mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-07-06 09:21:16 -03:00
51c0135250
- Rename py/agent_cli/ -> py/metadata_ops/ (module was never agent-related) - Rename tests/agent_cli/ -> tests/metadata_ops/ - Remove 9 low-value/debug INFO log points across agent_handlers.py, agent_service.py, llm_service.py, and metadata_ops/__init__.py - Keep LLM raw response at DEBUG level for diagnostics - Consolidate per-model progress + LLM result into single concise log line with basename instead of full path - Update package/class/method docstrings to clarify this is a pipeline infrastructure, not a true agent loop
435 lines
18 KiB
Python
435 lines
18 KiB
Python
"""Tests for the PostProcessor (py/services/agent/post_processor.py).
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PostProcessor delegates all I/O to AgentCLI — these tests mock AgentCLI
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functions and verify the business logic (conditions, merges, dispatch).
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"""
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from __future__ import annotations
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from datetime import datetime, timezone
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from unittest import mock
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import pytest
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from py.services.agent.post_processor import PostProcessor
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@pytest.fixture
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def processor():
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return PostProcessor()
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# ======================================================================
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# process() — routing
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# ======================================================================
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class TestProcessDispatch:
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@pytest.mark.asyncio
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async def test_unknown_skill_returns_error(self, processor):
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result = await processor.process(
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skill_name="nonexistent",
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model_path="/p.safetensors",
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llm_output={},
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metadata={},
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)
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assert result["success"] is False
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assert "nonexistent" in result["errors"][0]
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@pytest.mark.asyncio
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async def test_enrich_hf_metadata_routes_correctly(self, processor):
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview") as mock_dl,
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mock.patch("py.metadata_ops.refresh_cache") as mock_ref,
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):
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mock_apply.return_value = ["metadata_source"]
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mock_dl.return_value = None
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result = await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output={},
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metadata={"from_civitai": True},
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)
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assert result["success"] is True
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# ======================================================================
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# enrich_hf_metadata — field-level logic
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# ======================================================================
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class TestEnrichHfMetadata:
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"""Business logic tests for the enrich_hf_metadata post-processor."""
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MIN_LLM_OUTPUT = {
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"base_model": "",
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"trigger_words": [],
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"short_description": "",
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"tags": [],
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"recommended_width": 0,
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"recommended_height": 0,
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"preview_url": "",
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"confidence": "low",
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}
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# -- base_model ------------------------------------------------------
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@pytest.mark.asyncio
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async def test_base_model_overwrites_empty(self, processor):
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"""Empty current base_model → new value is applied."""
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llm = {**self.MIN_LLM_OUTPUT, "base_model": "Flux.1 D"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"base_model": ""},
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)
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applied = mock_apply.call_args[0][1]
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assert applied["base_model"] == "Flux.1 D"
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@pytest.mark.asyncio
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async def test_base_model_does_not_overwrite_existing_civitai(self, processor):
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"""Existing base_model from CivitAI → not overwritten."""
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llm = {**self.MIN_LLM_OUTPUT, "base_model": "Flux.1 D"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"base_model": "SDXL 1.0", "from_civitai": True},
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)
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# apply IS called (metadata_source, llm_enriched_at) but base_model not in it
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applied = mock_apply.call_args[0][1]
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assert "base_model" not in applied
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@pytest.mark.asyncio
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async def test_base_model_overwrites_existing_hf_model(self, processor):
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"""Existing base_model from HF → overwritten (LLM is more reliable)."""
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llm = {**self.MIN_LLM_OUTPUT, "base_model": "Flux.1 D"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"base_model": "SD 1.5", "from_civitai": False},
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)
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applied = mock_apply.call_args[0][1]
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assert applied["base_model"] == "Flux.1 D"
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@pytest.mark.asyncio
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async def test_base_model_skipped_when_llm_empty(self, processor):
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"""LLM returns empty base_model → nothing written."""
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={"base_model": ""},
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)
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applied = mock_apply.call_args[0][1]
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assert "base_model" not in applied
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# -- trigger_words ---------------------------------------------------
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@pytest.mark.asyncio
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async def test_trigger_words_merged(self, processor):
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"""New trigger words written when current list is empty."""
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llm = {**self.MIN_LLM_OUTPUT, "trigger_words": ["trigger1", "trigger2"]}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"trainedWords": []},
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)
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applied = mock_apply.call_args[0][1]
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assert applied["civitai"]["trainedWords"] == ["trigger1", "trigger2"]
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# -- short_description → civitai.description -------------------------
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@pytest.mark.asyncio
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async def test_short_description_written_to_civitai(self, processor):
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"""short_description written to civitai.description for HF models."""
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llm = {**self.MIN_LLM_OUTPUT, "short_description": "A short summary"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"from_civitai": False},
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)
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applied = mock_apply.call_args[0][1]
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assert applied["civitai"]["description"] == "A short summary"
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@pytest.mark.asyncio
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async def test_short_description_skipped_for_civitai_model(self, processor):
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"""short_description NOT written for CivitAI models (has own description)."""
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llm = {**self.MIN_LLM_OUTPUT, "short_description": "A short summary"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"from_civitai": True},
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)
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applied = mock_apply.call_args[0][1]
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assert "civitai" not in applied or "description" not in applied.get("civitai", {})
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# -- readme_content → modelDescription -------------------------------
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@pytest.mark.asyncio
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async def test_readme_content_converted_to_model_description(self, processor):
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"""Raw README converted to HTML and stored as modelDescription."""
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={"from_civitai": False},
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readme_content="# Hello\n\nThis is **bold**.",
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)
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applied = mock_apply.call_args[0][1]
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assert "<h1>Hello</h1>" in applied.get("modelDescription", "")
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assert "<strong>bold</strong>" in applied.get("modelDescription", "")
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@pytest.mark.asyncio
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async def test_readme_content_skipped_for_civitai_model(self, processor):
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"""README content NOT converted for CivitAI models."""
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={"from_civitai": True},
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readme_content="# Hello",
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)
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applied = mock_apply.call_args[0][1]
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assert "modelDescription" not in applied
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# -- gallery images → civitai.images ---------------------------------
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@pytest.mark.asyncio
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async def test_gallery_images_extracted_from_readme(self, processor):
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"""Widget entries in README → civitai.images."""
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readme = """---
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widget:
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- text: "a cat"
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output:
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url: images/cat.png
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---
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Content
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"""
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={
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"from_civitai": False,
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"hf_url": "https://huggingface.co/user/repo",
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},
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readme_content=readme,
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)
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applied = mock_apply.call_args[0][1]
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images = applied.get("civitai", {}).get("images", [])
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assert len(images) == 1
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assert images[0]["url"] == (
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"https://huggingface.co/user/repo/resolve/main/images/cat.png"
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)
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assert images[0]["meta"]["prompt"] == "a cat"
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@pytest.mark.asyncio
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async def test_gallery_images_skipped_for_civitai_model(self, processor):
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"""Gallery images NOT extracted for CivitAI models."""
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=None),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={
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"from_civitai": True,
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"hf_url": "https://huggingface.co/user/repo",
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},
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readme_content="---\nwidget:\n- text: a\n output:\n url: x.png\n---\n",
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)
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applied = mock_apply.call_args[0][1]
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civitai = applied.get("civitai", {})
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assert "images" not in civitai
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# -- tags ------------------------------------------------------------
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@pytest.mark.asyncio
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async def test_tags_merged_and_deduplicated(self, processor):
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llm = {**self.MIN_LLM_OUTPUT, "tags": ["flux", "lora", "STYLE"]}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"tags": ["anime"], "from_civitai": False},
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)
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merged = mock_apply.call_args[0][1]["tags"]
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assert "anime" in merged
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assert "flux" in merged
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assert "style" in merged # lowercased
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# "lora" and "STYLE" → "lora" and "style"
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assert len(merged) == 4 # anime, flux, lora, style
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# -- metadata_source & llm_enriched_at --------------------------------
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@pytest.mark.asyncio
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async def test_audit_fields_always_set(self, processor):
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={},
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)
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applied = mock_apply.call_args[0][1]
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assert applied["metadata_source"] == "agent:enrich_hf_metadata"
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assert "llm_enriched_at" in applied
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# -- preview download ------------------------------------------------
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@pytest.mark.asyncio
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async def test_preview_downloaded_when_url_provided(self, processor):
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llm = {**self.MIN_LLM_OUTPUT, "preview_url": "https://ex.com/img.png"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates") as mock_apply,
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mock.patch("py.metadata_ops.download_preview") as mock_dl,
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mock.patch("py.metadata_ops.refresh_cache"),
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):
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mock_dl.return_value = "/p.webp"
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result = await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={},
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)
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assert result["preview_downloaded"] is True
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mock_dl.assert_awaited_once_with("/p.safetensors", "https://ex.com/img.png")
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applied = mock_apply.call_args[0][1]
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assert applied["preview_url"] == "/p.webp"
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@pytest.mark.asyncio
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async def test_preview_skipped_when_exists(self, processor):
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"""If current_preview file exists on disk, skip download."""
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llm = {**self.MIN_LLM_OUTPUT, "preview_url": "https://ex.com/img.png"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates"),
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mock.patch("py.metadata_ops.download_preview") as mock_dl,
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mock.patch("py.metadata_ops.refresh_cache"),
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mock.patch("os.path.exists", return_value=True),
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"preview_url": "/existing/preview.webp"},
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)
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mock_dl.assert_not_called()
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# -- cache refresh ---------------------------------------------------
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@pytest.mark.asyncio
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async def test_cache_refreshed_when_updates_applied(self, processor):
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llm = {**self.MIN_LLM_OUTPUT, "base_model": "Flux.1 D"}
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates", return_value=["base_model"]),
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache") as mock_ref,
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=llm,
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metadata={"base_model": ""},
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)
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mock_ref.assert_awaited_once_with("/p.safetensors")
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@pytest.mark.asyncio
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async def test_cache_not_refreshed_when_nothing_changed(self, processor):
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with (
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mock.patch("py.metadata_ops.apply_metadata_updates", return_value=[]),
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mock.patch("py.metadata_ops.download_preview", return_value=False),
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mock.patch("py.metadata_ops.refresh_cache") as mock_ref,
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):
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await processor.process(
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skill_name="enrich_hf_metadata",
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model_path="/p.safetensors",
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llm_output=self.MIN_LLM_OUTPUT,
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metadata={"base_model": ""},
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)
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mock_ref.assert_not_called()
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# ======================================================================
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# Unit: _merge_tags
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# ======================================================================
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class TestMergeTags:
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def test_deduplicates_case_insensitive(self):
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existing = ["anime", "Flux"]
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new = ["flux", "LORA", "anime"]
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result = PostProcessor._merge_tags(existing, new)
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# All tags are lowercased (matching TagUpdateService behaviour)
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assert result == ["anime", "flux", "lora"]
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