Source code for camel.configs.ollama_config

# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
from __future__ import annotations

from typing import Sequence, Union

from camel.configs.base_config import BaseConfig
from camel.types import NOT_GIVEN, NotGiven




class OllamaConfig(BaseConfig):
    r"""Defines the parameters for generating chat completions using OpenAI
    compatibility

    Reference: https://github.com/ollama/ollama/blob/main/docs/openai.md

    Args:
        temperature (float, optional): Sampling temperature to use, between
            :obj:`0` and :obj:`2`. Higher values make the output more random,
            while lower values make it more focused and deterministic.
            (default: :obj:`0.2`)
        top_p (float, optional): An alternative to sampling with temperature,
            called nucleus sampling, where the model considers the results of
            the tokens with top_p probability mass. So :obj:`0.1` means only
            the tokens comprising the top 10% probability mass are considered.
            (default: :obj:`1.0`)
        response_format (object, optional): An object specifying the format
            that the model must output. Compatible with GPT-4 Turbo and all
            GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106. Setting to
            {"type": "json_object"} enables JSON mode, which guarantees the
            message the model generates is valid JSON. Important: when using
            JSON mode, you must also instruct the model to produce JSON
            yourself via a system or user message. Without this, the model
            may generate an unending stream of whitespace until the generation
            reaches the token limit, resulting in a long-running and seemingly
            "stuck" request. Also note that the message content may be
            partially cut off if finish_reason="length", which indicates the
            generation exceeded max_tokens or the conversation exceeded the
            max context length.
        stream (bool, optional): If True, partial message deltas will be sent
            as data-only server-sent events as they become available.
            (default: :obj:`False`)
        stop (str or list, optional): Up to :obj:`4` sequences where the API
            will stop generating further tokens. (default: :obj:`None`)
        max_tokens (int, optional): The maximum number of tokens to generate
            in the chat completion. The total length of input tokens and
            generated tokens is limited by the model's context length.
            (default: :obj:`None`)
        presence_penalty (float, optional): Number between :obj:`-2.0` and
            :obj:`2.0`. Positive values penalize new tokens based on whether
            they appear in the text so far, increasing the model's likelihood
            to talk about new topics. See more information about frequency and
            presence penalties. (default: :obj:`0.0`)
        frequency_penalty (float, optional): Number between :obj:`-2.0` and
            :obj:`2.0`. Positive values penalize new tokens based on their
            existing frequency in the text so far, decreasing the model's
            likelihood to repeat the same line verbatim. See more information
            about frequency and presence penalties. (default: :obj:`0.0`)
    """

    temperature: float = 0.2
    top_p: float = 1.0
    stream: bool = False
    stop: Union[str, Sequence[str], NotGiven] = NOT_GIVEN
    max_tokens: Union[int, NotGiven] = NOT_GIVEN
    presence_penalty: float = 0.0
    response_format: Union[dict, NotGiven] = NOT_GIVEN
    frequency_penalty: float = 0.0



OLLAMA_API_PARAMS = {param for param in OllamaConfig.model_fields.keys()}