single cache flag

.github/tests/lm_tests.py

@@ -399,7 +399,7 @@ def test_custom_tokenizer():
 @pytest.mark.parametrize("model", get_enabled("gpt-4o-mini"))
 def test_cache(setup_models, model):
     lm = setup_models[model]
-    lotus.settings.configure(lm=lm, enable_message_cache=True)
+    lotus.settings.configure(lm=lm, enable_cache=True)
 
     # Check that "What is the capital of France?" becomes cached
     first_batch = [
@@ -428,7 +428,7 @@ def test_cache(setup_models, model):
 @pytest.mark.parametrize("model", get_enabled("gpt-4o-mini"))
 def test_disable_cache(setup_models, model):
     lm = setup_models[model]
-    lotus.settings.configure(lm=lm, enable_message_cache=False)
+    lotus.settings.configure(lm=lm, enable_cache=False)
 
     batch = [
         [{"role": "user", "content": "Hello, world!"}],
@@ -452,7 +452,7 @@ def test_disable_cache(setup_models, model):
 @pytest.mark.parametrize("model", get_enabled("gpt-4o-mini"))
 def test_reset_cache(setup_models, model):
     lm = setup_models[model]
-    lotus.settings.configure(lm=lm, enable_message_cache=True)
+    lotus.settings.configure(lm=lm, enable_cache=True)
 
     batch = [
         [{"role": "user", "content": "Hello, world!"}],
@@ -482,7 +482,7 @@ def test_operator_cache(setup_models, model):
     cache = CacheFactory.create_cache(cache_config)
 
     lm = LM(model="gpt-4o-mini", cache=cache)
-    lotus.settings.configure(lm=lm, enable_operator_cache=True)
+    lotus.settings.configure(lm=lm, enable_cache=True)
 
     data = {
         "Course Name": [
@@ -538,7 +538,7 @@ def test_disable_operator_cache(setup_models, model):
     cache = CacheFactory.create_cache(cache_config)
 
     lm = LM(model="gpt-4o-mini", cache=cache)
-    lotus.settings.configure(lm=lm, enable_operator_cache=False)
+    lotus.settings.configure(lm=lm, enable_cache=False)
 
     data = {
         "Course Name": [

lotus/cache.py

@@ -20,7 +20,7 @@ def require_cache_enabled(func: Callable) -> Callable:
 
     @wraps(func)
     def wrapper(self, *args, **kwargs):
-        if not lotus.settings.enable_message_cache:
+        if not lotus.settings.enable_cache:
             return None
         return func(self, *args, **kwargs)
 
@@ -33,7 +33,7 @@ def operator_cache(func: Callable) -> Callable:
     @wraps(func)
     def wrapper(self, *args, **kwargs):
         model = lotus.settings.lm
-        use_operator_cache = lotus.settings.enable_operator_cache
+        use_operator_cache = lotus.settings.enable_cache
 
         if use_operator_cache and model.cache:
 

lotus/models/lm.py

@@ -55,14 +55,14 @@ def __call__(
         if all_kwargs.get("logprobs", False):
             all_kwargs.setdefault("top_logprobs", 10)
 
-        if lotus.settings.enable_message_cache:
+        if lotus.settings.enable_cache:
             # Check cache and separate cached and uncached messages
             hashed_messages = [self._hash_messages(msg, all_kwargs) for msg in messages]
             cached_responses = [self.cache.get(hash) for hash in hashed_messages]
 
         uncached_data = (
             [(msg, hash) for msg, hash, resp in zip(messages, hashed_messages, cached_responses) if resp is None]
-            if lotus.settings.enable_message_cache
+            if lotus.settings.enable_cache
             else [(msg, "no-cache") for msg in messages]
         )
 
@@ -72,7 +72,7 @@ def __call__(
         uncached_responses = self._process_uncached_messages(
             uncached_data, all_kwargs, show_progress_bar, progress_bar_desc
         )
-        if lotus.settings.enable_message_cache:
+        if lotus.settings.enable_cache:
             # Add new responses to cache
             for resp, (_, hash) in zip(uncached_responses, uncached_data):
                 if hash:
@@ -81,7 +81,7 @@ def __call__(
         # Merge all responses in original order and extract outputs
         all_responses = (
             self._merge_responses(cached_responses, uncached_responses)
-            if lotus.settings.enable_message_cache
+            if lotus.settings.enable_cache
             else uncached_responses
         )
         outputs = [self._get_top_choice(resp) for resp in all_responses]

lotus/settings.py

@@ -12,8 +12,7 @@ class Settings:
     reranker: lotus.models.Reranker | None = None
 
     # Cache settings
-    enable_message_cache: bool = False
-    enable_operator_cache: bool = False
+    enable_cache: bool = False
 
     # Serialization setting
     serialization_format: SerializationFormat = SerializationFormat.DEFAULT