Files
tradingagents/tradingagents/llm_clients/anthropic_client.py
Yijia-Xiao 61522e103e fix(llm): skip Anthropic effort kwarg on non-supporting models (#831)
Haiku 4.5 rejects the effort parameter with 400. AnthropicClient.get_llm()
now drops effort when the model isn't in the supported set (Opus 4.5+,
Sonnet 4.5+, mythos-preview). Forward-compat regex catches future
claude-{opus,sonnet}-X-Y releases automatically; Haiku and unknown
models stay excluded conservatively.

14 tests cover Haiku exclusion, current Opus/Sonnet inclusion, future-
version inheritance via pattern, mythos-preview, unknown-default
exclusion, and other passthrough kwargs surviving the effort-skip path.
2026-05-17 07:54:06 +00:00

69 lines
2.3 KiB
Python

import re
from typing import Any, Optional
from langchain_anthropic import ChatAnthropic
from .base_client import BaseLLMClient, normalize_content
from .validators import validate_model
_PASSTHROUGH_KWARGS = (
"timeout", "max_retries", "api_key", "max_tokens",
"callbacks", "http_client", "http_async_client", "effort",
)
# Anthropic's extended-thinking ``effort`` parameter is accepted by Opus 4.5+
# and Sonnet 4.5+ only. Haiku (any version shipped to date) 400s with
# ``"This model does not support the effort parameter"`` (#831). Future
# ``claude-{opus,sonnet}-X-Y`` releases inherit effort support via the
# forward-compat pattern below; future Haiku stays excluded by default.
_EFFORT_EXACT = {
"claude-mythos-preview", # non-standard preview name; effort-capable
}
_EFFORT_PATTERN = re.compile(r"^claude-(opus|sonnet)-\d+-\d+$")
def _supports_effort(model: str) -> bool:
"""Whether Anthropic accepts the ``effort`` parameter for this model."""
model_lc = model.lower()
return model_lc in _EFFORT_EXACT or bool(_EFFORT_PATTERN.match(model_lc))
class NormalizedChatAnthropic(ChatAnthropic):
"""ChatAnthropic with normalized content output.
Claude models with extended thinking or tool use return content as a
list of typed blocks. This normalizes to string for consistent
downstream handling.
"""
def invoke(self, input, config=None, **kwargs):
return normalize_content(super().invoke(input, config, **kwargs))
class AnthropicClient(BaseLLMClient):
"""Client for Anthropic Claude models."""
def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
super().__init__(model, base_url, **kwargs)
def get_llm(self) -> Any:
"""Return configured ChatAnthropic instance."""
self.warn_if_unknown_model()
llm_kwargs = {"model": self.model}
if self.base_url:
llm_kwargs["base_url"] = self.base_url
for key in _PASSTHROUGH_KWARGS:
if key not in self.kwargs:
continue
if key == "effort" and not _supports_effort(self.model):
continue
llm_kwargs[key] = self.kwargs[key]
return NormalizedChatAnthropic(**llm_kwargs)
def validate_model(self) -> bool:
"""Validate model for Anthropic."""
return validate_model("anthropic", self.model)