Welcome to the sweet and accessible world of Artificial Intelligence! At LokumAI, we develop open-source tools and projects that empower developers to build powerful, user-friendly, and cutting-edge AI applications.
🚀 Browse Our Projects | 👥 Our Team | 💼 LinkedIn | 🤗 Hugging Face
At LokumAI, we aim to make modern AI solutions accessible to everyone. Our primary focus is on:
- 🤖 Intelligent Chatbot Infrastructure: Building robust, flexible, and OpenAI-compatible backend APIs and user interfaces.
- 🧠 Leveraging Large Language Models (LLMs): Harnessing the power of LLMs for various applications, from conversational AI to complex reasoning.
- 🛠️ AI Agents & Agentic AI: Developing systems where AI agents can autonomously perform tasks and make decisions.
- 🔄 Model Context Protocol (MCP) & MCP-Adapters: Standardizing context and data flow between AI models with MCP, and building adapters for seamless integration.
- 🔍 Retrieval Augmented Generation (RAG): Enhancing LLM responses by dynamically retrieving and incorporating information from external knowledge bases.
- 🔗 Embeddings & Vector Databases (VectorDB): Utilizing embeddings for semantic search and similarity, powered by efficient vector databases.
- 🌐 Open-Source First: Committing to open-source principles to foster collaboration and innovation.
- 🐍 Python & FastAPI-centric Backends: Crafting high-performance and modern APIs.
- ✨ Modern Frontend Technologies: Delivering interactive and fluid user experiences with React and Next.js.
- 💾 Data Persistence: Working with robust databases like Postgres and MongoDB.
- 🤗 Hugging Face Ecosystem: Integrating with and contributing to the rich Hugging Face ecosystem of models and tools.
Here are some of our key projects:
1. 💬 talkto-api
An OpenAI-compatible chatbot backend API with AgenticAI capabilities, built with Python and FastAPI, adhering to OpenAPI standards. Enables easy creation of intelligent assistants and conversational applications.
- Technologies: Python, FastAPI, OpenAI Compatible, OpenAPI Standard, AgenticAI
- Purpose: To rapidly deploy advanced chatbot backends in a standardized way.
2. 🎨 talkto-ai
A modern chatbot UI developed with React and Next.js, designed to integrate seamlessly with talkto-api or similar OpenAI-compatible backends.
- Technologies: React, Next.js, TypeScript
- Purpose: To provide a user-friendly and customizable chatbot experience.
3. 🔌 mcp-client
A client/host application for Model Context Protocol (MCP) servers, often generated by tools like Gradio UI and LangChain/LangGraph. Bridge different AI models and services efficiently.
- Technologies: Python, Gradio, LangChain, LangGraph, MCP
- Purpose: To easily test and utilize MCP-based AI services.
4. 🗄️ query-mcp-server
An AI server built with FastAPI that translates natural language queries into SQL using the Model Context Protocol (MCP). Interact with your databases by talking to them!
- Technologies: Python, FastAPI, MCP, SQL
- Purpose: To simplify data analysis and querying processes using natural language.
A ready-to-use FastAPI-based template to kickstart your own OpenAI-compatible chatbot backend, accelerating development.
- Technologies: Python, FastAPI, OpenAI Compatible
- Purpose: To offer developers a solid starting point for their chatbot backend projects.
Want to contribute to LokumAI, share your ideas, or learn more about our projects?
- ⭐ Star our repositories!
- 🐞 Open Issues to report bugs or suggest new features.
- 🛠️ Submit Pull Requests with your code contributions.
- 🗣️ Join Discussions related to our projects (via the "Discussions" tab in relevant repositories).
Let's make AI "sweeter" together! 🍬
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