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Integration adapters

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Five stances, never one passed field

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Ingestion guarantees

• Explicit approval for writes. A batch is validated and lowered but not persisted unless it sets "dryRun": false. The SDK adapters are plan-only by default as well.
• Idempotency. Each event’s key is sha256(ecosystem, adapterId, eventType, nativeEventId). A replay returns replayed; the same key with different content returns conflict. The adapter version and occurredAt are not part of the conflict hash, so re-importing with an approximated time still replays.
• Tenant isolation. The organization comes only from the API key. An event that carries organizationId is rejected.
• Redaction and provenance. Events are stored through the agent-evidence ingest, which redacts payloads, evidence previews, and approval reasons server-side regardless of client claims, scans every other stored value for credentials, and keeps the source schema, adapter version, and parent event for each record.
• Manifest enforcement. An event is accepted only from a registered adapter, for an event type that adapter declares, with the stance the manifest declares for it.

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Adapter manifests and readiness

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Harness²

# Plan only: writes .evalgate/integrations/harness2-<namespace>.jsonl
evalgate harness import-harness2 "$HARNESS2_RUNS_DIR/jb-oc-agg2-s7"

# Ask EvalGate to validate without writing
evalgate harness import-harness2 "$HARNESS2_RUNS_DIR/jb-oc-agg2-s7" --send

# Write events and metadata-only harness outcomes
evalgate harness import-harness2 "$HARNESS2_RUNS_DIR/jb-oc-agg2-s7" --apply

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GEPA and DSPy

import gepa.optimize_anything as oa
from evalgate_sdk.assertions import contains_keywords
from evalgate_sdk.integrations.gepa import EvalGateMetric, GEPACandidateRecorder, gepa_evaluator

metric = EvalGateMetric({
    "keywords": lambda outputs, **_: contains_keywords(outputs, ["refund", "policy"]),
})
recorder = GEPACandidateRecorder()  # local JSONL; nothing is sent yet
result = oa.optimize_anything(
    seed_candidate="Answer the customer.",
    evaluator=gepa_evaluator(lambda candidate, example: run_agent(candidate, example), metric),
    config=oa.GEPAConfig(callbacks=[recorder]),
)
recorder.send(api_key=EVALGATE_API_KEY, base_url="https://www.evalgate.com", apply=False)  # validate

• recorder.send(...) returns ok and a failures list; with apply=True it validates every event first and writes nothing if any would be rejected.
• gepa_evaluator returns (score, side_info), so EvalGate feedback reaches GEPA’s reflection step.
• dspy_feedback_metric(metric) returns dspy.Prediction(score=..., feedback=...), which dspy.GEPA reads as score-with-feedback and dspy.Evaluate sums.
• GEPACandidateRecorder records candidate evaluations, acceptances, rejections, merges, and the best candidate with parent lineage. Pass it to GEPAConfig(callbacks=[...]) or dspy.GEPA(gepa_kwargs={"callbacks": [...]}). Candidate text is hashed unless capture_content=True. recorder.request_promotion(idx) records a pending promotion claim.

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OpenInference

• span kind, input.value / output.value, and flattened llm.input_messages.* / llm.output_messages.* when no value is set;
• model, provider (llm.provider or llm.system), prompt, completion, and total tokens, llm.cost.total, and the JSON llm.invocation_parameters;
• session.id. user.id, whether sent as a span or a resource attribute, is stored only as a SHA-256 digest.