51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
"""In-process fake backend for tests.
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Returns a canned string so the driver path can be exercised without an
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Ollama install. Configurable via ``DECNET_REALISM_FAKE_OUTPUT`` (env)
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or the ``output`` constructor arg — the env-var path lets integration
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tests run the worker end-to-end with deterministic output.
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"""
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from __future__ import annotations
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import os
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import time
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from typing import Optional
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from decnet.realism.llm.base import LLMBackend, LLMResult
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_DEFAULT_OUTPUT = (
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"Subject: Quick update\n\n"
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"Hi,\n\nFollowing up on the topic.\n\nBest regards,\nFake Persona\n"
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)
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class FakeBackend(LLMBackend):
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def __init__(
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self,
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*,
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model: str = "fake-model",
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timeout: float = 1.0,
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output: Optional[str] = None,
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success: bool = True,
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) -> None:
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self.model = model
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self.timeout = timeout
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self._output = (
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output
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if output is not None
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else os.environ.get("DECNET_REALISM_FAKE_OUTPUT", _DEFAULT_OUTPUT)
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)
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self._success = success
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async def generate(self, prompt: str) -> LLMResult: # noqa: ARG002
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t0 = time.monotonic()
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latency_ms = int((time.monotonic() - t0) * 1000)
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return LLMResult(
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success=self._success,
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text=self._output if self._success else "",
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model=self.model,
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latency_ms=latency_ms,
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extra={"rc": 0 if self._success else 1},
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)
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