llama-cpp-agent is a C++ library that enables developers to create local AI agents powered by llama.cpp. It supports plugin integration, conversation memory management, and multiple LLM backends for high-performance, privacy-preserving conversational assistants on desktop platforms.
AI Platforms & Frameworks
Tool Libraries
#AI Agents
#offline framework
#privacy-focused
#C++ implementation
#conversational assistants
#open-source
#low latency
#custom tools
#modular plugins
#data privacy
#local inference
#task workflows
#multi-LLM support
#cross-platform
#conversation memory
#lightweight design
#Developer Tools
#configurable settings
#user data protection
#AI Integration
...
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llama-cpp-agent
llama-cpp-agent is a C++ library that enables developers to create local AI agents powered by llama.cpp. It supports plugin integration, conversation memory management, and multiple LLM backends for high-performance, privacy-preserving conversational assistants on desktop platforms.
AI Platforms & Frameworks
Tool Libraries
#AI Agents
#offline framework
#privacy-focused
#C++ implementation
#conversational assistants
#open-source
#low latency
#custom tools
#modular plugins
#data privacy
#local inference
#task workflows
#multi-LLM support
#cross-platform
#conversation memory
#lightweight design
#Developer Tools
#configurable settings
#user data protection
#AI Integration
...
Featured
What is llama-cpp-agent?
llama-cpp-agent is an open-source C++ framework for running AI agents entirely offline. It leverages the llama.cpp inference engine to provide fast, low-latency interactions and supports a modular plugin system, configurable memory, and task execution. Developers can integrate custom tools, switch between different local LLM models, and build privacy-focused conversational assistants without external dependencies.
Who will use llama-cpp-agent?
- C++ developers
- AI researchers
- Privacy-conscious users
- Hobbyists building local assistants
- Edge computing engineers
How to use the llama-cpp-agent?
- Step1: Install llama.cpp and its prerequisites (CMake, a C++17 compiler).
- Step2: Clone the repository from GitHub.
- Step3: Create a build directory and run CMake to configure the project.
- Step4: Build the agent with make or your chosen build tool.
- Step5: Configure model files and plugin paths in the settings file.
- Step6: Run the agent binary and interact via the CLI or integrate into your application.
Platform
- mac
- windows
- linux
llama-cpp-agent's Core Features & Benefits
The Core Features
- Modular plugin system for custom tools
- Conversation memory management
- Multi-LLM backend support via llama.cpp
- Offline, local inference for privacy
- Configurable prompt and task workflows
The Benefits
- Low-latency local execution
- Full user data privacy
- Lightweight C++ implementation
- Open-source and customizable
- Cross-platform desktop support
llama-cpp-agent's Main Use Cases & Applications
- Building offline conversational assistants
- Automating local task workflows
- Prototyping privacy-focused chatbots
- Integrating AI agents into desktop apps
- Edge device AI demonstrations
FAQs of llama-cpp-agent
llama-cpp-agent Company Information
- Maximilian Winter
llama-cpp-agent Reviews
5/5
llama-cpp-agent's Main Competitors and alternatives?
- LangChain
- Auto-GPT
- BabyAGI
- rivet
- Haystack
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