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Overview

Mistral AI provides high-performance open and commercial models including Mistral Large and Codestral. Known for strong performance and European values. Model Class: MistralModel

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Authentication

export MISTRAL_API_KEY="..."

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Examples

from upsonic import Agent, Task
from upsonic.models.mistral import MistralModel

model = MistralModel(model_name="mistral-large-latest")
agent = Agent(model=model)

task = Task("Hello, how are you?")
result = agent.do(task)
print(result)

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Model Settings

You can set model parameters in two ways: on the model or on the Agent. On the model: 
from upsonic import Agent, Task
from upsonic.models.mistral import MistralModel, MistralModelSettings

model = MistralModel(
    model_name="mistral-large-latest",
    settings=MistralModelSettings(max_tokens=1024, temperature=0.7)
)
agent = Agent(model=model)
On the Agent: 
from upsonic import Agent, Task
from upsonic.models.mistral import MistralModelSettings

agent = Agent(
    model="mistral/mistral-large-latest",
    settings=MistralModelSettings(max_tokens=1024)
)

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Parameters

ParameterTypeDescriptionDefaultSource
max_tokensintMaximum tokens to generateModel defaultBase
temperaturefloatSampling temperature (0.0-1.0)0.7Base
top_pfloatNucleus sampling1.0Base
seedintRandom seedNoneBase
stop_sequenceslist[str]Stop generation sequencesNoneBase
presence_penaltyfloatToken presence penalty0.0Base
frequency_penaltyfloatToken frequency penalty0.0Base
timeoutfloatRequest timeout (seconds)600Base