Source code for langchain.chat_models.human
"""ChatModel wrapper which returns user input as the response.."""
import asyncio
from functools import partial
from io import StringIO
from typing import Any, Callable, Dict, List, Mapping, Optional
import yaml
from langchain.callbacks.manager import (
    AsyncCallbackManagerForLLMRun,
    CallbackManagerForLLMRun,
)
from langchain.chat_models.base import BaseChatModel
from langchain.llms.utils import enforce_stop_tokens
from langchain.pydantic_v1 import Field
from langchain.schema.messages import (
    BaseMessage,
    HumanMessage,
    _message_from_dict,
    messages_to_dict,
)
from langchain.schema.output import ChatGeneration, ChatResult
def _display_messages(messages: List[BaseMessage]) -> None:
    dict_messages = messages_to_dict(messages)
    for message in dict_messages:
        yaml_string = yaml.dump(
            message,
            default_flow_style=False,
            sort_keys=False,
            allow_unicode=True,
            width=10000,
            line_break=None,
        )
        print("\n", "======= start of message =======", "\n\n")
        print(yaml_string)
        print("======= end of message =======", "\n\n")
def _collect_yaml_input(
    messages: List[BaseMessage], stop: Optional[List[str]] = None
) -> BaseMessage:
    """Collects and returns user input as a single string."""
    lines = []
    while True:
        line = input()
        if not line.strip():
            break
        if stop and any(seq in line for seq in stop):
            break
        lines.append(line)
    yaml_string = "\n".join(lines)
    # Try to parse the input string as YAML
    try: