fix(cache): normalize stop param in cache key to prevent fragmentation

app/prompt_cache.py

@@ -69,7 +69,11 @@ def cache_key(
         "response_format": response_format or None,
         "seed": seed,
         "max_tokens": max_tokens,
-        "stop": stop,
+        # Normalize stop to a list: "stop": "foo" and "stop": ["foo"]
+        # produce the same upstream behavior, so they must share a cache
+        # entry. Without this, a string-vs-list difference fragments the
+        # cache for semantically identical requests.
+        "stop": [stop] if isinstance(stop, str) else stop,
         "tool_choice": tool_choice,
         "top_p": top_p,
         "n": n,

tests/unit/test_cache_stop_normalization.py

@@ -0,0 +1,40 @@
+"""Regression: prompt cache key must normalize stop to a list.
+
+OpenAI wire format accepts stop as either a string or a list of strings.
+stop="foo" and stop=["foo"] produce identical upstream behavior, so
+they must map to the same cache key. Without normalization, the two forms
+produce different SHA-256 digests and the cache is fragmented."""
+
+from app.prompt_cache import cache_key
+
+
+def _base_kwargs(**overrides):
+    kw = {
+        "model": "gpt-4o",
+        "messages": [{"role": "user", "content": "hello"}],
+        "temperature": 0,
+        "tools": None,
+        "response_format": None,
+        "seed": 42,
+    }
+    kw.update(overrides)
+    return kw
+
+
+def test_stop_string_vs_list_same_key():
+    k1 = cache_key(**_base_kwargs(stop="END"))
+    k2 = cache_key(**_base_kwargs(stop=["END"]))
+    assert k1 == k2
+
+
+def test_stop_list_order_matters():
+    k1 = cache_key(**_base_kwargs(stop=["a", "b"]))
+    k2 = cache_key(**_base_kwargs(stop=["b", "a"]))
+    assert k1 != k2
+
+
+def test_stop_multi_element_list_stable():
+    kw = _base_kwargs(stop=["a", "b", "c"])
+    k1 = cache_key(**kw)
+    k2 = cache_key(**kw)
+    assert k1 == k2