Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support
GENERATIVE AI
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Full RAG Application Code Chat Research Papers
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Full RAG Application code to chat with research papers
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Chat Interface for Research Papers Query System
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5. Chat with Research papers • 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()' -
Building AI Assistant with OpenAI API and ArxivToolkit
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4. Create and Initialize the AI assistant • Create a text input to enter their OpenAI API key using 'st.text_input()'
• If the OpenAI API key is provided, create an instance of Assistant with gpt-40 as LLM and ArxivToolkit as the tool. -
Building AI Agents with Streamlit Phidata and GPT-4o
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2. Import necessary libraries • Streamlit for building the web app
• Phidata for building AI agents
• OpenAI for using the gpt-4o
• arXiv to access the research papers -
Build AI Research Assistant with GPT-4o in 15 Python Lines
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Build an AI Research Assistant with GPT-4o in just 15 lines of Python Code (step-by-step instructions):
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Anthropic Model to Surpass GPT-4o Claims Analyst
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GPT-4o is not gonna replace humans. On the other hand, humans are gonna replace gpt-4o with a far better model coming from @AnthropicAI
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Government AI Training Data Collection and Privacy Concerns
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uncle sama wants you (as training data)
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Learn Any API Fast Using AI and Rapid Prototyping
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1) copy paste get started page from documentation (of any API you want to learn) into ChatGPT (or other AI) and ask it to describe.
2) ask it to come up with 10 distinct project ideas that leverage the API
3) pick one and ask it to prototype
4) copy/paste into Replit > run > -
Gen AI Unlocks Unstructured Data Processing Without Specialized Training
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Making use of unstructured data is one of the biggest unlock with Gen AI. We used to need to train very specific models – eg models specialized just on name recognition. Today, that’s just a prompt away. However, getting the data to the models in the right format, and then