feat(export): export harnesses to standalone Strands agents with connections#1630
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padmak30 wants to merge 8 commits into
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feat(export): export harnesses to standalone Strands agents with connections#1630padmak30 wants to merge 8 commits into
padmak30 wants to merge 8 commits into
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Extend `agentcore export harness` to faithfully export harnesses that reference
EXTERNAL AgentCore resources, in-project (--name) or by ARN (--arn), with no
manual IAM/wiring overrides.
- Auto-populate `connections[]` (memory/gateway/runtime/browser/codeInterpreter)
on the exported runtime instead of emitting IAM prose notes. Discovery env-var
names are derived from a single source of truth in schemas/connections.ts and
kept in lockstep with @aws/agentcore-cdk, so the names baked into the generated
agent code match what deploy injects.
- New --arn source: fetch a harness from the control plane and map it
(fetch-harness-spec.ts) — model (incl. LiteLLM), memory, runtime environment,
skills (git auth carried through), and tools.
- Add LiteLLM model-provider support (provider-prefixed model_ids; keyless via
IAM for bedrock/, apiKeyArn otherwise) across schema, template, and telemetry.
- Carry gateway outbound-auth (awsIam | none | oauth{providerArn, scopes,
grantType, customParameters}) end-to-end; render customParameters as valid
Python via safeJson and thread grantType -> auth_flow.
- Copy path-skill directories for generated-Dockerfile Container builds.
Verified live end-to-end: create harness -> export (in-project and by ARN) ->
deploy -> invoke; the agent reaches the external memory + gateway at runtime.
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Package TarballHow to installgh release download pr-1630-tarball --repo aws/agentcore-cli --pattern "*.tgz" --dir /tmp/pr-tarball
npm install -g /tmp/pr-tarball/aws-agentcore-0.20.2.tgz |
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Reviewed the PR end-to-end. Looks good to merge.
Highlights of what I checked:
- Test quality — No excessive mocking. The new unit tests (
fetch-harness-spec.test.ts,arn-s3-chain.test.ts,harness-mapper.test.ts,harness-action.test.ts) use pure data fixtures and exercise the real mappers/builders without stubbing fs or the AWS SDK; the network boundary (getHarness) is correctly drawn at the wrapper rather than mocked inside the unit tests. - Telemetry —
export.harnessis registered inCOMMAND_SCHEMASwithbuild_type,model_provider(incl.lite_llm),has_memory,has_gateway,has_container,has_execution_limits,notes_count. The action wraps execution inwithCommandRunTelemetryand records attrs after work is done, with a correctLiteLLM → lite_llmnormalization beforestandardize(). - Connection-name handshake — env-var name derivation (
connectionIdForTarget,connectionEnvToken,connectionEnvVarName) lives in one place (schema/schemas/connections.ts) and is consumed by both the CLI mapper and (per the description) the CDK wiring, which is the right shape for keeping the two repos in lockstep. - --arn fidelity —
mapApiHarnessToSpecdefensively handles both control-plane (PascalCase) and lowercased skill shapes, theSDK_UNKNOWN_MEMBERmanaged-memory fallback, and explicitly does NOT carryexecutionRoleArn(with a clear comment explaining why CDK needs to own the role for Container/connection grants). - External-resource modeling — Memory/gateway/runtime/browser/codeInterpreter all flow through typed
Connectionentries onAgentEnvSpecinstead of prose IAM notes; malformed browser/CI ARNs fall back to the AWS-managed default with a clear note rather than silently using the wrong target. S3 skills generate an inline policy +additionalPoliciesentry, with malformed-URI warnings rather than silent AccessDenied. - OAuth gateway end-to-end —
grantType → auth_flowmapping (CLIENT_CREDENTIALS→M2M, USER_FEDERATION→USER_FEDERATION) is correct; TOKEN_EXCHANGE is surfaced as a manual-step note since the decorator can't express it.customParametersrendered viasafeJsonis valid Python because the schema constrains values toRecord<string,string>. - Path-skill copy — Correctly rejects absolute paths and traversal, only copies dirs that resolve under the harness dir, and emits a verify-note for the unresolved case (which is the expected outcome for
--arn-fetched harnesses).
Caveats already called out in the PR description:
- The schema additions (
AgentEnvSpec.connections,AgentEnvSpec.additionalPolicies) require the CDK construct PR (aws/agentcore-l3-cdk-constructs#291) to merge and publish first — that checkbox is correctly left unchecked.
Nothing blocking from my read.
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Review fixes for the harness-export connections feature:
- main.py template: emit `import os` when browserIdentifierEnvVar or
codeInterpreterIdentifierEnvVar is set. A custom browser/code-interpreter
ARN renders `os.getenv(...)` at module scope, but `import os` was gated only
on filesystem mounts / file_operations / git-cred skills — so a Container
export with a custom tool ARN and none of those produced a main.py that
crashed at import with NameError. Snapshot updated.
- fetch-harness-spec: throw an early ValidationError when an --arn VPC harness
is missing explicit subnets/securityGroups, instead of emitting
networkMode:'VPC' with no networkConfig and crashing later in
writeProjectSpec's schema validation after the agent dir/code were written.
- connections.ts: drop the dead exported `connectionEnvVarName` (imported by
neither repo) and correct the "single source of truth" comment to name the
helpers actually shared across repos (connectionEnvToken / connectionTokenFor).
- harness-action: move the inline `import('../../../schema').HarnessSpec` type
to the top-of-file import (AGENTS.md: no inline imports).
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…ng it
A harness-owned ("managed") memory is a real resource with a service-populated
ARN once the harness is READY. mapMemory previously collapsed it to a bare
`{ mode: 'managed' }`, which resolveMemoryProviders ignores — so the exported
agent silently got no memory at all.
Map managedMemoryConfiguration.arn to `{ mode: 'existing', arn }` so it flows
through the existing external-memory path: a `memory` connection with
access: readwrite (IAM scoped to the ARN + discovery env var at deploy). The
bare `{ mode: 'managed' }` is now only a fallback for the no-ARN case
(unprovisioned harness, or an SDK-unknown variant); comments call out that this
fallback is not resolved downstream and where to wire it if needed.
- Type managedMemoryConfiguration on the harness client interface (was read via
`as Record<string, unknown>`); agentCoreMemoryConfiguration is now optional
since exactly one arm is populated.
- Tests: provisioned managed memory (with arn) -> existing-by-arn; managed
without arn -> managed; SDK-unknown -> managed.
Verified live: re-exporting a code-interpreter harness whose managed memory has
an ARN now emits a memory connection in agentcore.json (previously absent).
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A harness bedrockModelConfig whose apiFormat is `responses`/`chat_completions` (e.g. openai.gpt-5.5, openai.gpt-oss-120b) is served via the Bedrock Mantle OpenAI-compatible endpoint, NOT the Converse API. Export previously keyed only on the provider, generating a plain BedrockModel for these — so invocation failed at runtime with "ConverseStream ... The provided model identifier is invalid". Generate an OpenAI-style Mantle client instead: - load.py: build OpenAIModel (chat_completions) / OpenAIResponsesModel (proprietary responses) / MantleCompatResponsesModel (open-source responses), against the Mantle base URL (/openai/v1 for proprietary, /v1 for gpt-oss), authenticated with a short-lived Bedrock bearer token (region from AWS_REGION). - harness-mapper: detect Mantle, thread apiFormat/proprietary/params into the render config, and emit a bedrock-mantle IAM policy (CreateInference + CallWithBearerToken) via additionalPolicies — the runtime role's default bedrock:InvokeModel grant does not cover the bedrock-mantle service. - Add openai + aws-bedrock-token-generator deps and vend model/mantle_compat.py. Verified live end-to-end: export by ARN -> deploy -> invoke an openai.gpt-5.5 Mantle harness returns a real completion (previously the ConverseStream error).
Removed the "No AWS deployment target configured" note. It warned that `agentcore deploy` would fail with `Target "default" not found` when aws-targets.json is empty, but deploy already handles that case interactively (ensure-target.ts prompts for account/region and writes a default target). The note described a failure the deploy flow prevents, so it was noise.
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Description
Extend
agentcore export harnessto faithfully export harnesses that reference external AgentCore resources — in-project (--name) or by ARN (--arn) — with no manual IAM/wiring overrides.connections[](memory/gateway/runtime/browser/codeInterpreter) on the exported runtime instead of emitting IAM prose notes. Discovery env-var names are derived from a single source of truth inschemas/connections.ts, kept in lockstep with@aws/agentcore-cdk, so the names baked into the generated agent code match what deploy injects.--arnsource: fetch a harness from the control plane and map it (fetch-harness-spec.ts) — model (incl. LiteLLM), memory, runtime environment, skills (git auth carried through), and tools.bedrock/,apiKeyArnotherwise) across schema, template, and telemetry.awsIam | none | oauth{providerArn, scopes, grantType, customParameters}) threaded end-to-end;customParametersrendered as valid Python viasafeJsonandgrantType→auth_flow.Related Issue
Closes #
Dependent change
Requires the CDK construct PR: aws/agentcore-l3-cdk-constructs#291 (the connections wiring + lockstep schema). That should merge and publish first.
Type of Change
Testing
npm run test:unit(946 export + schema tests pass)npm run typecheck(clean)npm run lint(clean)src/assets/→ rannpm run test:update-snapshotsand committed the updated snapshot--name) and out-of-project (--arn), deployed, and invoked. In-project and out-of-project produce identical connection wiring. Verified runtime behavior: gateway tool executes, memory recall works, code-interpreter runs, S3/path/private-git skills load, and the OAuth connection's IAM + token-fetch wiring is correct.Checklist
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