Awesome AI Agents › Low-Code/No-Code Platforms
LLMStack is a no-code multi-agent framework designed to enable users to build generative AI agents, workflows, and applications tailored to their specific needs without requiring any coding skills. It allows chaining multiple large language models (LLMs) to create complex AI-driven solutions that can integrate seamlessly with users' own data, internal tools, and GPT-powered models. The platform supports importing various data types such as CSV, TXT, PDF, DOCX, and PPTX from multiple sources including Google Drive, Notion, websites, and direct uploads. It handles data preprocessing and vectorization automatically, storing the processed data in an integrated vector database. LLMStack offers a no-code builder interface that simplifies the creation of AI chains, enabling users to connect multiple LLMs and link them to their business processes and data. The framework supports deployment both on the cloud and on-premise, providing flexibility for different organizational needs. Additionally, applications and chatbots built with LLMStack can be accessed via HTTP APIs and triggered from popular communication platforms like Slack and Discord. The platform is multi-tenant, allowing the creation of multiple organizations with user access control to ensure data and AI chains are only accessible within the respective organizations. LLMStack is suitable for building a wide range of generative AI applications including AI Sales Development Representatives (SDRs) for personalized outreach, AI Research Analysts for generating reports and investment theses, Robotic Process Automation (RPA) automations for business process automation, text generation apps for marketing content, chatbots trained on custom data, multimedia generation applications, conversational AI systems, search augmentation tools, and bots for Discord and Slack. LLMStack is supported by comprehensive documentation, a quickstart guide, and a development guide. It also offers a cloud service called Promptly for users who prefer a hosted solution. The project encourages community contributions and provides an admin panel for managing users and organizations.
https://github.com/trypromptly/LLMStack
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