planoai obs: live LLM observability TUI (#891)

cli/test/test_obs_collector.py

@@ -0,0 +1,145 @@
+import time
+from datetime import datetime, timezone
+from types import SimpleNamespace
+from unittest.mock import MagicMock
+
+import pytest
+
+from planoai.obs.collector import LLMCall, LLMCallStore, span_to_llm_call
+
+
+def _mk_attr(key: str, value):
+    v = MagicMock()
+    if isinstance(value, bool):
+        v.WhichOneof.return_value = "bool_value"
+        v.bool_value = value
+    elif isinstance(value, int):
+        v.WhichOneof.return_value = "int_value"
+        v.int_value = value
+    elif isinstance(value, float):
+        v.WhichOneof.return_value = "double_value"
+        v.double_value = value
+    else:
+        v.WhichOneof.return_value = "string_value"
+        v.string_value = str(value)
+    kv = MagicMock()
+    kv.key = key
+    kv.value = v
+    return kv
+
+
+def _mk_span(
+    attrs: dict, start_ns: int | None = None, span_id_hex: str = "ab"
+) -> MagicMock:
+    span = MagicMock()
+    span.attributes = [_mk_attr(k, v) for k, v in attrs.items()]
+    span.start_time_unix_nano = start_ns or int(time.time() * 1_000_000_000)
+    span.span_id.hex.return_value = span_id_hex
+    return span
+
+
+def test_span_without_llm_model_is_ignored():
+    span = _mk_span({"http.method": "POST"})
+    assert span_to_llm_call(span, "plano(llm)") is None
+
+
+def test_span_with_full_llm_attrs_produces_call():
+    span = _mk_span(
+        {
+            "llm.model": "openai-gpt-5.4",
+            "model.requested": "router:software-engineering",
+            "plano.session_id": "sess-abc",
+            "plano.route.name": "software-engineering",
+            "llm.is_streaming": False,
+            "llm.duration_ms": 1234,
+            "llm.time_to_first_token": 210,
+            "llm.usage.prompt_tokens": 100,
+            "llm.usage.completion_tokens": 50,
+            "llm.usage.total_tokens": 150,
+            "llm.usage.cached_input_tokens": 30,
+            "llm.usage.cache_creation_tokens": 5,
+            "llm.usage.reasoning_tokens": 200,
+            "http.status_code": 200,
+            "request_id": "req-42",
+        }
+    )
+    call = span_to_llm_call(span, "plano(llm)")
+    assert call is not None
+    assert call.request_id == "req-42"
+    assert call.model == "openai-gpt-5.4"
+    assert call.request_model == "router:software-engineering"
+    assert call.session_id == "sess-abc"
+    assert call.route_name == "software-engineering"
+    assert call.is_streaming is False
+    assert call.duration_ms == 1234.0
+    assert call.ttft_ms == 210.0
+    assert call.prompt_tokens == 100
+    assert call.completion_tokens == 50
+    assert call.total_tokens == 150
+    assert call.cached_input_tokens == 30
+    assert call.cache_creation_tokens == 5
+    assert call.reasoning_tokens == 200
+    assert call.status_code == 200
+
+
+def test_pricing_lookup_attaches_cost():
+    class StubPricing:
+        def cost_for_call(self, call):
+            # Simple: 2 * prompt + 3 * completion, in cents
+            return 0.02 * (call.prompt_tokens or 0) + 0.03 * (
+                call.completion_tokens or 0
+            )
+
+    span = _mk_span(
+        {
+            "llm.model": "do/openai-gpt-5.4",
+            "llm.usage.prompt_tokens": 10,
+            "llm.usage.completion_tokens": 2,
+        }
+    )
+    call = span_to_llm_call(span, "plano(llm)", pricing=StubPricing())
+    assert call is not None
+    assert call.cost_usd == pytest.approx(0.26)
+
+
+def test_tpt_and_tokens_per_sec_derived():
+    call = LLMCall(
+        request_id="x",
+        timestamp=datetime.now(tz=timezone.utc),
+        model="m",
+        duration_ms=1000,
+        ttft_ms=200,
+        completion_tokens=80,
+    )
+    # (1000 - 200) / 80 = 10ms per token => 100 tokens/sec
+    assert call.tpt_ms == 10.0
+    assert call.tokens_per_sec == 100.0
+
+
+def test_tpt_returns_none_when_no_completion_tokens():
+    call = LLMCall(
+        request_id="x",
+        timestamp=datetime.now(tz=timezone.utc),
+        model="m",
+        duration_ms=1000,
+        ttft_ms=200,
+        completion_tokens=0,
+    )
+    assert call.tpt_ms is None
+    assert call.tokens_per_sec is None
+
+
+def test_store_evicts_fifo_at_capacity():
+    store = LLMCallStore(capacity=3)
+    now = datetime.now(tz=timezone.utc)
+    for i in range(5):
+        store.add(
+            LLMCall(
+                request_id=f"r{i}",
+                timestamp=now,
+                model="m",
+            )
+        )
+    snap = store.snapshot()
+    assert len(snap) == 3
+    assert [c.request_id for c in snap] == ["r2", "r3", "r4"]