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AI project showcase. Which includes code examples of langchain, llamaindex utilizing streamlit.

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AI Project Showcase

This repository serves as a collection of various AI projects demonstrating different concepts and techniques. Each subdirectory contains a separate project with its own codebase, data (if applicable), and documentation.

Getting Started:

For each project, refer to the individual README.md file within the corresponding subdirectory for specific setup and usage instructions.

Subdirectories:

Simple - Just a plain LLM user must provide openai key.

Agent_with_tools - Agent using tools (Calculator, Wikipedia, Prompt template) to formulate an answer.

LLM_simple_RAG - plain LLM to chat with documents (PDF, DOCX and TXT). Application uses Chroma as a simple vector store.

autogen_blog_writer - Example to agentic AI with autogen.

AWS_bedrock_call_model - Example to call model from AWS bedrock.

Azure ai foundry - Function calls - is a pdf of how to setup and execute function calls within Azure foundry.

Azure ai foundry - RAG - is a pdf of how to setup and execute a RAG system within Azure foundry.

Azure ai foundry - Simple Chat Flow - Code for a simple chat model in ai studio/Foundry

Azure ai foundry - Prompty - Simple prompt that leverages your azure foundry endpoint and api key. Just modify the .env

Azure ai foundry - Private Endpoints - Directions on how to setup a private endpoint within azure foundry

Semantic Kernal Simple Agent - C# code that gives a simple agent. Please look at the timeplanner class. You will just need to add your endpoint, key and deployment. Please make sure the deployment is an LLM that supports agents.

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AI project showcase. Which includes code examples of langchain, llamaindex utilizing streamlit.

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