add docs

metagpt/provider/bedrock/amazon_bedrock_api.py

@@ -11,14 +11,21 @@ import boto3
 
 @register_provider([LLMType.AMAZON_BEDROCK])
 class AmazonBedrockLLM(BaseLLM):
+    """
+    check out:
+    https://docs.aws.amazon.com/code-library/latest/ug/python_3_bedrock-runtime_code_examples.html
+    """
+
     def __init__(self, config: LLMConfig):
         self.config = config
         self.__client = self.__init_client("bedrock-runtime")
         self.__provider = get_provider(self.config.model)
-        logger.warning("Amazon bedrock doesn't support async now")
+        logger.warning(
+            "Amazon bedrock doesn't support asynchronous calls now")
 
     def __init_client(self, service_name: Literal["bedrock-runtime", "bedrock"]):
-        # access key from https://us-east-1.console.aws.amazon.com/iam
+        """initialize boto3 client"""
+        # access key and secret key from https://us-east-1.console.aws.amazon.com/iam
         self.__credentital_kwards = {
             "aws_secret_access_key": self.config.secret_key,
             "aws_access_key_id": self.config.access_key,
@@ -29,6 +36,14 @@ class AmazonBedrockLLM(BaseLLM):
         return client
 
     def list_models(self):
+        """list all available text-generation models
+
+        ```shell
+        ai21.j2-ultra-v1                    Support Streaming:False
+        meta.llama3-70b-instruct-v1:0       Support Streaming:True
+        ……
+        ```
+        """
         client = self.__init_client("bedrock")
         # only output text-generation models
         response = client.list_foundation_models(byOutputModality='TEXT')
@@ -38,12 +53,12 @@ class AmazonBedrockLLM(BaseLLM):
 
     @property
     def _generate_kwargs(self) -> dict:
-        # for now only use temperature due to the difference of request body
         model_max_tokens = get_max_tokens(self.config.model)
         if self.config.max_token > model_max_tokens:
             max_tokens = model_max_tokens
         else:
             max_tokens = self.config.max_token
+
         return {
             self.__provider.max_tokens_field_name: max_tokens,
             "temperature": self.config.temperature
@@ -81,8 +96,12 @@ class AmazonBedrockLLM(BaseLLM):
         full_text = ("".join(collected_content)).lstrip()
         return full_text
 
+    # boto3 don't support support asynchronous calls.
+    # for asynchronous version of boto3,check out:
+    # https://aioboto3.readthedocs.io/en/latest/usage.html
+    # However,aioboto3 doesn't support invoke model
+
     async def acompletion(self, messages: list[dict]):
-        # Amazon bedrock doesn't support async now
         return await self._achat_completion(messages)
 
     async def acompletion_text(self, messages: list[dict], stream: bool = False,

metagpt/provider/bedrock/utils.py

@@ -1,5 +1,6 @@
 from metagpt.logs import logger
 
+# max_tokens for each model
 NOT_SUUPORT_STREAM_MODELS = {
     "ai21.j2-grande-instruct": 8000,
     "ai21.j2-jumbo-instruct": 8000,
@@ -29,7 +30,7 @@ SUPPORT_STREAM_MODELS = {
     "mistral.mistral-large-2402-v1:0": 32000,
 }
 
-# TODO:use a general function for constructing chat templates.
+# TODO:use a more general function for constructing chat templates.
 
 
 def messages_to_prompt_llama2(messages: list[dict]):
@@ -64,6 +65,7 @@ def messages_to_prompt_llama3(messages: list[dict]):
         role = message["role"]
         content = message["content"]
         prompt += GENERAL_TEMPLATE.format(role=role, content=content)
+
     if role != "assistant":
         prompt += f"<|start_header_id|>assistant<|end_header_id|>"
 
@@ -77,11 +79,12 @@ def messages_to_prompt_claude(messages: list[dict]):
         role = message["role"]
         content = message["content"]
         prompt += GENERAL_TEMPLATE.format(role=role, content=content)
+
     if role != "assistant":
         prompt += f"\n\nAssistant:"
+
     return prompt
 
 
 def get_max_tokens(model_id) -> int:
     return (NOT_SUUPORT_STREAM_MODELS | SUPPORT_STREAM_MODELS)[model_id]
-