Check the Hugging Face space here
The world of Harry Potter is filled with captivating stories, intricate details, and a vast array of characters and events. PotterQuest offers a streamlined approach to explore and uncover the secrets hidden within the Harry Potter series. It aims to provide users with a comprehensive and efficient tool for answering Harry Potter-related questions using a single-line response. By leveraging the power of the open-source Large Language Model and a vector database, PotterQuest extracts answers from the rich content of the Harry Potter books. It has achieved impressive results without relying on any fancy external APIs. With a single-line answer, users can quickly find relevant information for their queries, allowing them to delve deeper into the magical universe created by J.K. Rowling. The project utilizes the Gradio framework to provide a user-friendly frontend for easy interaction.
- Develop a question-answering system specifically tailored to Harry Potter-related queries.
- Provide users with an intuitive interface to input questions and receive concise answers.
- Optimize the system to achieve accurate and relevant responses while maintaining efficiency.
- Utilize open-source resources and Langchain, to avoid reliance on external APIs.
The text version Harry Potter books undergo standard preprocessing techniques to prepare them for conversion into a vector database. This step ensures that the text is cleaned and formatted appropriately.
The preprocessed Harry Potter books are transformed into a vector database. This process involves encoding the textual information into numerical vectors using the open-source Hugging Face embedding model. By representing the books in vector form, efficient retrieval of relevant information becomes possible.
LangChain, a powerful language processing framework, is employed for question-answering against the vector database created in the previous step. The google/flan-ul2 model is used to power this step. Users can pose their queries related to the Harry Potter universe, and LangChain will search the vector database to extract concise, one-line answers.
To enhance the user experience and facilitate interaction, the project utilizes the Gradio framework. Gradio provides an intuitive frontend where users can input their questions and receive instant answers in a user-friendly format. The integration of Gradio ensures a seamless and accessible experience for users of the PotterQuest system.
The PotterQuest project successfully creates a powerful and efficient tool for exploring the magical world of Harry Potter. By leveraging open-source Hugging Face models and implementing a vector database with Langchain, PotterQuest provides users with single-line answers to their Harry Potter-related questions. PotterQuest is an excellent example of how open-source technology can be used to solve complex problems. With its streamlined approach and comprehensive coverage of the books, PotterQuest aims to be the go-to encyclopaedia for all fans of the Harry Potter series, offering quick and accurate insights into its secrets and intricacies without the need for a fancy API.