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langchain/docs/ecosystem/hazy_research.md
Harrison Chase 985496f4be
Docs refactor (#480) 
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>
2023-01-02 08:24:09 -08:00

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Hazy Research

This page covers how to use the Hazy Research ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific Hazy Research wrappers.

Installation and Setup

  • To use the manifest, install it with pip install manifest-ml

Wrappers

LLM

There exists an LLM wrapper around Hazy Research's manifest library. manifest is a python library which is itself a wrapper around many model providers, and adds in caching, history, and more.

To use this wrapper:

from langchain.llms.manifest import ManifestWrapper