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Mistral AI¶

Mistral AI provides high-performance open-weight models with excellent multilingual capabilities.

Quick Start¶

from sentimatrix import Sentimatrix
from sentimatrix.config import SentimatrixConfig, LLMConfig

config = SentimatrixConfig(
    llm=LLMConfig(
        provider="mistral",
        model="mistral-large-latest",
        api_key="your-mistral-key"  # Or set MISTRAL_API_KEY
    )
)

async with Sentimatrix(config) as sm:
    summary = await sm.summarize_reviews(reviews)

Available Models¶

Model	Context	Best For
`mistral-large-latest`	128K	Complex reasoning, analysis
`mistral-medium-latest`	32K	Balanced performance
`mistral-small-latest`	32K	Fast, cost-effective
`open-mistral-7b`	32K	Lightweight tasks
`open-mixtral-8x7b`	32K	MoE architecture
`open-mixtral-8x22b`	64K	High performance MoE
`codestral-latest`	32K	Code-focused tasks

Configuration¶

LLMConfig(
    provider="mistral",
    model="mistral-large-latest",
    api_key="your-key",           # Or MISTRAL_API_KEY env var
    temperature=0.7,              # 0.0-1.0
    max_tokens=4096,
    top_p=1.0,
    timeout=30,
)

Environment Variables¶

export MISTRAL_API_KEY="your-mistral-api-key"

Features¶

Multilingual: Excellent support for European languages
Function Calling: Native tool/function support
JSON Mode: Structured output generation
Streaming: Real-time response streaming

Pricing¶

Model	Input	Output
mistral-large	$2/1M	$6/1M
mistral-medium	$2.7/1M	$8.1/1M
mistral-small	$0.2/1M	$0.6/1M

Example: Multilingual Analysis¶

async with Sentimatrix(config) as sm:
    # Mistral excels at multilingual content
    reviews_fr = ["Excellent produit!", "Pas terrible..."]
    reviews_de = ["Tolles Produkt!", "Nicht empfehlenswert"]

    results_fr = await sm.analyze_batch(reviews_fr)
    results_de = await sm.analyze_batch(reviews_de)