Article Details

Title · Authors · Abstract · Keywords · DOI · References

Design and Implementation of Knowledge Question Answering System for Python Based on LangChain

ZHANG Ning

(College of Computer Science and Technology, Taiyuan Normal University, Taiyuan 030619, China)

Section：Computer Technology · Vol. 2026, Issue 5 · Pages：66-70,77 · 2096-4706（2026）05-0066-06 · CLC number：TP311 · Document code：A · DOI：10.19850/j.cnki.2096-4706.2026.05.013

Abstract

The development and application of large models become a mainstream trend. As the core programming language for the development and application of large models, the importance of Python continues to increase. To help undergraduate students learn and master this programming language efficiently, this paper designs and implements an intelligent Question Answering agent system to assist students in learning. This system takes LangChain framework as the core, integrates the locally deployed DeepSeek large model, and combines the local knowledge vector database constructed by Chroma to complete the analysis and intelligent response to student questions. Meanwhile, Vue3 and FastAPI frameworks are adopted to develop Web applications, providing a simple and easy-to-use interactive page for students. The proposed implementation scheme has positive practical significance for the application of agent technology in undergraduate teaching of colleges and universities.

Keywords

LangChain; agent; vector database; retrieval-augmented generation; Large Language Model

References

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About the authors

Zhang Ning (1975.10-), male, Han ethnicity, from Dalian, Liaoning, lecturer, master's student, research direction: computer applications.