cryptorugmunch
a7c30b12cd
Mass ruff auto-fix:
- ruff check --fix: 109 issues fixed (F401 unused imports,
I001 unsorted imports, UP037 quoted annotations, SIM105
suppressible exception, RUF100 unused-noqa)
- ruff check --fix --unsafe-fixes: 22 additional issues
- ruff format: 70 files reformatted
- Manual pass: fix 16 misplaced import httpx lines
- Manual pass: fix remaining E402 (import-after-docstring)
Result: 283 errors -> 30 errors.
The remaining 30 are real issues that need manual review:
5 F401 unused-import (likely auto-generated stubs)
5 F821 undefined-name (real bugs in code that references
redis/pydantic/LLMRegistry without imports)
3 BLE001 (the compliance LLM fallback is intentional; the
other two are real)
3 RUF012 mutable-class-default
3 SIM105, 3 SIM117, 2 E722, 2 E741
1 B007, 1 B025, 1 E402, 1 RUF200 (pyproject.toml issue)
Tests: 436/437 pass (1 pre-existing SSE sandbox failure).
format check + import sort: now clean.
make ci: still gated on the 30 remaining real issues.
Follow-up: triage the 30 issues file-by-file.
74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
# SPDX-License-Identifier: MIT
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# Copyright (c) 2026 Rug Munch Media LLC
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#
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# Part of Pry — https://git.rugmunch.io/RugMunchMedia/pryscraper
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# Licensed under MIT. See LICENSE.
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"""Tests for LLM provider system."""
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from llm_providers.base import LLMProvider, LLMResponse, ReferralConfig
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from llm_providers.registry import LLMRegistry
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def test_referral_config() -> None:
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rc = ReferralConfig()
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assert rc.enabled is True
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assert "openai" in rc.referral_links
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assert "anthropic" in rc.referral_links
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assert "pry" in rc.referral_links["openai"]
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def test_llm_registry_init() -> None:
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r = LLMRegistry()
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stats = r.get_stats()
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assert "providers" in stats
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assert "referral" in stats
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assert "fallback_chain" in stats
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def test_llm_registry_register() -> None:
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r = LLMRegistry()
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class FakeProvider(LLMProvider):
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name = "fake"
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async def complete(self, *args, **kwargs):
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return LLMResponse(text="ok", model="fake", provider="fake")
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async def embed(self, *args, **kwargs):
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return [0.1, 0.2]
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r.register(FakeProvider())
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assert "fake" in r.providers
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def test_llm_response_dataclass() -> None:
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r = LLMResponse(
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text="hello", model="m", provider="p", input_tokens=10, output_tokens=5, cost_usd=0.001
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)
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assert r.text == "hello"
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assert r.cost_usd == 0.001
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def test_provider_cost_estimation() -> None:
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class TestProvider(LLMProvider):
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cost_per_1k_input = 0.001
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cost_per_1k_output = 0.002
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async def complete(self, *args, **kwargs):
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return LLMResponse(text="", model="t", provider="t")
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async def embed(self, *args, **kwargs):
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return []
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p = TestProvider()
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cost = p.estimate_cost(1000, 500)
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assert abs(cost - 0.002) < 0.0001 # 0.001 + 0.001
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def test_referral_link_format() -> None:
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rc = ReferralConfig()
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for provider, link in rc.referral_links.items():
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# FlareSolverr is open-source, no affiliate
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if provider == "flaresolverr":
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continue
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assert "pry" in link, f"Link for {provider} missing referral: {link}"
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