rename safe_messages to trim_messages

docs/my-website/docs/completion/message_trimming.md

@@ -1,25 +1,25 @@
 # Trimming Input Messages
-**Use litellm.safe_messages() to ensure messages does not exceed a model's token limit or specified `max_tokens`**
+**Use litellm.trim_messages() to ensure messages does not exceed a model's token limit or specified `max_tokens`**
 
 ## Usage 
 ```python
 from litellm import completion
-from litellm.utils import safe_messages
+from litellm.utils import trim_messages
 
 response = completion(
     model=model, 
-    messages=safe_messages(messages, model) # safe_messages ensures tokens(messages) < max_tokens(model)
+    messages=trim_messages(messages, model) # trim_messages ensures tokens(messages) < max_tokens(model)
 ) 
 ```
 
 ## Usage - set max_tokens
 ```python
 from litellm import completion
-from litellm.utils import safe_messages
+from litellm.utils import trim_messages
 
 response = completion(
     model=model, 
-    messages=safe_messages(messages, model, max_tokens=10), # safe_messages ensures tokens(messages) < max_tokens
+    messages=trim_messages(messages, model, max_tokens=10), # trim_messages ensures tokens(messages) < max_tokens
 ) 
 ```
 

litellm/tests/test_utils.py

@@ -10,14 +10,14 @@ sys.path.insert(
 )  # Adds the parent directory to the system path
 import pytest
 import litellm
-from litellm.utils import safe_messages, get_token_count
+from litellm.utils import trim_messages, get_token_count
 
 # Assuming your trim_messages, shorten_message_to_fit_limit, and get_token_count functions are all in a module named 'message_utils'
 
 # Test 1: Check trimming of normal message
 def test_basic_trimming():
     messages = [{"role": "user", "content": "This is a long message that definitely exceeds the token limit."}]
-    trimmed_messages = safe_messages(messages, model="claude-2", max_tokens=8)
+    trimmed_messages = trim_messages(messages, model="claude-2", max_tokens=8)
     print("trimmed messages")
     print(trimmed_messages)
     # print(get_token_count(messages=trimmed_messages, model="claude-2"))
@@ -26,7 +26,7 @@ test_basic_trimming()
 
 def test_basic_trimming_no_max_tokens_specified():
     messages = [{"role": "user", "content": "This is a long message that is definitely under the token limit."}]
-    trimmed_messages = safe_messages(messages, model="gpt-4")
+    trimmed_messages = trim_messages(messages, model="gpt-4")
     print("trimmed messages for gpt-4")
     print(trimmed_messages)
     # print(get_token_count(messages=trimmed_messages, model="claude-2"))
@@ -38,7 +38,7 @@ def test_multiple_messages_trimming():
         {"role": "user", "content": "This is a long message that will exceed the token limit."},
         {"role": "user", "content": "This is another long message that will also exceed the limit."}
     ]
-    trimmed_messages = safe_messages(messages=messages, model="gpt-3.5-turbo", max_tokens=20)
+    trimmed_messages = trim_messages(messages=messages, model="gpt-3.5-turbo", max_tokens=20)
     print("Trimmed messages")
     print(trimmed_messages)
     # print(get_token_count(messages=trimmed_messages, model="gpt-3.5-turbo"))
@@ -50,7 +50,7 @@ def test_multiple_messages_no_trimming():
         {"role": "user", "content": "This is a long message that will exceed the token limit."},
         {"role": "user", "content": "This is another long message that will also exceed the limit."}
     ]
-    trimmed_messages = safe_messages(messages=messages, model="gpt-3.5-turbo", max_tokens=100)
+    trimmed_messages = trim_messages(messages=messages, model="gpt-3.5-turbo", max_tokens=100)
     print("Trimmed messages")
     print(trimmed_messages)
     assert(messages==trimmed_messages)
@@ -60,7 +60,7 @@ test_multiple_messages_no_trimming()
 
 def test_large_trimming():
     messages = [{"role": "user", "content": "This is a singlelongwordthatexceedsthelimit."}, {"role": "user", "content": "This is a singlelongwordthatexceedsthelimit."},{"role": "user", "content": "This is a singlelongwordthatexceedsthelimit."},{"role": "user", "content": "This is a singlelongwordthatexceedsthelimit."},{"role": "user", "content": "This is a singlelongwordthatexceedsthelimit."}]
-    trimmed_messages = safe_messages(messages, max_tokens=20, model="random")
+    trimmed_messages = trim_messages(messages, max_tokens=20, model="random")
     print("trimmed messages")
     print(trimmed_messages)
     assert(get_token_count(messages=trimmed_messages, model="random")) <= 20

litellm/utils.py

@@ -2496,7 +2496,7 @@ def shorten_message_to_fit_limit(
 # LiteLLM token trimmer 
 # this code is borrowed from https://github.com/KillianLucas/tokentrim/blob/main/tokentrim/tokentrim.py
 # Credits for this code go to Killian Lucas
-def safe_messages(
+def trim_messages(
     messages,
     model = None,
     system_message = None, # str of user system message