"""Wrapper around Konko AI's Completion API."""
import logging
import warnings
from typing import Any, Dict, List, Optional
from langchain_core.callbacks import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.llms import LLM
from pydantic import ConfigDict, SecretStr, model_validator
from langchain_community.utils.openai import is_openai_v1
logger = logging.getLogger(__name__)
[docs]
class Konko(LLM):
"""Konko AI models.
To use, you'll need an API key. This can be passed in as init param
``konko_api_key`` or set as environment variable ``KONKO_API_KEY``.
Konko AI API reference: https://docs.konko.ai/reference/
"""
base_url: str = "https://api.konko.ai/v1/completions"
"""Base inference API URL."""
konko_api_key: SecretStr
"""Konko AI API key."""
model: str
"""Model name. Available models listed here:
https://docs.konko.ai/reference/get_models
"""
temperature: Optional[float] = None
"""Model temperature."""
top_p: Optional[float] = None
"""Used to dynamically adjust the number of choices for each predicted token based
on the cumulative probabilities. A value of 1 will always yield the same
output. A temperature less than 1 favors more correctness and is appropriate
for question answering or summarization. A value greater than 1 introduces more
randomness in the output.
"""
top_k: Optional[int] = None
"""Used to limit the number of choices for the next predicted word or token. It
specifies the maximum number of tokens to consider at each step, based on their
probability of occurrence. This technique helps to speed up the generation
process and can improve the quality of the generated text by focusing on the
most likely options.
"""
max_tokens: Optional[int] = None
"""The maximum number of tokens to generate."""
repetition_penalty: Optional[float] = None
"""A number that controls the diversity of generated text by reducing the
likelihood of repeated sequences. Higher values decrease repetition.
"""
logprobs: Optional[int] = None
"""An integer that specifies how many top token log probabilities are included in
the response for each token generation step.
"""
model_config = ConfigDict(
extra="forbid",
)
@model_validator(mode="before")
@classmethod
def validate_environment(cls, values: Dict[str, Any]) -> Any:
"""Validate that python package exists in environment."""
try:
import konko
except ImportError:
raise ImportError(
"Could not import konko python package. "
"Please install it with `pip install konko`."
)
if not hasattr(konko, "_is_legacy_openai"):
warnings.warn(
"You are using an older version of the 'konko' package. "
"Please consider upgrading to access new features"
"including the completion endpoint."
)
return values
[docs]
def construct_payload(
self,
prompt: str,
stop: Optional[List[str]] = None,
**kwargs: Any,
) -> Dict[str, Any]:
stop_to_use = stop[0] if stop and len(stop) == 1 else stop
payload: Dict[str, Any] = {
**self.default_params,
"prompt": prompt,
"stop": stop_to_use,
**kwargs,
}
return {k: v for k, v in payload.items() if v is not None}
@property
def _llm_type(self) -> str:
"""Return type of model."""
return "konko"
[docs]
@staticmethod
def get_user_agent() -> str:
from langchain_community import __version__
return f"langchain/{__version__}"
@property
def default_params(self) -> Dict[str, Any]:
return {
"model": self.model,
"temperature": self.temperature,
"top_p": self.top_p,
"top_k": self.top_k,
"max_tokens": self.max_tokens,
"repetition_penalty": self.repetition_penalty,
}
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
"""Call out to Konko's text generation endpoint.
Args:
prompt: The prompt to pass into the model.
Returns:
The string generated by the model..
"""
import konko
payload = self.construct_payload(prompt, stop, **kwargs)
try:
if is_openai_v1():
response = konko.completions.create(**payload)
else:
response = konko.Completion.create(**payload)
except AttributeError:
raise ValueError(
"`konko` has no `Completion` attribute, this is likely "
"due to an old version of the konko package. Try upgrading it "
"with `pip install --upgrade konko`."
)
if is_openai_v1():
output = response.choices[0].text
else:
output = response["choices"][0]["text"]
return output
async def _acall(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
"""Asynchronously call out to Konko's text generation endpoint.
Args:
prompt: The prompt to pass into the model.
Returns:
The string generated by the model.
"""
import konko
payload = self.construct_payload(prompt, stop, **kwargs)
try:
if is_openai_v1():
client = konko.AsyncKonko()
response = await client.completions.create(**payload)
else:
response = await konko.Completion.acreate(**payload)
except AttributeError:
raise ValueError(
"`konko` has no `Completion` attribute, this is likely "
"due to an old version of the konko package. Try upgrading it "
"with `pip install --upgrade konko`."
)
if is_openai_v1():
output = response.choices[0].text
else:
output = response["choices"][0]["text"]
return output
