The difference between building LLM-powered applications in summer 2024 vs summer 2023?

powershell-agent-team.ps1

<#
    This PowerShell script is powered by my PSAI and PSAIAgent modules.
    PSAI - Is a port of the OpenAI Python SDK
    PSAIAgent - Is a PowerShell module that allows you turn an OpenAI LLM into an AI Assistant with memory and tools

    Register-Tool - Takes PowerShell functions signatures and creates the JSON to be used by OpenAI 

    New-Agent - Creates an AI Agent that can be used to interact with OpenAI
    Get-AgentResponse - Takes the agent and prompt, calls the OpenAI model, runs the functions if needed and returns the response
#>

$tools = $(
    Register-Tool Get-GHMetrics
    Register-Tool Invoke-WebSearch
)

$prompt = @"
Ragas
LangFuse
LangSmith-sdk
LangChain4j
Spring AI
DSPy

Find the github repos for each and the metrics, include date created in a table
In the intro, add a brief sentence describing each project
"@

$agent = New-Agent -ShowToolCalls -Tools $tools  -LLM (New-OpenAIChat 'gpt-4o') # Create a new agent and add the tools for capabilities
$agent | Get-AgentResponse $prompt

The prompt was inspired by this post from Marie-Alice BleteMarie-Alice Blete:

https://www.linkedin.com/posts/mblete_whats-the-big-difference-between-building-activity-7216426131741126656-eDXf?utm_source=share&utm_medium=member_desktop

Here is a brief description of each project along with their GitHub repository information and metrics in a table:

Project Descriptions

1. Ragas: A framework that helps evaluate Retrieval Augmented Generation (RAG) pipelines, enhancing the performance assessment of these LLM applications.
2. LangFuse: An open-source LLM engineering platform offering tools for observability, evaluation, prompt management, and more to simplify LLM engineering.
3. LangSmith-sdk: Client SDKs for interacting with the LangSmith platform, aiding teams in debugging, evaluating, and monitoring language models and intelligent agents.
4. LangChain4j: A Java library that integrates with major LLMs and vector stores to support building chatbots, assistants, and other LLM-powered applications.
5. Spring AI: An application framework for AI engineering that provides tools and APIs for integrating generative AI models into Java applications.
6. DSPy: A framework for algorithmically optimizing LM prompts and weights, particularly useful in complex systems requiring multiple LM usages within a pipeline.

Project Metrics

Project	GitHub Repository	Date Created	Stars	Forks	Issues	Pull Requests	Contributors	Commits	Last Commit
Ragas	Link	2023-05-08	5941	561	616	512	30	430	2024-07-29 06:53:41 AM
LangFuse	Link	2023-05-18	4960	449	447	1906	30	2251	2024-07-29 10:27:46 AM
LangSmith-sdk	Link	2023-05-30	359	60	200	655	27	1083	2024-07-26 07:54:10 PM
LangChain4j	Link	2023-06-20	4100	797	659	762	30	1034	2024-07-26 02:22:48 PM
Spring AI	Link	2023-06-27	2630	640	468	580	30	977	2024-07-27 09:42:00 PM
DSPy	Link	2023-01-09	14919	1145	627	642	30	2533	2024-07-26 07:01:05 PM

This table provides an overview of the key metrics for each project, highlighting their popularity, activity, and contributions.