LLM integrations and AI chatbot tools

Libraries, frameworks, and tools for building AI chatbots and conversational agents that integrate with large language models like OpenAI, Gemini, and other LLM APIs. The cluster spans plugin ecosystems (chat-plugin-sdk, lobe-chat-plugins), web integration layers (chat-plugin-web-crawler, chat-plugin-search-engine), and prompt management systems. Dominated by TypeScript and Python implementations, this area covers both the infrastructure for connecting LLMs to external data sources and APIs, and the application frameworks for deploying multi-model chat interfaces.

Libraries, frameworks, and tools for building autonomous AI agents that leverage large language models (LLMs) from providers like OpenAI and Anthropic. Projects in this cluster focus on agent orchestration, tool use, reasoning loops, and integrations with APIs and Kubernetes environments. The collection spans Python implementations (agent cores and orchestration), TypeScript/JavaScript frontends and SDKs, and supporting infrastructure for agentic workflows.

Unified interfaces and load-balancing systems for routing requests across multiple large language model APIs (OpenAI, Anthropic Claude, Google Gemini, DeepSeek, and others). The cluster includes API gateway implementations, request routing middleware, and adapter layers that abstract away provider-specific details and enable failover, load distribution, and cost optimization across disparate LLM backends. Most repos are written in TypeScript and Go, reflecting the infrastructure-heavy nature of this domain.

Applications and frameworks for building chatbot interfaces that integrate with large language models like ChatGPT, Claude, Gemini, and DeepSeek. The cluster spans multiple implementation languages (TypeScript, Python, and Rust) and includes both web-based chat clients and programmatic chat SDKs, with a focus on providing accessible interfaces to multiple LLM providers and enabling conversational AI features in user-facing products.

Libraries and frameworks for building autonomous AI agents using large language models, with emphasis on multi-agent coordination, task orchestration, and agent-to-agent communication. The cluster spans Python and TypeScript implementations of agent systems that leverage OpenAI and ChatGPT APIs, including workflow engines, agent squad management, and conversation frameworks. Central projects like Giselle, Agent6, Hive, and Argo demonstrate patterns for composing agents into larger systems with hierarchical control and specialized task delegation.

Libraries and frameworks for building applications powered by large language models, with emphasis on multi-agent systems, orchestration, and integration with APIs like OpenAI and Gemini. The cluster spans Python and TypeScript implementations of LLM chains, prompt engineering, agent coordination, and chat/agentic interfaces, ranging from foundational frameworks (LangChain, LangChain4j) to specialized agent platforms and specialized implementations like conversational bots and autonomous agent hubs.

Libraries and frameworks for building production applications with large language models, including retrieval-augmented generation (RAG), agent orchestration, and prompt caching. The cluster emphasizes practical tooling for LLM integration—caching responses for cost and latency optimization, structuring multi-step agent workflows, and evaluating model outputs—with most repos written in Python and centered around OpenAI and LangChain ecosystems. Central repos like GPTCache and LLPhant represent specialized layers (caching and agent frameworks respectively), while VLMEvalKit brings systematic evaluation methodology to the broader LLM application stack.

Resources and guides for crafting effective prompts for large language models like ChatGPT, Claude, and Gemini. This cluster spans educational materials (prompt engineering guides and collections), practical tools for prompt development and testing, and documentation of prompt patterns and techniques. Whether you're learning structured prompting methodologies or exploring real-world prompt examples and leaks, you'll find both foundational knowledge and implementation-focused projects here.