Fix/redis connection failure

examples/aws-serverless/adk/config.yaml

@@ -5,4 +5,4 @@ session:
   type: redis
   redis:
     prefix: "ak:adk:example:"
-    url: "redis://dev-examples-redis.qaandw.0001.apse2.cache.amazonaws.com:6379"
+    url: "redis://ak-openai-serverless-dev-examples-redis.qaandw.0001.apse2.cache.amazonaws.com:6379"

examples/aws-serverless/adk/deploy/main.tf

@@ -15,7 +15,7 @@ module "serverless_agents" {
   region               = var.region
   vpc_id               = var.vpc_id
   private_subnet_ids   = var.private_subnet_ids
-  memory_size          = 512
+  memory_size          = 1024
   timeout              = 60
   product_display_name = "AK Google ADK Serverless Example"
 

examples/aws-serverless/adk/lambda.py

@@ -6,19 +6,19 @@
 # Math specialist agent
 math_agent = Agent(
     name="math",
-    model=LiteLlm(model="openai/gpt-4o-mini"),
+    model=LiteLlm(model="openai/gpt-4.1-mini"),
     description="Specialist agent for math questions",
     instruction="""
     You provide help with math problems.
-    Explain your reasoning at each step and include examples.
+    no reasoning and no need for steps explanation. Just give the final answer.
     If prompted for anything else you refuse to answer.
     """,
 )
 
 # General purpose agent
 history_agent = Agent(
     name="history",
-    model=LiteLlm(model="openai/gpt-4o-mini"),
+    model=LiteLlm(model="openai/gpt-4.1-mini"),
     description="Agent for history questions",
     instruction="""
     You provide assistance with history queries.
@@ -28,7 +28,7 @@
 
 triage_agent = LlmAgent(
     name="triage",
-    model=LiteLlm(model="openai/gpt-4o-mini"),
+    model=LiteLlm(model="openai/gpt-4.1-mini"),
     description="Agent that routes the user to the appropriate specialist agent (math or history).",
     instruction="""
     You determine which agent to use based on the user's question.

examples/aws-serverless/crewai/config.yaml

@@ -4,5 +4,5 @@ logging:
 session:
   type: redis
   redis:
-    prefix: "ak:langgraph:example:"
+    prefix: "ak:crewai:example:"
     url: "redis://ak-openai-serverless-dev-examples-redis.qaandw.0001.apse2.cache.amazonaws.com:6379"

examples/aws-serverless/crewai/deploy/deploy.sh

@@ -9,8 +9,7 @@ create_deployment_package() {
     if [[ ${1-} != "local" ]]; then
       uv pip install -r requirements.txt --target=dist/data
     else
-      uv pip install -r requirements.txt --target=dist/data  --find-links ../../../ak-py/dist
-      uv pip install --force-reinstall --target=dist/data --find-links ../../../ak-py/dist agentkernel[redis,crewai,test] || true
+      uv pip install -r requirements.txt --target=dist/data --find-links ../../../ak-py/dist
     fi
     cp -r lambda.py config.yaml dist/data
     popd || exit 1

examples/aws-serverless/crewai/deploy/main.tf

@@ -15,7 +15,7 @@ module "serverless_agents" {
   region               = var.region
   vpc_id               = var.vpc_id
   private_subnet_ids   = var.private_subnet_ids
-  memory_size          = 512
+  memory_size          = 1024
   timeout              = 60
   product_display_name = "AK CrewAI Serverless Example"
 

examples/aws-serverless/crewai/lambda.py

@@ -1,21 +1,29 @@
+import os
+
 from agentkernel.aws import Lambda
 from agentkernel.crewai import CrewAIModule
 
+os.environ["CREWAI_TRACING_ENABLED"] = "false"
+
 from crewai import Agent
 
 math_agent = Agent(
     role="math",
     goal="Specialist agent for math questions",
-    backstory="You provide help with math problems. Explain your reasoning at each step and include examples. \
+    backstory="You provide help with math problems. no reasoning and no need for steps explanation. Just give the final answer. \
         If prompted for anything else you refuse to answer.",
     verbose=False,
+    tracing=False,
+    model="openai/gpt-4.1-mini",
 )
 
 history_agent = Agent(
     role="history",
     goal="Specialist agent for historical questions",
     backstory="You provide assistance with historical queries. Explain important events and context clearly.",
     verbose=False,
+    tracing=False,
+    model="openai/gpt-4.1-mini",
 )
 
 CrewAIModule([math_agent, history_agent])

examples/aws-serverless/crewai/lambda_test.py

@@ -42,4 +42,4 @@ async def http_client():
 @pytest.mark.order(1)
 async def test_math_agent(http_client):
     response = await http_client.send("What is 23 multiplied by 17?")
-    Test.compare(response, ["23 multiplied by 17 equals 391"])
+    Test.compare(response, ["391"])

examples/aws-serverless/langgraph/build.sh

@@ -11,6 +11,6 @@ if [[ ${1-} != "local" ]]; then
   uv sync --all-extras
 else
   # For local development of agentkernel, you can force reinstall from local dist
-  uv sync --find-links ../../../ak-py/dist --all-extras
+  uv sync --find-links ../../../ak-py/dist --all-extras 
   uv pip install --force-reinstall --find-links ../../../ak-py/dist agentkernel[redis,langgraph,test] || true
 fi

examples/aws-serverless/langgraph/deploy/deploy.sh

@@ -9,8 +9,7 @@ create_deployment_package() {
     if [[ ${1-} != "local" ]]; then
       uv pip install -r requirements.txt --target=dist/data
     else
-      uv pip install -r requirements.txt --target=dist/data  --find-links ../../../ak-py/dist
-      uv pip install --force-reinstall --target=dist/data --find-links ../../../ak-py/dist agentkernel[langgraph,redis,test] || true
+      uv pip install -r requirements.txt --target=dist/data --find-links ../../../ak-py/dist
     fi
     cp -r lambda.py custom_agent.py config.yaml dist/data
     popd || exit 1

examples/aws-serverless/langgraph/deploy/main.tf

@@ -15,7 +15,7 @@ module "serverless_agents" {
   region               = var.region
   vpc_id               = var.vpc_id
   private_subnet_ids   = var.private_subnet_ids
-  memory_size          = 512
+  memory_size          = 1024
   product_display_name = "AK Langraph Serverless Example"
 
   # Environment variables passed to lambda

examples/aws-serverless/langgraph/lambda.py

@@ -6,7 +6,7 @@
 from custom_agent import CustomAgent
 from langgraph.prebuilt import create_react_agent
 
-model = ChatOpenAI(model="gpt-4o-mini", temperature=0.0)
+model = ChatOpenAI(model="gpt-4.1-mini", temperature=0.0)
 
 # Math agent: Handles mathematical problems and calculations
 # Uses LangGraph's ReAct framework to provide step-by-step mathematical solutions

examples/aws-serverless/langgraph/pyproject.toml

@@ -3,13 +3,18 @@ name = "aws-serverless-langgraph"
 version = "0.1.0"
 description = "Demo of LangGraph based agents running in Agent Kernel on AWS Lambda"
 readme = "README.md"
-requires-python = ">=3.12"
+requires-python = ">=3.12,<3.13"
 dependencies = [
     "agentkernel[langgraph,redis]>=0.4.0",
     "langchain-litellm>=0.2.2",
-    "langchain-openai>=0.3.28",
+    "langchain-openai==1.1.6",
+    "langgraph==1.0.5",           
+    "langgraph-checkpoint==3.0.1",
+    "langgraph-prebuilt==1.0.5",  
+    "langgraph-sdk==0.3.1",
     "langgraph-supervisor>=0.0.29",
-    "openai>=1.99.1",
+    "langsmith==0.5.0",
+    "openai>=1.99.1",             
 ]
 
 [dependency-groups]