Row 7001

Row ID: 7001 | Dataset Entry | Axioma AXP Content Repository

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Hey r/MachineLearning, I published a new article where I built an observable semantic research paper application.

This is an extensive tutorial where I go in detail about:

1. Developing a RAG pipeline to process and retrieve the most relevant PDF documents from the arXiv API. 2. Developing a Chainlit driven web app with a Copilot for online paper retrieval. 3. Enhancing the app with LLM observability features from Literal AI.

You can read the article here: [https://medium.com/towards-data-science/building-an-observable-arxiv-rag-chatbot-with-langchain-chainlit-and-literal-ai-9c345fcd1cd8](https://medium.com/towards-data-science/building-an-observable-arxiv-rag-chatbot-with-langchain-chainlit-and-literal-ai-9c345fcd1cd8)

Code for the tutorial: [https://github.com/tahreemrasul/semantic\_research\_engine](https://github.com/tahreemrasul/semantic_research_engine)

FieldValue
text Hey r/MachineLearning, I published a new article where I built an observable semantic research paper application. This is an extensive tutorial where I go in detail about: 1. Developing a RAG pipeline to process and retrieve the most relevant PDF documents from the arXiv API. 2. Developing a Chainlit driven web app with a Copilot for online paper retrieval. 3. Enhancing the app with LLM observability features from Literal AI. You can read the article here: [https://medium.com/towards-data-sci…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-14
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Raw Record

{
  "text": "Hey r/MachineLearning, I published a new article where I built an observable semantic research paper application.\n\nThis is an extensive tutorial where I go in detail about:\n\n1. Developing a RAG pipeline to process and retrieve the most relevant PDF documents from the arXiv API.\n2. Developing a Chainlit driven web app with a Copilot for online paper retrieval.\n3. Enhancing the app with LLM observability features from Literal AI.\n\nYou can read the article here: [https://medium.com/towards-data-science/building-an-observable-arxiv-rag-chatbot-with-langchain-chainlit-and-literal-ai-9c345fcd1cd8](https://medium.com/towards-data-science/building-an-observable-arxiv-rag-chatbot-with-langchain-chainlit-and-literal-ai-9c345fcd1cd8)\n\nCode for the tutorial: [https://github.com/tahreemrasul/semantic\\_research\\_engine](https://github.com/tahreemrasul/semantic_research_engine)\n\n",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-14",
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}
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