fix: update anthropic

camel/configs/anthropic_config.py

@@ -13,10 +13,10 @@
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 from __future__ import annotations
 
-from typing import List, Union
+from typing import Any, ClassVar, List, Union
 
 from camel.configs.base_config import BaseConfig
-from camel.types import NOT_GIVEN, NotGiven
+from camel.types import NotGiven
 
 
 class AnthropicConfig(BaseConfig):
@@ -29,41 +29,43 @@ class AnthropicConfig(BaseConfig):
             generate before stopping. Note that Anthropic models may stop
             before reaching this maximum. This parameter only specifies the
             absolute maximum number of tokens to generate.
-            (default: :obj:`256`)
+            (default: :obj:`8192`)
         stop_sequences (List[str], optional): Sequences that will cause the
             model to stop generating completion text. Anthropic models stop
             on "\n\nHuman:", and may include additional built-in stop sequences
             in the future. By providing the stop_sequences parameter, you may
             include additional strings that will cause the model to stop
-            generating.
+            generating. (default: :obj:`[]`)
         temperature (float, optional): Amount of randomness injected into the
             response. Defaults to 1. Ranges from 0 to 1. Use temp closer to 0
             for analytical / multiple choice, and closer to 1 for creative
-            and generative tasks.
-            (default: :obj:`1`)
+            and generative tasks. (default: :obj:`1`)
         top_p (float, optional): Use nucleus sampling. In nucleus sampling, we
             compute the cumulative distribution over all the options for each
             subsequent token in decreasing probability order and cut it off
             once it reaches a particular probability specified by `top_p`.
             You should either alter `temperature` or `top_p`,
-            but not both.
-            (default: :obj:`0.7`)
+            but not both. (default: :obj:`0.7`)
         top_k (int, optional): Only sample from the top K options for each
             subsequent token. Used to remove "long tail" low probability
-            responses.
-            (default: :obj:`5`)
+            responses. (default: :obj:`5`)
         metadata: An object describing metadata about the request.
         stream (bool, optional): Whether to incrementally stream the response
             using server-sent events. (default: :obj:`False`)
     """
 
-    max_tokens: int = 256
-    stop_sequences: Union[List[str], NotGiven] = NOT_GIVEN
+    max_tokens: int = 8192
+    stop_sequences: ClassVar[Union[List[str], NotGiven]] = []
     temperature: float = 1
-    top_p: Union[float, NotGiven] = NOT_GIVEN
-    top_k: Union[int, NotGiven] = NOT_GIVEN
-    metadata: NotGiven = NOT_GIVEN
+    top_p: Union[float, NotGiven] = 0.7
+    top_k: Union[int, NotGiven] = 5
     stream: bool = False
 
+    def as_dict(self) -> dict[str, Any]:
+        config_dict = super().as_dict()
+        if "tools" in config_dict:
+            del config_dict["tools"]  # TODO: Support tool calling.
+        return config_dict
+
 
 ANTHROPIC_API_PARAMS = {param for param in AnthropicConfig.model_fields.keys()}

camel/models/anthropic_model.py

@@ -12,7 +12,7 @@
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
 import os
-from typing import Any, Dict, List, Literal, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
 from camel.configs import ANTHROPIC_API_PARAMS, AnthropicConfig
 from camel.messages import OpenAIMessage
@@ -102,27 +102,6 @@ def token_counter(self) -> BaseTokenCounter:
             self._token_counter = AnthropicTokenCounter(self.model_type)
         return self._token_counter
 
-    @dependencies_required('anthropic')
-    def count_tokens_from_prompt(
-        self, prompt: str, role: Literal["user", "assistant"]
-    ) -> int:
-        r"""Count the number of tokens from a prompt.
-
-        Args:
-            prompt (str): The prompt string.
-            role (Literal["user", "assistant"]): The role of the message
-                sender, either "user" or "assistant".
-
-        Returns:
-            int: The number of tokens in the prompt.
-        """
-        from anthropic.types.beta import BetaMessageParam
-
-        return self.client.beta.messages.count_tokens(
-            messages=[BetaMessageParam(content=prompt, role=role)],
-            model=self.model_type,
-        ).input_tokens
-
     def run(
         self,
         messages: List[OpenAIMessage],

camel/utils/token_counting.py

@@ -253,11 +253,11 @@ def count_tokens_from_messages(self, messages: List[OpenAIMessage]) -> int:
         Returns:
             int: Number of tokens in the messages.
         """
-        from anthropic.types.beta import BetaMessageParam
+        from anthropic.types import MessageParam
 
-        return self.client.beta.messages.count_tokens(
+        return self.client.messages.count_tokens(
             messages=[
-                BetaMessageParam(
+                MessageParam(
                     content=str(msg["content"]),
                     role="user" if msg["role"] == "user" else "assistant",
                 )

examples/models/role_playing_with_claude.py

@@ -100,4 +100,4 @@ def main(model_type=None) -> None:
 
 
 if __name__ == "__main__":
-    main(model_type=ModelType.CLAUDE_2_0)
+    main(model_type=ModelType.CLAUDE_3_5_SONNET)