hermes: harden routed vision normalization
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@ -25,7 +25,7 @@ spec:
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ai.bstein.dev/execution: Hermes Kanban with durable direct Codex and Claude Code CLI workers
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ai.bstein.dev/model-policy: Jetson-assisted AUTO routing, low through xhigh, cross-provider fallback
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ai.bstein.dev/placement: rpi5 preferred; Jetson deferred until state storage is available
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ai.bstein.dev/config-rev: "20260816-routed-vision-v3"
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ai.bstein.dev/config-rev: "20260816-routed-vision-v4"
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prometheus.io/scrape: "true"
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prometheus.io/path: /metrics
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prometheus.io/port: "9010"
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@ -226,13 +226,14 @@ def _normalize_input_images(response_input: list[Any]) -> None:
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def image_url_value(part: dict[str, Any]) -> tuple[str | None, str | None]:
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"""Return a Responses URL from URL-object or base64-source forms."""
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raw = part.get("image_url")
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if isinstance(raw, str):
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return raw, None
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candidates = [raw, part.get("source")]
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for candidate in candidates:
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if not isinstance(candidate, dict):
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continue
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def search(candidate: Any, depth: int = 0) -> tuple[str | None, str | None]:
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if isinstance(candidate, str):
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if candidate.startswith(("data:image/", "https://", "http://")):
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return candidate, None
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return None, None
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if not isinstance(candidate, dict) or depth > 4:
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return None, None
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detail = candidate.get("detail")
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url = candidate.get("url")
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if isinstance(url, str) and url.strip():
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@ -249,8 +250,39 @@ def _normalize_input_images(response_input: list[Any]) -> None:
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return f"data:{media_type};base64,{data}", (
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detail if isinstance(detail, str) else None
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)
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for nested in candidate.values():
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nested_url, nested_detail = search(nested, depth + 1)
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if nested_url:
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return nested_url, (
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detail if isinstance(detail, str) else nested_detail
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)
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return None, None
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for candidate in (part.get("image_url"), part.get("source"), part):
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image_url, detail = search(candidate)
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if image_url:
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return image_url, detail
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return None, None
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def image_shape(part: dict[str, Any]) -> str:
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"""Describe only structural types when an upstream image is malformed."""
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def describe(value: Any, depth: int = 0) -> Any:
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if depth > 3:
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return type(value).__name__
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if isinstance(value, dict):
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return {
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str(key)[:40]: describe(nested, depth + 1)
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for key, nested in list(value.items())[:12]
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}
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if isinstance(value, list):
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return [describe(nested, depth + 1) for nested in value[:4]]
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if isinstance(value, str):
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return f"str[{len(value)}]"
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return type(value).__name__
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return json.dumps(describe(part), sort_keys=True, separators=(",", ":"))
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for item in response_input:
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if not isinstance(item, dict):
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continue
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@ -268,7 +300,10 @@ def _normalize_input_images(response_input: list[Any]) -> None:
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if isinstance(detail, str) and detail and "detail" not in part:
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part["detail"] = detail
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if not isinstance(image_url, str) or not image_url.strip():
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raise ValueError("non-empty Responses image URL required")
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raise ValueError(
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"non-empty Responses image URL required; shape="
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+ image_shape(part)
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)
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part["type"] = "input_image"
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part["image_url"] = image_url
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part.pop("source", None)
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@ -824,7 +824,26 @@ def test_codex_broker_auth_and_request_contract(tmp_path: Path, monkeypatch):
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"type": "input_image",
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"image_url": "data:image/png;base64,cHJpdmF0ZQ==",
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}
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with pytest.raises(ValueError, match="non-empty Responses image URL"):
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nested_switchyard_items = [
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{
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"role": "user",
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"content": [
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{
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"type": "input_image",
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"image_url": {
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"image": {
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"original_url": "data:image/png;base64,cHJpdmF0ZQ=="
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}
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},
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}
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],
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}
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]
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nested_image = module._validate_payload(
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{"model": "gpt-5.6-terra", "input": nested_switchyard_items}
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)["input"][0]["content"][0]
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assert nested_image["image_url"] == "data:image/png;base64,cHJpdmF0ZQ=="
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with pytest.raises(ValueError, match=r"non-empty Responses image URL.*str\[4\]"):
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module._validate_payload(
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{
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"model": "gpt-5.6-terra",
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@ -833,7 +852,10 @@ def test_codex_broker_auth_and_request_contract(tmp_path: Path, monkeypatch):
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"type": "message",
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"role": "user",
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"content": [
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{"type": "input_image", "image_url": {"detail": "high"}}
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{
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"type": "input_image",
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"image_url": {"detail": "high"},
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}
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],
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}
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],
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