from typing import Any, Optional

from langchain_anthropic import ChatAnthropic

from .base_client import BaseLLMClient
from .validators import validate_model


class NormalizedChatAnthropic(ChatAnthropic):
    """ChatAnthropic with normalized content output.

    Newer Claude models can return content as a list of content blocks.
    This normalizes to a plain string for consistent downstream handling.
    """

    def _normalize_content(self, response):
        content = response.content
        if isinstance(content, list):
            texts = [
                item.get("text", "") if isinstance(item, dict) and item.get("type") == "text"
                else item if isinstance(item, str) else ""
                for item in content
            ]
            response.content = "\n".join(t for t in texts if t)
        return response

    def invoke(self, input, config=None, **kwargs):
        return self._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."""
        llm_kwargs = {"model": self.model}

        for key in ("timeout", "max_retries", "api_key", "max_tokens", "callbacks", "http_client", "http_async_client"):
            if key in self.kwargs:
                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)