Configure agents and models

Set defaults when you create or update the harness:

# Create a project if one does not already exist.
agentcore create

# Add a harness to the project
agentcore add harness \
  --name research-agent \
  --model-id us.anthropic.claude-sonnet-4-6-20250514-v1:0 \
  --system-prompt "You are a research assistant." \
  --tools agentcore-browser

agentcore deploy

Override on an invocation:

# Switch the model for one call
agentcore invoke --harness research-agent \
  --model-id us.anthropic.claude-opus-4-5-20251101-v1:0 \
  "Summarize this research paper"

# Swap tools for one call
agentcore invoke --harness research-agent \
  --tools agentcore-browser,code-interpreter \
  "Plot the citation counts as a bar chart"

Overridable at invoke time: --model-id, --tools, --system-prompt, --max-iterations, --max-tokens, --harness-timeout, --skills, --allowed-tools, --actor-id. Add --verbose to print raw streaming JSON events for debugging.

To change defaults permanently, edit app/<name>/harness.json and run agentcore deploy.

Defaults on create-harness:

aws bedrock-agentcore-control create-harness \
  --harness-name "research-agent" \
  --execution-role-arn "arn:aws:iam::123456789012:role/MyHarnessRole" \
  --system-prompt '[{"text": "You are a research assistant."}]' \
  --tools '[{"type": "agentcore_browser", "name": "browser"}]'

Overrides per invocation:

response = client.invoke_harness(
    harnessArn=HARNESS_ARN,
    runtimeSessionId=SESSION_ID,
    # These apply only to this call; the harness defaults stay intact
    model={"bedrockModelConfig": {"modelId": "us.anthropic.claude-opus-4-5-20251101-v1:0"}},
    systemPrompt=[{"text": "You are a terse research assistant. One paragraph answers only."}],
    tools=[
        {"type": "agentcore_browser", "name": "browser"},
        {"type": "agentcore_code_interpreter", "name": "code_interpreter"},
    ],
    messages=[{"role": "user", "content": [{"text": "Summarize this paper as a bullet list."}]}],
)

To change defaults permanently, use update-harness.

Add an API key to AgentCore Identity:

agentcore add credential --type api-key --name my-openai-key --api-key $OPENAI_API_KEY
agentcore deploy

Invoke with the OpenAI key you just added:

agentcore invoke --harness my-agent \
  --model-provider open_ai \
  --model-id gpt-5.4 \
  --api-key-arn arn:aws:bedrock-agentcore:us-west-2:123456789012:token-vault/default/apikeycredentialprovider/my-openai-key \
  --session-id "$(uuidgen)" \
  "Analyze this codebase and identify performance bottlenecks."

Switch back to Bedrock on the same session:

agentcore invoke --harness my-agent \
  --model-id us.anthropic.claude-sonnet-4-5-20250514-v1:0 \
  --session-id "$(uuidgen)" \
  "Now suggest fixes for the top three issues."

Register an API key with AgentCore Identity:

aws bedrock-agentcore-control create-api-key-credential-provider \
  --name my-openai-key \
  --api-key "$OPENAI_API_KEY"

Switch providers across turns of the same session:

# Turn 1: Bedrock
response = client.invoke_harness(
    harnessArn=HARNESS_ARN,
    runtimeSessionId=SESSION_ID,
    model={"bedrockModelConfig": {"modelId": "us.anthropic.claude-sonnet-4-5-20250514-v1:0"}},
    messages=[{"role": "user", "content": [{"text": "Analyze this codebase."}]}],
)

# Turn 2: OpenAI on the same session
response = client.invoke_harness(
    harnessArn=HARNESS_ARN,
    runtimeSessionId=SESSION_ID,
    model={
        "openAiModelConfig": {
            "modelId": "gpt-5.4",
            "apiKeyArn": "arn:aws:bedrock-agentcore:us-west-2:123456789012:token-vault/default/apikeycredentialprovider/my-openai-key",
        }
    },
    messages=[{"role": "user", "content": [{"text": "Now suggest fixes for the top three issues."}]}],
)