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Python: Fix file_search citations breaking assistant history roundtrip (#5557)
* Python: Fix file_search citations breaking assistant history roundtrip The Responses API rejects 'input_file' inside an assistant message, but the SDK was emitting it whenever an assistant Message contained a hosted_file content (which is what file_search citations become). Three coordinated fixes: 1. _prepare_content_for_openai now skips hosted_file for the assistant role instead of mapping to input_file (which the API rejects there). 2. The streaming response.output_text.annotation.added handler attaches file_citation, container_file_citation, and file_path as annotations on text content, matching the non-streaming path. Previously streaming produced standalone HostedFileContent items that always tripped (1). 3. output_text serialization preserves Annotation objects on roundtrip via a new _annotations_to_output_text helper instead of hardcoding 'annotations' to []. file_search citations now survive multi-agent forwarding. Closes #5556. * Address PR review - _annotations_to_output_text: fan out one entry per annotated_region for url_citation/container_file_citation (Annotation.annotated_regions is a Sequence; the API form carries one start/end per entry). - Validate region span bounds are ints before emitting; skip otherwise. - Add test for the file_path branch (annotation with file_id only). - Add test verifying streamed citation events coalesce onto surrounding text via _finalize_response so span indices reference the merged text, not the empty-text streaming carrier.
This commit is contained in:
Evan Mattson
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GitHub
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GitHub
parent
094f9903b3
commit
46ab47b9e1
@@ -241,6 +241,85 @@ OpenAIChatOptionsT = TypeVar(
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# endregion
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# region Helpers
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def _annotations_to_output_text(annotations: Sequence[Annotation] | None) -> list[dict[str, Any]]:
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"""Convert framework `Annotation` objects to Responses API `output_text` annotation dicts.
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Citations from `file_search`, `code_interpreter` file paths, and url citations all collapse
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to `Annotation(type="citation", ...)` in the framework. The original API form is recovered
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here so assistant messages roundtrip cleanly through history forwarding.
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Each Responses API annotation dict carries at most one `start_index`/`end_index` pair, so an
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`Annotation` with multiple `annotated_regions` is fanned out into one entry per region.
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Regions missing valid integer span bounds are skipped.
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"""
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if not annotations:
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return []
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out: list[dict[str, Any]] = []
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for annotation in annotations:
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if annotation.get("type") != "citation":
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continue
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props = annotation.get("additional_properties") or {}
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regions = annotation.get("annotated_regions") or []
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file_id = annotation.get("file_id")
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url = annotation.get("url")
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title = annotation.get("title")
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container_id = props.get("container_id")
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if container_id and file_id:
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for region in regions:
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start = region.get("start_index")
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end = region.get("end_index")
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if not (isinstance(start, int) and isinstance(end, int)):
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continue
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entry: dict[str, Any] = {
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"type": "container_file_citation",
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"container_id": container_id,
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"file_id": file_id,
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"start_index": start,
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"end_index": end,
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}
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if url:
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entry["filename"] = url
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out.append(entry)
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elif url and not file_id and regions:
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for region in regions:
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start = region.get("start_index")
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end = region.get("end_index")
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if not (isinstance(start, int) and isinstance(end, int)):
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continue
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out.append({
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"type": "url_citation",
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"url": url,
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"title": title or "",
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"start_index": start,
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"end_index": end,
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})
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elif file_id and url:
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entry = {
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"type": "file_citation",
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"file_id": file_id,
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"filename": url,
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}
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if (idx := props.get("index")) is not None:
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entry["index"] = idx
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out.append(entry)
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elif file_id:
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entry = {
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"type": "file_path",
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"file_id": file_id,
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}
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if (idx := props.get("index")) is not None:
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entry["index"] = idx
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out.append(entry)
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return out
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# endregion
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# region ResponsesClient
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@@ -1374,7 +1453,7 @@ class RawOpenAIChatClient( # type: ignore[misc]
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return {
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"type": "output_text",
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"text": content.text,
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"annotations": [],
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"annotations": _annotations_to_output_text(getattr(content, "annotations", None)),
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}
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return {
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"type": "input_text",
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@@ -1522,6 +1601,13 @@ class RawOpenAIChatClient( # type: ignore[misc]
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"approve": content.approved,
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}
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case "hosted_file":
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# `input_file` is an input-only content type in the Responses API and is rejected
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# inside an assistant message. Hosted-file content on an assistant message
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# represents a citation produced by a hosted tool (e.g., file_search) and cannot be
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# meaningfully replayed as input — drop it. The accompanying text annotations carry
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# the citation context for round-tripping.
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if role == "assistant":
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return {}
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return {
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"type": "input_file",
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"file_id": content.file_id,
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@@ -2502,45 +2588,63 @@ class RawOpenAIChatClient( # type: ignore[misc]
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ann_type = _get_ann_value("type")
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ann_file_id = _get_ann_value("file_id")
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# Hosted-file citations attach as text annotations (matching the non-streaming path)
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# so they don't roundtrip as standalone `input_file` items in assistant history.
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if ann_type == "file_path":
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if ann_file_id:
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annotation_obj = Annotation(
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type="citation",
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file_id=str(ann_file_id),
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additional_properties={
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"annotation_index": event.annotation_index,
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"index": _get_ann_value("index"),
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},
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raw_representation=annotation,
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)
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contents.append(
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Content.from_hosted_file(
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file_id=str(ann_file_id),
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additional_properties={
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"annotation_index": event.annotation_index,
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"index": _get_ann_value("index"),
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},
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raw_representation=event,
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)
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Content.from_text(text="", annotations=[annotation_obj], raw_representation=event)
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)
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elif ann_type == "file_citation":
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if ann_file_id:
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ann_filename = _get_ann_value("filename")
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annotation_obj = Annotation(
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type="citation",
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file_id=str(ann_file_id),
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url=ann_filename,
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additional_properties={
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"annotation_index": event.annotation_index,
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"index": _get_ann_value("index"),
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},
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raw_representation=annotation,
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)
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contents.append(
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Content.from_hosted_file(
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file_id=str(ann_file_id),
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additional_properties={
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"annotation_index": event.annotation_index,
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"filename": _get_ann_value("filename"),
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"index": _get_ann_value("index"),
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},
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raw_representation=event,
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)
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Content.from_text(text="", annotations=[annotation_obj], raw_representation=event)
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)
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elif ann_type == "container_file_citation":
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if ann_file_id:
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ann_filename = _get_ann_value("filename")
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ann_start = _get_ann_value("start_index")
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ann_end = _get_ann_value("end_index")
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annotation_obj = Annotation(
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type="citation",
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file_id=str(ann_file_id),
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url=ann_filename,
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additional_properties={
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"annotation_index": event.annotation_index,
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"container_id": _get_ann_value("container_id"),
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},
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raw_representation=annotation,
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)
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if ann_start is not None and ann_end is not None:
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annotation_obj["annotated_regions"] = [
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TextSpanRegion(
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type="text_span",
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start_index=ann_start,
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end_index=ann_end,
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)
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]
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contents.append(
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Content.from_hosted_file(
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file_id=str(ann_file_id),
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additional_properties={
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"annotation_index": event.annotation_index,
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"container_id": _get_ann_value("container_id"),
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"filename": _get_ann_value("filename"),
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"start_index": _get_ann_value("start_index"),
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"end_index": _get_ann_value("end_index"),
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},
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raw_representation=event,
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)
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Content.from_text(text="", annotations=[annotation_obj], raw_representation=event)
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)
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elif ann_type == "url_citation":
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ann_url = _get_ann_value("url")
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@@ -1914,6 +1914,285 @@ def test_hosted_file_content_preparation() -> None:
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assert result["file_id"] == "file_abc123"
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def test_assistant_text_preserves_citation_annotations_on_roundtrip() -> None:
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"""Citation annotations on assistant text should survive serialization back to the Responses API.
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Previously `output_text.annotations` was hardcoded to `[]`, silently dropping `file_search`
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citation context on every roundtrip. Preserving them keeps citations intact across
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multi-agent forwarding.
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"""
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from agent_framework._types import Annotation, TextSpanRegion
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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text_content = Content.from_text(
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"Per the docs, the answer is X. See also the report.",
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annotations=[
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Annotation(
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type="citation",
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file_id="file-abc123",
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url="guidelines.md",
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additional_properties={"index": 12},
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),
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Annotation(
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type="citation",
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title="Quarterly Report",
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url="https://example.com/report",
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annotated_regions=[TextSpanRegion(type="text_span", start_index=40, end_index=46)],
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),
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Annotation(
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type="citation",
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file_id="file-container456",
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url="data.csv",
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additional_properties={"container_id": "container-789"},
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annotated_regions=[TextSpanRegion(type="text_span", start_index=0, end_index=3)],
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),
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],
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)
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result = client._prepare_content_for_openai("assistant", text_content)
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assert result["type"] == "output_text"
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annotations = result["annotations"]
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assert len(annotations) == 3
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file_citation = next(a for a in annotations if a["type"] == "file_citation")
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assert file_citation["file_id"] == "file-abc123"
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assert file_citation["filename"] == "guidelines.md"
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assert file_citation["index"] == 12
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url_citation = next(a for a in annotations if a["type"] == "url_citation")
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assert url_citation["url"] == "https://example.com/report"
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assert url_citation["title"] == "Quarterly Report"
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assert url_citation["start_index"] == 40
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assert url_citation["end_index"] == 46
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container = next(a for a in annotations if a["type"] == "container_file_citation")
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assert container["file_id"] == "file-container456"
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assert container["container_id"] == "container-789"
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assert container["filename"] == "data.csv"
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assert container["start_index"] == 0
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assert container["end_index"] == 3
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def test_assistant_text_preserves_file_path_annotation() -> None:
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"""A `file_path`-style citation (file_id only, no url) should serialize as `file_path`."""
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from agent_framework._types import Annotation
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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text_content = Content.from_text(
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"See attached.",
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annotations=[
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Annotation(
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type="citation",
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file_id="file-only",
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additional_properties={"index": 42},
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),
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],
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)
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result = client._prepare_content_for_openai("assistant", text_content)
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assert result["type"] == "output_text"
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annotations = result["annotations"]
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assert annotations == [{"type": "file_path", "file_id": "file-only", "index": 42}]
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def test_assistant_text_fans_out_multiple_annotated_regions() -> None:
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"""A url_citation with multiple `annotated_regions` should emit one entry per region.
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The Responses API annotation dict carries one start/end pair, so a framework Annotation
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with N regions must produce N output annotation entries.
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"""
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from agent_framework._types import Annotation, TextSpanRegion
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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text_content = Content.from_text(
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"See report. The report says X. Also report.",
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annotations=[
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Annotation(
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type="citation",
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title="Report",
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url="https://example.com/report",
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annotated_regions=[
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TextSpanRegion(type="text_span", start_index=4, end_index=10),
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TextSpanRegion(type="text_span", start_index=16, end_index=22),
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TextSpanRegion(type="text_span", start_index=36, end_index=42),
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],
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),
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],
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)
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result = client._prepare_content_for_openai("assistant", text_content)
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annotations = result["annotations"]
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assert len(annotations) == 3
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assert all(a["type"] == "url_citation" for a in annotations)
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spans = [(a["start_index"], a["end_index"]) for a in annotations]
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assert spans == [(4, 10), (16, 22), (36, 42)]
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def test_assistant_text_skips_regions_with_invalid_span() -> None:
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"""Regions missing integer start/end bounds are skipped rather than emitted with `None`."""
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from agent_framework._types import Annotation, TextSpanRegion
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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text_content = Content.from_text(
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"See report.",
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annotations=[
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Annotation(
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type="citation",
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title="Report",
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url="https://example.com/report",
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annotated_regions=[
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TextSpanRegion(type="text_span"), # type: ignore[typeddict-item]
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TextSpanRegion(type="text_span", start_index=4, end_index=10),
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],
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),
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],
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)
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result = client._prepare_content_for_openai("assistant", text_content)
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annotations = result["annotations"]
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assert len(annotations) == 1
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assert annotations[0]["start_index"] == 4
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assert annotations[0]["end_index"] == 10
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def test_assistant_text_without_annotations_emits_empty_list() -> None:
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"""Plain assistant text should still emit `annotations: []` (Azure validation requires the field)."""
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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result = client._prepare_content_for_openai("assistant", Content.from_text("hello"))
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assert result["type"] == "output_text"
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assert result["text"] == "hello"
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assert result["annotations"] == []
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def test_streamed_file_citation_coalesces_onto_surrounding_text() -> None:
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"""Streamed citation events emit empty-text Content with annotations; `_finalize_response`
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coalesces consecutive text contents and unions their annotations, so the citation lands on
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the merged assistant text content (not a stray empty-text entry).
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Without this, span indices in the annotation would reference `text == ""` after roundtrip.
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"""
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text_event = MagicMock()
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text_event.type = "response.output_text.delta"
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text_event.delta = "Hello world."
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text_event.item_id = "item_1"
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text_event.output_index = 0
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text_event.content_index = 0
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citation_event = MagicMock()
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citation_event.type = "response.output_text.annotation.added"
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citation_event.annotation_index = 0
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citation_event.annotation = {
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"type": "file_citation",
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"file_id": "file-abc",
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"filename": "guidelines.md",
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"index": 5,
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}
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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chat_options = ChatOptions()
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function_call_ids: dict[int, tuple[str, str]] = {}
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update1 = client._parse_chunk_from_openai(text_event, chat_options, function_call_ids)
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update2 = client._parse_chunk_from_openai(citation_event, chat_options, function_call_ids)
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response = ChatResponse.from_updates([update1, update2])
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assert len(response.messages) == 1
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contents = response.messages[0].contents
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assert len(contents) == 1
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merged = contents[0]
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assert merged.type == "text"
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assert merged.text == "Hello world."
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assert merged.annotations is not None
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assert len(merged.annotations) == 1
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assert merged.annotations[0]["file_id"] == "file-abc"
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def test_streamed_file_citation_roundtrips_as_assistant_history() -> None:
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"""End-to-end: file_citation arrives via streaming, then gets forwarded as assistant history.
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Reproduces the user-reported sequential/group-chat workflow bug where one agent's
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`file_search` citations became `input_file` items in the next agent's request and were
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rejected by the Responses API.
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"""
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client = OpenAIChatClient(model="test-model", api_key="test-key")
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chat_options = ChatOptions()
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function_call_ids: dict[int, tuple[str, str]] = {}
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text_event = MagicMock()
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text_event.type = "response.output_text.delta"
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text_event.delta = "According to the docs, the answer is X."
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text_event.item_id = "item_1"
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text_event.output_index = 0
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text_event.content_index = 0
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citation_event = MagicMock()
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citation_event.type = "response.output_text.annotation.added"
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citation_event.annotation_index = 0
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citation_event.annotation = {
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"type": "file_citation",
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"file_id": "file-xyz789",
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"filename": "guidelines.md",
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"index": 12,
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}
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update1 = client._parse_chunk_from_openai(text_event, chat_options, function_call_ids)
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update2 = client._parse_chunk_from_openai(citation_event, chat_options, function_call_ids)
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assistant_history = Message(
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role="assistant",
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contents=[*update1.contents, *update2.contents],
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)
|
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prepared = client._prepare_message_for_openai(assistant_history)
|
||||
|
||||
assert len(prepared) == 1
|
||||
content_items = prepared[0].get("content", [])
|
||||
types = [c.get("type") for c in content_items]
|
||||
assert "input_file" not in types, f"input_file leaked into assistant history: {types}"
|
||||
output_text_items = [c for c in content_items if c.get("type") == "output_text"]
|
||||
assert any(
|
||||
any(a.get("type") == "file_citation" and a.get("file_id") == "file-xyz789" for a in c.get("annotations", []))
|
||||
for c in output_text_items
|
||||
), "file_citation annotation should survive the streaming → history roundtrip"
|
||||
|
||||
|
||||
def test_hosted_file_in_assistant_message_does_not_emit_input_file() -> None:
|
||||
"""Hosted file citations attached to an assistant message must not roundtrip as `input_file`.
|
||||
|
||||
The Responses API rejects `input_file` items inside an assistant role's content array;
|
||||
`input_file` is an input-only content type. This guards the multi-agent / sequential workflow
|
||||
case where one agent's `file_search` citations get forwarded as history to the next call.
|
||||
"""
|
||||
client = OpenAIChatClient(model="test-model", api_key="test-key")
|
||||
|
||||
assistant_msg = Message(
|
||||
role="assistant",
|
||||
contents=[
|
||||
Content.from_text("According to the docs, the answer is X."),
|
||||
Content.from_hosted_file(file_id="file_abc123"),
|
||||
],
|
||||
)
|
||||
|
||||
prepared = client._prepare_message_for_openai(assistant_msg)
|
||||
|
||||
assert len(prepared) == 1
|
||||
assistant_item = prepared[0]
|
||||
assert assistant_item["role"] == "assistant"
|
||||
content_types = [c.get("type") for c in assistant_item.get("content", [])]
|
||||
assert "input_file" not in content_types, (
|
||||
f"`input_file` is not valid inside an assistant message; got {content_types}"
|
||||
)
|
||||
assert "output_text" in content_types
|
||||
|
||||
|
||||
def test_function_approval_response_with_mcp_tool_call() -> None:
|
||||
"""Test function approval response content with MCP server tool call content."""
|
||||
client = OpenAIChatClient(model="test-model", api_key="test-key")
|
||||
@@ -2682,7 +2961,7 @@ def test_streaming_response_in_progress_type() -> None:
|
||||
|
||||
|
||||
def test_streaming_annotation_added_with_file_path() -> None:
|
||||
"""Test streaming annotation added event with file_path type extracts HostedFileContent."""
|
||||
"""Streaming `file_path` should attach as a text annotation, matching non-streaming."""
|
||||
client = OpenAIChatClient(model="test-model", api_key="test-key")
|
||||
chat_options = ChatOptions()
|
||||
function_call_ids: dict[int, tuple[str, str]] = {}
|
||||
@@ -2700,15 +2979,23 @@ def test_streaming_annotation_added_with_file_path() -> None:
|
||||
|
||||
assert len(response.contents) == 1
|
||||
content = response.contents[0]
|
||||
assert content.type == "hosted_file"
|
||||
assert content.file_id == "file-abc123"
|
||||
assert content.additional_properties is not None
|
||||
assert content.additional_properties.get("annotation_index") == 0
|
||||
assert content.additional_properties.get("index") == 42
|
||||
assert content.type == "text"
|
||||
assert content.annotations is not None
|
||||
assert len(content.annotations) == 1
|
||||
annotation = content.annotations[0]
|
||||
assert annotation["type"] == "citation"
|
||||
assert annotation["file_id"] == "file-abc123"
|
||||
assert annotation["additional_properties"]["annotation_index"] == 0
|
||||
assert annotation["additional_properties"]["index"] == 42
|
||||
|
||||
|
||||
def test_streaming_annotation_added_with_file_citation() -> None:
|
||||
"""Test streaming annotation added event with file_citation type extracts HostedFileContent."""
|
||||
"""Streaming `file_citation` should attach as a text annotation, matching non-streaming.
|
||||
|
||||
Previously the streaming path produced a standalone `HostedFileContent`, which then
|
||||
serialized as `input_file` in assistant history and was rejected by the Responses API.
|
||||
Annotations on text content roundtrip cleanly.
|
||||
"""
|
||||
client = OpenAIChatClient(model="test-model", api_key="test-key")
|
||||
chat_options = ChatOptions()
|
||||
function_call_ids: dict[int, tuple[str, str]] = {}
|
||||
@@ -2727,15 +3014,19 @@ def test_streaming_annotation_added_with_file_citation() -> None:
|
||||
|
||||
assert len(response.contents) == 1
|
||||
content = response.contents[0]
|
||||
assert content.type == "hosted_file"
|
||||
assert content.file_id == "file-xyz789"
|
||||
assert content.additional_properties is not None
|
||||
assert content.additional_properties.get("filename") == "sample.txt"
|
||||
assert content.additional_properties.get("index") == 15
|
||||
assert content.type == "text"
|
||||
assert content.annotations is not None
|
||||
assert len(content.annotations) == 1
|
||||
annotation = content.annotations[0]
|
||||
assert annotation["type"] == "citation"
|
||||
assert annotation["file_id"] == "file-xyz789"
|
||||
assert annotation["url"] == "sample.txt"
|
||||
assert annotation["additional_properties"]["annotation_index"] == 1
|
||||
assert annotation["additional_properties"]["index"] == 15
|
||||
|
||||
|
||||
def test_streaming_annotation_added_with_container_file_citation() -> None:
|
||||
"""Test streaming annotation added event with container_file_citation type."""
|
||||
"""Streaming `container_file_citation` should attach as a text annotation."""
|
||||
client = OpenAIChatClient(model="test-model", api_key="test-key")
|
||||
chat_options = ChatOptions()
|
||||
function_call_ids: dict[int, tuple[str, str]] = {}
|
||||
@@ -2756,13 +3047,19 @@ def test_streaming_annotation_added_with_container_file_citation() -> None:
|
||||
|
||||
assert len(response.contents) == 1
|
||||
content = response.contents[0]
|
||||
assert content.type == "hosted_file"
|
||||
assert content.file_id == "file-container123"
|
||||
assert content.additional_properties is not None
|
||||
assert content.additional_properties.get("container_id") == "container-456"
|
||||
assert content.additional_properties.get("filename") == "data.csv"
|
||||
assert content.additional_properties.get("start_index") == 10
|
||||
assert content.additional_properties.get("end_index") == 50
|
||||
assert content.type == "text"
|
||||
assert content.annotations is not None
|
||||
assert len(content.annotations) == 1
|
||||
annotation = content.annotations[0]
|
||||
assert annotation["type"] == "citation"
|
||||
assert annotation["file_id"] == "file-container123"
|
||||
assert annotation["url"] == "data.csv"
|
||||
assert annotation["additional_properties"]["container_id"] == "container-456"
|
||||
assert annotation["annotated_regions"] is not None
|
||||
assert len(annotation["annotated_regions"]) == 1
|
||||
region = annotation["annotated_regions"][0]
|
||||
assert region["start_index"] == 10
|
||||
assert region["end_index"] == 50
|
||||
|
||||
|
||||
def test_streaming_annotation_added_with_url_citation() -> None:
|
||||
|
||||
Reference in New Issue
Block a user