Skip to main content

An integration package connecting Mistral and LangChain

Project description

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"])

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langchain_mistralai-0.1.2.tar.gz (10.4 kB view details)

Uploaded Source

Built Distribution

langchain_mistralai-0.1.2-py3-none-any.whl (11.2 kB view details)

Uploaded Python 3

File details

Details for the file langchain_mistralai-0.1.2.tar.gz.

File metadata

  • Download URL: langchain_mistralai-0.1.2.tar.gz
  • Upload date:
  • Size: 10.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for langchain_mistralai-0.1.2.tar.gz
Algorithm Hash digest
SHA256 5b30dca47e8e3eaea7b1a40962c33588cd5245479dba6464eb3a83d850466c77
MD5 ebb71aa3097674fc4eef6a34c508f336
BLAKE2b-256 9a61f993187ec6e3f34e295a5dc8a1ed5af7e6377b7f8c53d29f3d15a7fd812a

See more details on using hashes here.

File details

Details for the file langchain_mistralai-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for langchain_mistralai-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 39889ee5aff37e15760fef245d3e5e5382183adeb0b46fc2060ba07b1d97c694
MD5 da3c74b2a4a1eab1dbc29317ff6df592
BLAKE2b-256 222af4dc2a26ab5b4951641799ce2ba477d5f1544e473ba6c3e997aeb0ea1d2f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page