forked from Archives/langchain
985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
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Cohere
This page covers how to use the Cohere ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific Cohere wrappers.
Installation and Setup
- Install the Python SDK with
pip install cohere
- Get an Cohere api key and set it as an environment variable (
COHERE_API_KEY
)
Wrappers
LLM
There exists an Cohere LLM wrapper, which you can access with
from langchain.llms import Cohere
Embeddings
There exists an Cohere Embeddings wrapper, which you can access with
from langchain.embeddings import CohereEmbeddings
For a more detailed walkthrough of this, see this notebook