update anthropic

Author: better629

metagpt/provider/anthropic_api.py

@@ -33,14 +33,21 @@ def _const_kwargs(self, messages: list[dict], stream: bool = False) -> dict:
             if messages[0]["role"] == "system":
                 kwargs["messages"] = messages[1:]
                 kwargs["system"] = messages[0]["content"]  # set system prompt here
+        if self.config.reasoning:
+            kwargs["thinking"] = {"type": "enabled", "budget_tokens": self.config.reasoning_tokens}
         return kwargs
 
     def _update_costs(self, usage: Usage, model: str = None, local_calc_usage: bool = True):
         usage = {"prompt_tokens": usage.input_tokens, "completion_tokens": usage.output_tokens}
         super()._update_costs(usage, model)
 
     def get_choice_text(self, resp: Message) -> str:
-        return resp.content[0].text
+        if len(resp.content) > 0:
+            self.reasoning_content = resp.content[0].thinking
+            text = resp.content[1].text
+        else:
+            text = resp.content[0].text
+        return text
 
     async def _achat_completion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> Message:
         resp: Message = await self.aclient.messages.create(**self._const_kwargs(messages))
@@ -53,20 +60,27 @@ async def acompletion(self, messages: list[dict], timeout: int = USE_CONFIG_TIME
     async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         stream = await self.aclient.messages.create(**self._const_kwargs(messages, stream=True))
         collected_content = []
+        collected_reasoning_content = []
         usage = Usage(input_tokens=0, output_tokens=0)
         async for event in stream:
             event_type = event.type
             if event_type == "message_start":
                 usage.input_tokens = event.message.usage.input_tokens
                 usage.output_tokens = event.message.usage.output_tokens
             elif event_type == "content_block_delta":
-                content = event.delta.text
-                log_llm_stream(content)
-                collected_content.append(content)
+                delta_type = event.delta.type
+                if delta_type == "thinking_delta":
+                    collected_reasoning_content.append(event.delta.thinking)
+                elif delta_type == "text_delta":
+                    content = event.delta.text
+                    log_llm_stream(content)
+                    collected_content.append(content)
             elif event_type == "message_delta":
                 usage.output_tokens = event.usage.output_tokens  # update final output_tokens
 
         log_llm_stream("\n")
         self._update_costs(usage)
         full_content = "".join(collected_content)
+        if collected_reasoning_content:
+            self.reasoning_content = "".join(collected_reasoning_content)
         return full_content

metagpt/provider/bedrock/bedrock_provider.py

@@ -57,12 +57,13 @@ def get_choice_text_from_stream(self, event) -> Union[bool, str]:
         rsp_dict = json.loads(event["chunk"]["bytes"])
         if rsp_dict["type"] == "content_block_delta":
             reasoning = False
-            if rsp_dict["delta"]["type"] == "text_delta":
+            delta_type = rsp_dict["delta"]["type"]
+            if delta_type == "text_delta":
                 completions = rsp_dict["delta"]["text"]
-            elif rsp_dict["delta"]["type"] == "thinking_delta":
+            elif delta_type == "thinking_delta":
                 completions = rsp_dict["delta"]["thinking"]
                 reasoning = True
-            elif rsp_dict["delta"]["type"] == "signature_delta":
+            elif delta_type == "signature_delta":
                 completions = ""
             return reasoning, completions
         else:

metagpt/provider/bedrock_api.py

@@ -146,7 +146,7 @@ def collect_content() -> str:
                     collected_reasoning_content.append(chunk_text)
                 else:
                     collected_content.append(chunk_text)
-                log_llm_stream(chunk_text)
+                    log_llm_stream(chunk_text)
             if collected_reasoning_content:
                 self.reasoning_content = "".join(collected_reasoning_content)
             return collected_content

requirements.txt

@@ -31,7 +31,7 @@ tqdm==4.66.2
 #unstructured[local-inference]
 # selenium>4
 # webdriver_manager<3.9
-anthropic==0.18.1
+anthropic==0.47.2
 typing-inspect==0.8.0
 libcst==1.0.1
 qdrant-client==1.7.0
@@ -84,4 +84,4 @@ spark_ai_python~=0.3.30
 agentops
 tree_sitter~=0.23.2
 tree_sitter_python~=0.23.2
-httpx==0.27.2
+httpx==0.28.1