langchain/libs/partners/mistralai/README.md

langchain-mistralai

This package contains the LangChain integrations for MistralAI through their mistralai SDK.

Installation

pip install -U langchain-mistralai

Chat Models

This package contains the ChatMistralAI class, which is the recommended way to interface with MistralAI models.

To use, install the requirements, and configure your environment.

export MISTRAL_API_KEY=your-api-key

Then initialize

from langchain_core.messages import HumanMessage
from langchain_mistralai.chat_models import ChatMistralAI

chat = ChatMistralAI(model="mistral-small")
messages = [HumanMessage(content="say a brief hello")]
chat.invoke(messages)

ChatMistralAI also supports async and streaming functionality:

# For async...
await chat.ainvoke(messages)

# For streaming...
for chunk in chat.stream(messages):
    print(chunk.content, end="", flush=True)

Embeddings

With MistralAIEmbeddings, you can directly use the default model 'mistral-embed', or set a different one if available.

Choose model

embedding.model = 'mistral-embed'

Simple query

res_query = embedding.embed_query("The test information")

Documents

res_document = embedding.embed_documents(["test1", "another test"])