LLM

Categories: Coding & Developer Tools, Chatbots & Assistants, Productivity | Pricing: Free | Official Website ↗

LLM is a CLI utility and Python library for interacting with various Large Language Models, both remote and local.

LLM is a command-line interface (CLI) tool and Python library designed to facilitate interaction with a wide range of Large Language Models (LLMs). It supports popular remote APIs like OpenAI, Anthropic's Claude, Google's Gemini, and Meta's Llama, as well as models that can be installed and run locally on a user's machine, such as those via Ollama. The tool allows users to run prompts, store prompts and responses in SQLite, generate and store embeddings, and extract structured content from text and images. Key functionalities include interactive chat sessions, the ability to grant models the execution of tools, and support for schemas to extract structured data. LLM is highly extensible through a plugin system, enabling users to add support for new models, embedding models, tools, and template loaders. It also provides robust logging capabilities, storing interactions in a SQLite database for later review and analysis.

Key Features

Run prompts from the command-line
Store prompts and responses in SQLite
Generate and store embeddings
Extract structured content from text and images
Grant models the ability to execute tools
Interactive chat with models
Support for remote and local LLMs
Extensible with plugins

Pros

Supports a wide range of LLMs, both remote and local
Provides a command-line interface for quick interactions
Offers a Python library for programmatic use
Logs all prompts and responses to SQLite for review
Highly extensible through a plugin system

Cons

Requires technical knowledge for setup and use
Relies on external API keys for commercial models
No graphical user interface (GUI)
Documentation can be extensive for new users
Local model setup can be complex

Use Cases

Automating text generation tasks
Building custom AI applications
Experimenting with different LLMs
Extracting structured data from unstructured text
Creating embedding-based search engines

Best For

Developers
Data scientists
Researchers
Anyone needing to interact with LLMs programmatically or via CLI

Integrations: OpenAI, Anthropic, Google Gemini, Meta Llama (via plugins), Ollama (via plugins)

Platforms: Web, macOS, Windows, Linux

Watch demo on YouTube ↗

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