test(ocr): record provider corpus with automatic Vertex authentication

litellm/litellm_core_utils/prompt_templates/image_handling.py

@@ -65,7 +65,7 @@ def _process_image_response(response: Response, url: str) -> str:
             )
         img_type = _img_type
     else:
-        img_type = image_type
+        img_type = image_type.partition(";")[0].strip().lower()
 
     result: Final = f"data:{img_type};base64,{base64_image}"
     in_memory_cache.set_cache(url, result)

litellm/llms/vertex_ai/ocr/deepseek_transformation.py

@@ -178,7 +178,7 @@ class VertexAIDeepSeekOCRConfig(BaseOCRConfig):
 
         # Build DeepSeek OCR request
         data: Final = {
-            "model": "deepseek-ai/" + model,
+            "model": "deepseek-ai/" + model.removeprefix("deepseek-ai/"),
             "messages": [{"role": "user", "content": [content_item]}],
         }
 

tests/route_parity/fixtures/cli.py

@@ -23,7 +23,7 @@ def _positive_int(value: str) -> int:
 
 def parse_recording_args(argv: Sequence[str] | None = None) -> RecordingArgs:
     parser: Final = argparse.ArgumentParser()
-    parser.add_argument("--concurrency", type=_positive_int, default=4)
+    parser.add_argument("--concurrency", type=_positive_int, default=1)
     parser.add_argument("--examples", type=_positive_int, default=4)
     parser.add_argument("--fixture-dir", type=Path)
     namespace: Final = parser.parse_args(argv)

tests/route_parity/fixtures/pipeline.py

@@ -132,6 +132,9 @@ def _record_job(job: RecordingJob[InputT], case_type: type[CaseT]) -> RecordedFi
         job.case_input,
         job.invocation.execute,
     )
+    status: Final = interactions[-1].response.status_code
+    if status in {408, 429} or status >= 500:
+        raise RuntimeError(f"Upstream returned transient HTTP {status}; rerun recording to retry")
     case: Final = case_type.model_validate(
         {
             "litellm_input": job.case_input,

tests/route_parity/fixtures/test_pipeline.py

@@ -44,8 +44,9 @@ class _ParityCase(BaseModel):
 class _Upstream(ThreadingHTTPServer):
     daemon_threads = True
 
-    def __init__(self) -> None:
+    def __init__(self, status: int = 200) -> None:
         super().__init__(("127.0.0.1", 0), _UpstreamHandler)
+        self.response_status: Final = status
 
     @property
     def url(self) -> str:
@@ -59,7 +60,9 @@ class _UpstreamHandler(BaseHTTPRequestHandler):
         length: Final = int(self.headers.get("content-length") or "0")
         self.rfile.read(length)
         body: Final = b"{}"
-        self.send_response(200)
+        server: Final = self.server
+        assert isinstance(server, _Upstream)
+        self.send_response(server.response_status)
         self.send_header("content-type", "application/json")
         self.send_header("content-length", str(len(body)))
         self.end_headers()
@@ -70,8 +73,8 @@ class _UpstreamHandler(BaseHTTPRequestHandler):
 
 
 @contextmanager
-def _upstream() -> Generator[_Upstream]:
-    server: Final = _Upstream()
+def _upstream(status: int = 200) -> Generator[_Upstream]:
+    server: Final = _Upstream(status)
     thread: Final = threading.Thread(target=server.serve_forever, daemon=True)
     thread.start()
     try:
@@ -189,3 +192,26 @@ def test_failure_does_not_stop_independent_recordings(tmp_path: Path) -> None:
     assert len(summary.failed) == 1
     assert summary.failed[0].target_name == "stale"
     assert summary.exit_code == 1
+
+
+@pytest.mark.parametrize("status", (408, 429, 500, 503))
+def test_transient_response_is_not_cached_and_can_be_retried(tmp_path: Path, status: int) -> None:
+    case_input: Final = _FixtureInput(identifier="retry")
+    with _upstream(status) as upstream:
+        target: Final = _target("retry", upstream.url, case_input, _Invocation())
+        failed: Final = record_fixtures((target,), tmp_path, 1, 1, _ParityCase)
+    assert failed.exit_code == 1
+    assert not fixture_path(tmp_path / "retry", case_input).exists()
+    with _upstream() as healthy_upstream:
+        healthy_target: Final = _target("retry", healthy_upstream.url, case_input, _Invocation())
+        retried: Final = record_fixtures((healthy_target,), tmp_path, 1, 1, _ParityCase)
+    assert retried.exit_code == 0
+    assert len(retried.recorded) == 1
+
+
+def test_provider_rejected_response_can_be_recorded(tmp_path: Path) -> None:
+    with _upstream(400) as upstream:
+        target: Final = _target("rejected", upstream.url, _FixtureInput(identifier="invalid"), _Invocation())
+        summary: Final = record_fixtures((target,), tmp_path, 1, 1, _ParityCase)
+    assert summary.exit_code == 0
+    assert len(summary.recorded) == 1

tests/test_litellm/litellm_core_utils/test_image_handling.py

@@ -1,17 +1,24 @@
-from unittest.mock import patch
+from typing import Final
 
 import pytest
 from httpx import Request, Response
 
 import litellm
-from litellm import constants
 from litellm.litellm_core_utils.prompt_templates import image_handling
 from litellm.litellm_core_utils.prompt_templates.image_handling import (
+    _process_image_response,
     async_convert_url_to_base64,
     convert_url_to_base64,
 )
 
 
+@pytest.mark.parametrize("content_type", ("application/pdf; qs=0.001", "Application/PDF; charset=binary"))
+def test_pdf_data_uri_uses_media_type_without_http_parameters(content_type: str) -> None:
+    response: Final = Response(200, headers={"Content-Type": content_type}, content=b"%PDF-1.4")
+    data_uri: Final = _process_image_response(response, "https://example.test/parameterized-content-type.pdf")
+    assert data_uri == "data:application/pdf;base64,JVBERi0xLjQ="
+
+
 @pytest.fixture(autouse=True)
 def _bypass_ssrf(monkeypatch):
     """Bypass SSRF validation in image handling tests — tests use fake URLs."""
@@ -107,9 +114,7 @@ class StreamingLargeImageClient:
             request=Request("GET", url),
         )
         # Mock the iter_bytes method to return our generator
-        response.iter_bytes = lambda chunk_size=8192: generate_chunks(
-            size_bytes, chunk_size
-        )
+        response.iter_bytes = lambda chunk_size=8192: generate_chunks(size_bytes, chunk_size)
         return response
 
 
@@ -207,9 +212,7 @@ def test_streaming_download_handles_petabyte_file(monkeypatch):
     """
     # Simulate a 1 petabyte file (1,000,000 GB)
     # Without streaming protection, this would cause OOM or hang indefinitely
-    client = StreamingLargeImageClient(
-        size_mb=1_000_000_000, include_content_length=False
-    )
+    client = StreamingLargeImageClient(size_mb=1_000_000_000, include_content_length=False)
     monkeypatch.setattr(litellm, "module_level_client", client)
 
     with pytest.raises(litellm.ImageFetchError) as excinfo:
@@ -258,8 +261,6 @@ def test_image_size_limit_disabled(monkeypatch):
     """
     Test that setting MAX_IMAGE_URL_DOWNLOAD_SIZE_MB to 0 disables all image URL downloads.
     """
-    import litellm.litellm_core_utils.prompt_templates.image_handling as image_handling
-
     monkeypatch.setattr(litellm, "module_level_client", SmallImageClient())
     monkeypatch.setattr(image_handling, "MAX_IMAGE_URL_DOWNLOAD_SIZE_MB", 0)
 

tests/test_litellm/ocr/fixtures/README.md

@@ -10,14 +10,32 @@ The recording command runs four stages:
 Run it with:
 
 ```shell
-uv run python -m tests.test_litellm.ocr.fixtures.record --examples 4 --concurrency 4
+uv run python -m tests.test_litellm.ocr.fixtures.record --examples 1000
 ```
 
-`--concurrency` caps provider calls across all targets. Independent jobs finish after a failure, then the command exits
-nonzero if any job failed
+`--concurrency` defaults to 1 and caps active recording jobs across all targets. Increase it explicitly when provider
+quotas permit. Concurrency limits do not guarantee a request-per-minute quota; HTTP 408, 429, and 5xx responses fail
+recording without being saved. Rerunning retries missing fixtures and reuses successful recordings
 
-New recordings are VCR YAML cassettes. The committed corpus contains 31 migrated cassettes: 18 Mistral, 9 Reducto v3,
-and 4 Reducto legacy. Their original response bytes, statuses, headers, and recording timestamps are preserved
+New recordings are VCR YAML cassettes. The corpus retains the original 31 migrated cassettes and adds live recordings
+for all four providers. Original response bytes, statuses, headers, and recording timestamps are preserved
+
+For Vertex, authenticate and select a project once:
+
+```shell
+gcloud auth login
+gcloud config set project YOUR_PROJECT_ID
+```
+
+The recording command reads the project from `VERTEXAI_PROJECT`, `VERTEX_PROJECT`, or the active gcloud configuration,
+then gets an OAuth access token with `gcloud auth print-access-token`. Tokens stay in memory and are removed from
+recorded headers. `VERTEX_AI_ACCESS_TOKEN` or the legacy `VERTEX_AI_API_KEY` can override token lookup. The
+`VERTEXT_API_KEY` express-mode key is not used as a Bearer token. Mistral defaults to `us-central1`; DeepSeek defaults
+to the global host and `global` location. `VERTEX_DEEPSEEK_LOCATION` and `VERTEX_DEEPSEEK_API_BASE` override the latter
+
+Azure accepts `AZURE_KEY` and `AZURE_ENDPOINT` as fallbacks for both Azure OCR contracts. Provider-specific variables
+take precedence. Set `AZURE_DEPLOYMENT_NAME=mistral-ocr-4-0` to record that deployment instead of the default
+`mistral-document-ai-2512`. Mistral and Reducto use `MISTRAL_API_KEY` and `REDUCTO_API_KEY`
 
 To migrate an existing JSON fixture directory locally:
 
@@ -34,11 +52,18 @@ OCR strategies generate public `litellm.ocr()` and `litellm.aocr()` inputs. Ever
 document, optional provider override, and LiteLLM keyword arguments. The fixture-only `contract` literal selects the
 input schema and is removed before calling the SDK. Strategies never build provider wire payloads
 
-Each contract has a required corpus containing a baseline and cases for its supported top-level OCR parameters. The
+Each contract's strategy contains baselines and cases for its supported top-level OCR parameters. The
 contracts are Mistral, Azure-hosted Mistral, Vertex-hosted Mistral, Azure Document Intelligence, Vertex DeepSeek,
 Reducto v3, and Reducto legacy. Credentials and endpoints only control target discovery, so a machine records the
 contracts it has configured and skips the rest
 
+`--examples 1000` exhausts the current finite strategies: 32 Mistral, 15 Azure Mistral, 17 Azure Document Intelligence,
+16 Vertex Mistral, 2 Vertex DeepSeek, 55 Reducto v3, and 3 Reducto legacy cases, including fixed rejected inputs.
+This covers the defined strategy choices, not every possible value accepted by the schemas. The live run recorded
+139 of these 140 cases. Vertex Mistral's standalone `document_annotation_format` case repeatedly returned HTTP 500
+and remains pending. Its bounding-box annotation, annotation-prompt, and confidence cases record upstream 404/422
+rejections; schema acceptance does not imply support by the hosted model
+
 Reducto fixtures record upload and parse responses. Their parity cases remain non-strict expected failures until the
 Rust OCR bridge supports Reducto. Azure and Vertex generation paths are unit-tested without credentials in CI, so the
 committed corpus does not need live recordings for every target

tests/test_litellm/ocr/fixtures/azure.py

@@ -5,7 +5,7 @@ from typing import Final, Literal, cast
 
 from hypothesis import strategies as st
 from hypothesis.strategies import SearchStrategy
-from pydantic import StrictInt, StrictStr, field_validator
+from pydantic import StrictInt, StrictStr, TypeAdapter, field_validator
 
 from tests.route_parity.fixtures.recording import UpstreamEndpoint
 from tests.test_litellm.ocr.fixtures.base import OcrDocument, OcrSdkInputBase
@@ -21,7 +21,7 @@ from tests.test_litellm.ocr.fixtures.mistral import (
     mistral_input_values_strategy,
 )
 
-AzureMistralModel = Literal["azure_ai/mistral-document-ai-2512",]
+AzureMistralModel = Literal["azure_ai/mistral-document-ai-2512", "azure_ai/mistral-ocr-4-0"]
 AzureMistralFixtureModel = AzureMistralModel | Literal["azure_ai/invalid-ocr-model-for-parity"]
 AzureDocumentIntelligenceModel = Literal[
     "azure_ai/doc-intelligence/prebuilt-read",
@@ -87,13 +87,16 @@ def _azure_mistral_input(values: dict[str, object], model: AzureMistralModel) ->
     return AzureMistralOcrSdkInput.model_validate({**values, "model": model})
 
 
-def azure_mistral_input_strategy(inline_image_data_uri: str) -> SearchStrategy[AzureMistralOcrSdkInput]:
+def azure_mistral_input_strategy(
+    inline_image_data_uri: str,
+    models: tuple[AzureMistralModel, ...] = AZURE_MISTRAL_MODELS,
+) -> SearchStrategy[AzureMistralOcrSdkInput]:
     # Foundry's active gateway schema rejects 2512-only controls and
     # document_annotation_prompt, even though native Mistral accepts them.
     return st.builds(
         _azure_mistral_input,
         values=mistral_input_values_strategy("2505", inline_image_data_uri, include_document_annotation_prompt=False),
-        model=st.sampled_from(AZURE_MISTRAL_MODELS),
+        model=st.sampled_from(models),
     )
 
 
@@ -171,17 +174,23 @@ def azure_document_intelligence_input_strategy() -> SearchStrategy[AzureDocument
 def azure_mistral_recording_targets(
     environ: Mapping[str, str], client: OcrFixtureClient, inline_image_data_uri: str
 ) -> tuple[OcrRecordingTarget, ...]:
-    api_key: Final = environ.get("AZURE_AI_API_KEY")
-    base_url: Final = environ.get("AZURE_AI_API_BASE")
+    api_key: Final = environ.get("AZURE_AI_API_KEY") or environ.get("AZURE_KEY")
+    base_url: Final = environ.get("AZURE_AI_API_BASE") or environ.get("AZURE_ENDPOINT")
     if not api_key or not base_url:
         return ()
+    deployment: Final = environ.get("AZURE_DEPLOYMENT_NAME")
+    models: Final = (
+        (TypeAdapter(AzureMistralModel).validate_python(f"azure_ai/{deployment.removeprefix('azure_ai/')}"),)
+        if deployment
+        else AZURE_MISTRAL_MODELS
+    )
     return (
         OcrRecordingTarget(
             name="azure-mistral",
             upstream=UpstreamEndpoint(base_url=base_url.rstrip("/")),
             strategy=cast(
                 SearchStrategy[OcrSdkInputBase],
-                azure_mistral_input_strategy(inline_image_data_uri),
+                azure_mistral_input_strategy(inline_image_data_uri, models),
             ),
             invocation=invoke_with_api_key(client, api_key),
             required_inputs=AZURE_MISTRAL_PROVIDER_REJECTED_INPUTS,
@@ -192,8 +201,8 @@ def azure_mistral_recording_targets(
 def azure_document_intelligence_recording_targets(
     environ: Mapping[str, str], client: OcrFixtureClient
 ) -> tuple[OcrRecordingTarget, ...]:
-    api_key: Final = environ.get("AZURE_DOCUMENT_INTELLIGENCE_API_KEY")
-    base_url: Final = environ.get("AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT")
+    api_key: Final = environ.get("AZURE_DOCUMENT_INTELLIGENCE_API_KEY") or environ.get("AZURE_KEY")
+    base_url: Final = environ.get("AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT") or environ.get("AZURE_ENDPOINT")
     if not api_key or not base_url:
         return ()
     return (

tests/test_litellm/ocr/fixtures/config.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
 import os
+import subprocess
+from collections.abc import Callable, Mapping
 from pathlib import Path
 from typing import Final
 
@@ -8,6 +10,35 @@ FIXTURE_DIR_ENV: Final = "LITELLM_OCR_FIXTURE_DIR"
 DEFAULT_FIXTURE_DIRECTORY: Final = Path(__file__).with_name("data")
 
 
+def read_gcloud(arguments: tuple[str, ...]) -> str:
+    try:
+        result: Final = subprocess.run(("gcloud", *arguments), capture_output=True, text=True, timeout=45, check=False)
+    except (OSError, subprocess.TimeoutExpired):
+        return ""
+    return result.stdout.strip() if result.returncode == 0 else ""
+
+
+def recording_environment(
+    environ: Mapping[str, str],
+    command_reader: Callable[[tuple[str, ...]], str] = read_gcloud,
+) -> Mapping[str, str]:
+    project: Final = (
+        environ.get("VERTEXAI_PROJECT")
+        or environ.get("VERTEX_PROJECT")
+        or command_reader(("config", "get-value", "project"))
+    )
+    if not project or project == "(unset)":
+        return environ
+    token: Final = (
+        environ.get("VERTEX_AI_ACCESS_TOKEN")
+        or environ.get("VERTEX_AI_API_KEY")
+        or command_reader(("auth", "print-access-token"))
+    )
+    if not token:
+        raise SystemExit("Vertex OCR needs OAuth credentials. Run `gcloud auth login` or set VERTEX_AI_ACCESS_TOKEN")
+    return {**environ, "VERTEXAI_PROJECT": project, "VERTEX_AI_API_KEY": token}
+
+
 def configured_fixture_directory() -> Path:
     configured: Final = os.environ.get(FIXTURE_DIR_ENV)
     return Path(configured).expanduser() if configured is not None else DEFAULT_FIXTURE_DIRECTORY

tests/test_litellm/ocr/fixtures/data/azure-document-intelligence/ed4c810b78a758aab2475b1eb7c9a5db92e60bc4711fb001fbb30616af660edf.yaml

@@ -0,0 +1,116 @@
+interactions:
+- request:
+    body: '{"urlSource":"https://dummyjson.com/image/800x300/ffffff/000000?text=invoice%20123&fontSize=24"}'
+    headers:
+      Accept:
+      - '*/*'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - litellm/1.101.0
+    method: POST
+    uri: http://parity-provider.invalid/documentintelligence/documentModels/prebuilt-layout:analyze?api-version=2024-11-30
+  response:
+    body:
+      string: ''
+    headers:
+      Date:
+      - Wed, 02 Sep 2026 22:36:01 GMT
+      Operation-Location:
+      - http://parity-provider.invalid/documentintelligence/documentModels/prebuilt-layout/analyzeResults/42554c0a-83ec-4db4-8cf8-e3ff9cd9dd2a?api-version=2024-11-30
+      Server:
+      - istio-envoy
+      Strict-Transport-Security:
+      - max-age=31536000; includeSubDomains; preload
+      X-Content-Type-Options:
+      - nosniff
+      apim-request-id:
+      - 42554c0a-83ec-4db4-8cf8-e3ff9cd9dd2a
+      x-envoy-upstream-service-time:
+      - '670'
+      x-ms-region:
+      - West US 3
+    status:
+      code: 202
+      message: ''
+- request:
+    body: ''
+    headers:
+      Accept:
+      - '*/*'
+      User-Agent:
+      - litellm/1.101.0
+    method: GET
+    uri: http://parity-provider.invalid/documentintelligence/documentModels/prebuilt-layout/analyzeResults/42554c0a-83ec-4db4-8cf8-e3ff9cd9dd2a?api-version=2024-11-30
+  response:
+    body:
+      string: '{"status":"running","createdDateTime":"2026-09-02T22:36:01Z","lastUpdatedDateTime":"2026-09-02T22:36:01Z"}'
+    headers:
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Wed, 02 Sep 2026 22:36:01 GMT
+      Retry-After:
+      - '4'
+      Server:
+      - istio-envoy
+      Strict-Transport-Security:
+      - max-age=31536000; includeSubDomains; preload
+      X-Content-Type-Options:
+      - nosniff
+      apim-request-id:
+      - 011f699b-8d28-4ecb-917b-24cd42ffee29
+      x-envoy-upstream-service-time:
+      - '12'
+      x-ms-region:
+      - West US 3
+    status:
+      code: 200
+      message: ''
+- request:
+    body: ''
+    headers:
+      Accept:
+      - '*/*'
+      User-Agent:
+      - litellm/1.101.0
+    method: GET
+    uri: http://parity-provider.invalid/documentintelligence/documentModels/prebuilt-layout/analyzeResults/42554c0a-83ec-4db4-8cf8-e3ff9cd9dd2a?api-version=2024-11-30
+  response:
+    body:
+      string: '{"status":"succeeded","createdDateTime":"2026-09-02T22:36:01Z","lastUpdatedDateTime":"2026-09-02T22:36:02Z","analyzeResult":{"apiVersion":"2024-11-30","modelId":"prebuilt-layout","stringIndexType":"textElements","content":"invoice
+        123","pages":[{"pageNumber":1,"angle":-0.12780000269412994,"width":800,"height":300,"unit":"pixel","words":[{"content":"invoice","polygon":[338,138,418,139,418,160,338,160],"confidence":0.994,"span":{"offset":0,"length":7}},{"content":"123","polygon":[424,139,461,138,461,160,424,160],"confidence":0.999,"span":{"offset":8,"length":3}}],"lines":[{"content":"invoice
+        123","polygon":[338,138,460,138,461,160,338,160],"spans":[{"offset":0,"length":11}]}],"spans":[{"offset":0,"length":11}]}],"tables":[],"paragraphs":[{"spans":[{"offset":0,"length":11}],"boundingRegions":[{"pageNumber":1,"polygon":[338,138,460,138,461,160,338,160]}],"role":"title","content":"invoice
+        123"}],"styles":[],"contentFormat":"text","sections":[{"spans":[{"offset":0,"length":11}],"elements":["/paragraphs/0"]}]}}'
+    headers:
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Wed, 02 Sep 2026 22:36:06 GMT
+      Server:
+      - istio-envoy
+      Strict-Transport-Security:
+      - max-age=31536000; includeSubDomains; preload
+      X-Content-Type-Options:
+      - nosniff
+      apim-request-id:
+      - 8940c1a9-9c86-4188-86bf-8f34bb8fb537
+      x-envoy-upstream-service-time:
+      - '32'
+      x-ms-region:
+      - West US 3
+    status:
+      code: 200
+      message: ''
+recorded_at: '2026-09-02T22:36:06.585674+00:00'
+ttl_seconds: 0
+version: 1
+x-litellm:
+  case:
+    litellm_input:
+      document:
+        image_url: https://dummyjson.com/image/800x300/ffffff/000000?text=invoice%20123&fontSize=24
+        type: image_url
+      model: azure_ai/doc-intelligence/prebuilt-layout
+  request_source: recorded
+  schema_version: 1

tests/test_litellm/ocr/fixtures/data/azure-mistral/b2aa9df433e9509c5665a180e8ba4f5ab8601cac8646bab83f819020512e2b94.yaml

@@ -0,0 +1,92 @@
+interactions:
+- request:
+    body: '{"model":"mistral-ocr-4-0","document":{"type":"image_url","image_url":"data:image/png;base64,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"}}'
+    headers:
+      Accept:
+      - '*/*'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - litellm/1.101.0
+    method: POST
+    uri: http://parity-provider.invalid/providers/mistral/azure/ocr
+  response:
+    body:
+      string: '{"pages":[{"index":0,"markdown":"$$\\text{DOC } 123$$","images":[],"tables":[],"hyperlinks":[],"header":null,"footer":null,"dimensions":{"dpi":200,"height":80,"width":320},"confidence_scores":null,"blocks":[{"top_left_x":0,"top_left_y":0,"bottom_right_x":320,"bottom_right_y":80,"content":"$$\\text{DOC
+        } 123$$","type":"equation"}]}],"model":"mistral-ocr-4-0","document_annotation":null,"usage_info":{"pages_processed":1,"doc_size_bytes":438}}'
+    headers:
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