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import unittest
from unittest import mock
import json
from services.config import config
from services.protocol import openai_v1_chat_complete, openai_v1_response
from services.protocol.chat_completion_cache import chat_completion_cache
from services.protocol.conversation import iter_conversation_payloads, sanitize_output_text
class ChatCompletionCacheTests(unittest.TestCase):
def setUp(self) -> None:
self.old_cache_settings = config.data.get("chat_completion_cache")
config.data["chat_completion_cache"] = {
"enabled": True,
"ttl_seconds": 60,
"max_entries": 32,
"dedupe_inflight": True,
"stream_cache": True,
"normalize_messages": True,
"drop_adjacent_duplicates": True,
"drop_assistant_history": False,
}
chat_completion_cache.clear()
def tearDown(self) -> None:
if self.old_cache_settings is None:
config.data.pop("chat_completion_cache", None)
else:
config.data["chat_completion_cache"] = self.old_cache_settings
chat_completion_cache.clear()
def test_repeated_non_stream_text_completion_uses_cache(self) -> None:
calls = 0
def fake_collect_text(_backend, _request):
nonlocal calls
calls += 1
return f"cached answer {calls}"
body = {
"model": "auto",
"messages": [{"role": "user", "content": "cache this exact prompt"}],
}
with (
mock.patch("services.protocol.openai_v1_chat_complete.text_backend", return_value=object()),
mock.patch("services.protocol.openai_v1_chat_complete.collect_text", side_effect=fake_collect_text),
):
first = openai_v1_chat_complete.handle(body)
second = openai_v1_chat_complete.handle(body)
self.assertEqual(calls, 1)
self.assertEqual(
first["choices"][0]["message"]["content"],
second["choices"][0]["message"]["content"],
)
def test_repeated_stream_text_completion_replays_cached_chunks(self) -> None:
calls = 0
def fake_stream_text_deltas(_backend, _request):
nonlocal calls
calls += 1
yield "streamed"
yield " answer"
body = {
"model": "auto",
"stream": True,
"messages": [{"role": "user", "content": "stream cache this exact prompt"}],
}
with (
mock.patch("services.protocol.openai_v1_chat_complete.text_backend", return_value=object()),
mock.patch(
"services.protocol.openai_v1_chat_complete.stream_text_deltas",
side_effect=fake_stream_text_deltas,
),
):
first = list(openai_v1_chat_complete.handle(body))
second = list(openai_v1_chat_complete.handle(body))
self.assertEqual(calls, 1)
self.assertEqual(first, second)
content = "".join(str(chunk["choices"][0]["delta"].get("content") or "") for chunk in second)
self.assertEqual(content, "streamed answer")
def test_adjacent_duplicate_messages_are_removed_before_upstream_call(self) -> None:
captured_messages = []
def fake_collect_text(_backend, request):
captured_messages.extend(request.messages or [])
return "ok"
body = {
"model": "auto",
"messages": [
{"role": "user", "content": "repeat me"},
{"role": "user", "content": "repeat me"},
{"role": "assistant", "content": "old answer"},
{"role": "user", "content": "next prompt"},
],
}
with (
mock.patch("services.protocol.openai_v1_chat_complete.text_backend", return_value=object()),
mock.patch("services.protocol.openai_v1_chat_complete.collect_text", side_effect=fake_collect_text),
):
openai_v1_chat_complete.handle(body)
self.assertEqual(
captured_messages,
[
{"role": "user", "content": "repeat me"},
{"role": "assistant", "content": "old answer"},
{"role": "user", "content": "next prompt"},
],
)
def test_chat_completion_usage_includes_cached_tokens(self) -> None:
with (
mock.patch("services.protocol.openai_v1_chat_complete.text_backend", return_value=object()),
mock.patch("services.protocol.openai_v1_chat_complete.collect_text", return_value="ok"),
):
response = openai_v1_chat_complete.handle({
"model": "auto",
"messages": [{"role": "user", "content": "usage shape"}],
})
details = response["usage"]["prompt_tokens_details"]
self.assertEqual(details["cached_tokens"], 0)
output_details = response["usage"]["completion_tokens_details"]
self.assertEqual(output_details["reasoning_tokens"], 0)
def test_responses_completed_usage_includes_cached_tokens(self) -> None:
with (
mock.patch("services.protocol.openai_v1_response.text_backend", return_value=object()),
mock.patch("services.protocol.openai_v1_response.stream_text_deltas", return_value=iter(["ok"])),
):
response = openai_v1_response.handle({
"model": "auto",
"input": "usage shape",
})
details = response["usage"]["input_tokens_details"]
self.assertEqual(details["cached_tokens"], 0)
output_details = response["usage"]["output_tokens_details"]
self.assertEqual(output_details["reasoning_tokens"], 0)
def test_repeated_responses_text_request_uses_cache(self) -> None:
calls = 0
def fake_stream_text_deltas(_backend, _request):
nonlocal calls
calls += 1
yield f"response cache {calls}"
body = {
"model": "auto",
"input": "cache this responses prompt",
"stream": True,
}
with (
mock.patch("services.protocol.openai_v1_response.text_backend", return_value=object()),
mock.patch("services.protocol.openai_v1_response.stream_text_deltas", side_effect=fake_stream_text_deltas),
):
first = list(openai_v1_response.handle(body))
second = list(openai_v1_response.handle(body))
self.assertEqual(calls, 1)
self.assertEqual(first, second)
def test_output_sanitizer_removes_chatgpt_annotation_markup(self) -> None:
text = (
"Repo: \ue200url\ue202basketikun/chatgpt2api"
"\ue202https://github.com/basketikun/chatgpt2api\ue201 "
"details \ue200cite\ue202turn0search0\ue201."
)
self.assertEqual(
sanitize_output_text(text),
"Repo: basketikun/chatgpt2api (https://github.com/basketikun/chatgpt2api) details .",
)
def test_stream_sanitizer_does_not_emit_partial_annotation_or_repeat_prefix(self) -> None:
events = [
{"p": "/message/content/parts/0", "o": "append", "v": "Repo: \ue200url\ue202chat"},
{"p": "/message/content/parts/0", "o": "append", "v": "gpt2api\ue202turn0search0\ue201 done \ue200cite\ue202turn0\ue201."},
"[DONE]",
]
payloads = [json.dumps(event, ensure_ascii=False) if isinstance(event, dict) else event for event in events]
deltas = [
str(event.get("delta") or "")
for event in iter_conversation_payloads(iter(payloads))
if event.get("type") == "conversation.delta"
]
self.assertEqual("".join(deltas), "Repo: chatgpt2api done .")
self.assertFalse(any("\ue200" in delta or "\ue202" in delta or "\ue201" in delta for delta in deltas))
def test_responses_tools_add_honest_no_tool_guard(self) -> None:
model, messages = openai_v1_response.text_response_parts({
"model": "auto",
"input": "run echo hi",
"tools": [{"type": "function", "name": "shell"}],
})
self.assertEqual(model, "auto")
self.assertEqual(messages[0]["role"], "system")
self.assertIn("cannot execute local tools", str(messages[0]["content"]))
if __name__ == "__main__":
unittest.main()
|