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479 lines
16 KiB
Python
479 lines
16 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Unit tests for the prompt-cache accounting chunk from the external-provider proxy.
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The streaming Anthropic + OpenAI Responses paths emit one extra include_usage
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SSE chunk (``choices: []`` with a ``usage`` block) before ``[DONE]`` so clients
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see cache savings. Covers the helper directly plus the Anthropic stream and the
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OpenAI Responses completed/incomplete streams.
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"""
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import asyncio
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import json
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import httpx
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from core.inference import external_provider as ep_mod
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from core.inference.external_provider import (
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ExternalProviderClient,
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_build_usage_chunk,
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)
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# ── _build_usage_chunk unit tests ───────────────────────────────────
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def test_build_usage_chunk_anthropic_shape():
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line = _build_usage_chunk(
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"chatcmpl-x",
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"anthropic",
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{
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"input_tokens": 8,
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"output_tokens": 862,
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"cache_creation_input_tokens": 1367,
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"cache_read_input_tokens": 18901,
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},
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)
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assert line is not None
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assert line.startswith("data: ")
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payload = json.loads(line[len("data: ") :])
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assert payload["id"] == "chatcmpl-x"
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assert payload["object"] == "chat.completion.chunk"
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assert payload["choices"] == []
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usage = payload["usage"]
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# Anthropic's input_tokens excludes cache buckets; prompt_tokens must
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# sum all three input components so downstream context/cost displays
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# see the real prompt size.
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assert usage["prompt_tokens"] == 8 + 1367 + 18901
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assert usage["completion_tokens"] == 862
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assert usage["total_tokens"] == 8 + 1367 + 18901 + 862
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assert usage["cache_creation_input_tokens"] == 1367
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assert usage["cache_read_input_tokens"] == 18901
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# OpenAI-style mirror for clients that key off prompt_tokens_details.
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assert usage["prompt_tokens_details"]["cached_tokens"] == 18901
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def test_build_usage_chunk_openai_shape():
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line = _build_usage_chunk(
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"chatcmpl-y",
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"openai",
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{
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"input_tokens": 5507,
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"output_tokens": 252,
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"input_tokens_details": {"cached_tokens": 4736},
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},
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)
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assert line is not None
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payload = json.loads(line[len("data: ") :])
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usage = payload["usage"]
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assert usage["prompt_tokens"] == 5507
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assert usage["completion_tokens"] == 252
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assert usage["total_tokens"] == 5759
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assert usage["prompt_tokens_details"]["cached_tokens"] == 4736
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# Anthropic-only keys must not leak onto the OpenAI shape.
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assert "cache_creation_input_tokens" not in usage
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assert "cache_read_input_tokens" not in usage
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def test_build_usage_chunk_missing_fields_default_to_zero():
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# OpenAI Responses can omit input_tokens_details when prompt caching is
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# unused; the helper should still emit a chunk with cached_tokens=0.
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line = _build_usage_chunk(
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"chatcmpl-z",
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"openai",
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{"input_tokens": 42, "output_tokens": 7},
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)
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assert line is not None
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payload = json.loads(line[len("data: ") :])
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assert payload["usage"]["prompt_tokens_details"]["cached_tokens"] == 0
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def test_build_usage_chunk_returns_none_when_all_zero():
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# If upstream errored before any usage event, suppress the chunk to
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# avoid a misleading "0 tokens" line.
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assert _build_usage_chunk("id", "anthropic", {}) is None
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assert _build_usage_chunk("id", "anthropic", None) is None
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assert _build_usage_chunk("id", "openai", {}) is None
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assert (
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_build_usage_chunk(
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"id",
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"openai",
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{
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"input_tokens": 0,
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"output_tokens": 0,
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"input_tokens_details": {"cached_tokens": 0},
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},
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)
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is None
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)
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# ── streaming integration tests ─────────────────────────────────────
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def _drive(coro):
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return asyncio.new_event_loop().run_until_complete(coro)
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async def _collect(agen):
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out = []
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async for line in agen:
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out.append(line)
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return out
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def _mock_http_client(monkeypatch, handler):
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transport = httpx.MockTransport(handler)
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monkeypatch.setattr(ep_mod, "_http_client", httpx.AsyncClient(transport = transport))
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def _make_anthropic_client() -> ExternalProviderClient:
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return ExternalProviderClient(
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provider_type = "anthropic",
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base_url = "https://api.anthropic.com/v1",
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api_key = "sk-ant-test",
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)
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def _make_openai_client() -> ExternalProviderClient:
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return ExternalProviderClient(
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provider_type = "openai",
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base_url = "https://api.openai.com/v1",
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api_key = "sk-openai-test",
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)
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def _make_custom_client() -> ExternalProviderClient:
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return ExternalProviderClient(
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provider_type = "custom",
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base_url = "http://custom.example/v1",
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api_key = "",
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)
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def _anthropic_sse(events: list[dict]) -> bytes:
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chunks: list[str] = []
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for event in events:
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chunks.append(f"event: {event['type']}")
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chunks.append(f"data: {json.dumps(event)}")
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chunks.append("")
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return ("\n".join(chunks) + "\n").encode("utf-8")
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def _openai_sse(events: list[dict]) -> bytes:
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# Responses API ships one `event:` line per object plus the data line.
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chunks: list[str] = []
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for event in events:
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chunks.append(f"event: {event['type']}")
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chunks.append(f"data: {json.dumps(event)}")
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chunks.append("")
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return ("\n".join(chunks) + "\n").encode("utf-8")
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def _usage_chunks(lines: list[str]) -> list[dict]:
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out: list[dict] = []
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for raw in lines:
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if not raw.startswith("data:"):
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continue
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payload = raw[len("data:") :].strip()
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if not payload or payload == "[DONE]":
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continue
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try:
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parsed = json.loads(payload)
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except json.JSONDecodeError:
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continue
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if isinstance(parsed, dict) and "usage" in parsed and parsed.get("choices") == []:
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out.append(parsed["usage"])
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return out
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def test_custom_provider_registry_is_hidden():
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from core.inference.providers import get_provider_info, list_available_providers
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info = get_provider_info("custom")
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assert info is not None
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assert info["hidden"] is True
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assert "custom" not in {p["provider_type"] for p in list_available_providers()}
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def test_custom_provider_uses_chat_completions_without_auth_key(monkeypatch):
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captured: dict = {}
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def handler(request: httpx.Request) -> httpx.Response:
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captured["url"] = str(request.url)
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captured["headers"] = dict(request.headers)
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captured["body"] = json.loads(request.content.decode("utf-8"))
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return httpx.Response(
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200,
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content = b'data: {"choices":[{"delta":{"content":"ok"}}]}\n\ndata: [DONE]\n\n',
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headers = {"content-type": "text/event-stream"},
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)
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_mock_http_client(monkeypatch, handler)
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async def run():
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client = _make_custom_client()
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lines = await _collect(
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client.stream_chat_completion(
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messages = [{"role": "user", "content": "ping"}],
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model = "Qwen/Qwen3-0.6B",
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temperature = 0.7,
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top_p = 0.95,
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max_tokens = 64,
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)
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)
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await client.close()
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return lines
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lines = _drive(run())
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assert captured["url"] == "http://custom.example/v1/chat/completions"
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assert "authorization" not in {k.lower() for k in captured["headers"]}
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assert captured["body"]["model"] == "Qwen/Qwen3-0.6B"
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assert any("ok" in line for line in lines)
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def test_custom_provider_test_endpoint_probes_chat_completion(monkeypatch):
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import importlib.util
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import sys
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from pathlib import Path
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module_path = Path(__file__).resolve().parents[1] / "routes" / "providers.py"
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spec = importlib.util.spec_from_file_location("_providers_route_under_test", module_path)
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assert spec is not None
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assert spec.loader is not None
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providers_route = importlib.util.module_from_spec(spec)
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sys.modules[spec.name] = providers_route
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spec.loader.exec_module(providers_route)
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captured: dict = {}
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class _FakeClient:
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def __init__(self, **kwargs):
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captured["init"] = kwargs
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async def chat_completion(self, **kwargs):
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captured["chat_completion"] = kwargs
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return {"choices": [{"message": {"content": "ok"}}]}
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async def list_models(self):
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raise AssertionError("custom provider test must not call /models")
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async def close(self):
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captured["closed"] = True
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monkeypatch.setattr(providers_route, "ExternalProviderClient", _FakeClient)
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async def run():
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return await providers_route.test_provider(
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providers_route.ProviderTestRequest(
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provider_type = "custom",
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base_url = "http://custom.example/v1",
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model_id = "Qwen/Qwen3-0.6B",
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),
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current_subject = "unsloth",
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)
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result = _drive(run())
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assert result.success is True
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assert result.models_count is None
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assert captured["init"]["provider_type"] == "custom"
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assert captured["chat_completion"]["model"] == "Qwen/Qwen3-0.6B"
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assert captured["chat_completion"]["max_tokens"] == 1
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assert captured["closed"] is True
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def test_custom_provider_test_endpoint_requires_model_id(monkeypatch):
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import importlib.util
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import sys
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from pathlib import Path
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module_path = Path(__file__).resolve().parents[1] / "routes" / "providers.py"
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spec = importlib.util.spec_from_file_location("_providers_route_under_test", module_path)
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assert spec is not None
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assert spec.loader is not None
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providers_route = importlib.util.module_from_spec(spec)
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sys.modules[spec.name] = providers_route
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spec.loader.exec_module(providers_route)
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class _FakeClient:
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def __init__(self, **kwargs):
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pass
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async def close(self):
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pass
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monkeypatch.setattr(providers_route, "ExternalProviderClient", _FakeClient)
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async def run():
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return await providers_route.test_provider(
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providers_route.ProviderTestRequest(
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provider_type = "custom",
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base_url = "http://custom.example/v1",
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),
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current_subject = "unsloth",
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)
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result = _drive(run())
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assert result.success is False
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assert "model ID" in result.message
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def test_anthropic_stream_emits_usage_chunk_before_done(monkeypatch):
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sse_events = [
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{
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"type": "message_start",
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"message": {
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"usage": {
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"input_tokens": 7,
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"output_tokens": 0,
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"cache_creation_input_tokens": 6253,
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"cache_read_input_tokens": 5713,
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}
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},
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},
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{
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"type": "message_delta",
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"delta": {"stop_reason": "end_turn"},
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"usage": {"output_tokens": 1066},
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},
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{"type": "message_stop"},
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]
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def handler(request: httpx.Request) -> httpx.Response:
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return httpx.Response(
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200,
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content = _anthropic_sse(sse_events),
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headers = {"content-type": "text/event-stream"},
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)
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_mock_http_client(monkeypatch, handler)
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async def run():
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client = _make_anthropic_client()
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return await _collect(
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client._stream_anthropic(
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messages = [{"role": "user", "content": "ping"}],
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model = "claude-opus-4-7",
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temperature = 0.7,
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top_p = 0.95,
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max_tokens = 64,
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)
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)
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lines = _drive(run())
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usages = _usage_chunks(lines)
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assert len(usages) == 1, f"expected one usage chunk, got {len(usages)}: {usages}"
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u = usages[0]
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# Real prompt size = uncached input + cache writes + cache reads.
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assert u["prompt_tokens"] == 7 + 6253 + 5713
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assert u["completion_tokens"] == 1066
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assert u["total_tokens"] == 7 + 6253 + 5713 + 1066
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assert u["cache_creation_input_tokens"] == 6253
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assert u["cache_read_input_tokens"] == 5713
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assert u["prompt_tokens_details"]["cached_tokens"] == 5713
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# Usage chunk must come before [DONE].
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data_lines = [ln for ln in lines if ln.startswith("data:")]
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done_idx = next(i for i, ln in enumerate(data_lines) if ln.strip().endswith("[DONE]"))
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usage_idx = next(
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i for i, ln in enumerate(data_lines) if '"usage":' in ln and '"choices": []' in ln
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)
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assert usage_idx < done_idx
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def test_openai_responses_stream_emits_usage_chunk_on_completed(monkeypatch):
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sse_events = [
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{"type": "response.created", "response": {"id": "resp_1"}},
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{
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"type": "response.completed",
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"response": {
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"id": "resp_1",
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"usage": {
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"input_tokens": 5507,
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"output_tokens": 252,
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"input_tokens_details": {"cached_tokens": 4736},
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},
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},
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},
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]
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def handler(request: httpx.Request) -> httpx.Response:
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return httpx.Response(
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200,
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content = _openai_sse(sse_events),
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headers = {"content-type": "text/event-stream"},
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)
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_mock_http_client(monkeypatch, handler)
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async def run():
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client = _make_openai_client()
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return await _collect(
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client._stream_openai_responses(
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messages = [{"role": "user", "content": "ping"}],
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model = "gpt-5.5",
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temperature = 0.7,
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top_p = 0.95,
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max_tokens = 64,
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enable_thinking = None,
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reasoning_effort = None,
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)
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)
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lines = _drive(run())
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usages = _usage_chunks(lines)
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assert len(usages) == 1, f"expected one usage chunk, got {len(usages)}: {usages}"
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u = usages[0]
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assert u["prompt_tokens"] == 5507
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assert u["completion_tokens"] == 252
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assert u["prompt_tokens_details"]["cached_tokens"] == 4736
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# OpenAI shape must NOT carry Anthropic-only keys.
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assert "cache_creation_input_tokens" not in u
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assert "cache_read_input_tokens" not in u
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def test_openai_responses_stream_emits_usage_chunk_on_incomplete(monkeypatch):
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sse_events = [
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{"type": "response.created", "response": {"id": "resp_2"}},
|
|
{
|
|
"type": "response.incomplete",
|
|
"response": {
|
|
"id": "resp_2",
|
|
"usage": {
|
|
"input_tokens": 1234,
|
|
"output_tokens": 1024,
|
|
"input_tokens_details": {"cached_tokens": 768},
|
|
},
|
|
},
|
|
},
|
|
]
|
|
|
|
def handler(request: httpx.Request) -> httpx.Response:
|
|
return httpx.Response(
|
|
200,
|
|
content = _openai_sse(sse_events),
|
|
headers = {"content-type": "text/event-stream"},
|
|
)
|
|
|
|
_mock_http_client(monkeypatch, handler)
|
|
|
|
async def run():
|
|
client = _make_openai_client()
|
|
return await _collect(
|
|
client._stream_openai_responses(
|
|
messages = [{"role": "user", "content": "ping"}],
|
|
model = "gpt-5.5",
|
|
temperature = 0.7,
|
|
top_p = 0.95,
|
|
max_tokens = 1024,
|
|
enable_thinking = None,
|
|
reasoning_effort = None,
|
|
)
|
|
)
|
|
|
|
lines = _drive(run())
|
|
usages = _usage_chunks(lines)
|
|
assert len(usages) == 1
|
|
assert usages[0]["prompt_tokens_details"]["cached_tokens"] == 768
|