Merge pull request #2 from aws-samples/fix/hardcoding

Fix hardcoding-related deployment issues

Author: najmia

.gitignore

@@ -54,6 +54,7 @@ logs/
 *.tfstate.*
 .terraform/
 .terraform.lock.hcl
+backend.hcl
 terraform.tfvars
 
 # AWS
@@ -75,7 +76,6 @@ terraform.tfvars
 
 # Dependencies
 node_modules/
-uv.lock
 
 # Temporary files
 *.tmp

README.md

@@ -65,19 +65,18 @@ Explore the README.md file under the **infra** directory for more details on the
 
 ### Test locally
 
-1. **Initialize the project**:
+1. **Initialize the project and dependencies**:
 ```bash
 cd cx-agent-backend
-pip install uv
-uv init
+uv venv
+uv sync --all-extras --frozen
 ```
-2. **Install dependencies**: `uv sync --frozen`
-3. **Run locally**: 
+2. **Run locally**: 
 ```bash
 cd src
 uv run run.py
 ```
-4. **Test the health endpoint**:
+3. **Test the health endpoint**:
 ```bash
 curl http://localhost:8080/ping
 ```
@@ -106,6 +105,8 @@ curl -X POST http://localhost:8080/api/v1/feedback \
 5. **Run the Streamlit app**:
 ```bash
 cd cx-agent-frontend
+uv venv
+uv sync --frozen
 uv run streamlit run src/app.py --server.port 8501 --server.address 127.0.0.1
 ```
 6. Access the web interface at `http://localhost:8501`

agentcore_runtime_deployment.ipynb

@@ -6,7 +6,9 @@
    "source": [
     "# LangGraph Agent Deployment to Amazon Bedrock AgentCore\n",
     "\n",
-    "This notebook demonstrates how to deploy a FastAPI LangGraph agent to Amazon Bedrock AgentCore Runtime and invoke it."
+    "This notebook demonstrates how to deploy a FastAPI LangGraph agent to Amazon Bedrock AgentCore Runtime and invoke it.\n",
+    "\n",
+    "It's tested to run in the Python virtual environment created in `cx-agent-backend`"
    ]
   },
   {
@@ -46,21 +48,26 @@
    "outputs": [],
    "source": [
     "# Configuration\n",
-    "AWS_REGION = \"us-east-1\"\n",
+    "AWS_REGION = os.environ.get(\"AWS_REGION\", os.environ.get(\"AWS_DEFAULT_REGION\", \"us-east-1\"))\n",
     "AWS_ACCOUNT_ID = boto3.client('sts').get_caller_identity()['Account']\n",
     "ECR_REPOSITORY = \"langgraph-cx-agent\"\n",
     "IMAGE_TAG = \"latest\"\n",
     "ECR_URI = f\"{AWS_ACCOUNT_ID}.dkr.ecr.{AWS_REGION}.amazonaws.com/{ECR_REPOSITORY}:{IMAGE_TAG}\"\n",
-    "AGENT_RUNTIME_NAME = \"langgraph_cx_agent_110902\"\n",
+    "AGENT_RUNTIME_NAME = \"langgraph_cx_agent\"\n",
     "AGENT_RUNTIME_ROLE_ARN = f\"arn:aws:iam::{AWS_ACCOUNT_ID}:role/agentic-ai-bedrock-role\" # deployed in the prerequisite section\n",
-    "USER_POOL_ID = \"<your-user-pool-id>\"  # Replace with your Cognito User Pool ID from the terraform deployment output\n",
-    "CLIENT_ID = \"<your-client-id>\"  # Replace with your Cognito App Client ID from the terraform deployment output\n",
-    "CLIENT_SECRET = \"<your-client-secret>\"  # Replace with your Cognito App Client Secret from the AWS console\n",
+    "USER_POOL_ID = \"\"  # TODO: Enter Cognito User Pool ID from the terraform deployment output\n",
+    "CLIENT_ID = \"\"  # TODO: Enter Cognito App Client ID from the terraform deployment output\n",
+    "CLIENT_SECRET = \"\"  # TODO: Enter Cognito App Client Secret from the AWS console\n",
     "\n",
     "print(f\"Account ID: {AWS_ACCOUNT_ID}\")\n",
     "print(f\"Region: {AWS_REGION}\")\n",
     "print(f\"ECR URI: {ECR_URI}\")\n",
-    "print(f\"User Pool ID: {USER_POOL_ID}\")"
+    "print(f\"User Pool ID: {USER_POOL_ID}\")\n",
+    "\n",
+    "if not (USER_POOL_ID and CLIENT_ID and CLIENT_SECRET):\n",
+    "    raise ValueError(\n",
+    "        \"Please set USER_POOL_ID, CLIENT_ID, and CLIENT_SECRET above\"\n",
+    "    )\n"
    ]
   },
   {
@@ -90,7 +97,10 @@
    "outputs": [],
    "source": [
     "# Login to ECR\n",
-    "!aws ecr get-login-password --region {AWS_REGION} | docker login --username AWS --password-stdin {AWS_ACCOUNT_ID}.dkr.ecr.{AWS_REGION}.amazonaws.com"
+    "!aws ecr get-login-password --region {AWS_REGION} | docker login --username AWS --password-stdin {AWS_ACCOUNT_ID}.dkr.ecr.{AWS_REGION}.amazonaws.com\n",
+    "\n",
+    "# Alternatively with Finch:\n",
+    "#!aws ecr get-login-password --region {AWS_REGION} | finch login --username AWS --password-stdin {AWS_ACCOUNT_ID}.dkr.ecr.{AWS_REGION}.amazonaws.com"
    ]
   },
   {
@@ -100,7 +110,10 @@
    "outputs": [],
    "source": [
     "# Build and tag Docker image for ARM64\n",
-    "!cd cx-agent-backend && docker buildx build --platform linux/arm64 -t {ECR_URI} --push ."
+    "!cd cx-agent-backend && docker buildx build --platform linux/arm64 -t {ECR_URI} --push .\n",
+    "\n",
+    "# Alternatively with Finch:\n",
+    "#!cd cx-agent-backend && finch build --platform linux/arm64 -t {ECR_URI} . && finch push {ECR_URI}"
    ]
   },
   {
@@ -177,7 +190,7 @@
     "        os.environ[var] = getpass.getpass(f\"Please provide your {var}\")\n",
     "\n",
     "\n",
-    "_set_if_undefined(\"USERNAME\")\n",
+    "_set_if_undefined(\"EMAIL_USERNAME\")\n",
     "_set_if_undefined(\"TEMPORARY_PASSWORD\")\n",
     "_set_if_undefined(\"PERMANENT_PASSWORD\")"
    ]
@@ -189,7 +202,7 @@
    "outputs": [],
    "source": [
     "# Access values later in the notebook\n",
-    "username = os.environ['USERNAME']\n",
+    "username = os.environ['EMAIL_USERNAME']\n",
     "temp_password = os.environ['TEMPORARY_PASSWORD']\n",
     "permanent_password = os.environ['PERMANENT_PASSWORD']"
    ]
@@ -280,7 +293,8 @@
     "    )\n",
     "    \n",
     "    access_token = response['AuthenticationResult']['AccessToken']\n",
-    "    print(f\"Access token: {access_token}\")\n",
+    "    os.environ[\"COGNITO_TOKEN\"] = access_token\n",
+    "    print(\"Access token fetched\")\n",
     "    \n",
     "except Exception as e:\n",
     "    print(f\"Error: {e}\")"
@@ -303,7 +317,7 @@
     "import urllib.parse\n",
     "import json\n",
     "\n",
-    "def invoke_agent(message, agent_arn, auth_token, session_id, region=\"us-east-1\"):\n",
+    "def invoke_agent(message, agent_arn, auth_token, session_id, region=AWS_REGION):\n",
     "    \"\"\"Invoke Bedrock AgentCore runtime with a message.\"\"\"\n",
     "    escaped_agent_arn = urllib.parse.quote(agent_arn, safe='')\n",
     "    url = f\"https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{escaped_agent_arn}/invocations?qualifier=DEFAULT\"\n",
@@ -338,8 +352,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "AUTH_TOKEN = \"\"\n",
-    "AGENT_ARN = \"\"\n",
+    "AUTH_TOKEN = os.environ[\"COGNITO_TOKEN\"]  # (See above)\n",
+    "AGENT_ARN = agent_runtime_arn\n",
     "SESSION_ID = str(uuid.uuid4())\n",
     "    \n",
     "result = invoke_agent(\"Hello, can you help me?\", AGENT_ARN, AUTH_TOKEN, SESSION_ID)\n",
@@ -393,7 +407,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -407,7 +421,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

cx-agent-backend/pyproject.toml

@@ -4,30 +4,31 @@ version = "0.1.0"
 description = "Clean Architecture CX Agent Backend"
 requires-python = ">=3.11"
 dependencies = [
+    "aws-opentelemetry-distro>=0.1.0",
+    "boto3>=1.34.0",
+    "dependency-injector>=4.41.0",
     "fastapi>=0.104.0",
-    "uvicorn[standard]>=0.24.0",
-    "pydantic>=2.5.0",
-    "pydantic-settings>=2.1.0",
     "langchain>=0.1.0",
+    "langchain-aws>=0.1.0",
     "langchain-core>=0.1.0",
     "langchain-openai>=0.1.0",
-    "langchain-aws>=0.1.0",
-    "langgraph>=0.1.0",
     "langfuse>=2.0.0",
-    "boto3>=1.34.0",
+    "langgraph>=0.1.0",
+    "pydantic>=2.5.0",
+    "pydantic-settings>=2.1.0",
     "structlog>=23.2.0",
-    "dependency-injector>=4.41.0",
     "tavily-python>=0.3.0",
-    "aws-opentelemetry-distro>=0.1.0",
+    "uvicorn[standard]>=0.24.0",
 ]
 
 [project.optional-dependencies]
 dev = [
+    "httpx>=0.25.0",
+    "ipykernel>=6.30.1",
+    "mypy>=1.7.0",
     "pytest>=7.4.0",
     "pytest-asyncio>=0.21.0",
-    "httpx>=0.25.0",
     "ruff>=0.1.0",
-    "mypy>=1.7.0",
 ]
 
 [build-system]
@@ -43,4 +44,4 @@ line-length = 88
 
 [tool.mypy]
 python_version = "3.11"
-strict = true
+strict = true

cx-agent-backend/src/domain/services/conversation_service.py

@@ -30,7 +30,7 @@ async def start_conversation(self, user_id: str) -> Conversation:
         return conversation
 
     async def send_message(
-        self, conversation_id: UUID, content: str, model: str = "gpt-4o-mini"
+        self, conversation_id: UUID, content: str, model: str
     ) -> tuple[Message, list[str]]:
         """Send a message and get AI response."""
         # Get conversation

cx-agent-backend/src/infrastructure/adapters/bedrock_guardrail_service.py

@@ -16,7 +16,7 @@
 class BedrockGuardrailService(GuardrailService):
     """Bedrock Guardrails implementation."""
 
-    def __init__(self, guardrail_id: str, region: str = "us-east-1"):
+    def __init__(self, guardrail_id: str, region: str | None = None):
         self._guardrail_id = guardrail_id
         self._client = boto3.client("bedrock-runtime", region_name=region)
 

cx-agent-backend/src/infrastructure/aws/secret_reader.py

@@ -4,7 +4,7 @@
 from infrastructure.config.settings import settings
 
 class AWSSecretsReader(SecretReader):
-    def read_secret(self, name: str, region: str = "us-east-1") -> str:
+    def read_secret(self, name: str) -> str:
         client = boto3.client("secretsmanager", region_name=settings.aws_region)
         try:
             response = client.get_secret_value(SecretId=name)

cx-agent-backend/src/infrastructure/config/settings.py

@@ -1,4 +1,5 @@
 """Application settings using Pydantic Settings."""
+from os import environ
 
 from pydantic import Field
 from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -22,10 +23,16 @@ class Settings(BaseSettings):
     debug: bool = Field(default=False, description="Debug mode")
 
     # LLM Settings
-    default_model: str = Field(default="gpt-4o-mini", description="Default LLM model")
+    default_model: str = Field(
+        default="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+        description="Default LLM model",
+    )
 
     # AWS Settings
-    aws_region: str = Field(default="us-east-1", description="AWS region")
+    aws_region: str = Field(
+        default=environ.get("AWS_REGION", environ.get("AWS_DEFAULT_REGION", "us-east-1")),
+        description="AWS region",
+    )
 
     # Logging
     log_level: str = Field(default="INFO", description="Log level")

cx-agent-backend/src/main.py

@@ -79,7 +79,7 @@ async def invocations(request: dict, http_request: Request):
         internal_request = SendMessageRequest(
             prompt=prompt,
             conversation_id=None,
-            model="gpt-4o-mini"
+            model=settings.default_model
         )
 
         # Call internal endpoint