Hello to our LangChain enthusiasts!
As we bid farewell to summer, the energy in the tech sphere is palpable! Projects are springing back to life, and the air is thick with innovation. Grab your favorite autumn drink, and let's catch up on all the thrilling updates that came our way.
Projects
Rivet is an IDE for creating complex AI agents and prompt chaining, and embedding it in your application.
AgentVerse is a flexible framework that simplifies building custom multi-agent environments for large language models (LLMs).
Langstream build and run event-driven Gen AI applications
GitWit is a container-based agent specialized in making useful commits to git repositories.
RestGPT is an LLM-based autonomous agent that can control applications via RESTful APIs
Magentic seamlessly integrate LLMs as Python functions
Promptfoo test your prompts. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality.
Videos
Superagent is a platform dedicated to the development and management of LLM agents, and this webinar delves into the technology that powers it.
James Briggs demonstrates building a chatbot using Retrieval Augmented Generation (RAG) with OpenAI's gpt-3.5-turbo
Hosted by Kelvin Lawerence, this session simplified the use of graphs with Amazon Neptune through Langchain and LLMs.
Articles
The new OpenAI GPT-4V model, short for GPT-4 with vision, allows users to instruct GPT-4 to analyze image inputs, marking a significant stride in AI research by incorporating additional modalities like images into large language models (LLMs). Read the full system card here.
Molly Cantillon for Langchain, demonstrates building a chatbot named Chat LangChain, which provides information about LangChain by indexing and navigating through the Python documentation and API reference, while also delving into its architectural framework. Link to the tutorial here.
Cloudflare published a tutorial on utilizing Langchain and Pinecone to index a Notion workspace, and on developing a custom ChatGPT plugin with Cloudflare Workers for querying purposes. You can read the tutorial here.
AutoGen from Microsoft streamlines the orchestration of large language model (LLM)-based workflows. Through customizable agents, it fosters a collaborative space among LLMs, tools, and humans to efficiently address complex tasks. This development heralds a new era in AI, with more robust and automated LLM applications. Explore the full insight into AutoGen's potential here.
Delve into Fine-tuning GPT-3.5-Turbo to efficiently convert natural language queries into SQL. Read the article here.
OpenAI released a guide for teachers about ChatGPT, including suggested prompts. Read it here.
This article analyzes how users are using ChatGPT including prompt types and commonly used words. Read it here.
The article explores improving Large Language Models (LLMs) performance through dataset-centric fine-tuning. Read it here.
That’s all for this month!
Thank you for being a part of this continuously evolving journey with LangChain! Your passion and backing truly illuminate our community. If this issue struck a chord with you, please share it with others. Together, we only get stronger!
If you believe something was overlooked or have a project in mind, please feel free to connect with us on our GitHub repository or at awesomelangchain[at]kyrolabs.com. We are eager to hear your thoughts.
Stay incredible, and see you in the next update!
This newsletter is crafted with love by the Kyrolabs team.
PS: At Kyrolabs, we are looking for individuals who are enthusiastic about AI Agents and LangChain. If you're keen on embarking on this exhilarating adventure with us, send us a note at contact[at]kyrolabs.com, sharing your interest in AI Agents and background.
Please note that we are not affiliated with the products or services mentioned in this update.