litellm/tests/e2e/llm_translation/test_ocr_rust_e2e.py
mubashir1osmani 8519d7fc24
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test: litellm fix failing tests (#32577)
* fix: rust ocr tests finally pass

* fix: move realtime dir

* fix(realtime): normalize azure realtime api_base to host for Foundry endpoints

The azure realtime handler appended the realtime path to api_base verbatim, so a
Foundry base carrying a project path (.../api/projects/<name>) produced an invalid
realtime URL and the websocket handshake hung. Normalize api_base to scheme and host
before building the realtime path so both Azure OpenAI and Foundry bases connect

Point the e2e realtime azure deployment at the GA gpt-realtime model and stop passing
the os.environ refs the realtime path never unwraps, resolving them from the gateway
env by name instead. Drop the local docker-compose scaffolding from the tree

* test(e2e): add Gateway.list_files and list_fine_tuning_jobs for the discovery suite

The discovery endpoints suite calls client.gateway.list_files and
list_fine_tuning_jobs, which did not exist on Gateway, so both tests errored with
AttributeError before reaching the proxy. Add the two GET wrappers using the
existing FileListResponse / FineTuningJobsResponse models

* revert(realtime): drop azure realtime api_base host-normalization

The azure realtime handshake failure was a config issue, not a litellm bug: the
realtime base was set to the Azure AI Foundry project endpoint (.../api/projects/<p>),
but the OpenAI-compatible realtime route lives at the resource root. litellm correctly
appends the realtime path to whatever base it is given, so pointing the realtime
deployment at the resource root is the fix and no core change is needed

* fix(ocr): route azure_ai doc-intelligence to its own endpoint at the source

get_llm_provider inherits AZURE_AI_API_BASE into api_base for every azure_ai/* OCR
model, but Azure Document Intelligence is a separate resource reached via
AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT, so doc-intelligence requests went to the wrong
host. Stop inheriting the azure_ai base for doc-intelligence models so api_base stays
unset and both the rust bridge and the python get_complete_url fall back to the
document-intelligence endpoint. This drops the earlier _rust_bridge_api_base reorder,
which only covered the rust path and let the env silently override an explicit api_base

* refactor(ocr): consolidate azure doc-intelligence detection; keep explicit api_base

Extract is_azure_document_intelligence_model as the single source of truth for the azure_ai doc-intelligence sub-route so the check is no longer duplicated across _prepare_ocr_request and _rust_bridge_api_base, and gate the dynamic_api_base suppression on the caller not supplying an api_base so an explicit endpoint is always honoured. Restore xai to the realtime PROVIDERS as a documented disabled entry instead of dropping it silently, and add a regression test pinning doc-intelligence api_base resolution.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Mubashir Osmani <mubashir@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-07-09 13:54:45 -07:00

156 lines
5.8 KiB
Python

"""Live e2e: Rust-backed OCR is reachable through the gateway across providers.
Each provider's OCR deployment is registered at runtime via /model/new and deleted
on teardown, so nothing is hardcoded into the gateway config. Every provider is its
own typed OcrProvider below: it owns the model id and the os.environ/* credential
references the proxy resolves at call time, so adding a provider is a new type
rather than another inline body. Start the proxy with the Rust OCR path enabled:
Each case creates its deployment, drives a real /v1/ocr call, and asserts a
well-formed OCR document comes back. Per the e2e "skip on environment, fail on
behavior" rule, a case skips when no proxy answers but fails (never skips) once a
request reaches it: the proxy fetches each provider's referenced secrets, so a
missing credential surfaces as a live provider error rather than silent green.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Protocol
import pytest
from e2e_config import unique_marker
from e2e_http import unwrap
from endpoints_client import EndpointsClient
from lifecycle import ResourceManager
from models import LiteLLMParamsBody, OcrBody, OcrDocument, OcrResponse
pytestmark = pytest.mark.e2e
# Tiny in-repo fixtures served via jsdelivr (sha-pinned, immutable) so the request
# bodies stay stable across runs.
TEST_PDF_URL = (
"https://cdn.jsdelivr.net/gh/BerriAI/litellm"
"@d769e81c90d453240c61fc572cdb27fae06a89d0"
"/tests/llm_translation/fixtures/dummy.pdf"
)
TEST_IMAGE_URL = (
"https://cdn.jsdelivr.net/gh/BerriAI/litellm"
"@d769e81c90d453240c61fc572cdb27fae06a89d0"
"/tests/image_gen_tests/test_image.png"
)
class OcrProvider(Protocol):
"""One OCR provider's deployment config: its model id plus the os.environ/*
credential references the proxy resolves at call time. Each provider owns which
env vars it reads, so a new provider is a new type, not another inline body."""
def litellm_params(self) -> LiteLLMParamsBody: ...
@dataclass(frozen=True, slots=True)
class MistralOcr:
model: str = "mistral/mistral-ocr-latest"
def litellm_params(self) -> LiteLLMParamsBody:
return LiteLLMParamsBody(model=self.model, api_key="os.environ/MISTRAL_API_KEY")
@dataclass(frozen=True, slots=True)
class AzureAiOcr:
"""azure_ai (mistral) OCR. The rust OCR path resolves credentials itself from
AZURE_AI_API_BASE / AZURE_AI_API_KEY when the deployment leaves them unset; it
does NOT unwrap an `os.environ/*` reference passed as api_base (it would be sent
to Azure verbatim), so we omit them and let litellm read the env vars by name."""
model: str
def litellm_params(self) -> LiteLLMParamsBody:
return LiteLLMParamsBody(model=self.model)
@dataclass(frozen=True, slots=True)
class AzureDocIntelligenceOcr:
"""azure_ai Document Intelligence OCR. A separate Azure resource from the
mistral one, so it has its own env vars: AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT /
AZURE_DOCUMENT_INTELLIGENCE_API_KEY, which the OCR config resolves from the
doc-intelligence model name when api_base/api_key are left unset."""
model: str = "azure_ai/doc-intelligence/prebuilt-layout"
def litellm_params(self) -> LiteLLMParamsBody:
return LiteLLMParamsBody(model=self.model)
@dataclass(frozen=True, slots=True)
class VertexOcr:
"""Vertex AI OCR (Mistral publisher). Only the location (not a secret) is set;
the project and credentials are left unset so the gateway resolves VERTEXAI_PROJECT
and VERTEXAI_CREDENTIALS from its own environment by name, keeping every secret on
the gateway like the azure_ai cases above. This is deliberate: the OCR path reads
vertex_project verbatim from litellm_params and never unwraps an `os.environ/*`
ref, so passing one would put the literal string in the request URL."""
model: str
location: str
def litellm_params(self) -> LiteLLMParamsBody:
return LiteLLMParamsBody(model=self.model, vertex_location=self.location)
@dataclass(frozen=True, slots=True)
class _OcrCase:
suffix: str
provider: OcrProvider
document: OcrDocument
RUST_OCR_CASES: tuple[_OcrCase, ...] = (
_OcrCase(
"mistral",
MistralOcr(),
OcrDocument(type="document_url", document_url=TEST_PDF_URL),
),
_OcrCase(
"azure-ai",
AzureAiOcr("azure_ai/mistral-document-ai-2512"),
OcrDocument(type="document_url", document_url=TEST_PDF_URL),
),
_OcrCase(
"azure-document-intelligence",
AzureDocIntelligenceOcr(),
OcrDocument(type="document_url", document_url=TEST_PDF_URL),
),
_OcrCase(
"vertex-mistral",
VertexOcr("vertex_ai/mistral-ocr-2505", "us-central1"),
OcrDocument(type="document_url", document_url=TEST_PDF_URL),
),
)
_CASE_IDS = tuple(case.suffix for case in RUST_OCR_CASES)
def _assert_ocr_document(response: OcrResponse) -> None:
assert response.object == "ocr", f"expected object='ocr', got {response.object!r}"
assert response.model, "response missing the resolved model name"
assert response.pages, "OCR returned no pages"
assert response.pages[0].markdown is not None, "first page has no markdown"
class TestRustOcrGateway:
@pytest.mark.parametrize("case", RUST_OCR_CASES, ids=_CASE_IDS)
def test_rust_ocr_response(
self, endpoints_client: EndpointsClient, resources: ResourceManager, case: _OcrCase
) -> None:
model = f"rust-ocr-{case.suffix}-{unique_marker()}"
model_id = endpoints_client.create_model(model, case.provider.litellm_params())
resources.defer(lambda: endpoints_client.delete_model(model_id))
key = resources.key()
response = unwrap(endpoints_client.gateway.ocr(key, OcrBody(model=model, document=case.document)))
_assert_ocr_document(response)