📚 Glossary

🧠 General Terms

  • LLM (Large Language Model)
    A machine learning model trained on vast amounts of text data to understand and generate human-like language. Examples include ChatGPT, Claude, Gemini, and Mistral.

  • Token
    A unit of text (word, part of a word, or symbol) used by LLMs for processing language.

  • Prompt
    A textual input given to an LLM to instruct or query it.

  • Context Window
    The amount of text (in tokens) an LLM can consider at once.

  • Fine-tuning
    Customizing a pre-trained LLM on specific data to specialize it for a task or domain.

  • Embedding
    A numerical representation of text used for semantic understanding, clustering, and retrieval tasks.

  • RAG (Retrieval-Augmented Generation)
    A technique where external data is fetched and combined with a prompt to help the LLM generate more accurate responses.

  • Chain-of-Thought Reasoning
    A prompting technique that encourages the model to “think step by step” before answering.

  • Hallucination
    When an LLM generates factually incorrect or fabricated information with confidence.

  • Agent
    A software entity that uses an LLM and tools to perform a task autonomously or semi-autonomously.

  • Memory
    Persistent storage of past interactions or user-specific data, allowing an agent or LLM to build continuity.

  • Tool Use
    The ability of an LLM or agent to use external APIs or tools (e.g., calculator, browser) to complete a task.

  • Multi-agent System
    A setup where multiple AI agents collaborate, often using LLMs, each with different roles or goals.

🚀 Mainstream LLMs (as of 2025)

  • GPT-4 / GPT-4 Turbo – OpenAI
    GPT-4 Turbo is faster and cheaper than GPT-4 with a 128k token context window. Powers ChatGPT.

  • Claude 3 – Anthropic
    Known for long context windows and safety features.

  • Gemini 1.5 – Google DeepMind
    Formerly Bard. Integrates with Google apps. Very large context support.

  • Mistral – Mistral AI
    Open-weight models such as Mistral 7B and Mixtral.

  • LLaMA – Meta
    Series of open-weight models, including LLaMA 2 and upcoming LLaMA 3.

  • Command R – Cohere
    RAG-optimized models, popular in enterprise use.

  • Grok – xAI (Elon Musk)
    Integrated with X (formerly Twitter). Focused on reasoning and open-source.

🛠️ CrewAI-Specific Terms

CrewAI is a Python framework for building collaborative LLM agents.

  • Crew
    A team of agents that work together to accomplish a task.

  • Agent (in CrewAI)
    An LLM-based worker with a defined role, goal, tools, and behavior.

  • Role
    Describes the function of the agent, e.g., “Researcher” or “Writer.”

  • Goal
    The specific objective assigned to the agent.

  • Backstory
    Optional narrative that gives personality or behavioral context to an agent.

  • Tools
    External functions or utilities agents can use (e.g., search, code execution).

  • Process
    The workflow strategy — sequential (agents act one after another) or collaborative.

  • Task
    A work item assigned to an agent with instructions and output expectations.

  • Output File
    Where the agent or crew stores results for reuse or review.

  • Memory
    Stores past outputs or steps to inform current and future agent reasoning.

🤖 AutoGPT / AgentGPT Providers and Frameworks

Frameworks that support autonomous or collaborative AI agents using LLMs and tools.

Provider / Project Description
CrewAI Python framework for defining structured agent teams with goals, memory, tools, and collaboration. 🔗
AutoGPT One of the original autonomous agents. Generates subgoals, uses tools, and stores memory. 🔗
AgentGPT Web-based UI for autonomous agents that think and act in the browser. 🔗
SuperAGI Full-featured open-source platform with GUI, memory, and marketplace for agents. 🔗
OpenAgents (Microsoft) Research-oriented agent platform with planning and tool use. 🔗
LangGraph Graph-based multi-agent coordination framework built on LangChain. 🔗
MetaGPT Simulates a software dev team (PM, Engineer, QA) using role-based agents. 🔗
ChatDev Simulates a virtual software company with agents playing different roles.
BabyAGI Lightweight agent framework that continuously generates and prioritizes tasks. 🔗
Camel-AI Agent communication framework focused on negotiation and collaboration. 🔗

⚙️ Related Ecosystem Tools

  • LangChain
    Framework for chaining prompts, memory, and tools together. Widely used in agent systems.

  • LlamaIndex
    Data indexing layer to connect LLMs with custom or private datasets.

  • Toolformer
    A fine-tuning technique to teach LLMs how and when to use tools.

  • OpenFunction Calling
    Technique that enables LLMs to invoke external APIs via structured JSON outputs (e.g., OpenAI’s function calling, Anthropic’s tool use).