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metadata
title: Publisher Chatbot 50k
emoji: πŸ“ˆ
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 4.31.5
app_file: rag.py
pinned: false

Steps for running rag -:

  1. Create .env file in root folder and add the following environment variables
OPENAI_API_KEY=<YOUR OPENAI KEY>
  1. Run the following commands:
    pip3 install -r requirements.txt
    python3 rag.py

Neo4j RAG course - https://www.deeplearning.ai/short-courses/knowledge-graphs-rag/

  1. langchain documentation retreiver - https://python.langchain.com/v0.1/docs/modules/data_connection/retrievers/vectorstore/
  2. https://medium.com/@shaktikanungo2019/3. conversational-ai-unveiling-the-first-rag-chatbot-with-langchain-8b9b04ee4b63
  3. https://medium.com/@vikrambhat2/building-a-rag-system-and-conversational-chatbot-with-custom-data-793e9617a865
  4. https://abvijaykumar.medium.com/retrieval-augmented-generation-rag-with-llamaindex-1828ef80314c
  5. https://medium.com/the-ai-forum/implementing-agentic-rag-using-langchain-b22af7f6a3b5