Vito Sansevero
6ce8e25a59
Review findings: an unreadable text link counts as built from a candidate only through that node's first output, so a LoRA loader's trigger-word output is unknown, not its text. A node with a seed input holds a template, never the prompt that ran. A sampler-less graph the rule cannot decide still links the A1111 positive a metadata saver wrote beside it, as the old scan did. Only plain numbers are numeric; words such as nan or inf are prompts.
105 lines
4.2 KiB
Python
105 lines
4.2 KiB
Python
"""``sampler_less_prompt``: the one wired text of a graph with no sampler (#252)."""
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import unittest
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from utils.prompt_pair_resolver import sampler_less_prompt
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def _guided(**nodes):
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"""``nodes`` plus a guider consuming node ``"1"``."""
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graph = {"9": {"class_type": "BasicGuider", "inputs": {"conditioning": ["1", 0]}}}
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graph.update(nodes)
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return graph
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class TestSamplerLessPrompt(unittest.TestCase):
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def test_not_a_graph_or_too_large_is_absent(self):
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for graph in (None, [], {}, "text"):
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self.assertEqual(sampler_less_prompt(graph)["state"], "absent")
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big = {str(i): {"class_type": "X", "inputs": {}} for i in range(3)}
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self.assertEqual(sampler_less_prompt(big, max_visits=2)["state"], "absent")
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def test_one_literal_text(self):
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graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": " a fox "}}})
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self.assertEqual(
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sampler_less_prompt(graph),
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{"state": "resolved", "text": "a fox", "texts": ["a fox"]},
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)
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def test_a_number_literal_is_never_a_prompt(self):
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for value in (2048, "2048", "1.5", " 7 "):
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graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": value}}})
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self.assertEqual(sampler_less_prompt(graph)["state"], "absent", value)
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def test_number_like_words_are_prompts(self):
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for value in ("nan", "inf", "Infinity", "1_000"):
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graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": value}}})
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self.assertEqual(sampler_less_prompt(graph)["text"], value)
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def test_an_own_node_with_unreadable_text_beside_another_text_is_ambiguous(self):
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graph = _guided(
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**{
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"1": {"class_type": "PromptManager", "inputs": {"text": ["5", 0]}},
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"5": {"class_type": "LLM", "inputs": {"seed": 3}},
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"2": {"class_type": "Enc", "inputs": {"text": "<lora:x:1>"}},
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"3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
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}
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)
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self.assertEqual(sampler_less_prompt(graph)["state"], "ambiguous")
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def test_unhashable_class_type_is_an_unknown_node_not_a_crash(self):
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graph = _guided(**{"1": {"class_type": ["x"], "inputs": {"text": "a fox"}}})
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self.assertEqual(sampler_less_prompt(graph)["text"], "a fox")
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def test_own_negative_node_is_not_authoritative(self):
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graph = _guided(
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**{
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"1": {"class_type": "Enc", "inputs": {"text": "a fox"}},
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"2": {
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"class_type": "PromptManagerNegative",
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"inputs": {"text": "blur"},
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},
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"3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
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}
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)
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found = sampler_less_prompt(graph)
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self.assertEqual(found["state"], "ambiguous")
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self.assertEqual(found["texts"], ["a fox", "blur"])
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def test_own_node_text_wins_over_an_untraceable_text(self):
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graph = _guided(
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**{
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"1": {"class_type": "PromptManagerText", "inputs": {"text": "a fox"}},
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"2": {"class_type": "Enc", "inputs": {"text": ["5", 0]}},
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"5": {"class_type": "LLM", "inputs": {"seed": 3}},
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"6": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
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}
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)
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self.assertEqual(sampler_less_prompt(graph)["text"], "a fox")
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def test_two_own_texts_are_ambiguous(self):
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graph = _guided(
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**{
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"1": {"class_type": "PromptManager", "inputs": {"text": "a fox"}},
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"2": {"class_type": "PromptManager", "inputs": {"text": "a cat"}},
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"3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
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}
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)
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self.assertEqual(sampler_less_prompt(graph)["state"], "ambiguous")
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def test_only_an_untraceable_text_is_ambiguous_with_nothing_to_show(self):
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graph = _guided(
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**{
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"1": {"class_type": "Enc", "inputs": {"text": ["5", 0]}},
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"5": {"class_type": "LLM", "inputs": {"seed": 3}},
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}
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)
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self.assertEqual(
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sampler_less_prompt(graph),
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{"state": "ambiguous", "text": None, "texts": []},
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)
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if __name__ == "__main__":
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unittest.main()
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