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test(batches): exercise real GCS validation for vertex batch output reads
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1 changed files with 93 additions and 0 deletions
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@ -18,7 +18,9 @@ import json
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import os
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import sys
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import httpx
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import pytest
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import respx
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sys.path.insert(0, os.path.abspath("../../../.."))
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@ -711,6 +713,97 @@ async def test_output_file_content_vertex_unified_file_id_extracts_gcs_uri(monke
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assert captured["custom_llm_provider"] == "vertex_ai"
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def _vertex_predictions_row(custom_id, prompt_tokens, completion_tokens):
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return {
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"request": {
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"contents": [{"role": "user", "parts": [{"text": "hi"}]}],
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"labels": {"litellm_custom_id": custom_id},
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},
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"status": "",
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"response": {
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"candidates": [
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{
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"content": {"role": "model", "parts": [{"text": "ok"}]},
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"finishReason": "STOP",
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}
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],
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"usageMetadata": {
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"promptTokenCount": prompt_tokens,
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"candidatesTokenCount": completion_tokens,
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"totalTokenCount": prompt_tokens + completion_tokens,
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},
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"modelVersion": "gemini-3.6-flash",
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},
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"processed_time": "2026-07-30T00:00:00.000000+00:00",
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}
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@pytest.fixture
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def respx_interceptable_httpx_client(monkeypatch):
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monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
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litellm.in_memory_llm_clients_cache.flush_cache()
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yield
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litellm.in_memory_llm_clients_cache.flush_cache()
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@pytest.mark.asyncio
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@respx.mock
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async def test_output_file_content_vertex_managed_uri_accepted_by_real_validation(respx_interceptable_httpx_client):
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managed_output_uri = (
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"gs://litellm-bucket/litellm-vertex-files/publishers/google/models/"
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"gemini-3.6-flash/abc-123/prediction-model/predictions.jsonl"
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)
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rows = [
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_vertex_predictions_row("request-1", 10, 5),
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_vertex_predictions_row("request-2", 20, 10),
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]
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route = respx.get(url__regex=r"https://storage\.googleapis\.com/storage/v1/b/litellm-bucket/o/.*").mock(
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return_value=httpx.Response(200, content=_vertex_jsonl(rows))
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)
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result = await bu._get_batch_output_file_content_as_dictionary(
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_batch(managed_output_uri),
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custom_llm_provider="vertex_ai",
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litellm_params={
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"api_key": "test-token",
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"vertex_project": "proj-1",
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"vertex_location": "us-central1",
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"gcs_bucket_name": "litellm-bucket",
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},
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)
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assert route.call_count == 1
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request = route.calls.last.request
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assert request.url.raw_path == (
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b"/storage/v1/b/litellm-bucket/o/"
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b"litellm-vertex-files%2Fpublishers%2Fgoogle%2Fmodels%2Fgemini-3.6-flash"
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b"%2Fabc-123%2Fprediction-model%2Fpredictions.jsonl?alt=media"
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)
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assert [row["custom_id"] for row in result] == ["request-1", "request-2"]
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assert all(row["response"]["status_code"] == 200 for row in result)
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assert all(row["response"]["body"]["model"] == "gemini-3.6-flash" for row in result)
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assert [row["response"]["body"]["usage"]["prompt_tokens"] for row in result] == [10, 20]
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assert [row["response"]["body"]["usage"]["completion_tokens"] for row in result] == [5, 10]
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@pytest.mark.asyncio
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@respx.mock
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async def test_output_file_content_vertex_foreign_bucket_rejected_by_real_validation():
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with pytest.raises(Exception, match="does not match the configured storage bucket"):
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await bu._get_batch_output_file_content_as_dictionary(
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_batch("gs://attacker-bucket/litellm-vertex-files/x/predictions.jsonl"),
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custom_llm_provider="vertex_ai",
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litellm_params={
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"api_key": "test-token",
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"vertex_project": "proj-1",
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"vertex_location": "us-central1",
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"gcs_bucket_name": "litellm-bucket",
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},
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)
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assert respx.mock.calls.call_count == 0
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@pytest.mark.asyncio
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async def test_handle_completed_vertex_batch_computes_cost_usage_and_models(monkeypatch):
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import litellm.files.main as files_main
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