Research and developing a system driven by a Large Language Model for extracting information from various company knowledge bases. The focus will be in the implementation of a RAG pipeline (Retrieve and generate) that supports information retrieval from both text documents and structured databases. The output will be provided to users through two experimental interfaces: a simple chat web app, an integration with the Outlook API. Responses will differentiated based on the requesting user, considering the required technical depth and information access permissions.
Research and developing a system driven by a Large Language Model for extracting information from various company knowledge bases. The focus will be in the implementation of a RAG pipeline (Retrieve and generate) that supports information retrieval from both text documents and structured databases. The output will be provided to users through two experimental interfaces: a simple chat web app, an integration with the Outlook API. Responses will differentiated based on the requesting user, considering the required technical depth and information access permissions.
GenAI chatbot for querying company's resources
HASSEN, HANEN
2023/2024
Abstract
Research and developing a system driven by a Large Language Model for extracting information from various company knowledge bases. The focus will be in the implementation of a RAG pipeline (Retrieve and generate) that supports information retrieval from both text documents and structured databases. The output will be provided to users through two experimental interfaces: a simple chat web app, an integration with the Outlook API. Responses will differentiated based on the requesting user, considering the required technical depth and information access permissions.File | Dimensione | Formato | |
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Hanen_Hassen.pdf
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https://hdl.handle.net/20.500.12608/73138