litellm/tests/e2e/llm_translation/test_ocr_rust_e2e.py
mubashir1osmani ec8088f064
test(e2e): vendor API testing coverage (#34557)
* test(e2e): cover vendor strategy gaps for chat contract, image edits, auth, team activity

Resolves the first slice of LIT-4778 (vendor API testing strategy): image edits happy path, chat multi-turn + validation + sanitization, LLM-route auth header matrix, and /team/daily/activity structure

* test(e2e): expand vendor API strategy coverage across endpoints

Adds validation cases on existing endpoint suites, plus vector stores, search,
bedrock native, realtime HTTP secrets/calls, responses retrieve, files/batches
contract, and chat stream SSE. Registers coverage cells for LIT-4778

* test(e2e): finish vendor strategy open items

Audio transcription negatives, vector-store file attach/poll/search,
OpenAI moderation category matrix across chat/messages/responses, and
smoke model matrix for chat (LIT-4778)

* test(e2e): harden vendor strategy suite against live env edges

Fix stream [DONE] tracking, XSS no-crash contract, realtime model routing,
vector store list/search models, responses validation, and provider-denied
Bedrock paths so the suite is stable against a live proxy

* test(e2e): rename suites, drop vendor_contract, fix greptile gaps

Move shared status helpers into e2e_http, rename chat auth headers and
chat security suites, remove vendor_contract and dev_config files_settings,
and tighten transcription validation plus vector-store search assertions

* test(e2e): route bedrock stream disconnects through e2e_http

Catch mid-stream RequestException in the shared harness so bedrock native
tests do not import requests directly
2026-08-12 01:07:52 +00:00

177 lines
6.7 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 hard-fail contract, a case
fails when no proxy answers and also fails 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 assert_client_error, unwrap
from endpoints_client import EndpointsClient
from lifecycle import ResourceManager
from models import LiteLLMParamsBody, OcrBody, OcrDocument, OcrResponse
from pydantic import BaseModel
pytestmark = pytest.mark.e2e
class _OptionalOcrBody(BaseModel):
model: str | None = None
document: dict[str, object] | None = None
# 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.proxy.ocr(key, OcrBody(model=model, document=case.document)))
_assert_ocr_document(response)
@pytest.mark.skip(reason="stage red: product gap, /v1/ocr 500s (aocr TypeError) on missing document instead of 400")
@pytest.mark.covers("llm.ocr.openai.input_validation.nonstream.works")
def test_missing_document_returns_error(
self, endpoints_client: EndpointsClient, resources: ResourceManager
) -> None:
model = f"rust-ocr-val-{unique_marker()}"
model_id = endpoints_client.create_model(model, MistralOcr().litellm_params())
resources.defer(lambda: endpoints_client.delete_model(model_id))
key = resources.key()
result = endpoints_client.proxy.transport.send(
"/v1/ocr",
headers=endpoints_client.proxy.transport.bearer(key),
json=_OptionalOcrBody(model=model),
)
assert_client_error(result, "ocr missing document")