cdcoonce/Portfolio_Website

Deploy Skill

Rebuild and deploy the portfolio chat agent Lambda function to AWS.

When to Use

• After updating any file in WebContent/context/
• After modifying lambda/lambda_function.py
• When the user says "deploy", "redeploy", "push to Lambda", or "update the chat agent"

Workflow

1. Rebuild knowledge base — Regenerate lambda/knowledge_base.json from context files
2. Clean previous build — Remove old package/ directory and deployment.zip
3. Install dependencies — Install Python packages for Linux/x86_64 target
4. Package — Copy handler and knowledge base into package, create zip
5. Deploy — Update Lambda function code via AWS CLI
6. Verify — Confirm deployment succeeded

Commands

Step 1: Rebuild Knowledge Base

python scripts/build_knowledge_base.py

Verify output shows expected project count and no errors.

Step 2: Clean and Install Dependencies

cd lambda
rm -rf package/ deployment.zip
pip install -r requirements.txt -t package/ \
  --platform manylinux2014_x86_64 \
  --only-binary=:all: \
  --implementation cp \
  --python-version 3.12

The --platform and --only-binary flags ensure compiled extensions are built for Amazon Linux, not macOS.

Step 3: Package Deployment Zip

cp lambda_function.py knowledge_base.json package/
cd package && zip -r ../deployment.zip . && cd ..

Step 4: Deploy to Lambda

aws lambda update-function-code \
  --function-name portfolio-chat-agent \
  --zip-file fileb://lambda/deployment.zip

Run this from the repository root so the fileb:// path resolves correctly.

Step 5: Verify

Check that the response includes:

• "LastUpdateStatus": "InProgress" or "Successful"
• "FunctionName": "portfolio-chat-agent"
• Updated CodeSha256 value

Configuration

Setting	Value
Function name	portfolio-chat-agent
Runtime	python3.12
Region	us-west-1
Memory	256 MB
Timeout	30 seconds
Architecture	x86_64

Rules

• Never print or log the Anthropic API key. If the AWS CLI response includes environment variables, do not echo them back to the user.
• Always rebuild the knowledge base first. Even if only lambda_function.py changed, rebuilding ensures the knowledge base is current.
• Run from the repository root. The fileb:// path in the deploy command is relative to the working directory.
• Do not modify Lambda environment variables unless the user explicitly asks to update the API key.

Troubleshooting

Problem	Solution
No module named 'pydantic_core._pydantic_core'	Missing --platform flag during pip install — dependencies were built for macOS instead of Linux
Unable to load paramfile fileb://	Wrong working directory — run the deploy command from the repository root
ResourceNotFoundException	Lambda function doesn't exist yet — use aws lambda create-function (see docs/plans/chat-agent/aws-setup.md Step 7)
CodeStorageExceededException	Deployment zip too large — check for unnecessary dependencies in requirements.txt

Reference Documentation

• aws-setup.md — full AWS account setup, IAM roles, initial Lambda creation, and Function URL configuration