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Navveen Balani Making systems intelligent, efficient & responsible

🤖 Are you embarking on the journey to build your own large language…

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🤖 Are you embarking on the journey to build your own large language model (LLM) chatbot using your own content? Harness the power of Google’s Vertex AI Generative AI Studio and Lang Chain!

Google Vertex AI Generative AI Studio provides access to a suite of generative AI models. This tool enables you to test, fine-tune, and deploy these models, enhancing the performance of your AI applications.

One of the key features of Vertex AI is the Pathways Language Model API (PaLM API). The PaLM API provides access to Google’s LLMs, which can generate text and code in response to natural language prompts. These models are fine-tuned for a range of tasks, such as classification, summarization, entity extraction, multi-turn chat, semantic search, recommendation, classification, outlier detection, and code generation.

When dealing with large volumes of text, you can adopt various techniques to manage context effectively:
➢ Stuffing: A straightforward approach where the entire document is used as context. However, it can be inefficient for larger documents.
➢ Map-Reduce: This approach splits documents into smaller chunks and processes them in parallel, offering improved efficiency but with increased complexity.
➢ Refine: This technique involves running an initial prompt on a small chunk, generating an output, and refining the output based on new document content. It’s more efficient than Map-Reduce but less direct.
➢ Map-Reduce with Similarity search: This is the most complex yet efficient method. It involves creating embeddings of smaller chunks and conducting vector similarity searches to find relevant context.

LangChain, a Python package designed for natural language processing tasks, effectively uses these techniques for question-answering over large documents. By combining the capabilities of the Vertex AI PaLM API with LangChain, you can create an efficient, robust question-answering system capable of processing and extracting valuable information from extensive volumes of text.

Here is the Github Notebook that provides these details
https://lnkd.in/dUj_gYei

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