fix(spend): normalize legacy guardrail shapes and float token stats in compression savings reader

litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py

@@ -11,6 +11,7 @@ from fastapi import HTTPException
 
 import litellm
 from httpx import Response as HttpxResponse
+from litellm.proxy.spend_tracking.compression_savings import HEADROOM_GUARDRAIL_PROVIDER
 from typing_extensions import TypeGuard
 
 from litellm._logging import verbose_proxy_logger
@@ -487,7 +488,7 @@ class HeadroomGuardrail(CustomGuardrail):
             guardrail_json_response=stats,
             request_data=request_data,
             guardrail_status="success",
-            guardrail_provider="headroom",
+            guardrail_provider=HEADROOM_GUARDRAIL_PROVIDER,
             start_time=start_time,
             end_time=end_time,
             duration=end_time - start_time,

litellm/proxy/spend_tracking/compression_savings.py

@@ -10,11 +10,11 @@ HEADROOM_GUARDRAIL_PROVIDER = "headroom"
 
 
 def _saved_tokens_or_zero(value: object) -> int:
-    if isinstance(value, bool) or not isinstance(value, int):
+    if isinstance(value, bool) or not isinstance(value, (int, float)):
         return 0
     if value < 0:
         return 0
-    return value
+    return int(value)
 
 
 def _tokens_saved_from_stats(stats: object) -> int:
@@ -32,9 +32,10 @@ def _headroom_entry_saved_tokens(entry: object) -> int:
 
 
 def _headroom_saved_tokens(guardrail_information: object) -> int:
-    if not isinstance(guardrail_information, list):
+    entries = [guardrail_information] if isinstance(guardrail_information, Mapping) else guardrail_information
+    if not isinstance(entries, list):
         return 0
-    return sum(_headroom_entry_saved_tokens(entry) for entry in guardrail_information)
+    return sum(_headroom_entry_saved_tokens(entry) for entry in entries)
 
 
 def extract_compression_saved_tokens(metadata: Mapping[str, object]) -> int:
@@ -52,6 +53,8 @@ def extract_compression_saved_tokens(metadata: Mapping[str, object]) -> int:
     different stages (guardrail pre-call vs deployment pre-call), so when both
     fire on one request their measured savings are independent and additive;
     summing them never double-counts. Malformed or missing values contribute 0.
+    A bare dict ``guardrail_information`` is treated as a single entry, matching
+    the spend-log redactor's normalization of that legacy shape.
     """
     return _tokens_saved_from_stats(metadata.get("compression_savings")) + _headroom_saved_tokens(
         metadata.get("guardrail_information")

tests/test_litellm/proxy/spend_tracking/test_compression_savings.py

@@ -69,7 +69,6 @@ def test_non_headroom_guardrail_entries_ignored():
         {},
         {"tokens_saved": None},
         {"tokens_saved": "7000"},
-        {"tokens_saved": 12.5},
         {"tokens_saved": True},
         {"tokens_saved": -5},
         {"tokens_before": 100, "tokens_after": 50},
@@ -108,3 +107,25 @@ def test_valid_headroom_entry_survives_alongside_malformed_ones():
         ]
     }
     assert extract_compression_saved_tokens(metadata) == 600
+
+
+def test_float_tokens_saved_counts_as_int():
+    entry = {"guardrail_provider": "headroom", "guardrail_response": {"tokens_saved": 600.0}}
+    assert extract_compression_saved_tokens({"guardrail_information": [entry]}) == 600
+    assert extract_compression_saved_tokens({"compression_savings": {"tokens_saved": 7000.0}}) == 7000
+    assert extract_compression_saved_tokens({"compression_savings": {"tokens_saved": 12.5}}) == 12
+
+
+def test_bare_dict_guardrail_information_counts_as_single_entry():
+    assert extract_compression_saved_tokens({"guardrail_information": HEADROOM_ENTRY}) == 600
+
+
+def test_headroom_writer_and_reader_share_provider_slug():
+    from litellm.proxy.guardrails.guardrail_hooks.headroom.headroom import (
+        HEADROOM_GUARDRAIL_PROVIDER as writer_slug,
+    )
+    from litellm.proxy.spend_tracking.compression_savings import (
+        HEADROOM_GUARDRAIL_PROVIDER as reader_slug,
+    )
+
+    assert writer_slug == reader_slug == "headroom"