bhattbhavesh91 / pdf-q-a-llamaindex-llama2

Chat with your PDF files using LlamaIndex, Astra DB (Apache Cassandra), and Gradient's open-source models, including LLama2 and Streamlit, all designed for seamless interaction with PDF files.

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Build a PDF Document Question Answering System with Llama2, LlamaIndex

I'll walk you through the steps to create a powerful PDF Document-based Question Answering System using using Retrieval Augmented Generation. We'll harness the power of LlamaIndex, enhanced with the Llama2 model API using Gradient's LLM solution, seamlessly merge it with DataStax's Apache Cassandra as a vector database. This innovative blend unlocks exciting opportunities for immersive interactions with pdf documents through engaging conversations. Get ready to explore this cutting-edge technology!

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Chat with your PDF files using LlamaIndex, Astra DB (Apache Cassandra), and Gradient's open-source models, including LLama2 and Streamlit, all designed for seamless interaction with PDF files.

License:Apache License 2.0


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Language:Jupyter Notebook 78.2%Language:Python 21.8%