import json
 import logging
 import os
+import re
 from typing import Any
 
 # Configure root logger
@@ -82,3 +84,34 @@ def get_max_iterations() -> int:
     except ValueError:
         logger.warning(f"Invalid MAX_ITERATIONS value. Defaulting to {DEFAULT_MAX_ITERATIONS}.")
         return DEFAULT_MAX_ITERATIONS
+
+
+# CRI (Cross-Region Inference) prefix pattern
+CRI_PREFIX_PATTERN = re.compile(r"^(global|us|eu|apac|jp)\.")
+
+# Prompt caching configuration
+# Based on: https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html
+# Load from environment variable (injected by CDK from TypeScript definition)
+_supported_cache_fields_env = os.environ.get("SUPPORTED_CACHE_FIELDS")
+if _supported_cache_fields_env:
+    SUPPORTED_CACHE_FIELDS: dict[str, list[str]] = json.loads(_supported_cache_fields_env)
+else:
+    # Fallback if environment variable is not set (should not happen in production)
+    logger.warning("SUPPORTED_CACHE_FIELDS not found in environment, using empty fallback")
+    SUPPORTED_CACHE_FIELDS: dict[str, list[str]] = {}
+
+
+def get_supported_cache_fields(model_id: str) -> list[str]:
+    """Get supported cache fields for a model (removes CRI prefix before lookup)"""
+    base_model_id = CRI_PREFIX_PATTERN.sub("", model_id)
+    return SUPPORTED_CACHE_FIELDS.get(base_model_id, [])
+
+
+def supports_prompt_cache(model_id: str) -> bool:
+    """Check if a model supports prompt caching (system or messages)"""
+    return len(get_supported_cache_fields(model_id)) > 0
+
+
+def supports_tools_cache(model_id: str) -> bool:
+    """Check if a model supports tools caching"""
+    return "tools" in get_supported_cache_fields(model_id)

packages/cdk/lib/construct/generic-agent-core.ts

@@ -20,6 +20,7 @@ import {
 import { BucketInfo } from 'generative-ai-use-cases';
 import * as path from 'path';
 import { loadMCPConfig } from '../utils/mcp-config-loader';
+import { SUPPORTED_CACHE_FIELDS } from '@generative-ai-use-cases/common';
 
 export interface AgentCoreRuntimeConfig {
   name: string;
@@ -102,6 +103,7 @@ export class GenericAgentCore extends Construct {
         environmentVariables: {
           FILE_BUCKET: bucketName,
           MCP_SERVERS: JSON.stringify(genericMcpServers),
+          SUPPORTED_CACHE_FIELDS: JSON.stringify(SUPPORTED_CACHE_FIELDS),
         },
       },
       agentBuilder: {
@@ -115,6 +117,7 @@ export class GenericAgentCore extends Construct {
         environmentVariables: {
           FILE_BUCKET: bucketName,
           MCP_SERVERS: JSON.stringify(agentBuilderMcpServers),
+          SUPPORTED_CACHE_FIELDS: JSON.stringify(SUPPORTED_CACHE_FIELDS),
         },
       },
     };