Source code for haive.core.models.llm.providers.cohere

"""Cohere Provider Module.

This module implements the Cohere language model provider for the Haive framework,
supporting Cohere's Command models with advanced generation and reasoning capabilities.

The provider handles API key management, model configuration, and safe imports of
the langchain-cohere package dependencies.

Examples:
    Basic usage:

    .. code-block:: python

        from haive.core.models.llm.providers.cohere import CohereProvider

        provider = CohereProvider(
            model="command-r-plus",
            temperature=0.7,
            max_tokens=1000
        )
        llm = provider.instantiate()

    With custom parameters::

        provider = CohereProvider(
            model="command-r",
            temperature=0.1,
            k=40,
            p=0.9,
            frequency_penalty=0.1
        )

.. autosummary::
   :toctree: generated/

   CohereProvider
"""

from typing import Any

from pydantic import Field

from haive.core.models.llm.provider_types import LLMProvider
from haive.core.models.llm.providers.base import BaseLLMProvider, ProviderImportError


[docs] class CohereProvider(BaseLLMProvider): """Cohere language model provider configuration. This provider supports Cohere's Command models including Command R+, Command R, and other models optimized for reasoning, generation, and multilingual tasks. Attributes: provider (LLMProvider): Always LLMProvider.COHERE model (str): The Cohere model to use temperature (float): Sampling temperature (0.0-5.0) max_tokens (int): Maximum tokens in response k (int): Top-k sampling parameter p (float): Top-p nucleus sampling parameter frequency_penalty (float): Frequency penalty parameter presence_penalty (float): Presence penalty parameter stop_sequences (list): Stop sequences for generation Examples: High-performance reasoning:: provider = CohereProvider( model="command-r-plus", temperature=0.3, max_tokens=2000, k=40 ) Creative writing:: provider = CohereProvider( model="command-r", temperature=0.9, p=0.95, frequency_penalty=0.2 ) """ provider: LLMProvider = Field( default=LLMProvider.COHERE, description="Provider identifier" ) # Cohere model parameters temperature: float | None = Field( default=None, ge=0, le=5, description="Sampling temperature (0.0-5.0 for Cohere)", ) max_tokens: int | None = Field( default=None, ge=1, description="Maximum tokens in response" ) k: int | None = Field( default=None, ge=0, le=500, description="Top-k sampling parameter" ) p: float | None = Field( default=None, ge=0, le=1, description="Top-p nucleus sampling parameter" ) frequency_penalty: float | None = Field( default=None, ge=0, le=1, description="Frequency penalty parameter" ) presence_penalty: float | None = Field( default=None, ge=0, le=1, description="Presence penalty parameter" ) stop_sequences: list[str] | None = Field( default=None, description="Stop sequences for generation" ) def _get_chat_class(self) -> type[Any]: """Get the Cohere chat class.""" try: from langchain_cohere import ChatCohere return ChatCohere except ImportError as e: raise ProviderImportError( provider=self.provider.value, package=self._get_import_package(), message="Cohere requires langchain-cohere. Install with: pip install langchain-cohere", ) from e def _get_default_model(self) -> str: """Get the default Cohere model.""" return "command-r-plus" def _get_import_package(self) -> str: """Get the required package name.""" return "langchain-cohere" def _get_initialization_params(self, **kwargs) -> dict[str, Any]: """Get Cohere-specific initialization parameters.""" params = { "model": self.model, **kwargs, } # Add model parameters if specified if self.temperature is not None: params["temperature"] = self.temperature if self.max_tokens is not None: params["max_tokens"] = self.max_tokens if self.k is not None: params["k"] = self.k if self.p is not None: params["p"] = self.p if self.frequency_penalty is not None: params["frequency_penalty"] = self.frequency_penalty if self.presence_penalty is not None: params["presence_penalty"] = self.presence_penalty if self.stop_sequences is not None: params["stop"] = self.stop_sequences # Add API key api_key = self.get_api_key() if api_key: params["cohere_api_key"] = api_key # Add extra params params.update(self.extra_params or {}) return params def _get_env_key_name(self) -> str: """Get the environment variable name for API key.""" return "COHERE_API_KEY"
[docs] @classmethod def get_models(cls) -> list[str]: """Get available Cohere models.""" return [ "command-r-plus", "command-r", "command-nightly", "command-light", "command-light-nightly", ]