Crate llm_weaver

Flexible library developed for creating and managing coherent narratives which leverage LLMs (Large Language Models) to generate dynamic responses.

Built based on OpenAI’s recommended tactics, LLM Weaver facilitates extended interactions with any LLM, seamlessly handling conversations that exceed a model’s maximum context token limitation.

Loom is the core of this library. It prompts the configured LLM and stores the message history as TapestryFragment instances. This trait is highly configurable through the Config trait to support a wide range of use cases.

Nomenclature

• Tapestry: A collection of TapestryFragment instances.
• TapestryFragment: A single part of a conversation containing a list of messages along with other metadata.
• ContextMessage: Represents a single message in a TapestryFragment instance.
• Loom: The machine that drives all of the core methods that should be used across any service that needs to prompt LLM and receive a response.
• LLM: Language Model.

Architecture

Please refer to the architecture::Diagram for a visual representation of the core components of this library.

Usage

You must implement the Config trait, which defines the necessary types and methods needed by Loom.

This library uses Redis as the default storage backend for storing TapestryFragment. It is expected that a Redis instance is running and that the following environment variables are set:

• REDIS_PROTOCOL
• REDIS_HOST
• REDIS_PORT
• REDIS_PASSWORD

Should there be a need to integrate a distinct storage backend, you have the flexibility to create a custom handler by implementing the TapestryChestHandler trait and injecting it into the Config::Chest associated type.

Re-exports

• pub use storage::TapestryChestHandler;

Modules

• architecture
• storage
• types

Structs

• BoundedU8
  An u8 constrained to be in the range MIN..=MAX.
• ContextMessage
  Context message that represent a single message in a TapestryFragment instance.
• LlmConfig
• TapestryFragment
  Represents a single part of a conversation containing a list of messages along with other metadata.

Traits

• Config
  A trait consisting of the main configuration needed to implement Loom.
• Llm
• Loom
  The machine that drives all of the core methods that should be used across any service that needs to prompt LLM and receive a response.
• RedisWrite
  Abstraction trait for redis command abstractions.
• TapestryId
  Represents a unique identifier for any arbitrary entity.
• ToRedisArgs
  Used to convert a value into one or multiple redis argument strings. Most values will produce exactly one item but in some cases it might make sense to produce more than one.

Type Aliases

• Result