Crate llm_chain

🚀 llm-chain 🚀

llm-chain is the ultimate toolbox for developers looking to supercharge their applications with the power of Large Language Models (LLMs)! 🎉

This versatile crate lets you chain together LLMs, making it incredibly useful for:

• Effortlessly summarizing lengthy documents 📚
• Allow your bots to interact with the environment using tools.
• Seamlessly chaining together multiple prompts to tackle complex tasks.
• ChatGPT model support
• LLaMA model support

And that’s not all! llm-chain is also your best friend when it comes to creating and managing prompts for LLMs. Say goodbye to hassle and bloated syntax! Quickly create and manage prompts with our intuitive templating system, and let llm-chain handle the rest! 🤩

Keep in mind that this crate is a library, which means it doesn’t include any LLMs out of the box. But fear not! We also offer the llm-chain-openai crate, which brings the power of OpenAI’s LLMs right to your fingertips! 🪄 We recommend starting with that crate to make the most of llm-chain. 😉

So, buckle up and dive into the amazing world of LLMs! Unlock the full potential of your applications with llm-chain and watch them soar! 🌈💥

To help you get started, we’ve prepared a comprehensive tutorial that will guide you through the process of using llm-chain. The tutorial covers everything from installation to advanced usage, so you’ll be well-equipped to make the most of this powerful toolbox.

Happy coding, and may your LLM adventures be both exciting and productive! 🥳🚀

Re-exports

pub use parameters::Parameters;

Modules

agents

chains

Chains are multi-step modes of execution for LLMs such as Sequential or MapReduce.

document_stores

executor

Utilities for working with executors

frame

A frame is the combination of a Step and an Executor. It wraps common behavior used by different chain types.

options

output

parameters

Parameters are used to pass data steps of the chain. This module implements them.

parsing

Functions for parsing the output of LLMs, including YAML and Markdown.

prompt

Module implementing prompts and prompt templates. Contains the prompt! macro, Prompts and PromptTemplates.

schema

Schema for Documents that can be stored in vector stores.

serialization

Envelope Serialization

step

Steps are individual LLM invocations in a chain. They are a combination of a prompt and a configuration.

summarization

Opinionated text summarization functionality

tokens

Tokens Module

tools

Tool Access Module

traits

Traits Module

Macros

executor

A macro that creates a new executor for a specified model.

multitool

options

options! is a declarative macro that facilitates the creation of an Options instance.

parameters

A macro that creates a new Parameters instance with the provided key-value pairs.

prompt

Creates a TextPrompt or a ChatPrompt based on the number of arguments provided.