by Maximilian-Winter · Agent Tool · ★ 620
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llama-cpp-agent Not Longer Maintained. Use instead ToolAgents or other Python agentic frameworks. [] Introduction The llama-cpp-agent framework is a tool designed to simplify interactions with Large Language Models (LLMs). It provides an interface for chatting with LLMs, executing function calls, generating structured output, performing retrieval augmented generation, and processing text using agentic chains with tools. The framework uses guided sampling to constrain the model output to the user defined structures. This way also models not fine-tuned to do function calling and JSON output will be able to do it. The framework is compatible with the llama.cpp server, llama-cpp-python and its server, and with TGI and vllm servers. Key Features Simple Chat Interface: Engage in seamless conversations with LLMs. Structured Output: Generate structured output (objects) from LLMs. Singl
| Stars | 620 |
| Forks | 69 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 41.75/100 |
| Open Issues | 24 |
| Last Updated | 2026-03-09 |
| Created | 2023-12-29 |
| Platforms | python |
| Est. Tokens | ~383k |
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llama-cpp-agent is The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured ou. It is categorized as a Agent Tool with 620 GitHub stars.
llama-cpp-agent is primarily written in Python. It covers topics such as agents, function-calling, llamacpp.
You can find installation instructions and usage details in the llama-cpp-agent GitHub repository at github.com/Maximilian-Winter/llama-cpp-agent. The project has 620 stars and 69 forks, indicating an active community.
The top alternatives to llama-cpp-agent on Agent Skills Hub include LLMCompiler, holmesgpt, Awesome-AI-For-Security. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.