mirror of
https://github.com/AstrBotDevs/AstrBot.git
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Soulter
8b82d03d94
* fix: bound model input images below 512 KiB * fix: reuse compliant model image files without copying * docs: simplify image size setting hint * fix: centralize model image preparation and attachment notices * fix: clarify input image maximum edge length label
2262 lines
71 KiB
Python
2262 lines
71 KiB
Python
import base64
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import builtins
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from io import BytesIO
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from pathlib import Path
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from types import SimpleNamespace
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import httpx
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import pytest
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from openai import AsyncAzureOpenAI, AsyncOpenAI
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from openai.types.chat.chat_completion import ChatCompletion
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from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
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from PIL import Image as PILImage
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import astrbot.core.provider.sources.openai_source as openai_source_module
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import astrbot.core.provider.sources.request_retry as request_retry
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from astrbot.core.exceptions import EmptyModelOutputError
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from astrbot.core.provider.entities import LLMResponse
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from astrbot.core.provider.sources.groq_source import ProviderGroq
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from astrbot.core.provider.sources.openai_source import ProviderOpenAIOfficial
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from astrbot.core.utils.media_utils import ResolvedMediaData, file_uri_to_path
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class _ErrorWithBody(Exception):
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def __init__(self, message: str, body: dict):
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super().__init__(message)
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self.body = body
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class _ErrorWithResponse(Exception):
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def __init__(self, message: str, response_text: str):
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super().__init__(message)
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self.response = SimpleNamespace(text=response_text)
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def _make_provider(overrides: dict | None = None) -> ProviderOpenAIOfficial:
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provider_config = {
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"id": "test-openai",
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"type": "openai_chat_completion",
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"model": "gpt-4o-mini",
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"key": ["test-key"],
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}
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if overrides:
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provider_config.update(overrides)
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return ProviderOpenAIOfficial(
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provider_config=provider_config,
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provider_settings={},
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)
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def _make_groq_provider(overrides: dict | None = None) -> ProviderGroq:
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provider_config = {
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"id": "test-groq",
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"type": "groq_chat_completion",
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"model": "qwen/qwen3-32b",
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"key": ["test-key"],
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}
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if overrides:
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provider_config.update(overrides)
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return ProviderGroq(
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provider_config=provider_config,
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provider_settings={},
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)
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@pytest.mark.parametrize(
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("overrides", "expected_client"),
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[
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({}, AsyncOpenAI),
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(
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{
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"api_version": "2024-02-01",
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"api_base": "https://example.openai.azure.com/openai",
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},
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AsyncAzureOpenAI,
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),
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],
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)
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@pytest.mark.asyncio
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async def test_provider_client_disables_sdk_builtin_retries(overrides, expected_client):
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provider = _make_provider(overrides)
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try:
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assert isinstance(provider.client, expected_client)
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assert provider.client.max_retries == 0
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finally:
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await provider.terminate()
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@pytest.mark.asyncio
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async def test_query_attempts_exactly_request_max_retries_times(monkeypatch):
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monkeypatch.setattr(request_retry, "REQUEST_RETRY_WAIT_MIN_S", 0)
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monkeypatch.setattr(request_retry, "REQUEST_RETRY_WAIT_MAX_S", 0)
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provider = _make_provider()
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try:
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calls = 0
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async def failing_create(**kwargs):
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nonlocal calls
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calls += 1
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raise httpx.ConnectError("temporary connection failure")
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monkeypatch.setattr(provider.client.chat.completions, "create", failing_create)
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with pytest.raises(httpx.ConnectError):
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await provider._query(
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payloads={
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"model": "gpt-4o-mini",
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"messages": [{"role": "user", "content": "hi"}],
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},
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tools=None,
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request_max_retries=2,
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)
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assert calls == 2
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finally:
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await provider.terminate()
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def test_create_http_client_uses_openai_httpx_module(monkeypatch):
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captured: dict[str, object] = {}
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fake_httpx_module = object()
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from openai import _base_client as openai_base_client
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monkeypatch.setattr(
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openai_base_client,
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"httpx",
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fake_httpx_module,
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raising=False,
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)
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def fake_create_proxy_client(
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provider_label: str,
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proxy: str | None = None,
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headers: dict[str, str] | None = None,
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verify=None,
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httpx_module=None,
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):
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captured["httpx_module"] = httpx_module
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return object()
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monkeypatch.setattr(
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openai_source_module,
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"create_proxy_client",
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fake_create_proxy_client,
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)
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provider = ProviderOpenAIOfficial.__new__(ProviderOpenAIOfficial)
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provider._create_http_client({"proxy": ""})
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assert captured["httpx_module"] is fake_httpx_module
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def test_create_http_client_falls_back_to_global_httpx_module(monkeypatch):
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captured: dict[str, object] = {}
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def fake_create_proxy_client(
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provider_label: str,
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proxy: str | None = None,
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headers: dict[str, str] | None = None,
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verify=None,
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httpx_module=None,
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):
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captured["httpx_module"] = httpx_module
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return object()
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real_import = builtins.__import__
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def fake_import(name, globals=None, locals=None, fromlist=(), level=0):
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if name == "openai" and fromlist:
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raise ImportError("missing openai._base_client")
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return real_import(name, globals, locals, fromlist, level)
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monkeypatch.setattr(
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openai_source_module,
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"create_proxy_client",
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fake_create_proxy_client,
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)
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monkeypatch.setattr(builtins, "__import__", fake_import)
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provider = ProviderOpenAIOfficial.__new__(ProviderOpenAIOfficial)
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provider._create_http_client({"proxy": ""})
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assert captured["httpx_module"] is openai_source_module.httpx
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@pytest.mark.asyncio
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async def test_get_models_retries_transient_request_error(monkeypatch):
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monkeypatch.setattr(request_retry, "REQUEST_RETRY_WAIT_MIN_S", 0)
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monkeypatch.setattr(request_retry, "REQUEST_RETRY_WAIT_MAX_S", 0)
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class FakeModels:
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def __init__(self):
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self.calls = 0
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async def list(self):
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self.calls += 1
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if self.calls == 1:
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raise httpx.ConnectError("temporary connection failure")
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return SimpleNamespace(
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data=[
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SimpleNamespace(id="gpt-b"),
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SimpleNamespace(id="gpt-a"),
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]
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)
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models = FakeModels()
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provider = ProviderOpenAIOfficial.__new__(ProviderOpenAIOfficial)
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provider.client = SimpleNamespace(models=models)
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assert await provider.get_models() == ["gpt-a", "gpt-b"]
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assert models.calls == 2
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@pytest.mark.asyncio
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async def test_text_chat_passes_request_max_retries_to_query():
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captured: dict[str, object] = {}
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provider = ProviderOpenAIOfficial.__new__(ProviderOpenAIOfficial)
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provider.api_keys = ["test-key"]
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provider.client = SimpleNamespace(api_key=None)
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async def fake_prepare_chat_payload(*args, **kwargs):
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return {"messages": [], "model": "gpt-4o-mini"}, []
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async def fake_query(payloads, func_tool, *, request_max_retries=None):
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captured["request_max_retries"] = request_max_retries
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return LLMResponse(role="assistant", completion_text="ok")
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provider._prepare_chat_payload = fake_prepare_chat_payload
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provider._query = fake_query
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await provider.text_chat(prompt="hello", request_max_retries=2)
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assert captured["request_max_retries"] == 2
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@pytest.mark.asyncio
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async def test_handle_api_error_content_moderated_removes_images():
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provider = _make_provider(
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{"image_moderation_error_patterns": ["file:content-moderated"]}
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)
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try:
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payloads = {
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "hello"},
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{
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,abcd"},
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},
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],
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}
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]
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}
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context_query = payloads["messages"]
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success, *_rest = await provider._handle_api_error(
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Exception("Content is moderated [WKE=file:content-moderated]"),
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payloads=payloads,
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context_query=context_query,
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func_tool=None,
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chosen_key="test-key",
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available_api_keys=["test-key"],
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retry_cnt=0,
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max_retries=10,
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)
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assert success is False
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updated_context = payloads["messages"]
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assert isinstance(updated_context, list)
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assert updated_context[0]["content"] == [{"type": "text", "text": "hello"}]
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finally:
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await provider.terminate()
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@pytest.mark.asyncio
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async def test_handle_api_error_model_not_vlm_removes_images_and_retries_text_only():
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provider = _make_provider()
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try:
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payloads = {
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "hello"},
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{
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,abcd"},
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},
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],
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}
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]
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}
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context_query = payloads["messages"]
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success, *_rest = await provider._handle_api_error(
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Exception("The model is not a VLM and cannot process images"),
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payloads=payloads,
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context_query=context_query,
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func_tool=None,
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chosen_key="test-key",
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available_api_keys=["test-key"],
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retry_cnt=0,
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max_retries=10,
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)
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assert success is False
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updated_context = payloads["messages"]
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assert isinstance(updated_context, list)
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assert updated_context[0]["content"] == [{"type": "text", "text": "hello"}]
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finally:
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await provider.terminate()
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@pytest.mark.asyncio
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async def test_handle_api_error_model_not_vlm_after_fallback_raises():
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provider = _make_provider()
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try:
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payloads = {
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "hello"},
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{
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,abcd"},
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},
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],
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}
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]
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}
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context_query = payloads["messages"]
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with pytest.raises(Exception, match="not a VLM"):
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await provider._handle_api_error(
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Exception("The model is not a VLM and cannot process images"),
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payloads=payloads,
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context_query=context_query,
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func_tool=None,
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chosen_key="test-key",
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available_api_keys=["test-key"],
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retry_cnt=1,
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max_retries=10,
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image_fallback_used=True,
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)
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finally:
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await provider.terminate()
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@pytest.mark.asyncio
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async def test_handle_api_error_content_moderated_with_unserializable_body():
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provider = _make_provider({"image_moderation_error_patterns": ["blocked"]})
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try:
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payloads = {
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "hello"},
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{
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,abcd"},
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},
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],
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}
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]
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}
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context_query = payloads["messages"]
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err = _ErrorWithBody(
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"upstream error",
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{"error": {"message": "blocked"}, "raw": object()},
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)
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success, *_rest = await provider._handle_api_error(
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err,
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payloads=payloads,
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context_query=context_query,
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func_tool=None,
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chosen_key="test-key",
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available_api_keys=["test-key"],
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retry_cnt=0,
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max_retries=10,
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)
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assert success is False
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assert payloads["messages"][0]["content"] == [{"type": "text", "text": "hello"}]
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finally:
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await provider.terminate()
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def test_extract_error_text_candidates_truncates_long_response_text():
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long_text = "x" * 20000
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err = _ErrorWithResponse("upstream error", long_text)
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candidates = ProviderOpenAIOfficial._extract_error_text_candidates(err)
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assert candidates
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assert max(len(candidate) for candidate in candidates) <= (
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ProviderOpenAIOfficial._ERROR_TEXT_CANDIDATE_MAX_CHARS
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)
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@pytest.mark.asyncio
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async def test_openai_payload_keeps_reasoning_content_in_assistant_history():
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provider = _make_provider()
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try:
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payloads = {
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"messages": [
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{
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"role": "assistant",
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"content": [
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{"type": "think", "think": "step 1"},
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{"type": "text", "text": "final answer"},
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],
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}
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]
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}
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provider._finally_convert_payload(payloads)
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assistant_message = payloads["messages"][0]
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assert assistant_message["content"] == [
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{"type": "text", "text": "final answer"}
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]
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assert assistant_message["reasoning_content"] == "step 1"
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finally:
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await provider.terminate()
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|
|
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@pytest.mark.asyncio
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async def test_groq_payload_drops_reasoning_content_from_assistant_history():
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provider = _make_groq_provider()
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try:
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payloads = {
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"messages": [
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{
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"role": "assistant",
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"content": [
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{"type": "think", "think": "step 1"},
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{"type": "text", "text": "final answer"},
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],
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}
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]
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}
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provider._finally_convert_payload(payloads)
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assistant_message = payloads["messages"][0]
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assert assistant_message["content"] == [
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{"type": "text", "text": "final answer"}
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]
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assert "reasoning_content" not in assistant_message
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assert "reasoning" not in assistant_message
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finally:
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await provider.terminate()
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|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_content_moderated_without_images_raises():
|
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provider = _make_provider(
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{"image_moderation_error_patterns": ["file:content-moderated"]}
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)
|
|
try:
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payloads = {
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"messages": [
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{
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"role": "user",
|
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"content": [{"type": "text", "text": "hello"}],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
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err = Exception("Content is moderated [WKE=file:content-moderated]")
|
|
|
|
with pytest.raises(Exception, match="content-moderated"):
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await provider._handle_api_error(
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err,
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payloads=payloads,
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context_query=context_query,
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func_tool=None,
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chosen_key="test-key",
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|
available_api_keys=["test-key"],
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|
retry_cnt=0,
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|
max_retries=10,
|
|
)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_content_moderated_detects_structured_body():
|
|
provider = _make_provider(
|
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{"image_moderation_error_patterns": ["content_moderated"]}
|
|
)
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
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},
|
|
],
|
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}
|
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]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = _ErrorWithBody(
|
|
"upstream error",
|
|
{"error": {"code": "content_moderated", "message": "blocked"}},
|
|
)
|
|
|
|
success, *_rest = await provider._handle_api_error(
|
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err,
|
|
payloads=payloads,
|
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context_query=context_query,
|
|
func_tool=None,
|
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chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
assert success is False
|
|
assert payloads["messages"][0]["content"] == [{"type": "text", "text": "hello"}]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_content_moderated_supports_custom_patterns():
|
|
provider = _make_provider(
|
|
{"image_moderation_error_patterns": ["blocked_by_policy_code_123"]}
|
|
)
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = Exception("upstream: blocked_by_policy_code_123")
|
|
|
|
success, *_rest = await provider._handle_api_error(
|
|
err,
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
assert success is False
|
|
assert payloads["messages"][0]["content"] == [{"type": "text", "text": "hello"}]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_content_moderated_without_patterns_raises():
|
|
provider = _make_provider()
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = Exception("Content is moderated [WKE=file:content-moderated]")
|
|
|
|
with pytest.raises(Exception, match="content-moderated"):
|
|
await provider._handle_api_error(
|
|
err,
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_unknown_image_error_raises():
|
|
provider = _make_provider()
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
|
|
with pytest.raises(Exception, match="unknown provider image upload error"):
|
|
await provider._handle_api_error(
|
|
Exception("some unknown provider image upload error"),
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_invalid_attachment_removes_images_and_retries_text_only():
|
|
provider = _make_provider()
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = _ErrorWithBody(
|
|
"upstream error",
|
|
{
|
|
"error": {
|
|
"code": "INVALID_ATTACHMENT",
|
|
"message": "download attachment: unexpected status 404",
|
|
}
|
|
},
|
|
)
|
|
|
|
success, *_rest = await provider._handle_api_error(
|
|
err,
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
|
|
assert success is False
|
|
assert payloads["messages"][0]["content"] == [{"type": "text", "text": "hello"}]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_invalid_attachment_without_images_raises():
|
|
provider = _make_provider()
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [{"type": "text", "text": "hello"}],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = _ErrorWithBody(
|
|
"upstream error",
|
|
{
|
|
"error": {
|
|
"code": "INVALID_ATTACHMENT",
|
|
"message": "download attachment: unexpected status 404",
|
|
}
|
|
},
|
|
)
|
|
|
|
with pytest.raises(_ErrorWithBody, match="upstream error"):
|
|
await provider._handle_api_error(
|
|
err,
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=0,
|
|
max_retries=10,
|
|
)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_handle_api_error_invalid_attachment_after_fallback_raises():
|
|
provider = _make_provider()
|
|
try:
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "hello"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
}
|
|
context_query = payloads["messages"]
|
|
err = _ErrorWithBody(
|
|
"upstream error",
|
|
{
|
|
"error": {
|
|
"code": "INVALID_ATTACHMENT",
|
|
"message": "download attachment: unexpected status 404",
|
|
}
|
|
},
|
|
)
|
|
|
|
with pytest.raises(_ErrorWithBody, match="upstream error"):
|
|
await provider._handle_api_error(
|
|
err,
|
|
payloads=payloads,
|
|
context_query=context_query,
|
|
func_tool=None,
|
|
chosen_key="test-key",
|
|
available_api_keys=["test-key"],
|
|
retry_cnt=1,
|
|
max_retries=10,
|
|
image_fallback_used=True,
|
|
)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_materializes_context_http_image_urls(monkeypatch):
|
|
provider = _make_provider()
|
|
try:
|
|
|
|
async def fake_resolve_media_ref_to_base64_data(
|
|
media_ref: str,
|
|
*,
|
|
media_type: str,
|
|
strict: bool = False,
|
|
) -> ResolvedMediaData:
|
|
assert media_ref == "https://example.com/quoted.png"
|
|
assert media_type == "image"
|
|
assert strict is False
|
|
return ResolvedMediaData(base64_data="abcd", mime_type="image/png")
|
|
|
|
monkeypatch.setattr(
|
|
openai_source_module,
|
|
"resolve_media_ref_to_base64_data",
|
|
fake_resolve_media_ref_to_base64_data,
|
|
)
|
|
|
|
contexts = [
|
|
{
|
|
"role": "user",
|
|
"metadata": {"source": "quoted"},
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://example.com/quoted.png",
|
|
"id": "ctx-img",
|
|
"detail": "high",
|
|
},
|
|
},
|
|
],
|
|
}
|
|
]
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=contexts,
|
|
)
|
|
|
|
assert payloads["messages"][0]["content"] == [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "data:image/png;base64,abcd",
|
|
"detail": "high",
|
|
},
|
|
},
|
|
]
|
|
assert payloads["messages"][0]["content"][1]["image_url"].get("id") is None
|
|
assert contexts[0]["content"][1]["image_url"] == {
|
|
"url": "https://example.com/quoted.png",
|
|
"id": "ctx-img",
|
|
"detail": "high",
|
|
}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_skips_materialization_for_text_only_context(
|
|
monkeypatch,
|
|
):
|
|
provider = _make_provider()
|
|
try:
|
|
|
|
async def fail_if_called(_context_query):
|
|
raise AssertionError("materialization should be skipped")
|
|
|
|
monkeypatch.setattr(
|
|
provider, "_materialize_context_image_parts", fail_if_called
|
|
)
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[{"role": "user", "content": "hello"}],
|
|
)
|
|
|
|
assert payloads["messages"] == [{"role": "user", "content": "hello"}]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_skips_materialization_for_text_only_parts(
|
|
monkeypatch,
|
|
):
|
|
provider = _make_provider()
|
|
try:
|
|
|
|
async def fail_if_called(_context_query):
|
|
raise AssertionError("materialization should be skipped")
|
|
|
|
monkeypatch.setattr(
|
|
provider, "_materialize_context_image_parts", fail_if_called
|
|
)
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[
|
|
{
|
|
"role": "user",
|
|
"content": [{"type": "text", "text": "hello"}],
|
|
}
|
|
],
|
|
)
|
|
|
|
assert payloads["messages"] == [
|
|
{
|
|
"role": "user",
|
|
"content": [{"type": "text", "text": "hello"}],
|
|
}
|
|
]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_materializes_context_http_image_urls_with_detected_mime(
|
|
monkeypatch, tmp_path
|
|
):
|
|
provider = _make_provider()
|
|
try:
|
|
image_path = tmp_path / "quoted-image.png"
|
|
PILImage.new("RGBA", (1, 1), (255, 0, 0, 255)).save(image_path)
|
|
|
|
async def fake_download(url: str, target_path: str) -> None:
|
|
assert url == "https://example.com/quoted.png"
|
|
with open(target_path, "wb") as f:
|
|
f.write(image_path.read_bytes())
|
|
|
|
monkeypatch.setattr(
|
|
"astrbot.core.utils.media_utils.download_file",
|
|
fake_download,
|
|
)
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://example.com/quoted.png",
|
|
},
|
|
},
|
|
],
|
|
}
|
|
],
|
|
)
|
|
|
|
image_payload = payloads["messages"][0]["content"][1]["image_url"]
|
|
assert image_payload["url"].startswith("data:image/png;base64,")
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_materializes_context_file_uri_image_urls(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
image_path = tmp_path / "quoted-image.png"
|
|
PILImage.new("RGBA", (1, 1), (255, 0, 0, 255)).save(image_path)
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": image_path.as_uri(),
|
|
},
|
|
},
|
|
],
|
|
}
|
|
],
|
|
)
|
|
|
|
image_payload = payloads["messages"][0]["content"][1]["image_url"]
|
|
assert image_payload["url"].startswith("data:image/png;base64,")
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
def test_file_uri_to_path_preserves_windows_drive_letter():
|
|
# Compare as Path objects so the assertion is independent of the host
|
|
# path separator convention.
|
|
assert Path(file_uri_to_path("file:///C:/tmp/quoted-image.png")) == Path(
|
|
"C:/tmp/quoted-image.png"
|
|
)
|
|
|
|
|
|
def test_file_uri_to_path_preserves_windows_netloc_drive_letter():
|
|
assert Path(file_uri_to_path("file://C:/tmp/quoted-image.png")) == Path(
|
|
"C:/tmp/quoted-image.png"
|
|
)
|
|
|
|
|
|
def test_file_uri_to_path_preserves_remote_netloc_as_unc_path():
|
|
assert Path(file_uri_to_path("file://server/share/quoted-image.png")) == Path(
|
|
"//server/share/quoted-image.png"
|
|
)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_image_part_rejects_invalid_local_file(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
invalid_file = tmp_path / "not-image.txt"
|
|
invalid_file.write_text("not an image")
|
|
|
|
assert await provider._resolve_image_part(str(invalid_file)) is None
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_image_part_rejects_invalid_file_uri(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
invalid_file = tmp_path / "not-image.txt"
|
|
invalid_file.write_text("not an image")
|
|
|
|
assert await provider._resolve_image_part(invalid_file.as_uri()) is None
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_image_ref_to_data_url_mode_controls_invalid_file_behavior(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
invalid_file = tmp_path / "not-image.txt"
|
|
invalid_file.write_text("not an image")
|
|
|
|
assert (
|
|
await provider._image_ref_to_data_url(str(invalid_file), mode="safe")
|
|
is None
|
|
)
|
|
with pytest.raises(ValueError, match="Invalid image file"):
|
|
await provider._image_ref_to_data_url(str(invalid_file), mode="strict")
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_materialize_context_image_parts_returns_new_messages(monkeypatch):
|
|
provider = _make_provider()
|
|
try:
|
|
context_query = [
|
|
{
|
|
"role": "user",
|
|
"metadata": {"source": "quoted"},
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://example.com/quoted.png",
|
|
"detail": "high",
|
|
},
|
|
},
|
|
],
|
|
},
|
|
{"role": "assistant", "content": "plain text"},
|
|
]
|
|
|
|
async def fake_resolve(image_url: str, *, image_detail: str | None = None):
|
|
assert image_url == "https://example.com/quoted.png"
|
|
assert image_detail == "high"
|
|
return {
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "data:image/png;base64,abcd",
|
|
"detail": "high",
|
|
},
|
|
}
|
|
|
|
monkeypatch.setattr(provider, "_resolve_image_part", fake_resolve)
|
|
|
|
materialized = await provider._materialize_context_image_parts(context_query)
|
|
|
|
assert materialized is not context_query
|
|
assert materialized[0] is not context_query[0]
|
|
assert materialized[0]["metadata"] is context_query[0]["metadata"]
|
|
assert materialized[0]["content"][0] is context_query[0]["content"][0]
|
|
assert (
|
|
materialized[0]["content"][1]["image_url"]["url"]
|
|
== "data:image/png;base64,abcd"
|
|
)
|
|
assert (
|
|
context_query[0]["content"][1]["image_url"]["url"]
|
|
== "https://example.com/quoted.png"
|
|
)
|
|
assert materialized[1] is not context_query[1]
|
|
assert materialized[1]["content"] == "plain text"
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_encode_image_bs64_missing_file_raises(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
missing_path = tmp_path / "missing-image.png"
|
|
with pytest.raises(FileNotFoundError):
|
|
await provider.encode_image_bs64(str(missing_path))
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_encode_image_bs64_invalid_file_raises(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
invalid_file = tmp_path / "not-image.txt"
|
|
invalid_file.write_text("not an image")
|
|
|
|
with pytest.raises(ValueError, match="Invalid image file"):
|
|
await provider.encode_image_bs64(str(invalid_file))
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_encode_image_bs64_supports_base64_scheme():
|
|
provider = _make_provider()
|
|
try:
|
|
image_data = await provider.encode_image_bs64("base64://abcd")
|
|
|
|
assert image_data == "data:image/jpeg;base64,abcd"
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_encode_image_bs64_supports_file_uri(tmp_path):
|
|
provider = _make_provider()
|
|
try:
|
|
image_path = tmp_path / "quoted-image.png"
|
|
PILImage.new("RGBA", (1, 1), (255, 0, 0, 255)).save(image_path)
|
|
|
|
image_data = await provider.encode_image_bs64(image_path.as_uri())
|
|
|
|
assert image_data.startswith("data:image/png;base64,")
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_image_part_supports_base64_scheme():
|
|
provider = _make_provider()
|
|
try:
|
|
assert await provider._resolve_image_part("base64://abcd") == {
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,abcd"},
|
|
}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_image_part_preserves_base64_png_mime_type():
|
|
provider = _make_provider()
|
|
try:
|
|
image_buffer = BytesIO()
|
|
PILImage.new("RGBA", (1, 1), (255, 0, 0, 255)).save(
|
|
image_buffer,
|
|
format="PNG",
|
|
)
|
|
image_base64 = base64.b64encode(image_buffer.getvalue()).decode("ascii")
|
|
|
|
image_part = await provider._resolve_image_part(f"base64://{image_base64}")
|
|
|
|
assert image_part == {
|
|
"type": "image_url",
|
|
"image_url": {"url": f"data:image/png;base64,{image_base64}"},
|
|
}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_materializes_context_localhost_file_uri_image_urls(
|
|
tmp_path,
|
|
):
|
|
provider = _make_provider()
|
|
try:
|
|
image_path = tmp_path / "quoted-image.png"
|
|
PILImage.new("RGBA", (1, 1), (255, 0, 0, 255)).save(image_path)
|
|
|
|
localhost_uri = f"file://localhost{image_path.as_posix()}"
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": localhost_uri,
|
|
},
|
|
},
|
|
],
|
|
}
|
|
],
|
|
)
|
|
|
|
image_payload = payloads["messages"][0]["content"][1]["image_url"]
|
|
assert image_payload["url"].startswith("data:image/png;base64,")
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_audio_part_supports_data_audio_uri(tmp_path, monkeypatch):
|
|
monkeypatch.setattr(
|
|
"astrbot.core.utils.media_utils.get_astrbot_temp_path",
|
|
lambda: str(tmp_path),
|
|
)
|
|
provider = _make_provider()
|
|
try:
|
|
audio_bytes = b"RIFF\x24\x00\x00\x00WAVEfmt " + b"\x00" * 16
|
|
audio_ref = f"data:audio/wav;base64,{base64.b64encode(audio_bytes).decode()}"
|
|
|
|
audio_part = await provider._resolve_audio_part(audio_ref)
|
|
|
|
assert audio_part == {
|
|
"type": "input_audio",
|
|
"input_audio": {
|
|
"data": base64.b64encode(audio_bytes).decode("utf-8"),
|
|
"format": "wav",
|
|
},
|
|
}
|
|
assert not list(tmp_path.iterdir())
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_resolve_audio_part_supports_base64_scheme(tmp_path, monkeypatch):
|
|
monkeypatch.setattr(
|
|
"astrbot.core.utils.media_utils.get_astrbot_temp_path",
|
|
lambda: str(tmp_path),
|
|
)
|
|
provider = _make_provider()
|
|
try:
|
|
audio_bytes = b"RIFF\x24\x00\x00\x00WAVEfmt " + b"\x00" * 16
|
|
audio_ref = f"base64://{base64.b64encode(audio_bytes).decode()}"
|
|
|
|
audio_part = await provider._resolve_audio_part(audio_ref)
|
|
|
|
assert audio_part == {
|
|
"type": "input_audio",
|
|
"input_audio": {
|
|
"data": base64.b64encode(audio_bytes).decode("utf-8"),
|
|
"format": "wav",
|
|
},
|
|
}
|
|
assert not list(tmp_path.iterdir())
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_audio_preprocess_failure_does_not_log_media_ref(monkeypatch):
|
|
provider = _make_provider()
|
|
captured: dict[str, object] = {}
|
|
|
|
async def fake_resolve_media_ref_to_base64_data(*args, **kwargs):
|
|
raise ValueError("boom")
|
|
|
|
def fake_warning(message, *args, **kwargs):
|
|
captured["message"] = message
|
|
captured["args"] = args
|
|
|
|
monkeypatch.setattr(
|
|
openai_source_module,
|
|
"resolve_media_ref_to_base64_data",
|
|
fake_resolve_media_ref_to_base64_data,
|
|
)
|
|
monkeypatch.setattr(openai_source_module.logger, "warning", fake_warning)
|
|
|
|
try:
|
|
audio_ref = "data:audio/wav;base64," + "A" * 1000
|
|
|
|
assert await provider._resolve_audio_part(audio_ref) is None
|
|
|
|
assert captured["message"] == "音频预处理失败，将忽略。错误: %s"
|
|
assert len(captured["args"]) == 1
|
|
assert str(captured["args"][0]) == "boom"
|
|
rendered_log_args = f"{captured['message']} {captured['args']}"
|
|
assert audio_ref not in rendered_log_args
|
|
assert "data:audio" not in rendered_log_args
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_prepare_chat_payload_keeps_original_context_image_when_materialization_fails(
|
|
monkeypatch,
|
|
):
|
|
provider = _make_provider()
|
|
try:
|
|
|
|
async def fake_resolve_media_ref_to_base64_data(
|
|
media_ref: str,
|
|
*,
|
|
media_type: str,
|
|
strict: bool = False,
|
|
) -> None:
|
|
assert media_ref == "https://example.com/expired.png"
|
|
assert media_type == "image"
|
|
assert strict is False
|
|
return None
|
|
|
|
monkeypatch.setattr(
|
|
openai_source_module,
|
|
"resolve_media_ref_to_base64_data",
|
|
fake_resolve_media_ref_to_base64_data,
|
|
)
|
|
|
|
payloads, _ = await provider._prepare_chat_payload(
|
|
prompt=None,
|
|
contexts=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://example.com/expired.png",
|
|
},
|
|
},
|
|
],
|
|
}
|
|
],
|
|
)
|
|
|
|
assert payloads["messages"][0]["content"] == [
|
|
{"type": "text", "text": "look"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://example.com/expired.png",
|
|
},
|
|
},
|
|
]
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_apply_provider_specific_request_overrides_disables_ollama_thinking():
|
|
provider = _make_provider(
|
|
{
|
|
"provider": "ollama",
|
|
"ollama_disable_thinking": True,
|
|
}
|
|
)
|
|
try:
|
|
extra_body = {
|
|
"reasoning": {"effort": "high"},
|
|
"reasoning_effort": "low",
|
|
"think": True,
|
|
"temperature": 0.2,
|
|
}
|
|
|
|
provider._apply_provider_specific_request_overrides({}, extra_body)
|
|
|
|
assert extra_body["reasoning_effort"] == "none"
|
|
assert "reasoning" not in extra_body
|
|
assert "think" not in extra_body
|
|
assert extra_body["temperature"] == 0.2
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_provider_specific_request_overrides_sets_minimax_m3_max_tokens():
|
|
provider = _make_provider({"provider": "nvidia"})
|
|
try:
|
|
payloads = {"model": "minimaxai/minimax-m3"}
|
|
extra_body = {"temperature": 0.2}
|
|
|
|
provider._apply_provider_specific_request_overrides(payloads, extra_body)
|
|
|
|
assert payloads["max_tokens"] == 8192
|
|
assert extra_body == {"temperature": 0.2}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_minimax_m3_max_tokens_preserves_custom_extra_body_value():
|
|
provider = _make_provider({"provider": "nvidia"})
|
|
try:
|
|
payloads = {"model": "minimaxai/minimax-m3"}
|
|
extra_body = {"max_tokens": 4096}
|
|
|
|
provider._apply_provider_specific_request_overrides(payloads, extra_body)
|
|
|
|
assert "max_tokens" not in payloads
|
|
assert extra_body["max_tokens"] == 4096
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_minimax_m3_max_tokens_preserves_standard_payload_value():
|
|
provider = _make_provider({"provider": "nvidia"})
|
|
try:
|
|
payloads = {
|
|
"model": "minimaxai/minimax-m3",
|
|
"max_tokens": 2048,
|
|
}
|
|
extra_body = {}
|
|
|
|
provider._apply_provider_specific_request_overrides(payloads, extra_body)
|
|
|
|
assert payloads["max_tokens"] == 2048
|
|
assert extra_body == {}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_nvidia_request_does_not_set_max_tokens_for_other_models():
|
|
provider = _make_provider({"provider": "nvidia"})
|
|
try:
|
|
payloads = {"model": "nvidia/usdcode"}
|
|
extra_body = {}
|
|
|
|
provider._apply_provider_specific_request_overrides(payloads, extra_body)
|
|
|
|
assert "max_tokens" not in payloads
|
|
assert "max_tokens" not in extra_body
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_injects_reasoning_effort_none_for_ollama(monkeypatch):
|
|
provider = _make_provider(
|
|
{
|
|
"provider": "ollama",
|
|
"ollama_disable_thinking": True,
|
|
"custom_extra_body": {
|
|
"reasoning": {"effort": "high"},
|
|
"temperature": 0.1,
|
|
},
|
|
}
|
|
)
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "qwen3.5:4b",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
await provider._query(
|
|
payloads={
|
|
"model": "qwen3.5:4b",
|
|
"messages": [{"role": "user", "content": "hello"}],
|
|
},
|
|
tools=None,
|
|
)
|
|
|
|
extra_body = captured_kwargs["extra_body"]
|
|
assert extra_body["reasoning_effort"] == "none"
|
|
assert "reasoning" not in extra_body
|
|
assert extra_body["temperature"] == 0.1
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_parse_openai_completion_raises_empty_model_output_error():
|
|
provider = _make_provider()
|
|
try:
|
|
completion = ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-empty",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": None,
|
|
"refusal": None,
|
|
"tool_calls": None,
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 0,
|
|
"total_tokens": 1,
|
|
},
|
|
}
|
|
)
|
|
|
|
with pytest.raises(EmptyModelOutputError):
|
|
await provider._parse_openai_completion(completion, tools=None)
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_parse_openai_completion_reads_nested_data_choices():
|
|
provider = _make_provider()
|
|
try:
|
|
completion = ChatCompletion.model_construct(
|
|
id=None,
|
|
object="chat.completion",
|
|
created=None,
|
|
model=None,
|
|
choices=None,
|
|
data={
|
|
"id": "gen_test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "deepseek/deepseek-v4-flash",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "PONG",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 12,
|
|
"completion_tokens": 38,
|
|
"total_tokens": 50,
|
|
},
|
|
},
|
|
)
|
|
|
|
response = await provider._parse_openai_completion(completion, tools=None)
|
|
|
|
assert response.completion_text == "PONG"
|
|
assert response.id == "gen_test"
|
|
assert response.usage is not None
|
|
assert response.usage.input_other == 12
|
|
assert response.usage.output == 38
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_stream_extracts_usage_from_empty_choices_chunk(monkeypatch):
|
|
provider = _make_provider()
|
|
try:
|
|
chunks = [
|
|
ChatCompletionChunk.model_validate(
|
|
{
|
|
"id": "chatcmpl-stream",
|
|
"object": "chat.completion.chunk",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"delta": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": None,
|
|
}
|
|
],
|
|
}
|
|
),
|
|
ChatCompletionChunk.model_validate(
|
|
{
|
|
"id": "chatcmpl-stream",
|
|
"object": "chat.completion.chunk",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"delta": {},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
}
|
|
),
|
|
ChatCompletionChunk.model_validate(
|
|
{
|
|
"id": "chatcmpl-stream",
|
|
"object": "chat.completion.chunk",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [],
|
|
"usage": {
|
|
"prompt_tokens": 2550,
|
|
"completion_tokens": 125,
|
|
"total_tokens": 2675,
|
|
"prompt_tokens_details": {
|
|
"cached_tokens": 2488,
|
|
},
|
|
},
|
|
}
|
|
),
|
|
]
|
|
|
|
async def fake_stream():
|
|
for chunk in chunks:
|
|
yield chunk
|
|
|
|
async def fake_create(**kwargs):
|
|
return fake_stream()
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
responses = [
|
|
response
|
|
async for response in provider._query_stream(
|
|
payloads={
|
|
"model": "gpt-4o-mini",
|
|
"messages": [{"role": "user", "content": "hello"}],
|
|
},
|
|
tools=None,
|
|
)
|
|
]
|
|
|
|
final_response = responses[-1]
|
|
assert final_response.completion_text == "ok"
|
|
assert final_response.usage is not None
|
|
assert final_response.usage.input_other == 62
|
|
assert final_response.usage.input_cached == 2488
|
|
assert final_response.usage.output == 125
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
def test_sanitize_assistant_messages_removes_orphaned_tool_messages():
|
|
payloads = {
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{
|
|
"role": "tool",
|
|
"tool_call_id": "missing_call",
|
|
"content": "stale result",
|
|
},
|
|
{"role": "user", "content": "continue"},
|
|
]
|
|
}
|
|
|
|
ProviderOpenAIOfficial._sanitize_assistant_messages(payloads)
|
|
|
|
assert payloads["messages"] == [
|
|
{"role": "user", "content": "hello"},
|
|
{"role": "user", "content": "continue"},
|
|
]
|
|
|
|
|
|
def test_sanitize_assistant_messages_keeps_valid_tool_messages_only():
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "tool", "tool_call_id": "call_00", "content": "one"},
|
|
{
|
|
"role": "tool",
|
|
"tool_call_id": "",
|
|
"content": "empty id should not be valid",
|
|
},
|
|
]
|
|
}
|
|
|
|
ProviderOpenAIOfficial._sanitize_assistant_messages(payloads)
|
|
|
|
assert payloads["messages"] == [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "tool", "tool_call_id": "call_00", "content": "one"},
|
|
]
|
|
|
|
|
|
def test_sanitize_assistant_messages_removes_stale_duplicate_tool_message():
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "tool", "tool_call_id": "call_00", "content": "one"},
|
|
{
|
|
"role": "tool",
|
|
"tool_call_id": "call_00",
|
|
"content": "stale duplicate",
|
|
},
|
|
{"role": "assistant", "content": "done"},
|
|
]
|
|
}
|
|
|
|
ProviderOpenAIOfficial._sanitize_assistant_messages(payloads)
|
|
|
|
assert payloads["messages"] == [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "tool", "tool_call_id": "call_00", "content": "one"},
|
|
{"role": "assistant", "content": "done"},
|
|
]
|
|
|
|
|
|
def test_sanitize_assistant_messages_resets_tool_ids_after_non_tool_message():
|
|
payloads = {
|
|
"messages": [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "user", "content": "new turn"},
|
|
{
|
|
"role": "tool",
|
|
"tool_call_id": "call_00",
|
|
"content": "stale late result",
|
|
},
|
|
]
|
|
}
|
|
|
|
ProviderOpenAIOfficial._sanitize_assistant_messages(payloads)
|
|
|
|
assert payloads["messages"] == [
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call_00",
|
|
"type": "function",
|
|
"function": {"name": "search", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "user", "content": "new turn"},
|
|
]
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_filters_empty_assistant_message_without_tool_calls(monkeypatch):
|
|
"""Test that empty assistant messages without tool_calls are filtered out."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{"role": "assistant", "content": ""}, # Should be filtered
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# The empty assistant message should be filtered out
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 2
|
|
assert messages[0] == {"role": "user", "content": "hello"}
|
|
assert messages[1] == {"role": "user", "content": "world"}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_filters_null_content_assistant_message_without_tool_calls(
|
|
monkeypatch,
|
|
):
|
|
"""Test that assistant messages with null content and no tool_calls are filtered."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{"role": "assistant", "content": None}, # Should be filtered
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# The null content assistant message should be filtered out
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 2
|
|
assert messages[0] == {"role": "user", "content": "hello"}
|
|
assert messages[1] == {"role": "user", "content": "world"}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_converts_empty_content_to_none_with_tool_calls(monkeypatch):
|
|
"""Test that empty content with tool_calls is converted to None (OpenAI spec)."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{
|
|
"role": "assistant",
|
|
"content": "",
|
|
"tool_calls": [
|
|
{
|
|
"id": "call-123",
|
|
"type": "function",
|
|
"function": {"name": "test", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# The assistant message with tool_calls should be kept but content set to None
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 3
|
|
assert messages[1]["role"] == "assistant"
|
|
assert messages[1]["content"] is None
|
|
assert messages[1]["tool_calls"] is not None
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_keeps_valid_assistant_message_with_content(monkeypatch):
|
|
"""Test that valid assistant messages with content are kept."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{"role": "assistant", "content": "response"},
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# All messages should be kept
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 3
|
|
assert messages[1] == {"role": "assistant", "content": "response"}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_keeps_assistant_message_with_tool_calls_and_none_content(
|
|
monkeypatch,
|
|
):
|
|
"""Test that assistant messages with tool_calls and None content are kept."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{
|
|
"role": "assistant",
|
|
"content": None,
|
|
"tool_calls": [
|
|
{
|
|
"id": "call-123",
|
|
"type": "function",
|
|
"function": {"name": "test", "arguments": "{}"},
|
|
}
|
|
],
|
|
},
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# The assistant message with tool_calls should be kept
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 3
|
|
assert messages[1]["role"] == "assistant"
|
|
assert messages[1]["content"] is None
|
|
assert messages[1]["tool_calls"] is not None
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_does_not_filter_user_or_system_messages(monkeypatch):
|
|
"""Test that user and system messages are not affected by the filter."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {
|
|
"role": "assistant",
|
|
"content": "ok",
|
|
},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "system", "content": ""}, # Empty system message
|
|
{"role": "user", "content": ""}, # Empty user message
|
|
{"role": "assistant", "content": ""}, # Should be filtered
|
|
{"role": "user", "content": "hello"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
# Only assistant message should be filtered
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 3
|
|
assert messages[0] == {"role": "system", "content": ""}
|
|
assert messages[1] == {"role": "user", "content": ""}
|
|
assert messages[2] == {"role": "user", "content": "hello"}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_stream_filters_empty_assistant_message(monkeypatch):
|
|
"""Regression for #7721: streaming path must also filter empty assistant messages.
|
|
|
|
Previously only ``_query`` sanitized the payload; ``_query_stream`` forwarded
|
|
the raw history and strict providers (e.g. DeepSeek Reasoner) returned 400 on
|
|
the next turn after a tool call whose assistant entry had reasoning only.
|
|
"""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_stream():
|
|
yield ChatCompletionChunk.model_validate(
|
|
{
|
|
"id": "chatcmpl-stream",
|
|
"object": "chat.completion.chunk",
|
|
"created": 0,
|
|
"model": "deepseek-reasoner",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"delta": {"role": "assistant", "content": "ok"},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
}
|
|
)
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return fake_stream()
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "deepseek-reasoner",
|
|
"messages": [
|
|
{"role": "user", "content": "hello"},
|
|
{"role": "assistant", "content": ""}, # should be filtered
|
|
{"role": "user", "content": "world"},
|
|
],
|
|
}
|
|
|
|
async for _ in provider._query_stream(payloads=payloads, tools=None):
|
|
pass
|
|
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 2
|
|
assert messages[0] == {"role": "user", "content": "hello"}
|
|
assert messages[1] == {"role": "user", "content": "world"}
|
|
finally:
|
|
await provider.terminate()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_query_filters_empty_list_content_assistant_message(monkeypatch):
|
|
"""Empty-list content (``content == []``) must also be filtered, not just ``""`` / ``None``."""
|
|
provider = _make_provider()
|
|
try:
|
|
captured_kwargs = {}
|
|
|
|
async def fake_create(**kwargs):
|
|
captured_kwargs.update(kwargs)
|
|
return ChatCompletion.model_validate(
|
|
{
|
|
"id": "chatcmpl-test",
|
|
"object": "chat.completion",
|
|
"created": 0,
|
|
"model": "gpt-4o-mini",
|
|
"choices": [
|
|
{
|
|
"index": 0,
|
|
"message": {"role": "assistant", "content": "ok"},
|
|
"finish_reason": "stop",
|
|
}
|
|
],
|
|
"usage": {
|
|
"prompt_tokens": 1,
|
|
"completion_tokens": 1,
|
|
"total_tokens": 2,
|
|
},
|
|
}
|
|
)
|
|
|
|
monkeypatch.setattr(provider.client.chat.completions, "create", fake_create)
|
|
|
|
payloads = {
|
|
"model": "gpt-4o-mini",
|
|
"messages": [
|
|
{"role": "user", "content": "hi"},
|
|
{"role": "assistant", "content": []}, # should be filtered
|
|
{"role": "user", "content": "again"},
|
|
],
|
|
}
|
|
|
|
await provider._query(payloads=payloads, tools=None)
|
|
|
|
messages = captured_kwargs["messages"]
|
|
assert len(messages) == 2
|
|
assert messages[0] == {"role": "user", "content": "hi"}
|
|
assert messages[1] == {"role": "user", "content": "again"}
|
|
finally:
|
|
await provider.terminate()
|