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* test(e2e): migrate access-control and inference-endpoint regression tests Move the access-control and non-chat inference-endpoint cases from litellm-regression-tests onto the shared e2e harness so a regression in either fails here first access_control/ asserts the gateway's authorization and error-shape contract: a key limited to one model is denied 403 (key_model_access_denied) when it calls another, a key scoped to allowed_routes=["llm_api_routes"] is forbidden 403 from a management route, and an unknown model is rejected 400 before any provider is called. The source asserted 401 for the disallowed-model case against an older proxy; the live contract is now a 403, so the guard tracks current behavior llm_translation/ gains one file per non-chat inference endpoint (/v1/responses, /v1/messages, /embeddings, /v1/rerank, /v1/audio/speech, /v1/images/generations). Each test registers the deployment it needs through /model/new, drives real provider traffic, asserts the parsed body carries real content instead of just a 200, then deletes the model on teardown, so nothing is hardcoded into the gateway config * Update endpoints_client.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
"""Live e2e: POST /v1/images/generations returns an image.
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Registers an OpenAI image deployment at runtime and asserts the response carries a
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generated image (url or base64). Migrated from
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litellm-regression-tests/tests/test_inference_endpoints.py.
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"""
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from __future__ import annotations
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import pytest
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from e2e_config import unique_marker
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from e2e_http import require_successful_call
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from endpoints_client import EndpointsClient, ImagesResult
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from lifecycle import ResourceManager
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from models import LiteLLMParamsBody
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pytestmark = pytest.mark.e2e
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class TestImageGeneration:
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def test_image_generation_returns_image(
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self, endpoints_client: EndpointsClient, resources: ResourceManager
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) -> None:
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model = f"e2e-image-{unique_marker()}"
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model_id = endpoints_client.create_model(
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model,
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LiteLLMParamsBody(
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model="openai/gpt-image-1-mini", api_key="os.environ/OPENAI_API_KEY"
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),
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)
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resources.defer(lambda: endpoints_client.delete_model(model_id))
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key = resources.key()
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result = endpoints_client.images(key, model, "Draw a cute cat")
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require_successful_call(result)
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parsed = ImagesResult.model_validate_json(result.body)
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assert parsed.data, f"/images/generations returned no data: {result.body[:300]}"
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first = parsed.data[0]
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assert first.b64_json or first.url, (
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f"generated image has neither b64_json nor url: {result.body[:300]}"
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)
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