The Question Improver Agent This agent by @sockcymbal is an LLM-driven "tool for thought" designed to elevate the quality and depth of user-posed questions It won 1st place at the AI for Thought Hackathon at @AGIHouseSF It has some great prompts! https://
github.com/sockcymbal/Que
stionImprover
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@langchain
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Question Improver Agent: LLM-Driven Tool for Thought
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Can LLMs Replace Data Analysts Using Custom SQL Agents
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Can LLMs Replace Data Analysts? Getting Answers Using SQL This is an involved *31 minute read* on how to create a custom data science agent by Mariya Mansurova A great read for custom tools and custom agents (almost all production agents are custom) https://
towardsdatascience.com/can-llms-repla
ce-data-analysts-getting-answers-using-sql-8cf7da132259
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Build Full-Stack RAG App with TypeScript Tutorial
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Build a Full-Stack RAG App with TypeScript In our newest YouTube tutorial, @BraceSproul walks through how to build a RAG app from scratch This covers prompting, API server, databases, web client application and more By the end of this video, you’ll have a complete
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Open-Source TypeScript RAG Chatbot Builder Solution
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Open-Source RAG Chatbot Builder One of the most popular use cases for GPTs is uploading it some data and creating a chatbot over that data Did you know there's an open-source solution that can do the same thing built entirely in typescript? @dialoqbase by @n4ze3m Uses
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Evaluating RAG Pipelines with LangChain and RAGAS
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Evaluating RAG pipelines using LangChain and Ragas LangChain can help you build RAG pipelines, but how do you evaluate them? We have a great integration with RAGAS to do exactly that! h/t @DataScienceHarp for writing all about it Blog: https://
deci.ai/blog/evaluatin
g-rag-pipelines-using-langchain-and-ragas/
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Building RAGs with LangChain: Practical Tutorial
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Building your own RAGs with LangChain A practical tutorial from Madhav Thacker (Senior Data Scientist @Shopify
) on how to build your own RAGs with @langchain Thanks to our friends at @arizeai for organizing! YouTube: https://
youtube.com/watch?v=IUEny5
cbys8
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Multimodal RAG with LangChain and GPT-4 Vision Guide
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Multimodal RAG using Langchain Expression Language And GPT4-Vision Great guide from Plaban Nayak on multimodal RAG. We suspect this will become more and more popular – so now's a great time to become an expert! Blog: https://
medium.aiplanet.com/multimodal-rag
-using-langchain-expression-language-and-gpt4-vision-8a94c8b02d21
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Quivr: Local GenAI Second Brain with Llama2 and Docker
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Quivr: your GenAI 2nd Brain One of the most popular RAG apps out their is Quivr. Even better: it can be run completely locally Check out this awesome video by @mesudarshan on how to run it – Llama2 model with @OLLAMA – Uses @Docker & @supabase & @langchain – LangSmith for
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LangChain State of AI 2023: Year Review Trends
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As the year draws to a close, highlighting two pieces of content that really summed up 2023 for LangChain: LangChain State of AI 2023: highlighting all the trends in models, vectorstores, retrieval and evaluation that we saw over the past year https://
blog.langchain.dev/langchain-stat
e-of-ai-2023/
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Mixtral vs GPT-3.5: LangChain Integration Performance Comparison
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LangChain x Mixtral x TogetherAI This community blog post takes a deep dive into comparing Mixtral performance vs GPT-3.5 on 15 questions of reasoning, logic, and coding Great example of how to use it in LangChain via @togethercompute Blog: