Notebook examples for using OpenAI's Assistants API with the file search (knowledge retrieval) functionality.
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Updated
Sep 13, 2024 - Jupyter Notebook
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knowledge-retrieval
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🚀 Revolutionize your data interaction with a cutting-edge chatbot built on Retrieval-Augmented Generation (RAG) and OpenAI’s GPT-4. Upload documents, create custom knowledge bases, and get precise, contextual answers. Ideal for research, business operations, customer support, and more!
natural-language-processing
openai
semantic-search
knowledge-management
document-processing
rag
pdf-search
vector-database
ai-chatbot
gpt-4
azure-openai
retrieval-augmented-generation
knowledge-retrieval
document-chatbot
ai-powered-chatbot
machine-learning-chatbot
custom-knowledge-base
research-chatbot
business-chatbot
customer-support-chatbot
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Updated
Sep 11, 2024 - HTML
An end-to-end multi-source knowledge retrieval system using LangChain, FAISS, and OpenAI embeddings. This Retrieval-Augmented Generation (RAG) pipeline intelligently searches across Wikipedia, arXiv, and custom websites, optimizing source selection and delivering precise, real-time results based on query relevance.
python
machine-learning
natural-language-processing
information-retrieval
semantic-search
document-search
faiss
ai-pipeline
langchain
retrieval-augmented-generation
openai-embeddings
langchain-tools
knowledge-retrieval
multi-source-retrieval
langchain-agents
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Updated
Nov 3, 2024 - Jupyter Notebook
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