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* feat: switch model providers to AWS Bedrock (Claude) and Fireworks (non-Claude)
Migrate off direct provider APIs: AWS Bedrock for Anthropic/Claude via the
cross-region inference profile us.anthropic.claude-opus-4-8, Fireworks AI for
all non-Claude models. Drop OpenAI (gpt-5.5) and Google (gemini-3.5-flash)
entirely. DEFAULT_MODEL_ID is now Bedrock Claude; all Fireworks models stay
freely selectable for the agent and reviewer graphs and via team/profile
defaults.
- pyproject: add langchain-aws (ChatBedrockConverse + boto3)
- options.py: Bedrock Claude entry + default; remove openai/google entries
- model.py: bedrock_converse provider_model_kwargs (effort -> thinking budget),
region pin in make_model, bedrock<->fireworks fallback pairing, AWS_REGION/
FIREWORKS_API_KEY local-dev validation
- server.py: provider-aware fallback kwargs build
- sanitize_thinking_blocks: also sanitize ChatBedrockConverse thinking blocks
- model_fallback: treat transient botocore ClientError codes as fallback-worthy
- eval_jobs: repoint hardcoded eval model id to Bedrock Claude
- tests: repoint dropped model ids; drop obsolete google test module
* fix(bedrock): use adaptive thinking + output_config.effort for Opus 4.8
The handoff spec wired Bedrock Converse thinking as
{type: enabled, budget_tokens: N}, but Opus 4.7+ rejects that with a
ValidationException: thinking.type "enabled" is not supported; it requires
thinking.type "adaptive" plus output_config.effort. Verified by live invoke
against us.anthropic.claude-opus-4-8 (account 328440206208, us-east-1):
the enabled+budget shape 400s, adaptive+effort returns normally.
Map profile effort to additional_model_request_fields:
{thinking: {type: adaptive, display: summarized},
output_config: {effort: <low|medium|high|xhigh|max>}}
reusing anthropic_thinking_for/anthropic_effort_for. Update the two
subagent-model tests asserting the old shape.
* fix(deploy): seed Bedrock/Fireworks models, not the dropped anthropic:/openai: ids
Model selection is store-driven, so seed_store.sh's team_settings/default seed is
what runs in prod. It still seeded the removed providers, which would fail at runtime
after the migration:
- agent/builder: anthropic:claude-opus-4-8 -> bedrock_converse:us.anthropic.claude-opus-4-8
- reviewer: openai:gpt-5.5 (dropped) -> bedrock_converse:us.anthropic.claude-opus-4-8
(set SEED_REVIEWER_MODEL to a Fireworks model for a cross-family reviewer)
- fetch-config REQUIRED_PROVIDER_KEYS default ANTHROPIC_API_KEY,OPENAI_API_KEY ->
FIREWORKS_API_KEY (Bedrock auths via host IAM role; dropping the old keys would
otherwise fail-fast at boot)
- docs (DEPLOYMENT/ROTATION/put-config) updated to match.
Surfaced by the cross-family review + verified against deploy/.
* fix(bedrock): security-review NITs — region resolution, error sanitization, reasoning-block strip
From /sh-security-review (all confirmed-low):
- model.py: resolve region from AWS_REGION OR AWS_DEFAULT_REGION (matches
validate_local_dev_llm_config) so the validated region is the one actually used.
- model_fallback.py: sanitize Bedrock AccessDenied/ResourceNotFound errors to the
error code only, so the role ARN + account id in the raw botocore message never
reach logs or the user channel (CWE-209).
- sanitize_thinking_blocks.py: also strip empty Bedrock reasoning_content blocks
(Converse emits reasoning_content, not thinking) so the middleware is not a no-op
on Bedrock; + unit tests. (Empty blocks replay fine today; defensive.)
* deploy(bedrock): grant instance-role Bedrock invoke + repoint LLM_MODEL_ID / eval model ids
Deployment-readiness for the Bedrock migration (PR #62):
- instance-role.ts: least-privilege bedrock:InvokeModel[WithResponseStream] on the
us.anthropic.claude-opus-4-8 inference-profile ARN + the foundation-model ARN in
each routed region (us-east-1/2, us-west-2). The model runs in the server process
on the box, so the EC2 instance role is the principal. Simulator-verified (allowed
for opus-4-8, implicitDeny for other models) and synth-verified. Passed the
mandatory GPT-4.1 IAM cross-review (no blockers, least-privilege confirmed).
- config-store.ts: IaC SSM LLM_MODEL_ID anthropic:claude-opus-4-8 ->
bedrock_converse:us.anthropic.claude-opus-4-8. This SSM value overrides
seed_store.sh's default via pick precedence, so the seed-script fix alone was
insufficient — both sources now point at the supported Bedrock id.
- infra/README.md + evals/reviewer/config.toml: repoint stale anthropic:/google_genai:
ids to the Bedrock id (config.toml's model_id was an active, now-broken value).
AWS_REGION is already wired via user-data.sh (IMDS -> boot.env), so no change needed there.
* chore(secrets): drop OPENAI/GOOGLE/GROQ key shells (revoked, providers removed)
Those three providers were dropped in the Bedrock/Fireworks migration and their keys
revoked; the live Secrets Manager objects (open-swe-{dev,prod}/{OPENAI,GOOGLE,GROQ}_API_KEY)
were deleted (7-day recovery). Remove them from the IaC so a future cdk deploy does not
recreate the shells, and from fetch-config's mirror array so boot stops requesting them:
- config-store.ts SECRET_VARS + descriptions (28 -> 25 shells)
- fetch-config.sh SECRET_VARS array (kept in lockstep)
- put-config.sh: drop the put_secret lines; ANTHROPIC_API_KEY re-labelled optional
(eval judge only — Bedrock builder/reviewer auth via the host IAM role).
REQUIRED_PROVIDER_KEYS is not set in SSM, so it uses the FIREWORKS_API_KEY default.
75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
import pytest
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from agent.dashboard.options import SUPPORTED_MODELS
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from agent.utils.model import (
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fallback_model_id_for,
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fireworks_reasoning_effort_for,
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provider_model_kwargs,
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)
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def test_fireworks_reasoning_effort_maps_effort() -> None:
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for effort in ("none", "low", "medium", "high", "xhigh", "max"):
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assert fireworks_reasoning_effort_for(effort) == effort
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assert fireworks_reasoning_effort_for("bogus") is None
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assert fireworks_reasoning_effort_for(None) is None
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def test_provider_model_kwargs_for_fireworks() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/kimi-k2p7-code",
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"high",
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max_tokens=16_000,
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)
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assert kwargs["max_tokens"] == 16_000
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assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}
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def test_kimi_k2p7_is_supported() -> None:
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kimi_k2p7 = next(
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(m for m in SUPPORTED_MODELS if m["id"].endswith("kimi-k2p7-code")),
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None,
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)
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assert kimi_k2p7 is not None
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assert kimi_k2p7["efforts"] == ["low", "medium", "high"]
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assert "none" not in kimi_k2p7["efforts"]
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assert kimi_k2p7["default_effort"] == "high"
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kwargs = provider_model_kwargs(kimi_k2p7["id"], "high", max_tokens=16_000)
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assert kwargs["model_kwargs"] == {"reasoning_effort": "high"}
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def test_provider_model_kwargs_for_fireworks_none_disables_reasoning() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/deepseek-v4-pro",
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"none",
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max_tokens=16_000,
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)
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assert kwargs["model_kwargs"] == {"reasoning_effort": "none"}
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def test_provider_model_kwargs_for_fireworks_unknown_effort_omits_reasoning() -> None:
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kwargs = provider_model_kwargs(
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"fireworks:accounts/fireworks/models/glm-5p1",
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"bogus",
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max_tokens=16_000,
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)
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assert "model_kwargs" not in kwargs
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def test_fireworks_falls_back_to_bedrock() -> None:
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assert (
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fallback_model_id_for("fireworks:accounts/fireworks/models/deepseek-v4-pro")
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== "bedrock_converse:us.anthropic.claude-opus-4-8"
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)
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@pytest.mark.parametrize(
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("model_id", "effort"),
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[(m["id"], effort) for m in SUPPORTED_MODELS for effort in m["efforts"]],
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)
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def test_every_supported_effort_translates_to_a_reasoning_kwarg(model_id: str, effort: str) -> None:
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"""Each effort surfaced in the UI must map to a provider reasoning param."""
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kwargs = provider_model_kwargs(model_id, effort, max_tokens=16_000)
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assert set(kwargs) - {"max_tokens"}, (
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f"{model_id} effort {effort!r} did not produce a reasoning kwarg"
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)
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