Fix Bedrock token count and IDs for Anthropic models

libs/aws/langchain_aws/chat_models/bedrock.py

@@ -1,5 +1,6 @@
 import logging
 import re
+import warnings
 from collections import defaultdict
 from operator import itemgetter
 from typing import (
@@ -51,6 +52,7 @@
     _combine_generation_info_for_llm_result,
 )
 from langchain_aws.utils import (
+    anthropic_tokens_supported,
     get_num_tokens_anthropic,
     get_token_ids_anthropic,
 )
@@ -620,16 +622,24 @@ def _combine_llm_outputs(self, llm_outputs: List[Optional[dict]]) -> dict:
         return final_output
 
     def get_num_tokens(self, text: str) -> int:
-        if self._model_is_anthropic:
-            return get_num_tokens_anthropic(text)
-        else:
-            return super().get_num_tokens(text)
+        if self._model_is_anthropic and not self.custom_get_token_ids:
+            if anthropic_tokens_supported():
+                return get_num_tokens_anthropic(text)
+        return super().get_num_tokens(text)
 
     def get_token_ids(self, text: str) -> List[int]:
-        if self._model_is_anthropic:
-            return get_token_ids_anthropic(text)
-        else:
-            return super().get_token_ids(text)
+        if self._model_is_anthropic and not self.custom_get_token_ids:
+            if anthropic_tokens_supported():
+                return get_token_ids_anthropic(text)
+            else:
+                warnings.warn(
+                    f"Falling back to default token method due to missing or incompatible `anthropic` installation "
+                    f"(needs <=0.38.0).\n\nIf using `anthropic>0.38.0`, it is recommended to provide the model "
+                    f"class with a custom_get_token_ids method implementing a more accurate tokenizer for Anthropic. "
+                    f"For get_num_tokens, as another alternative, you can implement your own token counter method "
+                    f"using the ChatAnthropic or AnthropicLLM classes."
+                )
+        return super().get_token_ids(text)
 
     def set_system_prompt_with_tools(self, xml_tools_system_prompt: str) -> None:
         """Workaround to bind. Sets the system prompt with tools"""

libs/aws/langchain_aws/llms/bedrock.py

@@ -33,6 +33,7 @@
 
 from langchain_aws.function_calling import _tools_in_params
 from langchain_aws.utils import (
+    anthropic_tokens_supported,
     enforce_stop_tokens,
     get_num_tokens_anthropic,
     get_token_ids_anthropic,
@@ -1301,13 +1302,21 @@ async def _acall(
         return "".join([chunk.text for chunk in chunks])
 
     def get_num_tokens(self, text: str) -> int:
-        if self._model_is_anthropic:
-            return get_num_tokens_anthropic(text)
-        else:
-            return super().get_num_tokens(text)
+        if self._model_is_anthropic and not self.custom_get_token_ids:
+            if anthropic_tokens_supported():
+                return get_num_tokens_anthropic(text)
+        return super().get_num_tokens(text)
 
     def get_token_ids(self, text: str) -> List[int]:
-        if self._model_is_anthropic:
-            return get_token_ids_anthropic(text)
-        else:
-            return super().get_token_ids(text)
+        if self._model_is_anthropic and not self.custom_get_token_ids:
+            if anthropic_tokens_supported():
+                return get_token_ids_anthropic(text)
+            else:
+                warnings.warn(
+                    f"Falling back to default token method due to missing or incompatible `anthropic` installation "
+                    f"(needs <=0.38.0).\n\nFor `anthropic>0.38.0`, it is recommended to provide the model "
+                    f"class with a custom_get_token_ids method implementing a more accurate tokenizer for Anthropic. "
+                    f"For get_num_tokens, as another alternative, you can implement your own token counter method "
+                    f"using the ChatAnthropic or AnthropicLLM classes."
+                )
+        return super().get_token_ids(text)

libs/aws/langchain_aws/utils.py

@@ -1,21 +1,39 @@
 import re
 from typing import Any, List
 
+from packaging import version
+
 
 def enforce_stop_tokens(text: str, stop: List[str]) -> str:
     """Cut off the text as soon as any stop words occur."""
     return re.split("|".join(stop), text, maxsplit=1)[0]
 
 
-def _get_anthropic_client() -> Any:
+def anthropic_tokens_supported() -> bool:
+    """Check if we have all requirements for Anthropic count_tokens() and get_tokenizer()."""
     try:
         import anthropic
     except ImportError:
-        raise ImportError(
-            "Could not import anthropic python package. "
-            "This is needed in order to accurately tokenize the text "
-            "for anthropic models. Please install it with `pip install anthropic`."
-        )
+        return False
+
+    anthropic_version = version.parse(anthropic.__version__)
+    if anthropic_version > version.parse("0.38.0"):
+        return False
+    else:
+        httpx_import_msg = "httpx<=0.27.2 is required."
+        try:
+            import httpx
+        except ImportError:
+            raise ImportError(httpx_import_msg)
+        httpx_version = version.parse(httpx.__version__)
+        if httpx_version > version.parse("0.27.2"):
+            raise ImportError(httpx_import_msg)
+        else:
+            return True
+
+
+def _get_anthropic_client() -> Any:
+    import anthropic
     return anthropic.Anthropic()