Gen AI bring us one step closer to this world — where we can express requirements in English, and use models to translate them to programs. When used as part of a program, they allow us to work with unstructured data, and provide a way to deal with uncertainty.
LLMS
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Prompt engineering test comparing Claude 3.5 Sonnet performance
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Latest findings? Claude sonnet 3.5 can’t do this… Prompt: 3 Result
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Testing Large Language Models with Specific Prompts
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I will share 3 prompts to test 3 giant LLMs with: Let me show you:
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Replacing Google Search with AI Tools
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Google search is dead. It's been 2 months since I last used Google for search. Instead, I've relied on ChatGPT, Claude, and Perplexity. Here's how I use AI for search:
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LLM Tips and Tutorials for Sharing Knowledge
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If you find this useful, RT to share it with your friends. Don't forget to follow me @Saboo_Shubham_ for more such LLMs tips and tutorials.
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Awesome LLM Apps with RAG and AI Agents on GitHub
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Find all the awesome LLM Apps demo with RAG and AI agents in the following Github Repo. P.S: Don't forget to star the repo to show your support
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Web Search Integration with Claude Sonnet 3.5
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5. Search the Web with the new Claude Sonnet 3.5 • Create a text input for the user to enter their query using 'st.text_input()'
• If a question is asked, run the assistant to get the answer and display it using 'st.write()' -
Build AI Assistant with Claude and DuckDuckGo Integration
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4. Create and Initialize the AI assistant • Create a text input to enter their Anthropic API key using 'st.text_input()'
• If the Anthropic API key is provided, create an instance of Assistant with claude sonnet 3.5 as LLM and DuckDuckGo as the tool. -
Essential Libraries for Building AI Agents with Streamlit
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2. Import necessary libraries • Streamlit for building the web app
• Phidata for building AI agents
• Anthropic for using Claude via API
• Duckduckgo for the search functionality