TradingAgents/tradingagents/llm_clients/bedrock_client.py

55 lines
1.7 KiB
Python

from typing import Any, Optional
from botocore.config import Config as BotoConfig
from langchain_aws import ChatBedrockConverse
from .base_client import BaseLLMClient, normalize_content
_BEDROCK_MODELS = [
"us.anthropic.claude-sonnet-4-6",
"us.anthropic.claude-haiku-4-5-20251001-v1:0",
"us.anthropic.claude-opus-4-6-v1",
"us.anthropic.claude-sonnet-4-5-20250929-v1:0",
]
_PASSTHROUGH_KWARGS = (
"region_name",
"credentials_profile_name",
"max_tokens",
"temperature",
"callbacks",
)
class NormalizedChatBedrockConverse(ChatBedrockConverse):
def invoke(self, input, config=None, **kwargs):
return normalize_content(super().invoke(input, config, **kwargs))
async def ainvoke(self, input, config=None, **kwargs):
return normalize_content(await super().ainvoke(input, config, **kwargs))
class BedrockClient(BaseLLMClient):
"""Client for Amazon Bedrock models via ChatBedrockConverse."""
def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
super().__init__(model, base_url, **kwargs)
def get_llm(self) -> Any:
self.warn_if_unknown_model()
llm_kwargs = {
"model_id": self.model,
"config": BotoConfig(read_timeout=300, retries={"max_attempts": 3}),
}
if self.base_url and "openai.com" not in self.base_url:
llm_kwargs["endpoint_url"] = self.base_url
for key in _PASSTHROUGH_KWARGS:
if key in self.kwargs:
llm_kwargs[key] = self.kwargs[key]
if "region_name" not in llm_kwargs:
llm_kwargs["region_name"] = "us-east-1"
return NormalizedChatBedrockConverse(**llm_kwargs)
def validate_model(self) -> bool:
return self.model in _BEDROCK_MODELS