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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CODE
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Installing Clarifai SDK, Llama-index, and Setting Up PAT
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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 Chat PDF Files GPT-4 Mini
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Build a LLM app with RAG to chat with PDF files using GPT-4 o mini in just 4 lines of Python code:
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Pgvector Now Faster than Pinecone at 75% Less Cost
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Pgvector Is Now Faster than Pinecone at 75% Less Cost https://
bit.ly/4cA1REU
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Cleaning Tables with Merged Cells for Data Processing
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Cleaning tables with merged cells https://
bit.ly/3W0t3p3 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Training AI Models: Data Assembly Challenges for News Organizations
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at this point the newspaper should train the model first. but even assembling the data seems next to impossible
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Picklescan open source security library gets new logo
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Picklescan (OS library for security scans of pickle files) has a new logo hat/tip Matthieu Maitre and @LucSGeorges GH repo: https://
github.com/mmaitre314/pic
klescan
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Google AI for Software Development at ICML2024
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Expo day at #ICML2024 continues with "AI for software development at Google" at 4pm CEST this afternoon in Hall A8. Learn how we improve developer productivity and satisfaction with AI-based assistance that ranges from code suggestions & review to bug management & planning.
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Arize Phoenix: LLM Monitoring with One Line of Code
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#solarllm @ArizePhoenix is amazing. Adding just one line can run a monitoring server:
ssession = px.launch_app() You can monitor the entire LLM-related input and output on a chain with one line:
LangChainInstrumentor().instrument() Check out the full example at the SolarLLM -
ArizePhoenix: One-Line LLM Monitoring and Chain Instrumentation
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@ArizePhoenix is amazing. Start the local monitoring server by running one line of code: ssession = px.launch_app() With just one line of code, you can monitor all input and output related to LLMs on the link chain:
LangChainInstrumentor().instrument() Check out the full