mirror of https://github.com/hwchase17/langchain
docs: `providers` updates 1 (#20256)
- Proviers pages: added missed integrations; fixed format - `mistralai` converted from notebook to .mdx formaterick/docs-ignore-echo-false-blocks
Leonid Ganeline
2 weeks ago
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GitHub
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# Anthropic
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All functionality related to Anthropic models.
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>[Anthropic](https://www.anthropic.com/) is an AI safety and research company, and is the creator of `Claude`.
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This page covers all integrations between `Anthropic` models and `LangChain`.
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[Anthropic](https://www.anthropic.com/) is an AI safety and research company, and is the creator of Claude.
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This page covers all integrations between Anthropic models and LangChain.
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## Installation and Setup
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## Installation
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To use `Anthropic` models, you need to install a python package:
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To use Anthropic models, you will need to install the `langchain-anthropic` package.
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You can do this with the following command:
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```
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pip install langchain-anthropic
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```bash
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pip install -U langchain-anthropic
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```
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## Environment Setup
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To use Anthropic models, you will need to set the `ANTHROPIC_API_KEY` environment variable.
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You need to set the `ANTHROPIC_API_KEY` environment variable.
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You can get an Anthropic API key [here](https://console.anthropic.com/settings/keys)
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## `ChatAnthropic`
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## LLMs
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`ChatAnthropic` is a subclass of LangChain's `ChatModel`.
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You can import this wrapper with the following code:
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### [Legacy] AnthropicLLM
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```
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from langchain_anthropic import ChatAnthropic
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model = ChatAnthropic(model='claude-3-opus-20240229')
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**NOTE**: `AnthropicLLM` only supports legacy `Claude 2` models.
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To use the newest `Claude 3` models, please use `ChatAnthropic` instead.
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See a [usage example](/docs/integrations/llms/anthropic).
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```python
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from langchain_anthropic import AnthropicLLM
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model = AnthropicLLM(model='claude-2.1')
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```
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Read more in the [ChatAnthropic documentation](/docs/integrations/chat/anthropic).
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## Chat Models
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## [Legacy] `AnthropicLLM`
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### ChatAnthropic
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`AnthropicLLM` is a subclass of LangChain's `LLM`. It is a wrapper around Anthropic's
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text-based completion endpoints.
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See a [usage example](/docs/integrations/chat/anthropic).
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```python
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from langchain_anthropic import AnthropicLLM
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from langchain_anthropic import ChatAnthropic
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model = ChatAnthropic(model='claude-3-opus-20240229')
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```
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model = AnthropicLLM(model='claude-2.1')
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```
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@ -1,78 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# MistralAI\n",
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"\n",
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"Mistral AI is a platform that offers hosting for their powerful open source models.\n",
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"\n",
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"You can access them via their [API](https://docs.mistral.ai/api/).\n",
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"\n",
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"A valid [API key](https://console.mistral.ai/users/api-keys/) is needed to communicate with the API.\n",
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"\n",
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"You will also need the `langchain-mistralai` package:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install -qU langchain-core langchain-mistralai"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"id": "y8ku6X96sebl"
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},
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"outputs": [],
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"source": [
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"from langchain_mistralai import ChatMistralAI, MistralAIEmbeddings"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"See the docs for their\n",
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"\n",
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"- [Chat Model](/docs/integrations/chat/mistralai)\n",
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"- [Embeddings Model](/docs/integrations/text_embedding/mistralai)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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@ -0,0 +1,34 @@
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# MistralAI
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>[Mistral AI](https://docs.mistral.ai/api/) is a platform that offers hosting for their powerful open source models.
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## Installation and Setup
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A valid [API key](https://console.mistral.ai/users/api-keys/) is needed to communicate with the API.
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You will also need the `langchain-mistralai` package:
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```bash
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pip install langchain-mistralai
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```
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## Chat models
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### ChatMistralAI
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See a [usage example](/docs/integrations/chat/mistralai).
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```python
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from langchain_mistralai.chat_models import ChatMistralAI
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```
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## Embedding models
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### MistralAIEmbeddings
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See a [usage example](/docs/integrations/text_embedding/mistralai).
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```python
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from langchain_mistralai import MistralAIEmbeddings
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```
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