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47 lines
2.0 KiB
Python
47 lines
2.0 KiB
Python
from backend.apps.agents.browser.browser_fast_path import (
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_normalize_for_classifier,
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_parse_verdict,
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fast_path_eligible,
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)
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def test_browsy_first_messages_are_eligible():
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for p in (
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"go to tyler chen's linkedin hes in entrepreneurs first and text him 'hi'",
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"open hacker news and tell me the top story",
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"look up on amazon how much a herman miller aeron costs",
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"check https://example.com/pricing and summarize the tiers",
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):
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assert fast_path_eligible(p, "agent", "dash1", True, False), p
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def test_non_browsy_or_gated_messages_fall_through():
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assert not fast_path_eligible("write me a poem about autumn", "agent", "dash1", True, False)
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assert not fast_path_eligible("fix the bug in agent_manager.py", "agent", "dash1", True, False)
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browsy = "open hacker news and tell me the top story"
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assert not fast_path_eligible(browsy, "chat", "dash1", True, False)
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assert not fast_path_eligible(browsy, "agent", None, True, False)
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assert not fast_path_eligible(browsy, "agent", "dash1", False, False)
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assert not fast_path_eligible(browsy, "agent", "dash1", True, True)
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assert not fast_path_eligible("", "agent", "dash1", True, False)
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def test_verdict_parsing_is_strict():
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assert _parse_verdict("YES")
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assert _parse_verdict("yes, this is browser-only")
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assert not _parse_verdict("NO")
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assert not _parse_verdict("Maybe")
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assert not _parse_verdict("")
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def test_text_normalizes_to_message_without_phone_number():
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assert (
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_normalize_for_classifier("go to maya's linkedin and text her thanks")
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== "go to maya's linkedin and message her thanks"
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)
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assert _normalize_for_classifier("keep texting until he replies").startswith("keep message")
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sms = "text 4085551234 saying im running late"
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assert _normalize_for_classifier(sms) == sms
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count = "count messages containing the exact text r10-os"
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assert "message r10-os" in _normalize_for_classifier(count)
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