examples: 5 hand-curated fixtures + parametrized regression suite

tests/fixtures/reddit/example_001.json

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+{
+  "post": {
+    "reddit_id": "fx001",
+    "source_sub": "ExpatFIRE",
+    "url": "https://reddit.com/fx001",
+    "title": "Pulled the trigger — FIRE'd in Manila at 38",
+    "body": "Net worth $1.2M, wife + 1 kid, USD-denominated assets in VTI/BND. Expecting to spend ~$24k/yr. Retired last September.",
+    "created_at": "2026-01-15"
+  },
+  "expected": {
+    "country": "Philippines",
+    "city": "Manila",
+    "portfolio_native": 1200000,
+    "annual_exp_native": 24000,
+    "raw_currency": "USD",
+    "age": 38,
+    "family_size": 3,
+    "fi_status": "FIRE",
+    "is_retired": true
+  }
+}

tests/fixtures/reddit/example_002.json

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+{
+  "post": {
+    "reddit_id": "fx002",
+    "source_sub": "leanfire",
+    "url": "https://reddit.com/fx002",
+    "title": "Pulled the trigger in Manchester — leanFIRE at 44",
+    "body": "Net worth £620k, single, no kids. Spending ~£18k/yr in Manchester (UK). Not strictly retired — doing freelance one day a week. Lean by choice, not by force.",
+    "created_at": "2026-02-12"
+  },
+  "expected": {
+    "country": "United Kingdom",
+    "city": "Manchester",
+    "portfolio_native": 620000,
+    "annual_exp_native": 18000,
+    "raw_currency": "GBP",
+    "age": 44,
+    "family_size": 1,
+    "fi_status": "leanFIRE",
+    "is_retired": false
+  }
+}

tests/fixtures/reddit/example_003.json

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+{
+  "post": {
+    "reddit_id": "fx003",
+    "source_sub": "coastFIRE",
+    "url": "https://reddit.com/fx003",
+    "title": "Coasting in Bali — $850k portfolio, still working remote",
+    "body": "Hit my coast number at 35: $850k invested, expecting to grow to FIRE by 50 without contributing. Living in Ubud, Indonesia with my partner. Spending around $30k/yr between us. Working remote part-time for fun.",
+    "created_at": "2026-03-05"
+  },
+  "expected": {
+    "country": "Indonesia",
+    "city": "Bali",
+    "portfolio_native": 850000,
+    "annual_exp_native": 30000,
+    "raw_currency": "USD",
+    "age": 35,
+    "family_size": 2,
+    "fi_status": "coastFIRE",
+    "is_retired": false
+  }
+}

tests/fixtures/reddit/example_004.json

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+{
+  "post": {
+    "reddit_id": "fx004",
+    "source_sub": "EuropeFIRE",
+    "url": "https://reddit.com/fx004",
+    "title": "FIRE'd at 41 in Lisbon, Portugal",
+    "body": "Portfolio €1.05M, mostly accumulating VWCE. Retired 6 months ago. Wife and two kids — family of 4. Spending €38k/yr in Lisbon (Portugal), including rent. NHR visa locked in.",
+    "created_at": "2026-04-20"
+  },
+  "expected": {
+    "country": "Portugal",
+    "city": "Lisbon",
+    "portfolio_native": 1050000,
+    "annual_exp_native": 38000,
+    "raw_currency": "EUR",
+    "age": 41,
+    "family_size": 4,
+    "fi_status": "FIRE",
+    "is_retired": true
+  }
+}

tests/fixtures/reddit/example_005.json

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+{
+  "post": {
+    "reddit_id": "fx005",
+    "source_sub": "FIRE_Ind",
+    "url": "https://reddit.com/fx005",
+    "title": "Net worth update: ₹2.5 crore at 32",
+    "body": "Saved ₹2,50,00,000 (~$300k) net worth at 32 in Bangalore, India. Single. Still working at a product company. Spending ~₹12,00,000/yr. Target: ₹8 crore by 45 to FIRE.",
+    "created_at": "2026-05-01"
+  },
+  "expected": {
+    "country": "India",
+    "city": "Bangalore",
+    "portfolio_native": 25000000,
+    "annual_exp_native": 1200000,
+    "raw_currency": "INR",
+    "age": 32,
+    "family_size": 1,
+    "fi_status": "accumulating",
+    "is_retired": false
+  }
+}

tests/test_examples_fixtures.py

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+"""Regression suite for LLM extraction — drives the extractor against
+hand-curated fixtures and asserts the parsed JSON matches expectations.
+
+Each fixture is `{post: RawPost, expected: dict}`. The test does NOT
+hit a live LLM — it mocks the response to return the *expected* JSON,
+exercising the parser, validator, and currency-handling paths."""
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import httpx
+import pytest
+import respx
+
+from fire_planner.examples.llm_extract import extract_with_qwen
+from fire_planner.examples.models import RawPost
+
+LLAMA_URL = "http://llama-cpp.llama-cpp.svc.cluster.local:8000/v1/chat/completions"
+
+FIXTURE_DIR = Path(__file__).parent / "fixtures" / "reddit"
+
+
+def _fixtures() -> list[Path]:
+    return sorted(FIXTURE_DIR.glob("example_*.json"))
+
+
+@respx.mock
+@pytest.mark.asyncio
+@pytest.mark.parametrize("fixture_path", _fixtures(), ids=lambda p: p.stem)
+async def test_extractor_matches_fixture(fixture_path: Path) -> None:
+    data = json.loads(fixture_path.read_text())
+    post = RawPost.model_validate(data["post"])
+    expected = data["expected"]
+    expected_with_conf = {**expected, "confidence": 0.9}
+
+    respx.post(LLAMA_URL).respond(
+        200,
+        json={"choices": [{"message": {"content": json.dumps(expected_with_conf)}}]},
+    )
+
+    async with httpx.AsyncClient() as client:
+        out = await extract_with_qwen(post, llama_url=LLAMA_URL, client=client)
+
+    assert out is not None
+    for k, v in expected.items():
+        actual = getattr(out, k)
+        if hasattr(actual, "__float__"):
+            assert float(actual) == float(v), f"{fixture_path.stem}: {k}"
+        else:
+            # Pydantic StrEnum compares equal to its string value
+            assert actual == v or str(actual) == v, f"{fixture_path.stem}: {k}"