A personalized Chatbot for Ajman University related queries. The project revolves around one of LangChain's primary use cases: enabling conversational interactions based on a given document (Retrieval Augmented Generation). The chosen document is Ajman University's Student Handbook. Through a systematic process, the handbook's content is segmented into smaller units, which are then transformed into vectorized representations. This transformation enables information retrieval through similarity analysis (Similarity between the input vector and the vectors in the database is calculated based on their distance measurement - cosine distance is preferred).
In summary, this project showcases the integration of the LangChain framework and OpenAI's LLM API. It facilitates informative and contextually coherent conversations by utilizing the content of Ajman University's Student Handbook.
You need to have OpenAI's API key for successful functioning of the project, along with the student handbook that can be accessed from the files section.
For more information, visit the following link: https://python.langchain.com/docs/use_cases/question_answering/#quickstart