Source code for langchain.chat_models.bedrock
from typing import Any, Dict, Iterator, List, Optional
from langchain.callbacks.manager import (
    CallbackManagerForLLMRun,
)
from langchain.chat_models.anthropic import convert_messages_to_prompt_anthropic
from langchain.chat_models.base import BaseChatModel
from langchain.llms.bedrock import BedrockBase
from langchain.pydantic_v1 import Extra
from langchain.schema.messages import AIMessage, AIMessageChunk, BaseMessage
from langchain.schema.output import ChatGeneration, ChatGenerationChunk, ChatResult
[docs]class ChatPromptAdapter:
    """Adapter class to prepare the inputs from Langchain to prompt format
    that Chat model expects.
    """
[docs]    @classmethod
    def convert_messages_to_prompt(
        cls, provider: str, messages: List[BaseMessage]
    ) -> str:
        if provider == "anthropic":
            prompt = convert_messages_to_prompt_anthropic(messages=messages)
        else:
            raise NotImplementedError(
                f"Provider {provider} model does not support chat."
            )
        return prompt
[docs]class BedrockChat(BaseChatModel, BedrockBase):
    @property
    def _llm_type(self) -> str:
        """Return type of chat model."""
        return "amazon_bedrock_chat"
    class Config:
        """Configuration for this pydantic object."""
        extra = Extra.forbid
    def _stream(
        self,
        messages: List[BaseMessage],
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> Iterator[ChatGenerationChunk]:
        provider = self._get_provider()