Learn autoflow
Learn how to use autoflow with Shoulder.dev
Knowledge Graph Creation and Management
Understanding the underlying structure of the knowledge graph and how data is organized. Methods for adding, editing, and updating information within the graph. Importance of ensuring accuracy and consistency of data. Techniques for leveraging the knowledge graph for query answering and knowledge discovery.
Understanding the user experience of the conversational search interface. How the system interprets and responds to user queries. Capabilities of the search engine in handling complex questions and natural language. Exploring the integration of external data sources and the ability to customize the search experience.
Website Crawler and Data Acquisition
Understanding the process of crawling and indexing websites. Methods for identifying relevant and high-quality content to include in the knowledge graph. Techniques for handling different website structures and formats. Managing data extraction, cleaning, and transformation.
Understanding the role of LlamaIndex in the system. How the RAG framework processes user queries and retrieves relevant information from the knowledge graph. Techniques for generating coherent and informative responses. Exploring the customization options for fine-tuning the RAG framework.
Embedding and Vector Similarity Search
Understanding the concept of vector embeddings and how they are used for semantic similarity search. How the system creates embeddings for data within the knowledge graph. Understanding the algorithms used for finding similar concepts and relationships in the graph.
Understanding the purpose and functionality of the embeddable JavaScript widget. How the widget interacts with the backend system to provide conversational search capabilities. Integration techniques for embedding the widget into different web applications.
Understanding the architectural design of the system and its ability to handle large amounts of data and traffic. Exploring the performance characteristics of the underlying components. Identifying potential performance bottlenecks and optimization strategies.
Understanding the options for deploying the autoflow system. Configuring the system to meet specific requirements and integrate with existing infrastructure. Managing the system’s lifecycle, including updates and maintenance.
Learn the codebase to contribute to autoflow
