Vito
6c7e4d5b35
* chore: start 3.2.4 * feat: track prompt usage (run_count, last_used_at) with server-side sorting - Migration adds last_used_at and run_count; existing prompts are estimated from linked images (count, newest image time, else created_at). The backfill only touches NULL rows, so it self-heals rows written after a downgrade or an interrupted upgrade. - Every node run records a use, including re-runs of an existing prompt; a tracking failure is logged and never blocks generation. - search_prompts/get_recent_prompts accept a whitelisted sort key (last_used, created, run_count, rating, text); default stays newest first. Refs #90 * feat: sort param on /recent and /search; microsecond last_used_at - /prompt_manager/recent and /search accept ?sort= (whitelisted in the DB layer; unknown values fall back to newest first). - last_used_at is written with microseconds from Python so a re-run in the same millisecond as another save still sorts first; ordering stays correct against millisecond values from the backfill. Refs #90 * feat: server-side sort in admin UI with Recently Used / Most Used and run badges - New web/js/prompt-list-sort.js owns the sort options, validation and request URLs; admin.js fills the dropdown from it and re-fetches from the server on change, so every sort spans all pages (the old client-side sort only reordered the current page). - Default sort is Recently Used; prompt cards show a run-count badge with the last-used time on hover. - The node's Recent button now lists recently used prompts. - Contract test keeps the UI sort keys and the node's key in sync with the server whitelist. Refs #90 * fix: link images and count runs by the positive prompt, not node execution With a negative-prompt PromptManager node in the workflow, every executed PromptManager node pushed onto the image-linking queue, so images could be linked to the negative prompt or to a previous run. ComfyUI also skips unchanged nodes, so re-runs of the same prompt were never counted. - utils/prompt_graph.py finds the PromptManager nodes feeding a sampler's positive input (KSampler, CFG/Basic guiders, ControlNet and combine pass-throughs, PromptManagerText into encoders), falling back to all PromptManager nodes when none can be traced. - Runs are counted by a ComfyUI on-prompt hook when a workflow is queued; prompts not yet saved are counted when the node first saves them. - Nodes receive the queued graph (hidden PROMPT/UNIQUE_ID). Only the run's positive prompt becomes the current prompt; only batch items with linked text are pushed onto the FIFO queue. - The image monitor links from the image's own metadata first, using the positive node, and falls back to the queue for batch items. Refs #90 * fix: address review — count cached runs of linked text, keep repeated pending runs - Text from known pure string nodes (core PrimitiveString/StringConcatenate, WAS Text Concatenate/Multiline, pysssss ShowText) is resolved at queue time, so cached re-runs of such prompts are counted and their images link from metadata. Unknown nodes are never guessed; the node compares its real text with the queue-time resolution and falls back to counting and queueing itself on any mismatch. - A new prompt queued several times before its first run keeps every pending run; the first save records all of them. - Registration flag is a threading.Event; consistent unittest imports; logging instead of print in the init fallback. * refactor: unquote PendingFirstUse annotation so Tuple usage is visible
245 lines
8.2 KiB
Python
245 lines
8.2 KiB
Python
"""Tests for utils.prompt_graph: which PromptManager nodes feed a positive input."""
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import os
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import sys
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import unittest
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from utils.prompt_graph import (
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positive_prompt_nodes,
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resolve_text,
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run_prompt_nodes,
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)
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def pm(text="a cat", **inputs):
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return {"class_type": "PromptManager", "inputs": {"text": text, **inputs}}
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def ksampler(positive, negative, model="20"):
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return {
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"class_type": "KSampler",
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"inputs": {
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"positive": [positive, 0],
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"negative": [negative, 0],
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"model": [model, 0],
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},
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}
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LOADER = {
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"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": "m.safetensors"},
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}
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class TestPositivePromptNodes(unittest.TestCase):
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def test_positive_and_negative_prompt_manager_nodes(self):
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# Negative listed first, as in the #75 / pmtest workflow
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graph = {
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"176": pm("blurry"),
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"134": pm("a cat"),
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"5": ksampler("134", "176"),
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"20": LOADER,
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}
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self.assertEqual(positive_prompt_nodes(graph), ["134"])
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def test_negative_only_prompt_manager_is_never_positive(self):
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graph = {
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"176": pm("blurry"),
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"6": {"class_type": "CLIPTextEncode", "inputs": {"text": "a cat"}},
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"5": ksampler("6", "176"),
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"20": LOADER,
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}
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self.assertEqual(positive_prompt_nodes(graph), [])
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def test_through_controlnet_and_combine_pass_throughs(self):
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graph = {
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"1": pm("subject"),
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"2": pm("style"),
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"3": pm("blurry"),
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"4": {
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"class_type": "ConditioningCombine",
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"inputs": {"conditioning_1": ["1", 0], "conditioning_2": ["2", 0]},
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},
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"5": {
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"class_type": "ControlNetApplyAdvanced",
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"inputs": {"positive": ["4", 0], "negative": ["3", 0], "strength": 1.0},
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},
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"6": {
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"class_type": "KSampler",
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"inputs": {
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"positive": ["5", 0],
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"negative": ["5", 1],
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"model": ["20", 0],
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},
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},
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"20": LOADER,
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}
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self.assertEqual(sorted(positive_prompt_nodes(graph)), ["1", "2"])
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def test_cfg_guider_and_basic_guider(self):
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graph = {
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"1": pm("fox"),
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"2": pm("watermark"),
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"3": {
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"class_type": "CFGGuider",
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"inputs": {
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"positive": ["1", 0],
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"negative": ["2", 0],
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"model": ["20", 0],
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"cfg": 5,
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},
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},
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"4": pm("owl"),
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"5": {
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"class_type": "BasicGuider",
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"inputs": {"conditioning": ["4", 0], "model": ["20", 0]},
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},
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"20": LOADER,
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}
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self.assertEqual(sorted(positive_prompt_nodes(graph)), ["1", "4"])
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def test_prompt_manager_text_wired_into_an_encoder(self):
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graph = {
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"1": {"class_type": "PromptManagerText", "inputs": {"text": "a castle"}},
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"2": {"class_type": "CLIPTextEncode", "inputs": {"text": ["1", 0]}},
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"3": {"class_type": "PromptManagerText", "inputs": {"text": "lowres"}},
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"4": {"class_type": "CLIPTextEncode", "inputs": {"text": ["3", 0]}},
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"5": ksampler("2", "4"),
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"20": LOADER,
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}
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self.assertEqual(positive_prompt_nodes(graph), ["1"])
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def test_node_used_as_both_positive_and_negative_counts_as_positive(self):
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graph = {"1": pm("same"), "5": ksampler("1", "1"), "20": LOADER}
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self.assertEqual(positive_prompt_nodes(graph), ["1"])
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def test_two_samplers_sharing_a_prompt_list_it_once(self):
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graph = {
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"1": pm("hero"),
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"2": pm("blurry"),
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"5": ksampler("1", "2"),
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"14": ksampler("1", "2"),
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"20": LOADER,
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}
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self.assertEqual(positive_prompt_nodes(graph), ["1"])
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def test_graph_without_sampler_or_malformed_input(self):
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self.assertEqual(positive_prompt_nodes({"1": pm()}), [])
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for bad in (None, [], "x", {"1": None}, {"1": {"inputs": None}}):
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self.assertEqual(positive_prompt_nodes(bad), [], repr(bad))
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def test_cycles_terminate(self):
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loop = {
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"class_type": "Weird",
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"inputs": {
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"conditioning": ["9", 0],
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"conditioning_1": ["9", 0],
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"positive": ["9", 0],
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},
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}
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graph = {"9": loop, "5": ksampler("9", "9"), "20": LOADER}
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self.assertEqual(positive_prompt_nodes(graph), [])
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class TestRunPromptNodes(unittest.TestCase):
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"""The prompt nodes that represent a run, with a safe fallback."""
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def test_uses_positive_nodes_when_found(self):
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graph = {
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"176": pm("blurry"),
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"134": pm("a cat"),
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"5": ksampler("134", "176"),
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"20": LOADER,
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}
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self.assertEqual(run_prompt_nodes(graph), ["134"])
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def test_unrecognised_sampler_falls_back_to_every_prompt_manager_node(self):
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graph = {
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"1": pm("a cat"),
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"9": {"class_type": "ExoticSampler", "inputs": {"cond": ["1", 0]}},
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"2": {"class_type": "PromptManagerText", "inputs": {"text": "x"}},
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}
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self.assertEqual(sorted(run_prompt_nodes(graph)), ["1", "2"])
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def test_malformed_graph(self):
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self.assertEqual(run_prompt_nodes(None), [])
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class TestResolveText(unittest.TestCase):
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"""Text known at queue time: typed, or from known pure string nodes."""
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def _linked(self, source):
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return {"1": pm(["2", 0]), "2": source}
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def test_typed_text(self):
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self.assertEqual(resolve_text({"1": pm(" a cat ")}, "1"), "a cat")
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def test_core_primitive_string(self):
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for cls in ("PrimitiveString", "PrimitiveStringMultiline"):
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graph = self._linked({"class_type": cls, "inputs": {"value": "a cat"}})
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self.assertEqual(resolve_text(graph, "1"), "a cat", cls)
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def test_core_string_concatenate(self):
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graph = self._linked(
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{
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"class_type": "StringConcatenate",
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"inputs": {
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"string_a": "a cat",
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"string_b": "at dusk",
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"delimiter": ", ",
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},
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}
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)
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self.assertEqual(resolve_text(graph, "1"), "a cat, at dusk")
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def test_was_text_concatenate_skips_empty_and_cleans_whitespace(self):
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graph = self._linked(
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{
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"class_type": "Text Concatenate",
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"inputs": {
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"delimiter": " ",
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"clean_whitespace": "true",
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"text_a": " a cat ",
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"text_b": "",
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"text_c": ["3", 0],
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},
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}
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)
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graph["3"] = {"class_type": "PrimitiveString", "inputs": {"value": "at dusk"}}
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self.assertEqual(resolve_text(graph, "1"), "a cat at dusk")
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def test_pass_through_nodes(self):
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for cls in ("ShowText|pysssss", "Text Multiline"):
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graph = self._linked({"class_type": cls, "inputs": {"text": "a cat"}})
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self.assertEqual(resolve_text(graph, "1"), "a cat", cls)
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def test_unknown_and_batch_sources_are_never_guessed(self):
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for source in (
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{"class_type": "PromptSearchList", "inputs": {"search_text": "cat"}},
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{
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"class_type": "SomeTextReplace",
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"inputs": {"text": "a cat", "find": "cat", "replace": "dog"},
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},
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):
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self.assertIsNone(
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resolve_text(self._linked(source), "1"), source["class_type"]
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)
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def test_cycles_and_missing_links(self):
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graph = {
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"1": pm(["2", 0]),
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"2": {
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"class_type": "StringConcatenate",
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"inputs": {"string_a": ["2", 0], "string_b": "x", "delimiter": ""},
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},
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}
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self.assertIsNone(resolve_text(graph, "1"))
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self.assertIsNone(resolve_text({"1": pm(["9", 0])}, "1"))
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if __name__ == "__main__":
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unittest.main()
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