litellm/tests/e2e/e2e_http.py
Sameer Kankute a16d9c6f9e
test(e2e): add live batches suite across providers and routing scenarios (#30958)
* tests: add e2e tests for spend, budgets and llms

* style: make chained comparison of status_code clearer

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* remove e2e_tests folder

* test: add spend tracking tests

* fix: p0 issues, added types and shared functions for each test suite

* style: carry clearer status_code comparison into renamed e2e dir

* refactor: migrate to gateway client

* fix: add new tests, split gateway

* test(e2e): add live batches suite across providers and routing scenarios

* test(batches): cover real cost tracking on completed batch retrieve

* test(e2e): assert managed vs raw file and batch id shapes per routing scenario

* test(e2e): assert full response shape of each batches and files endpoint

* test(e2e): only accept transitional statuses for a freshly created batch

* test(prompt-factory): make test_convert_url deterministic with a data URL

picsum.photos is down (HTTP 522), so test_convert_url failed on every
run. Swap the live external image for an inline data: URL and assert the
round-trip through convert_url_to_base64 genuinely.

A data URL is already inline base64 image data, so convert_url_to_base64
now short-circuits it instead of attempting an impossible HTTP fetch;
add a regression for that branch in the mapped image_handling test

* fix: pass through async image data urls

* fix(image-handling): short-circuit data URLs in async path too

Bugbot flagged that convert_url_to_base64 returns data: base64 URLs
unchanged but async_convert_url_to_base64 still tried to fetch them,
so async OCR flows (Bedrock, Azure) would reject inline images the sync
path accepts. Add the same guard to the async function and a regression
test that asserts the async path returns the data URL without touching
the HTTP client

* Fix: openai batches lifecycle

* Fix: add e2e azure openai tests

* Fix e2e for vertex ai

* Add all models for testing

* test(managed-files): assert idempotent upsert in store_unified_file_id

store_unified_file_id switched from create to upsert to avoid
UniqueViolationError when re-storing the same unified_file_id (e.g.
batch output files stored before metadata is available). Update the
unit test to assert the upsert call and its create payload instead of
the removed create call.

* test(batches): reconcile vertex_ai native batch-id comment with fallback guard

* fix(test-config): keep rust-ocr models in model_list by moving files_settings after it

* fix(test-config): move batch models after OCR block to keep merge with internal_staging clean

* fix(batches): use '24hrs' completion window and allow managed-files listing with provider filter

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* style: ruff format transformation.py and endpoints.py

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(e2e/batches): set Azure raw_model to gpt-4.1-mini-batch to match deployed model

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(vertex-ai/batches): correct completion_window to 24h per Literal type definition

* test(vertex-ai/batches): align completion_window assertion to 24h

* fix: update managed file metadata on upsert

---------

Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-07-02 08:05:23 -07:00

363 lines
11 KiB
Python

"""The ONLY module permitted to call ``requests.*``.
Enforced by tests/code_coverage_tests/check_e2e_no_raw_requests.py. Every request
body / query / header / response is a pydantic model; outcomes are a tagged union
(``Result[R]``) so callers ``match`` on them instead of catching exceptions.
Named e2e_http (not http) so it does not shadow the stdlib ``http`` package that
requests itself imports.
"""
from __future__ import annotations
from typing import Generic, Iterator, Literal, NewType, TypeVar, cast
import pytest
import requests
from pydantic import BaseModel, ConfigDict, Field
URL = NewType("URL", str)
class Headers(BaseModel):
"""Base for header models. Subclasses may alias to hyphenated header names
(e.g. ``x-litellm-api-key``); serialization uses by_alias."""
model_config = ConfigDict(populate_by_name=True)
class AuthHeaders(Headers):
# litellm accepts either; set whichever the call needs, leave the other None.
authorization: str | None = None
x_litellm_api_key: str | None = Field(default=None, alias="x-litellm-api-key")
class NoBody(BaseModel):
"""Empty body/query for routes that take none."""
class FileUploadForm(BaseModel):
"""Multipart form fields for POST /v1/files. The file bytes are passed
separately; `model` is not here because the proxy reads it from the query
(?model=) not the form."""
purpose: str = "batch"
target_model_names: str | None = None
custom_llm_provider: str | None = None
# ---------- Result types ----------
R = TypeVar("R", bound=BaseModel)
class Success(BaseModel, Generic[R]):
kind: Literal["success"] = "success"
data: R
class NetworkError(BaseModel):
kind: Literal["network"] = "network"
message: str
class UnauthorizedError(BaseModel):
kind: Literal["unauthorized"] = "unauthorized"
class RateLimitedError(BaseModel):
kind: Literal["rate_limited"] = "rate_limited"
retry_after_seconds: int | None = None
# litellm overloads 429 for budget_exceeded too, so keep the body to tell them apart.
body: str = ""
class ValidationError(BaseModel):
kind: Literal["validation"] = "validation"
message: str
class UnknownApiError(BaseModel):
kind: Literal["unknown"] = "unknown"
status_code: int
body: str
type Result[R: BaseModel] = (
Success[R]
| NetworkError
| UnauthorizedError
| RateLimitedError
| ValidationError
| UnknownApiError
)
class ProbeResult(BaseModel):
"""A route's reachability: status + body, no schema validation. Healthy ==
route exists (not 404) and the handler did not crash (not 5xx)."""
status_code: int
body: str
@property
def healthy(self) -> bool:
return 200 <= self.status_code < 500 and self.status_code != 404
class StreamingResponse(BaseModel):
"""Raw outcome for calls whose body is provider-native or streamed: status, the
x-litellm-call-id header (== SpendLogs.request_id), the content-type (which
tells streaming `text/event-stream` from non-streaming `application/json`), and
the body. Used by passthrough and streaming, where one validated JSON model
does not fit."""
status_code: int
call_id: str | None = None # x-litellm-call-id header
content_type: str | None = None
body: str
chunks: int = 0 # streamed events (0 for non-streaming)
@property
def ok(self) -> bool:
return 200 <= self.status_code < 300
@property
def is_streaming(self) -> bool:
return "text/event-stream" in (self.content_type or "")
def _hdr(resp: requests.Response, name: str) -> str | None:
value = resp.headers.get(name)
return value if isinstance(value, str) else None
def unwrap[R: BaseModel](result: Result[R]) -> R:
match result:
case Success(data=data):
return data
case _:
raise AssertionError(result)
def is_ok[R: BaseModel](result: Result[R]) -> bool:
match result:
case Success():
return True
case _:
return False
def require_successful_call(result: StreamingResponse) -> None:
"""A call that should have succeeded but didn't is a hard failure, never a skip:
if the proxy can't make a call it's expected to, the test must fail."""
if result.ok:
return
pytest.fail(
f"upstream call failed (status {result.status_code}); body={result.body[:300]}"
)
def _headers(headers: BaseModel) -> dict[str, str]:
dumped: dict[str, object] = headers.model_dump(by_alias=True, exclude_none=True)
return {key: str(value) for key, value in dumped.items()}
def _params(params: BaseModel | None) -> dict[str, str]:
if params is None:
return {}
dumped: dict[str, object] = params.model_dump(by_alias=True, exclude_none=True)
return {key: str(value) for key, value in dumped.items()}
def _classify[R: BaseModel](
resp: requests.Response, response_type: type[R]
) -> Result[R]:
if resp.status_code == 401:
return UnauthorizedError()
if resp.status_code == 429:
return RateLimitedError(body=resp.text)
if not resp.ok:
return UnknownApiError(status_code=resp.status_code, body=resp.text)
try:
return Success(data=response_type.model_validate(resp.json()))
except Exception as exc: # noqa: BLE001 - any parse/validation failure is a value
return ValidationError(message=str(exc))
def post[R: BaseModel](
url: URL,
*,
headers: BaseModel,
json: BaseModel,
response_type: type[R],
timeout: float = 30.0,
) -> Result[R]:
try:
resp = requests.post(
str(url),
headers=_headers(headers),
json=json.model_dump(by_alias=True, exclude_none=True),
timeout=timeout,
)
except requests.RequestException as exc:
return NetworkError(message=str(exc))
return _classify(resp, response_type)
def get[R: BaseModel](
url: URL,
*,
headers: BaseModel,
params: BaseModel,
response_type: type[R],
timeout: float = 30.0,
) -> Result[R]:
try:
resp = requests.get(
str(url),
headers=_headers(headers),
params=params.model_dump(by_alias=True, exclude_none=True),
timeout=timeout,
)
except requests.RequestException as exc:
return NetworkError(message=str(exc))
return _classify(resp, response_type)
def delete[R: BaseModel](
url: URL,
*,
headers: BaseModel,
json: BaseModel,
response_type: type[R],
timeout: float = 30.0,
) -> Result[R]:
try:
resp = requests.delete(
str(url),
headers=_headers(headers),
json=json.model_dump(by_alias=True, exclude_none=True),
timeout=timeout,
)
except requests.RequestException as exc:
return NetworkError(message=str(exc))
return _classify(resp, response_type)
def probe(
url: URL, *, headers: BaseModel, params: BaseModel, timeout: float = 30.0
) -> ProbeResult:
try:
resp = requests.get(
str(url),
headers=_headers(headers),
params=params.model_dump(by_alias=True, exclude_none=True),
timeout=timeout,
)
except requests.RequestException as exc:
return ProbeResult(status_code=-1, body=str(exc))
return ProbeResult(status_code=resp.status_code, body=resp.text)
def _streaming_outcome(resp: requests.Response, stream: bool) -> StreamingResponse:
call_id = _hdr(resp, "x-litellm-call-id")
content_type = _hdr(resp, "content-type")
if not stream or not (200 <= resp.status_code < 300):
return StreamingResponse(
status_code=resp.status_code,
call_id=call_id,
content_type=content_type,
body=resp.text,
)
lines = cast("Iterator[bytes]", resp.iter_lines())
chunks = sum(1 for line in lines if line)
return StreamingResponse(
status_code=resp.status_code,
call_id=call_id,
content_type=content_type,
body="<streamed>",
chunks=chunks,
)
def send(
url: URL,
*,
headers: BaseModel,
json: BaseModel,
params: BaseModel | None = None,
stream: bool = False,
timeout: float = 60.0,
) -> StreamingResponse:
"""Raw POST returning the unparsed HTTP outcome: status, full body, and the
x-litellm-call-id header. For native/passthrough bodies and for calls judged by
status rather than a typed JSON model (e.g. a budget block is a non-2xx). With
``stream=True`` the SSE body is consumed and its events counted instead."""
try:
resp = requests.post(
str(url),
headers=_headers(headers),
params=_params(params),
json=json.model_dump(by_alias=True, exclude_none=True),
stream=stream,
timeout=timeout,
)
except requests.RequestException as exc:
return StreamingResponse(status_code=-1, body=str(exc))
return _streaming_outcome(resp, stream)
def stream(
url: URL, *, headers: BaseModel, json: BaseModel, timeout: float = 60.0
) -> StreamingResponse:
"""Streaming (SSE) call: consumes the stream counting events, and captures the
x-litellm-call-id + content-type headers. Body is elided."""
return send(url, headers=headers, json=json, stream=True, timeout=timeout)
def upload[R: BaseModel](
url: URL,
*,
headers: BaseModel,
form: FileUploadForm,
filename: str,
content: bytes,
params: BaseModel | None = None,
response_type: type[R],
timeout: float = 60.0,
) -> Result[R]:
"""Multipart POST for file uploads (/v1/files). Form fields come from `form`,
the file bytes are sent as the `file` part, and `params` carries any query
routing (e.g. ?model=). requests sets the multipart Content-Type itself."""
dumped: dict[str, object] = form.model_dump(by_alias=True, exclude_none=True)
data = {key: str(value) for key, value in dumped.items()}
try:
resp = requests.post(
str(url),
headers=_headers(headers),
params=_params(params),
data=data,
files={"file": (filename, content, "application/jsonl")},
timeout=timeout,
)
except requests.RequestException as exc:
return NetworkError(message=str(exc))
return _classify(resp, response_type)
def download(
url: URL, *, headers: BaseModel, timeout: float = 60.0
) -> StreamingResponse:
"""Raw GET for file content (/v1/files/{id}/content): provider-native bytes, no
schema. Returns the decoded body and the x-litellm-call-id header."""
try:
resp = requests.get(str(url), headers=_headers(headers), timeout=timeout)
except requests.RequestException as exc:
return StreamingResponse(status_code=-1, body=str(exc))
return StreamingResponse(
status_code=resp.status_code,
call_id=_hdr(resp, "x-litellm-call-id"),
content_type=_hdr(resp, "content-type"),
body=resp.text,
)