fix MR comments:

- improve documentations
- remove AgentPattern from exports
-  add system prompt

Author: razkenari

docs/STREAMING.md

@@ -7,7 +7,10 @@ Your agent sends streaming events in SSE format. This guide explains how to inte
 ## Integration Steps
 
 1. **Your agent sends streaming events** (SSE format)
-2. **Update `agentCoreService.js`** to parse your agent's events
+2. **Update the appropriate parser file** to handle your agent's events:
+   - For **Strands agents**: Modify `frontend/src/services/strandsParser.js`
+   - For **LangGraph agents**: Modify `frontend/src/services/langgraphParser.js`
+   - For **other agent frameworks**: Create a new parser file and import it in `agentCoreService.js`
 3. **Update `ChatInterface.tsx`** (optional) to display additional info like tool usage
 4. **UI displays the parsed text** in real-time
 

frontend/src/services/agentCoreService.js

@@ -5,74 +5,20 @@
  * AgentCore Service - Streaming Response Handler
  *
  * Handles streaming responses from AgentCore agents using Server-Sent Events (SSE).
- * Dynamically loads the appropriate parser based on the agent pattern in aws-exports.json.
  *
- * CUSTOMIZATION GUIDE
- * See strandsParser.js and langgraphParser.js for sample implementation of parsers for Strands and Langgraph.
- * Modify strandsParser.js or langgraphParser.js when You need to handle additional event types (e.g., tool calls, images). 
- * Create a new parser file to support other agent frameworks (not Strands or LangGraph), and replace the parser
- * with your agent's specific event parsing logic.
+ * CUSTOMIZATION FOR OTHER AGENT TYPES:
+ * This service uses separate parser files for Strands and LangGraph agents.
+ * Both parsers try each streaming event, each processes its format and ignores others.
+ * To support other agent frameworks, create a new parser file and add a call in the streaming loop.
+ * See strandsParser.js and langgraphParser.js for examples.
  */
 
 import * as strandsParser from './strandsParser.js';
 import * as langgraphParser from './langgraphParser.js';
 
-// Parser selection based on agent pattern
-let activeParser = null;
-
-/**
- * Load and select the appropriate parser based on agent pattern
- */
-const loadParser = async () => {
-  if (activeParser) {
-    return activeParser;
-  }
-
-  try {
-    const response = await fetch("/aws-exports.json");
-    const config = await response.json();
-    const pattern = config.agentPattern || "strands-single-agent";
-
-    // Select parser based on exact pattern match
-    if (pattern === 'strands-single-agent') {
-      activeParser = strandsParser;
-      console.log(`Using Strands parser for pattern: ${pattern}`);
-    } else if (pattern === 'langgraph-single-agent') {
-      activeParser = langgraphParser;
-      console.log(`Using LangGraph parser for pattern: ${pattern}`);
-    } else {
-      throw new Error(
-        `Unsupported agent pattern: "${pattern}". ` +
-        `Supported patterns: "strands-single-agent", "langgraph-single-agent". ` +
-        `To add support for this pattern, create a parser file and update loadParser() in agentCoreService.js.`
-      );
-    }
-    
-    return activeParser;
-  } catch (error) {
-    console.error("Failed to load agent pattern:", error);
-    // Default to Strands parser as fallback
-    console.warn("Defaulting to Strands parser");
-    activeParser = strandsParser;
-    return activeParser;
-  }
-};
-
-// Generate a UUID-like string that meets AgentCore requirements (min 33 chars)
+// Generate a UUID
 const generateId = () => {
-  const timestamp = Date.now().toString(36)
-  
-  // Use cryptographically secure random number generation
-  const getSecureRandom = () => {
-    const array = new Uint32Array(1)
-    crypto.getRandomValues(array)
-    return array[0].toString(36)
-  }
-  
-  const random1 = getSecureRandom()
-  const random2 = getSecureRandom()
-  const random3 = getSecureRandom()
-  return `${timestamp}-${random1}-${random2}-${random3}`
+  return crypto.randomUUID();
 }
 
 // Configuration - will be populated from aws-exports.json
@@ -104,9 +50,6 @@ export const invokeAgentCore = async (query, sessionId, onStreamUpdate, accessTo
       throw new Error("Agent Runtime ARN not configured")
     }
 
-    // Load the appropriate parser
-    const parser = await loadParser();
-
     // Bedrock Agent Core endpoint
     const endpoint = `https://bedrock-agentcore.${AGENT_CONFIG.AWS_REGION}.amazonaws.com`
 
@@ -168,8 +111,11 @@ export const invokeAgentCore = async (query, sessionId, onStreamUpdate, accessTo
 
           for (const line of lines) {
             if (line.trim()) {
-              // Use the dynamically loaded parser
-              completion = parser.parseStreamingChunk(line, completion, onStreamUpdate);
+              // Both parsers try each event, each processes its format and ignores others
+              // No overlap between formats, so both can safely run
+              // Suggestion: Keep only the parser for your agent type to reduce unnecessary processing
+              completion = strandsParser.parseStreamingChunk(line, completion, onStreamUpdate);
+              completion = langgraphParser.parseStreamingChunk(line, completion, onStreamUpdate);
             }
           }
         }

infra-cdk/config.yaml

@@ -5,4 +5,4 @@ stack_name_base: genaiid-agentcore-starter-pack
 admin_user_email: null # Example: admin@example.com
 
 backend:
-  pattern: strands-single-agent # Available patterns: strands-single-agent
+  pattern: strands-single-agent # Available patterns: strands-single-agent, langgraph-single-agent

infra-cdk/lib/backend-stack.ts

@@ -231,12 +231,6 @@ export class BackendStack extends cdk.NestedStack {
       description: "ARN of the agent memory resource",
       value: memoryArn,
     })
-
-    // Agent pattern output for frontend parser selection
-    new cdk.CfnOutput(this, "AgentPattern", {
-      description: "Agent pattern type (e.g., strands-single-agent, langgraph-single-agent)",
-      value: pattern,
-    })
   }
 
   private createRuntimeSSMParameters(config: AppConfig): void {

patterns/langgraph-single-agent/langgraph_agent.py

@@ -79,6 +79,9 @@ async def create_langgraph_agent(user_id: str, session_id: str, tools: list):
     This function sets up a LangGraph StateGraph that can access tools through
     the AgentCore Gateway and maintains conversation memory.
     """
+    system_prompt = """You are a helpful assistant with access to tools via the Gateway.
+    When asked about your tools, list them and explain what they do."""
+
     # Create Bedrock model
     bedrock_model = ChatBedrock(
         model_id="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
@@ -103,7 +106,8 @@ async def create_langgraph_agent(user_id: str, session_id: str, tools: list):
         graph = create_react_agent(
             model=bedrock_model,
             tools=tools,
-            checkpointer=checkpointer
+            checkpointer=checkpointer,
+            prompt=system_prompt
         )
 
         print("[AGENT] Agent created successfully with Gateway tools")

scripts/post-deploy.py

@@ -60,7 +60,7 @@ def generate_aws_exports(stack_name):
             output_map[output['OutputKey']] = output['OutputValue']
 
         # Validate required outputs
-        required = ["CognitoClientId", "CognitoUserPoolId", "AmplifyUrl", "RuntimeArn", "FeedbackApiUrl", "AgentPattern"]
+        required = ["CognitoClientId", "CognitoUserPoolId", "AmplifyUrl", "RuntimeArn", "FeedbackApiUrl"]
         missing = [key for key in required if key not in output_map]
 
         if missing:
@@ -76,7 +76,6 @@ def generate_aws_exports(stack_name):
             "scope": "email openid profile",
             "automaticSilentRenew": True,
             "agentRuntimeArn": output_map['RuntimeArn'],
-            "agentPattern": output_map['AgentPattern'],
             "awsRegion": region,
             "feedbackApiUrl": output_map['FeedbackApiUrl'],
         }