LLMling
by phil65
LLMling is a framework for declarative LLM application development, focusing on resource management, prompt templates, and tool execution. It provides a YAML-based configuration system for setting up custom MPC servers serving content defined in YAML files.
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What is LLMling?
LLMling is a framework that enables developers to define LLM applications using YAML configurations. It provides tools for managing resources (files, text, CLI output), creating prompts, and executing Python functions (tools) callable by the LLM. It also supports the Machine Chat Protocol (MCP) for standardized LLM interaction.
How to use LLMling?
LLMling can be used via its CLI, through the llmling-agent (pydantic-AI based agent), or as a server (mcp-server-llmling). The CLI allows managing configurations, resources, tools, and prompts. The agent provides function calling capabilities to interact with LLMs. The server exposes LLMling components over HTTP/SSE using the MCP protocol.
Key features of LLMling
YAML-based configuration
Resource management (files, text, CLI output)
Prompt templating
Tool execution (Python functions)
Machine Chat Protocol (MCP) support
CLI for management
Agent integration (pydantic-AI)
Server capabilities (HTTP/SSE)
Use cases of LLMling
Building custom LLM applications
Creating chatbots with access to specific knowledge bases
Automating tasks using LLMs and Python tools
Integrating LLMs into existing systems
Developing code analysis and review tools
Creating web scraping and data extraction applications
FAQ from LLMling
What is the minimum Python version required?
What is the minimum Python version required?
Python 3.12 or higher is required.
What is MCP?
What is MCP?
MCP stands for Machine Chat Protocol, a standardized protocol for LLM interaction.
How do I define tools?
How do I define tools?
Tools are defined as Python functions or classes and configured in the YAML configuration file.
Can I use file watching with resources?
Can I use file watching with resources?
Yes, the path and image resource types support file watching to automatically detect changes.
Where can I find more documentation?
Where can I find more documentation?
More documentation can be found in the docs directory of the GitHub repository, including introduction, quick example, usage, YAML configuration, CLI, resources, prompts, tools, server, and extending guides.