WangShen007
20fef2b9f3
One word everywhere: ReplyPier in UI copy, package and image names, the replypier.site domains (app/api/docs/help), REPLYPIER_* settings and the --rp-* design tokens. - public widget API is window.ReplyPier with replypierId / replypierBaseUrl / replypierConfig / replypierToken, loader at webclient/replypier.min.js; both bundles rebuilt from source - NOTICE, llms.txt, CONTRIBUTING, HELP_CENTER_INFRA and the demo runtime config rewritten; the demo config ships no third-party keys - migration adds the ReplyPier managed model value to the AI model enum - local compose project, database, role, volume and Docker network carry the same name
96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
"""
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Copyright 2024-2026 ReplyPier
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import asyncio
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from types import SimpleNamespace
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from typing import List
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import pytest
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from app.agents.chat_agent import ChatAgent
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from app.agents.history_memory import BoundedHistoryMemory
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OVERFLOW = Exception(
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"This model's maximum context length is 128000 tokens. However, your messages resulted in 145155 tokens"
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)
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class _FakeAgent:
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"""Stands in for the agno Agent: each arun() consumes the next outcome and
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records the history budget in force at that moment."""
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def __init__(self, outcomes: List):
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self.outcomes = list(outcomes)
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self.memory = BoundedHistoryMemory()
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self.calls = 0
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self.budgets: List[int] = []
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async def arun(self, **kwargs):
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self.calls += 1
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self.budgets.append(getattr(self.memory, "history_max_chars", None))
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outcome = self.outcomes.pop(0)
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if isinstance(outcome, BaseException):
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raise outcome
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return outcome
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def _chat_agent(outcomes: List) -> ChatAgent:
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shell = ChatAgent.__new__(ChatAgent)
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shell.agent = _FakeAgent(outcomes)
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return shell
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@pytest.mark.asyncio
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async def test_overflow_retries_once_without_history_then_restores_budget():
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shell = _chat_agent([OVERFLOW, "ok"])
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assert await shell._arun("hi", "s1") == "ok"
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assert shell.agent.calls == 2
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assert shell.agent.budgets[1] == 0
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assert shell.agent.memory.history_max_chars > 0
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@pytest.mark.asyncio
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async def test_other_errors_are_not_retried():
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shell = _chat_agent([Exception("rate limit exceeded")])
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with pytest.raises(Exception, match="rate limit"):
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await shell._arun("hi", "s1")
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assert shell.agent.calls == 1
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@pytest.mark.asyncio
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async def test_second_overflow_surfaces():
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shell = _chat_agent([OVERFLOW, OVERFLOW])
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with pytest.raises(Exception, match="maximum context length"):
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await shell._arun("hi", "s1")
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assert shell.agent.calls == 2
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@pytest.mark.asyncio
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async def test_timeout_is_not_retried():
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shell = _chat_agent([asyncio.TimeoutError()])
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with pytest.raises(asyncio.TimeoutError):
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await shell._arun("hi", "s1")
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assert shell.agent.calls == 1
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@pytest.mark.asyncio
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async def test_plain_memory_is_not_retried():
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shell = _chat_agent([OVERFLOW])
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shell.agent.memory = SimpleNamespace()
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with pytest.raises(Exception, match="maximum context length"):
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await shell._arun("hi", "s1")
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assert shell.agent.calls == 1
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