Build a LLM app with RAG to chat with PDF files using the latest Claude 3.5 Sonnet in just 4 lines of Python code (step-by-step guide):
@sumanth_077
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Daily Content Sharing on Python Data Science and Machine Learning
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That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Chat with Your Data: Summarizing PDF Files in App
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Step 4: Chat with your data Finally, once the data has been ingested into the app, chat with your data. Here we are asking it to summarize the pdf file.
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Upload PDF Research Paper Data to Clarifai Vector Database
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Step 3: Upload the data, Here we are uploading the pdf file of a research paper. Once you upload the data, it will embed and index the data into your Clarifai app. Clarifai Apps acts as your vector database.
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Setting up RAG system with Clarifai and Gemini-1.5 Flash model
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Step 2: Next, import the RAG class and set up the RAG system by passing your Clarifai user ID and the Gemini-1.5 Flash model URL from the Clarifai community. You can find it here: http://
clarifai.com/gcp/generate/m
odels/gemini-1_5-flash
… Once you sign up, you can find your user ID here: -
Install Clarifai SDK Llama-index Setup Guide Instructions
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Step 1: Install the Clarifai Python SDK, Llama-index, and set your Clarifai Personal Access Token as an environment variable. Sign up for the platform, and you can access the PAT here: https://
clarifai.com/settings/secur
ity
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Build RAG System in 4 Lines Using Clarifai SDK
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You can build a RAG system with just 4 lines of code using @clarifai Python SDK. Below is the entire code. Let's look at it step by step:
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Build RAG LLM App Chat PDF Files Gemini Flash
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Build a LLM app with RAG to chat with PDF files using Gemini Flash in just 4 lines of Python code (step-by-step instructions):
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Daily Content Sharing on Python, Data Science, and Machine Learning
By
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That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Implementing PCA Transform and Inverse Transform Methods
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Now define the "transform" method that transforms the input data into a lower-dimensional representation using the calculated eigenvectors. Finally the "inverse_transform" method to reconstructs the reduced data back to the original space using eigenvectors and mean.