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from langchain_cohere import ChatCohere |
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from pydantic.v1 import SecretStr |
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from langflow.base.models.model import LCModelComponent |
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from langflow.field_typing import LanguageModel |
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from langflow.inputs.inputs import HandleInput |
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from langflow.io import FloatInput, SecretStrInput |
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class CohereComponent(LCModelComponent): |
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display_name = "Cohere" |
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description = "Generate text using Cohere LLMs." |
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documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/cohere" |
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icon = "Cohere" |
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name = "CohereModel" |
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inputs = [ |
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*LCModelComponent._base_inputs, |
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SecretStrInput( |
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name="cohere_api_key", |
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display_name="Cohere API Key", |
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info="The Cohere API Key to use for the Cohere model.", |
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advanced=False, |
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value="COHERE_API_KEY", |
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), |
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FloatInput(name="temperature", display_name="Temperature", value=0.75), |
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HandleInput( |
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name="output_parser", |
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display_name="Output Parser", |
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info="The parser to use to parse the output of the model", |
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advanced=True, |
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input_types=["OutputParser"], |
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), |
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] |
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def build_model(self) -> LanguageModel: |
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cohere_api_key = self.cohere_api_key |
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temperature = self.temperature |
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api_key = SecretStr(cohere_api_key).get_secret_value() if cohere_api_key else None |
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return ChatCohere( |
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temperature=temperature or 0.75, |
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cohere_api_key=api_key, |
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) |
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