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130 lines
4.4 KiB
Python
130 lines
4.4 KiB
Python
from __future__ import annotations
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import base64
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from app_server_harness import AppServerHarness
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from app_server_helpers import TINY_PNG_BYTES
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from openai_codex import Codex, ImageInput, LocalImageInput, SkillInput, TextInput
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def test_remote_image_input_is_materialized_before_responses_api(
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tmp_path,
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) -> None:
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"""Remote image inputs should be inlined by the app-server."""
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with AppServerHarness(tmp_path) as harness:
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remote_image_url = harness.responses.serve_bytes(
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"/codex.png",
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TINY_PNG_BYTES,
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content_type="image/png",
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)
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harness.responses.enqueue_assistant_message(
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"remote image received",
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response_id="remote-image",
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)
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config = harness.app_server_config()
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config.config_overrides = ("features.materialize_remote_images=true",)
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with Codex(config=config) as codex:
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result = codex.thread_start().run(
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[
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TextInput("Describe the remote image."),
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ImageInput(remote_image_url),
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]
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)
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request = harness.responses.single_request()
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assert {
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"final_response": result.final_response,
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"contains_user_prompt": "Describe the remote image." in request.message_input_texts("user"),
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"image_urls": request.message_image_urls("user"),
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} == {
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"final_response": "remote image received",
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"contains_user_prompt": True,
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"image_urls": [f"data:image/png;base64,{base64.b64encode(TINY_PNG_BYTES).decode('ascii')}"],
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}
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def test_local_image_input_reaches_responses_api(
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tmp_path,
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) -> None:
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"""Local image inputs should become data URLs after crossing the app-server."""
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local_image = tmp_path / "local.png"
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local_image.write_bytes(TINY_PNG_BYTES)
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with AppServerHarness(tmp_path) as harness:
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harness.responses.enqueue_assistant_message(
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"local image received",
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response_id="local-image",
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)
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with Codex(config=harness.app_server_config()) as codex:
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result = codex.thread_start().run(
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[
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TextInput("Describe the local image."),
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LocalImageInput(str(local_image)),
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]
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)
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request = harness.responses.single_request()
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assert {
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"final_response": result.final_response,
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"contains_user_prompt": "Describe the local image." in request.message_input_texts("user"),
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"image_url_is_png_data_url": request.message_image_urls("user")[-1].startswith(
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"data:image/png;base64,"
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),
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} == {
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"final_response": "local image received",
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"contains_user_prompt": True,
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"image_url_is_png_data_url": True,
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}
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def test_skill_input_injects_loaded_skill_body(tmp_path) -> None:
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"""SkillInput should inject the selected loaded skill into model input."""
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skill_body = "Use the word cobalt."
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with AppServerHarness(tmp_path) as harness:
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skill_file = harness.workspace / ".agents" / "skills" / "demo" / "SKILL.md"
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skill_file.parent.mkdir(parents=True)
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skill_file.write_text(f"---\nname: demo\ndescription: demo skill\n---\n\n{skill_body}\n")
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skill_path = skill_file.resolve()
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harness.responses.enqueue_assistant_message(
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"skill received",
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response_id="skill-input",
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)
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with Codex(config=harness.app_server_config()) as codex:
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result = codex.thread_start().run(
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[
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TextInput("Use the selected skill."),
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SkillInput("demo", str(skill_path)),
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]
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)
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request = harness.responses.single_request()
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skill_blocks = [
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text for text in request.message_input_texts("user") if text.startswith("<skill>")
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]
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assert {
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"final_response": result.final_response,
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"skill_blocks": [
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{
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"has_name": "<name>demo</name>" in text,
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"has_path": f"<path>{skill_path}</path>" in text,
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"has_body": skill_body in text,
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}
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for text in skill_blocks
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],
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} == {
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"final_response": "skill received",
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"skill_blocks": [
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{
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"has_name": True,
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"has_path": True,
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"has_body": True,
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}
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],
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}
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