4e91f4e754
* feat(resolve): category-peer subreddit map for Step 0.55 Introduces scripts/lib/categories.py with a curated category->peer-subs map and wires scripts/lib/resolve.py auto_resolve() to merge peers into the WebSearch-extracted subreddit list. Named 2026-04-22 failure mode: a "Prompting GPT Image 2" run resolved only r/OpenAI + r/ChatGPT and missed r/StableDiffusion, r/midjourney, r/dalle2, r/aiArt where prompting techniques actually live. Map is static, curated, ~11 categories (ai_image_generation, ai_video_generation, ai_music_generation, ai_coding_agent, ai_agent_framework, ai_chat_model, saas_screen_recording, saas_productivity, prediction_markets, crypto_defi, dev_tool_cli). First-match-wins ordering from most-specific to least-specific. Compound-term patterns only (no bare common nouns like "image", "ai"). auto_resolve now: - calls detect_category(topic) after _extract_subreddits - merges peer_subs case-insensitively, caps at MAX_SUBS (10) - preserves every WebSearch-returned sub (freshest signal) - emits [Resolve] Matched category=<id>, adding peers: <list> on stderr only when peers were actually added - returns new "category" key in the result dict for observability - wraps classifier in try/except so failures degrade to unwidened list Includes drive-by: test_full_resolve / test_partial_failure searches_run expectations bumped from 3->4 / 2->3 to match the current queries dict (subreddit + news + x_handle + github). * feat(skill): Step 0.55 category-peer expansion and self-check Adds Section 2a (category-peer expansion, MANDATORY for product topics) and the Step 0.55 self-check checkpoint that fires immediately before the Resolved block displays. Structural mirror of the engine-side categories.py map: same categories, same peer subs, same priority order. The model-side path now: - Applies category-peer expansion to the WebSearch-resolved subs on every product-in-a-known-category run. - Emits the (+ <category_id> peers) annotation on the Reddit line of the Resolved block as the observable contract. Absence on a product-in-a-known-category topic is a Step 0.55 regression. - Runs a self-check before emitting Resolved: "does the resolved list include at least 2 peer subs for the matched category? if not, widen NOW and do not run the engine yet." Mirror of the Python map lives inside Step 0.55 as a table for the model to pattern-match against; extrapolation to unlisted categories is explicitly allowed. Worked example (the exact failing query) appears below the table so reviewers can see before/after at a glance. Both changes land inside the existing Step 0.55 block. No new top-level section, no new LAW. LAWs 1-6 wording unchanged. * test: end-to-end regression for GPT Image 2 failure mode Stubs grounding.web_search to return the OpenAI-only subs that caused the 2026-04-22 failure, then asserts that auto_resolve widens to include the image-gen peers and emits the [Resolve] Matched category=ai_image_generation stderr line. Covers the cap boundary and the uncategorized-topic no-op path. Fixture tests/fixtures/prompting-gpt-image-2-resolved-block.md is documentation-grade (not parsed by tests) and shows the pre-fix vs post-fix Resolved block shape so reviewers can evaluate future categories.py edits against the original bug. --------- Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
351 lines
13 KiB
Python
351 lines
13 KiB
Python
import io
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import sys
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import unittest
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from contextlib import redirect_stderr
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from pathlib import Path
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from unittest.mock import patch
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "scripts"))
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from lib import resolve
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from lib.resolve import MAX_SUBS, _merge_category_peers
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class TestHasBackend(unittest.TestCase):
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def test_no_keys_returns_false(self):
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self.assertFalse(resolve._has_backend({}))
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def test_brave_key_returns_true(self):
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self.assertTrue(resolve._has_backend({"BRAVE_API_KEY": "key"}))
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def test_exa_key_returns_true(self):
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self.assertTrue(resolve._has_backend({"EXA_API_KEY": "key"}))
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def test_serper_key_returns_true(self):
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self.assertTrue(resolve._has_backend({"SERPER_API_KEY": "key"}))
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class TestExtractSubreddits(unittest.TestCase):
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def test_extracts_from_title_and_snippet(self):
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items = [
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{"title": "Check out r/MachineLearning", "snippet": "Also r/artificial", "url": ""},
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{"title": "More at r/datascience", "snippet": "", "url": ""},
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]
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result = resolve._extract_subreddits(items)
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self.assertEqual(result, ["MachineLearning", "artificial", "datascience"])
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def test_extracts_from_url(self):
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items = [
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{"title": "Discussion", "snippet": "", "url": "https://reddit.com/r/python/comments/123"},
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]
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result = resolve._extract_subreddits(items)
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self.assertEqual(result, ["python"])
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def test_deduplicates_case_insensitive(self):
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items = [
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{"title": "r/Python", "snippet": "r/python is great", "url": ""},
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]
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result = resolve._extract_subreddits(items)
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self.assertEqual(len(result), 1)
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def test_empty_items_returns_empty(self):
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self.assertEqual(resolve._extract_subreddits([]), [])
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def test_no_subreddits_in_text(self):
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items = [{"title": "No subreddits here", "snippet": "Just text", "url": ""}]
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self.assertEqual(resolve._extract_subreddits(items), [])
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class TestExtractXHandle(unittest.TestCase):
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def test_extracts_from_url(self):
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items = [
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{"title": "OpenAI on X", "snippet": "Updates from @OpenAI", "url": "https://x.com/OpenAI"},
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]
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result = resolve._extract_x_handle(items)
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self.assertEqual(result, "openai")
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def test_extracts_from_text(self):
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items = [
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{"title": "Follow @elonmusk", "snippet": "Also @elonmusk tweeted", "url": ""},
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]
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result = resolve._extract_x_handle(items)
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self.assertEqual(result, "elonmusk")
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def test_filters_generic_handles(self):
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items = [
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{"title": "Go to @twitter", "snippet": "Visit @x", "url": ""},
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]
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result = resolve._extract_x_handle(items)
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self.assertEqual(result, "")
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def test_empty_items_returns_empty(self):
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self.assertEqual(resolve._extract_x_handle([]), "")
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class TestBuildContextSummary(unittest.TestCase):
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def test_builds_from_snippets(self):
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items = [
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{"snippet": "First news item about topic."},
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{"snippet": "Second news item with details."},
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{"snippet": "Third item ignored."},
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]
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result = resolve._build_context_summary(items)
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self.assertIn("First news item", result)
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self.assertIn("Second news item", result)
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# Only first 2 snippets used
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self.assertNotIn("Third item", result)
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def test_truncates_long_text(self):
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items = [{"snippet": "A" * 200}, {"snippet": "B" * 200}]
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result = resolve._build_context_summary(items)
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self.assertLessEqual(len(result), 300)
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self.assertTrue(result.endswith("..."))
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def test_empty_items_returns_empty(self):
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self.assertEqual(resolve._build_context_summary([]), "")
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def test_items_with_empty_snippets(self):
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items = [{"snippet": ""}, {"snippet": ""}]
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self.assertEqual(resolve._build_context_summary(items), "")
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class TestAutoResolve(unittest.TestCase):
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def test_no_backend_returns_empty(self):
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result = resolve.auto_resolve("test topic", {})
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self.assertEqual(result["subreddits"], [])
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self.assertEqual(result["x_handle"], "")
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self.assertEqual(result["context"], "")
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self.assertEqual(result["searches_run"], 0)
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@patch("lib.resolve.grounding.web_search")
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def test_full_resolve(self, mock_search):
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def side_effect(query, date_range, config):
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if "subreddit" in query:
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return [
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{"title": "r/technology discussion", "snippet": "Also r/gadgets", "url": ""},
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], {"label": "brave"}
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if "news" in query:
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return [
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{"snippet": "Major tech breakthrough announced this week."},
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], {"label": "brave"}
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if "handle" in query:
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return [
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{"title": "TechCo on X", "snippet": "@TechCo", "url": "https://x.com/TechCo"},
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], {"label": "brave"}
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return [], {}
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mock_search.side_effect = side_effect
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result = resolve.auto_resolve("tech", {"BRAVE_API_KEY": "fake"})
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self.assertEqual(result["subreddits"], ["technology", "gadgets"])
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self.assertEqual(result["x_handle"], "techco")
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self.assertIn("breakthrough", result["context"])
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self.assertEqual(result["searches_run"], 4)
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self.assertEqual(mock_search.call_count, 4)
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@patch("lib.resolve.grounding.web_search")
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def test_search_failure_graceful(self, mock_search):
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mock_search.side_effect = RuntimeError("API error")
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result = resolve.auto_resolve("test", {"BRAVE_API_KEY": "fake"})
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self.assertEqual(result["subreddits"], [])
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self.assertEqual(result["x_handle"], "")
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self.assertEqual(result["context"], "")
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self.assertEqual(result["searches_run"], 0)
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@patch("lib.resolve.grounding.web_search")
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def test_partial_failure(self, mock_search):
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call_count = 0
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def side_effect(query, date_range, config):
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nonlocal call_count
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call_count += 1
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if "subreddit" in query:
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return [{"title": "r/cooking tips", "snippet": "", "url": ""}], {}
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if "news" in query:
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raise RuntimeError("Timeout")
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return [], {}
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mock_search.side_effect = side_effect
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result = resolve.auto_resolve("cooking", {"EXA_API_KEY": "fake"})
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self.assertEqual(result["subreddits"], ["cooking"])
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# News search failed, so context is empty
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self.assertEqual(result["context"], "")
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# 3 out of 4 succeeded (subreddit, x_handle, github; news failed)
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self.assertEqual(result["searches_run"], 3)
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class MergeCategoryPeersHappyPath(unittest.TestCase):
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def test_image_gen_topic_appends_peers(self):
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merged, category = _merge_category_peers(
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"Prompting GPT Image 2",
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["OpenAI", "ChatGPT", "singularity"],
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)
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self.assertEqual(category, "ai_image_generation")
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self.assertIn("OpenAI", merged)
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self.assertIn("ChatGPT", merged)
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self.assertIn("singularity", merged)
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self.assertIn("StableDiffusion", merged)
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self.assertIn("midjourney", merged)
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self.assertIn("dalle2", merged)
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def test_preserves_websearch_order_then_appends_peers(self):
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merged, _ = _merge_category_peers(
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"Prompting GPT Image 2",
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["OpenAI", "ChatGPT"],
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)
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self.assertEqual(merged[0], "OpenAI")
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self.assertEqual(merged[1], "ChatGPT")
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self.assertEqual(merged[2], "StableDiffusion")
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def test_emits_stderr_log_when_peers_added(self):
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buf = io.StringIO()
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with redirect_stderr(buf):
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_merge_category_peers(
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"Prompting GPT Image 2",
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["OpenAI", "ChatGPT"],
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)
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output = buf.getvalue()
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self.assertIn("Matched category=ai_image_generation", output)
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self.assertIn("StableDiffusion", output)
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class MergeCategoryPeersDedupe(unittest.TestCase):
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def test_peer_already_in_websearch_not_duplicated(self):
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merged, _ = _merge_category_peers(
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"midjourney v7 prompts",
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["midjourney", "aiArt"],
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)
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self.assertEqual(
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sum(1 for s in merged if s.lower() == "midjourney"),
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1,
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)
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def test_dedupe_is_case_insensitive(self):
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merged, _ = _merge_category_peers(
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"Prompting GPT Image 2",
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["STABLEDIFFUSION"],
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)
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lower = [s.lower() for s in merged]
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self.assertEqual(lower.count("stablediffusion"), 1)
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def test_no_log_when_all_peers_already_present(self):
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buf = io.StringIO()
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with redirect_stderr(buf):
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_merge_category_peers(
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"Prompting GPT Image 2",
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[
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"StableDiffusion",
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"midjourney",
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"dalle2",
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"aiArt",
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"PromptEngineering",
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"MediaSynthesis",
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],
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)
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self.assertNotIn("Matched category=", buf.getvalue())
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class MergeCategoryPeersEdgeCases(unittest.TestCase):
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def test_topic_with_no_category_returns_unchanged(self):
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merged, category = _merge_category_peers(
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"Kanye West",
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["Kanye", "hiphopheads"],
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)
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self.assertIsNone(category)
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self.assertEqual(merged, ["Kanye", "hiphopheads"])
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def test_empty_subreddit_list_with_category_still_adds_peers(self):
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merged, category = _merge_category_peers("Prompting GPT Image 2", [])
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self.assertEqual(category, "ai_image_generation")
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self.assertIn("StableDiffusion", merged)
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def test_empty_topic_returns_unchanged(self):
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merged, category = _merge_category_peers("", ["foo", "bar"])
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self.assertIsNone(category)
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self.assertEqual(merged, ["foo", "bar"])
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def test_none_topic_returns_unchanged(self):
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merged, category = _merge_category_peers(None, ["foo", "bar"])
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self.assertIsNone(category)
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self.assertEqual(merged, ["foo", "bar"])
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def test_no_log_when_topic_has_no_category(self):
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buf = io.StringIO()
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with redirect_stderr(buf):
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_merge_category_peers("Kanye West", ["Kanye"])
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self.assertNotIn("Matched category=", buf.getvalue())
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class MergeCategoryPeersCap(unittest.TestCase):
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def test_cap_is_enforced_at_max_subs(self):
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websearch_subs = [f"Sub{i}" for i in range(9)]
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merged, _ = _merge_category_peers(
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"Prompting GPT Image 2",
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websearch_subs,
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)
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self.assertEqual(len(merged), MAX_SUBS)
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for s in websearch_subs:
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self.assertIn(s, merged)
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self.assertEqual(len(merged) - len(websearch_subs), 1)
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self.assertEqual(merged[9], "StableDiffusion")
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def test_cap_preserves_highest_priority_peer_when_trimming(self):
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websearch_subs = [f"Sub{i}" for i in range(8)]
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merged, _ = _merge_category_peers(
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"Prompting GPT Image 2",
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websearch_subs,
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)
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self.assertEqual(len(merged), MAX_SUBS)
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self.assertEqual(merged[8], "StableDiffusion")
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self.assertEqual(merged[9], "midjourney")
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class MergeCategoryPeersClassificationFailure(unittest.TestCase):
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def test_classification_error_returns_unwidened_list_and_logs(self):
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original = resolve.categories.detect_category
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def boom(_topic):
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raise RuntimeError("synthetic classifier failure")
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resolve.categories.detect_category = boom
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try:
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buf = io.StringIO()
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with redirect_stderr(buf):
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merged, category = _merge_category_peers(
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"Prompting GPT Image 2",
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["OpenAI"],
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)
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self.assertEqual(merged, ["OpenAI"])
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self.assertIsNone(category)
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self.assertIn("Category classification failed", buf.getvalue())
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finally:
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resolve.categories.detect_category = original
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class AutoResolveCategoryIntegration(unittest.TestCase):
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@patch("lib.resolve.grounding.web_search")
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def test_auto_resolve_returns_category_key(self, mock_search):
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def side_effect(query, date_range, config):
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if "subreddit" in query:
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return [
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{"title": "r/OpenAI", "snippet": "r/ChatGPT r/singularity", "url": ""},
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], {}
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return [], {}
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mock_search.side_effect = side_effect
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result = resolve.auto_resolve(
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"Prompting GPT Image 2",
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{"BRAVE_API_KEY": "fake"},
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)
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self.assertEqual(result["category"], "ai_image_generation")
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self.assertIn("StableDiffusion", result["subreddits"])
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self.assertIn("OpenAI", result["subreddits"])
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def test_no_backend_returns_category_none(self):
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result = resolve.auto_resolve("test topic", {})
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self.assertIsNone(result["category"])
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if __name__ == "__main__":
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unittest.main()
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