Chat2Graph integrates with the TuGraph graph database to deliver a conversational interface for graph data exploration. Through pre-built connectors and a prompt-engineering layer, it translates user intents into valid graph queries, handles schema discovery, suggests optimizations, and executes queries in real time. Results can be rendered as tables, JSON, or network visualizations via a web UI. Developers can customize prompt templates, integrate custom plugins, or embed Chat2Graph in Python applications. It's ideal for rapid prototyping of graph-powered applications and enables domain experts to analyze relationships in social networks, recommendation systems, and knowledge graphs without writing manual Cypher syntax.

Airtest is an advanced automation framework designed for UI testing of games and applications. It provides a platform-independent API which enables developers to create test scripts that work on various operating systems and devices, such as Windows, Android, iOS, and others. With features like visual testing, it minimizes the effort required for test creation. Airtest supports integration with popular programming languages like Python and can automate interactions with UI elements easily, making it a go-to solution for developers seeking to enhance their testing processes and ensure consistent application performance.

Chainlit is an open-source async Python framework designed to help developers build and deploy scalable Conversational AI and agentic applications rapidly. It supports integrations with popular Python libraries and frameworks to provide a seamless development experience. With Chainlit, users can create production-ready chat applications that can handle complex interactions and retain conversational context.

ChatTTS is a generative speech model specifically optimized for dialogue-driven applications. Leveraging advanced neural architectures, it produces natural and expressive speech with controllable prosody and speaker similarity. Users can specify speaker identities, adjust speaking rate and pitch, and fine-tune emotional tone to match diverse conversational contexts. The model is open-source and hosted on Hugging Face, enabling seamless integration via Python APIs or direct model inference in local environments. ChatTTS supports real-time synthesis, batch processing, and multi-lingual capabilities, making it suitable for chatbots, virtual assistants, interactive storytelling, and accessibility tools that require dynamic, human-like voice interactions.