As a full-stack developer, I successfully completed a project that revolutionizes data connection and document querying. This powerful tool incorporates various data connectors, including Discord, Twitter, Google Docs, Notion, epub, mbox, and more, enabling seamless import of raw data. By creating an index of the provided documents and implementing prompt engineering, users can ask specific questions about the content, even uploading complete books for chapter-based inquiries.
Key Features:
Extensive Data Connectors: The tool supports a wide range of data connectors, facilitating the import of raw data from platforms such as Discord, Twitter, Google Docs, Notion, and more.
Document Indexing: I implemented the functionality to create an index of documents from sources like Notion and Google Docs, allowing for efficient retrieval and querying.
Versatile Document Queries: Users can ask a variety of questions regarding the provided documents, including specific chapters from locally uploaded books like Harry Potter.
Prompt Engineering: Through prompt engineering techniques, the tool generates precise and tailored responses to user inquiries, ensuring accurate and relevant information retrieval.
Technologies Used:
Angular Web Framework: Leveraging the lightweight and flexible Angular framework, I built a user-friendly web-based UI for seamless interaction with the tool.
Python Flask Framework: I utilized the Python Flask framework to connect and import raw data from various sources, ensuring smooth data integration.
Database Storage: All generated outputs are efficiently stored in a database, facilitating easy retrieval and display within the UI.
Bullet Points:
Wide range of data connectors
Efficient document indexing
Versatile document queries
Precise prompt engineering
Angular web-based UI
Python Flask for data integration
Database storage for outputs