Microsoft launched the best course on Generative AI! The free 18 lesson course is available on Github and will teach you everything you need to know to start building Generative AI applications.
@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 Applications
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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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Uploading PDF Research Papers 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 GPT-4o 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 GPT-4o(omni) model URL from the Clarifai community. You can find it here: https://
clarifai.com/openai/chat-co
mpletion/models/gpt-4o
… Once you sign up, you can find your user ID here: https://
clarifai.com/settings -
Install Clarifai SDK Llama-index Setup Guide
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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 with 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 LLM RAG App to Chat with PDFs Using GPT-4 Omni
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Build a LLM app with RAG to chat with PDF files using GPT-4 o (omni) 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
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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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Predict Method Implementation with Binary Classification Threshold
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Finally the predict method: It uses the trained model to make predictions based on input features. This method applies a threshold of 0.5 to make binary predictions, returning 1 for positive class predictions and 0 for negative class predictions.