Build an Advanced RAG Chatbot with Neo4j Knowledge Graph

Advanced RAG (Retrieval-Augmented Generation) and knowledge graphs make AI chatbots more powerful and context-aware. Your chatbot can digest more data sources than just one document. We feed the chatbot with different text data regarding the event of Sam Altman's surprising exit and return to OpenAI. This video walks you through how to build the system with LLM tools.

0:00 Intro
0:42 Load wiki articles
1:23 Load news data
1:46 Steps of entity and relationship extraction
2:04 What is spaCy-llm?
2:41 Why I chose spaCy-llm?
3:15 Summarize articles with LangChain
4:28 spaCy-llm for entities and relationships
5:55 GPT-4 refining results and cypher queries
6:40 Neo4j Knowledge graph + advanced RAG
7:24 Outro

What the video covers:

- Constructing a Neo4j knowledge graph with the help of spacy-llm for labeling entities and relationships.
- Building advanced RAG on top of knowledge graph.
- Besides chatting with the AI chatbot, interact with the graph interface on the Streamlit app.

Check out the full code here:
https://github.com/leannchen86/openai...

#generativeai #llm #neo4j #aichatbot #knowledgegraph #datascienceprojects


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