test(cost): trim the docstrings on the realtime cost-map regressions

Each of the four tests this PR added carried several lines of rationale for
why the map was wrong. Cut them to one line saying what the test pins, and
keep the two facts that explain a number rather than the change: the cached
tokens dropping out of the bill, and why the 2.5 Flash control has to be
there, both now assertion messages where they fire

tests/test_litellm/test_cost_calculator.py

@@ -299,10 +299,7 @@ GPT_REALTIME_2_FAMILY: Final = (
 
 
 def test_gpt_realtime_2_family_prices_audio_cache_writes_and_reads_alike(_local_model_cost_map: None) -> None:
-    """Azure publishes one cached-audio meter per gpt-realtime-2 deployment, charged at the same rate for
-    the write that populates the cache and the read that hits it. azure/gpt-realtime-2 carried only the
-    read side, so it was the one family member reporting no cache-creation audio price for a deployment
-    whose meter publishes one."""
+    """Azure publishes one cached-audio meter per gpt-realtime-2 deployment, so the write rate equals the read."""
     audio_cache_rates: Final = {
         model: (
             litellm.model_cost[model].get("cache_read_input_audio_token_cost"),
@@ -326,12 +323,7 @@ GEMINI_LIVE_NATIVE_AUDIO_CASES: Final = (
 def test_gemini_live_native_audio_carries_no_cached_input_rate(
     _local_model_cost_map: None, model: str, provider: str
 ) -> None:
-    """Google publishes no cached-input price for the Live API. Its pricing table prints N/A in both
-    cached columns for every Gemini 2.5 Flash Live API row, and no Live or native-audio model appears
-    under either implicit or explicit context caching. Two of these entries priced a cached read at
-    7.5e-08 regardless, which billed 0.008 here. With no invented rate the cached tokens drop out of
-    the bill, which is inert in practice because Vertex reports no cachedContentTokenCount on a Live
-    session."""
+    """Google prints N/A in both cached columns for every Live API row, so no cached-input rate can be charged."""
     assert litellm.get_model_info(model, custom_llm_provider=provider)["cache_read_input_token_cost"] is None
 
     prompt_usd, _ = cost_per_token(
@@ -346,21 +338,19 @@ def test_gemini_live_native_audio_carries_no_cached_input_rate(
         ),
     )
 
-    assert prompt_usd == pytest.approx(1_000 * 5e-07)
+    assert prompt_usd == pytest.approx(1_000 * 5e-07), "the 100k cached tokens drop out with no cached rate to charge"
 
 
 @pytest.mark.parametrize(("model", "provider"), GEMINI_LIVE_NATIVE_AUDIO_CASES)
 def test_gemini_live_native_audio_declares_prompt_caching_unsupported(
     _local_model_cost_map: None, model: str, provider: str
 ) -> None:
-    """The capability claim is what made the absent cached rate read as a pricing gap rather than a
-    vendor limitation. The flag has to say False rather than go missing: get_model_info maps an absent
-    key to None, which is how this map spells "nobody checked", where False records the vendor's
-    documented no. The 2.5 Flash control is load-bearing because supports_prompt_caching turns any
-    lookup error into False, so without it a broken lookup would read as a pass."""
+    """The vendor's documented no has to be recorded as False, since an absent key reads back as None."""
     assert litellm.get_model_info(model, custom_llm_provider=provider)["supports_prompt_caching"] is False
     assert supports_prompt_caching(model=model, custom_llm_provider=provider) is False
-    assert supports_prompt_caching(model="gemini-2.5-flash", custom_llm_provider="vertex_ai") is True
+    assert supports_prompt_caching(model="gemini-2.5-flash", custom_llm_provider="vertex_ai") is True, (
+        "control: the helper swallows a lookup error into False, so without this a broken lookup reads as a pass"
+    )
 
 
 def test_cost_calculator_with_usage(_local_model_cost_map, monkeypatch):
@@ -4460,14 +4450,7 @@ def test_gemini_live_native_audio_ga_realtime_cost(_local_model_cost_map: None)
 def test_gemini_live_native_audio_limits_and_capabilities_match_vendor_model_card(
     _local_model_cost_map: None, model: str
 ) -> None:
-    """Google's card for model ID gemini-live-2.5-flash-native-audio gives a 128K context window and
-    64K maximum output tokens, and marks structured output and URL context as not supported. Its
-    modality list is text, image, audio and video, with no document input, so pdf input cannot be
-    advertised either. The entry claimed a 1M window, an off-by-one 65535 output cap, and all three
-    capabilities.
-
-    Both ids resolve to the one bare entry, which is why no vertex_ai/-prefixed twin is needed.
-    """
+    """Google's card for model ID gemini-live-2.5-flash-native-audio is the source for these limits and flags."""
     info = litellm.get_model_info(model)
 
     assert info["max_input_tokens"] == 131072