matrix-pygmalion-bot/matrix_pygmalion_bot/bot/wrappers/langchain_koboldcpp.py

"""KoboldCpp LLM wrapper for testing purposes."""
import asyncio
import time
import logging
from typing import Any, List, Mapping, Optional

import json
import requests
import functools

from langchain.llms.base import LLM

from langchain.schema import BaseMessage, AIMessage, HumanMessage, SystemMessage, ChatMessage

logger = logging.getLogger(__name__)


class KoboldCpp(LLM):
    """KoboldCpp LLM wrapper for testing purposes."""

    endpoint_url: str = "http://172.16.33.10:5001/api/latest/generate"

    temperature: Optional[float] = 0.7
    """The temperature to use for sampling."""

    max_context: Optional[int] = 2048
    """The maximum context size."""

    max_tokens: Optional[int] = 256
    """The maximum number of tokens to generate."""

    top_p: Optional[float] = 0.90
    """The top-p value to use for sampling."""

    repeat_penalty: Optional[float] = 1.15
    """The penalty to apply to repeated tokens."""

    top_k: Optional[int] = 20
    """The top-k value to use for sampling."""

    stop: Optional[List[str]] = []
    """A list of strings to stop generation when encountered."""

#    model_kwargs: Dict[str, Any] = Field(default_factory=dict)

    @property
    def _llm_type(self) -> str:
        """Return type of llm."""
        return "KoboldCpp"

    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
        """First try to lookup in queries, else return 'foo' or 'bar'."""

        #params = self.model_kwargs or {}
        input_data = {
            "prompt": prompt,
            "max_context_length": self.max_context,
            "max_length": self.max_tokens,
            "temperature": self.temperature,
            "top_k": self.top_k,
            "top_p": self.top_p,
            "rep_pen": self.repeat_penalty,
            "rep_pen_range": 256,
            "stop_sequence": self.stop,
        }
        
        if stop:
            input_data["stop_sequence"] = stop

        headers = {
            "Content-Type": "application/json",
        }

        logger.info(f"sending request to koboldcpp.")
        logger.warning(f"WARNING: request is blocking. try to use llm's _acall()")

        TRIES = 30
        for i in range(TRIES):
            try:
                r = requests.post(self.endpoint_url, json=input_data, headers=headers, timeout=600)
                r_json = r.json()
            except requests.exceptions.RequestException as e:
                raise ValueError(f"http connection error.")
            logger.info(r_json)
            if r.status_code == 200:
                try:
                    response = r_json["results"][0]["text"]
                except KeyError:
                    raise ValueError(f"LangChain requires 'results' key in response.")
                break
            elif r.status_code == 503:
                logger.info(f"api is busy. waiting...")
                time.sleep(5)
            else:
                raise ValueError(f"http error. unknown response code")
        for s in input_data["stop_sequence"]:
            response = response.removesuffix(s).rstrip()
        return response


    async def _acall(self, prompt: str, stop: Optional[List[str]] = None) -> str:
        """Call out to KoboldCpp's completion endpoint asynchronuosly."""

        #params = self.model_kwargs or {}
        input_data = {
            "prompt": prompt,
            "max_context_length": self.max_context,
            "max_length": self.max_tokens,
            "temperature": self.temperature,
            "top_k": self.top_k,
            "top_p": self.top_p,
            "rep_pen": self.repeat_penalty,
            "rep_pen_range": 256,
            "stop_sequence": self.stop,
        }
        
        if stop:
            input_data["stop_sequence"] = stop

        headers = {
            "Content-Type": "application/json",
        }

        logger.info(f"sending request to koboldcpp.")

        TRIES = 30
        for i in range(TRIES):
            try:
                loop = asyncio.get_running_loop()
                #r = requests.post(self.endpoint_url, json=input_data, headers=headers, timeout=600)
                r = await loop.run_in_executor(None, functools.partial(requests.post, self.endpoint_url, json=input_data, headers=headers, timeout=600))
                r_json = r.json()
            except requests.exceptions.RequestException as e:
                raise ValueError(f"http connection error.")
            logger.info(r_json)
            if r.status_code == 200:
                try:
                    response = r_json["results"][0]["text"]
                except KeyError:
                    raise ValueError(f"LangChain requires 'results' key in response.")
                break
            elif r.status_code == 503:
                logger.info(f"api is busy. waiting...")
                await asyncio.sleep(5)
            else:
                raise ValueError(f"http error. unknown response code")
        for s in input_data["stop_sequence"]:
            response = response.removesuffix(s).rstrip()
        return response


    @property
    def _identifying_params(self) -> Mapping[str, Any]:
        return {}

    def get_num_tokens(self, text: str) -> int:
        """Estimate num tokens."""
        return len(text)//4+1


    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
        """Estimate num tokens."""
        tokens_per_message = 3
        tokens_per_name = 1
        num_tokens = 0
        messages_dict = [_convert_message_to_dict(m) for m in messages]
        for message in messages_dict:
            num_tokens += tokens_per_message
            for key, value in message.items():
                if key == "content":
                    num_tokens += self.get_num_tokens(value)
                elif key == "name":
                    num_tokens += tokens_per_name
        num_tokens += 3
        return num_tokens

def _convert_message_to_dict(message: BaseMessage) -> dict:
    if isinstance(message, ChatMessage):
        message_dict = {"role": message.role, "content": message.content}
    elif isinstance(message, HumanMessage):
        message_dict = {"role": "user", "content": message.content}
    elif isinstance(message, AIMessage):
        message_dict = {"role": "assistant", "content": message.content}
    elif isinstance(message, SystemMessage):
        message_dict = {"role": "system", "content": message.content}
    else:
        raise ValueError(f"Got unknown type {message}")
    if "name" in message.additional_kwargs:
        message_dict["name"] = message.additional_kwargs["name"]
    return message_dict