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--- |
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title: Publisher Chatbot 50k |
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emoji: π |
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colorFrom: purple |
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colorTo: blue |
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sdk: gradio |
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sdk_version: 4.31.5 |
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app_file: rag.py |
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pinned: false |
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--- |
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## Steps for running rag -: |
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1. Create .env file in root folder and add the following environment variables |
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``` |
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OPENAI_API_KEY=<YOUR OPENAI KEY> |
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``` |
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2. Run the following commands: |
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``` |
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pip3 install -r requirements.txt |
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python3 rag.py |
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``` |
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Neo4j RAG course - https://www.deeplearning.ai/short-courses/knowledge-graphs-rag/ |
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1. langchain documentation retreiver - https://python.langchain.com/v0.1/docs/modules/data_connection/retrievers/vectorstore/ |
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2. https://medium.com/@shaktikanungo2019/3. conversational-ai-unveiling-the-first-rag-chatbot-with-langchain-8b9b04ee4b63 |
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3. https://medium.com/@vikrambhat2/building-a-rag-system-and-conversational-chatbot-with-custom-data-793e9617a865 |
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4. https://abvijaykumar.medium.com/retrieval-augmented-generation-rag-with-llamaindex-1828ef80314c |
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5. https://medium.com/the-ai-forum/implementing-agentic-rag-using-langchain-b22af7f6a3b5 |
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