Building a Context-Aware Chatbot Using OpenAI, Pinecone and Vercel AI SDK

📖 Tutorials and walkthroughs; Building AI powered apps

Building a Context-Aware Chatbot Using OpenAI, Pinecone and Vercel AI SDK
In this post from the Pinecone blog, you are lead through building a full-stack js application that creates a context-aware chatbot leveraging Retrieval Augmented Generation (RAG). You'll use the powerful Vercel AI SDK in our Next.js app alongside the Pinecone search API and OpenAI API.

Building personal LLM powered translation tool
In this post Geoffrey Litt shows how he used GPT-4 to build a quick GUI app that translates English text messages to Japanese. Geoffrey had been using ChatGPT for the translations, but found that a custom GUI worked better for my needs.

Building a Meeting Minutes Summarizer
In this tutorial from OpenAI, learn to leverage OpenAI's Whisper and GPT-4 models to develop an automated meeting minutes generator. The tool can reduce an hour long meeting recording into a 2 or 3 minute summary highlighting the key takeaways and next steps.

Automated Web Research with LangChain's Retriever
In this LangChain blog post they talk through the motivations for creating an AI retriever that aims to automate web research. Originally intending to build a web research agent, the team found that a simpler, easily-configurable retriever was more effective. The retriever uses a language model to generate search queries, execute multiple searches in parallel, scrapes pages, indexes documents, and retrieves the most relevant ones.

🧰 Tools for AI app builders

Experiment with models, prompts, and vector databases in just a few lines of code
Hegel AI is an open source tool that aims to help developers test, compare and evaluate large language models like GPT-4 with just a few lines of code.
This is useful for tasks like:

• Monitoring language models for regressions

• Auditing models for safety issues

• Comparing performance of vector databases

Hegel AI handles the infrastructure, allowing easy setup of experiments in notebooks and test suites.

Highly performant, open source vector database
Qdrant is an open source vector data store written in Rust. Accessible by a REST or gRPC interface with clients available in most mainstream languages. Can be hosted locally or via Qdrant’s cloud service.

Open-source Copilot alternative available as a self-hosted or cloud
Refact is an open source AI code assistant with autocompletion, chat features and fine-tuning powered by contrast.code and starchat models. Its fine-tuning feature lets you optimize models for your own codebase, making suggestions even more relevant. Run it self-hosted in Docker or install extensions for VS Code or JetBrains IDEs.

Hugging Face’s Text Generation Inference
Hugging Face’s Text Generation Inference is an open-source solution for deploying and serving Large Language Models (LLMs). It enables high-performance text generation using Tensor Parallelism and dynamic batching for popular LLMs, including StarCoder, BLOOM, GPT-NeoX, Llama, and T5. It is already used by customers such as IBM and Grammarly.

A developer’s guide to prompt engineering and LLMs
The article gives an overview of how generative AI models like LLMs work and how developers can use prompt engineering to fine tune them for their applications. The author walks through the example of building an IT support chatbot before diving into GitHub Copilot's prompt engineering pipeline. Developers interested in leveraging LLMs for their projects can learn from GitHub Copilot's systematic approach to prompt engineering and adapting it for their use cases.

Autochain Speeds Building Generative Agents
AutoChain simplifies the process of building custom generative agents using large language models. Overall, the goal of AutoChain appears to be enabling developers to rapidly iterate on generative agents by both simplifying agent customization and accelerating evaluation of different use cases. Agents can be built with two layers of abstraction: the LLMs and added custom tools. Additionally, the framework aims to automatically evaluate agents through simulated multi-turn conversations which test different user scenarios.

VectorAdmin - Full Control Over Your Embeddings
VectorAdmin is a general admin UI designed to give you advanced management of your vector-embedded data. It aims to provide the database management controls you would expect for traditional databases, but for your embeddings.

📰 Generative AI news and trends

PhotoGuard: Protecting Your Pictures from AI Manipulation Estimated
Researchers at MIT have created a new tool called PhotoGuard that can protect your pictures from AI manipulation. It works by altering photos in tiny ways that are invisible to the human eye but prevent them from being manipulated. If someone tries to use an editing app based on a generative AI model to manipulate an image that has been “immunized” by PhotoGuard, the result will look unrealistic or warped.

Generative AI and the Future of Work in America Estimated
A special report by McKinsey Global Institute on Generative AI and the future of work in America reveals that by 2030, activities that account for up to 30% of hours currently worked across the US economy could be automated. However, generative AI is more likely to enhance the way STEM, creative, and business and legal professionals work rather than eliminate a significant number of jobs outright.

EU AI Act Considerations for Open ML Developers
The EU AI Act will shape how AI development interacts with democratic values, and how society is impacted. Hugging Face and partners make recommendations to support open and transparent ML innovation, while upholding the AI Act's goals.

🎓 Courses

Create AI Apps to Demonstrate Models in Just 1 Hour
[course: 1hr]
Want a quick way to create user interfaces for your machine learning projects? This short course from DeepLearning.AI teaches you how to use Gradio, an open source library, to create interactive apps and demos in just 1 hour.

Master Evaluating & Debugging Generative AI
[course: 1hr]
I recently came across a fantastic short course on "Evaluating and Debugging Generative AI" by DeepLearning.AI. It teaches how to evaluate programs using LLMs and generative image models with platform-independent tools. You'll learn to instrument a training notebook, add tracking, versioning, and logging, and implement monitoring and tracing of LLMs over time in complex interactions. A must-try for any developer looking to level up their AI skills!

⌨️ Put down the keyboard

Interview with Codeium
[listen: 40min]
Codeium, an AI startup, aims to boost developer productivity with its AI-powered code acceleration toolkit. It features autocomplete, chat, and search functions. The company’s CEO and head of business discussed the future of software development with AI on NVIDIA’s AI Podcast.