GitHub / easonlai / chatbot_with_pdf_streamlit
This code example shows how to make a chatbot for semantic search over documents using Streamlit, LangChain, and various vector databases. The chatbot lets users ask questions and get answers from a document collection. The code is in Python and can be customized for different scenarios and data.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/easonlai%2Fchatbot_with_pdf_streamlit
PURL: pkg:github/easonlai/chatbot_with_pdf_streamlit
étoiles: 15
forks: 5
issues ouvertes: 0
licence: None
langage: Jupyter Notebook
taille: 6,57 Mo
dépendances analysées: En attente
date de création: il y a presque 2 ans
date de mise à jour: il y a 10 mois
enregistré: il y a presque 2 ans
dernière synchronisation: il y a 3 mois
Sujets: azure, azure-cognitive-search, azure-openai, chroma, document-search, embedding-models, gpt-3, gpt-35-turbo, langchain, langchain-python, openai, pinecone, python, semantic-search, streamlit, vector-database, vector-search, vector-similarity