Auth Layer for AI Agents

Today’s top AI Highlights:

1. This SDK makes your AI agents handle multi-service auth in 15 lines of code

2. Opensource package to switch between LLMs with one line of code

3. For the first time, you can run Qwen2-Audio on your device

4. LangChain’s AI agent to build and optimize your prompts

5. AI frontend pair programmer that turns your ideas into production-ready code

& so much more!

Read time: 3 mins

AI Tutorials

A ChatGPT-like assistant that runs entirely offline and recalls past conversations—an AI that learns from each chat and personalizes its responses, all without any internet dependency. Giving this kind of control to users is a powerful way to make AI both secure and adaptable for private use cases.

In this tutorial, we’ll build a local ChatGPT clone using Llama 3.1 8B with a memory feature, making it capable of recalling past conversations. All components, from the language model to memory and vector storage, will run on your local machine

We share hands-on tutorials like this 2-3 times a week, designed to help you stay ahead in the world of AI. If you're serious about levelling up your AI skills and staying ahead of the curve, subscribe now and be the first to access our latest tutorials.

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Latest Developments

AI Agents Get Their Own Authentication Layer 🔐

Building AI agents should be about writing great code, not wrestling with auth flows. But when your agent needs to work with multiple services, you're suddenly juggling OAuth flows, API keys, and JWT tokens - each service with its own authentication maze.

Composio has launched AgentAuth, a dedicated authentication solution that streamlines how AI agents connect with third-party services. The platform manages complex authentication flows across 250+ applications, eliminating the need for developers to handle OAuth, API keys, and token refresh mechanisms manually. Built specifically for AI agent development, AgentAuth integrates with major frameworks like LangChain, LlamaIndex, and CrewAI.

Key Highlights:

1. Developer-First Implementation - Single SDK handles all auth flows with pre-built configurations for 250+ apps - implement authentication in under 15 lines of code with built-in token refresh and error handling. Includes comprehensive webhook support for real-time connection monitoring.

2. Framework Compatibility - Compatible with 15+ agent frameworks including LangChain, LlamaIndex, and CrewAI. Developers can use existing agent code without modifications - AgentAuth seamlessly handles the authentication layer while maintaining framework-native syntax.

3. Authentication Management - Manage all your agent's authentication needs through a single dashboard, streamlining oversight and troubleshooting of connections.

4. Deployment Options - Choose between self-hosting for maximum control or a managed solution for ease of use, fitting diverse deployment needs.

One Python Package Handles All Your LLM API Calls 🧳

Andrew Ng has released aisuite, a Python package that makes working with multiple LLM providers much simpler through a unified interface. If you've ever dealt with juggling different APIs while testing various models, this open-source tool helps streamline that process - just change a single string to swap between GPT-4, Claude, Llama, or other models.

The package handles all the provider-specific requirements behind the scenes and currently supports OpenAI, Anthropic, Azure, Google, AWS, Groq, Mistral, HuggingFace, and Ollama, with more on the way. Built as a thin wrapper around existing Python client libraries, it maintains high performance while making it easier to develop and test across different providers.

Key Highlights:

1. Smooth model switching - Switch between any supported model by changing just the model string (e.g., 'openai:gpt-4o' to 'anthropic:claude-3-5-sonnet') while keeping the rest of your code identical - particularly useful when benchmarking different models or implementing fallbacks.

2. Granular installation options - Install only the dependencies you need with targeted pip commands - use 'pip install aisuite' for the base package, 'pip install aisuite[anthropic]' for specific provider support, or 'pip install aisuite[all]' for full functionality across all providers.

3. Developer-friendly architecture - Implements a convention-based approach for provider modules, making it straightforward to add support for new LLM providers - each provider requires just one implementation file following a standard naming pattern in the providers directory.

4. Production-ready stability - Uses either HTTP endpoints or official SDKs for API calls, ensuring reliable production deployment while maintaining consistent error handling and response formatting across different providers.

Quick Bites

You can now run Qwen2-Audio multimodal model locally on your device using the Nexa SDK. Just install the SDK and use the nexa run qwen2audio command to start experimenting with speech processing, translation, and more – all with quantized versions optimized for edge deployment.

Ollama’s new version 0.4 now lets you easily provide your Python functions as tools for Ollama to use, letting the model call them as needed. Plus, enjoy full typing support and check out the updated examples on GitHub to get started quickly.

Cursor has removed its long context mode, including the popular claude-3.5-200k in the new 0.43 version released recently. Cursor is however hinting at a shift towards an agent-based approach for potentially better context handling.

Jina AI released jina-clip-v2, a 0.9B parameter multimodal embedding model that supports 89 languages and higher image resolution (512x512). Leverage “Matryoshka” representations to optimize storage and compute by truncating embeddings down to 64 dimensions without sacrificing significant performance. You can access the model via API, cloud marketplaces, or vector databases (Pinecone, Weaviate, Qdrant) to build RAG applications.

LangChain just launched "Prompt Canvas" in LangSmith, a slick new UX that lets you team up with an AI agent to build and refine your prompts. You can chat with the agent to get suggestions, directly edit prompts in a canvas, and even define custom quick actions to share best prompting practices across your team.

Claude now lets you choose response styles: Normal, Concise, Explanatory, and Formal. You can select these options or even create custom styles. These settings will adjust key elements of Claude's responses, such as tone, voice, vocabulary, and detail level, for a personalized experience.

Tools of the Trade

1. Superflex: AI assistant in VS Code that converts Figma designs, images, and text prompts into production-ready frontend code. It also helps with refactoring and building new features through a chat interface.

2. Git Pulse: A unique way to explore popular open source projects. Git Pulse analyzes commits from open source projects and summarizes them using AI, making it easier to explore and understand a project's development history.

3. LlamaChunk: Opensource tool for splitting documents into semantically meaningful chunks for RAG apps. It uses the Llama-70B model to predict the best locations to split the text, outperforming traditional chunking methods in terms of retrieval accuracy and signal-to-noise ratio.

4. Awesome LLM Apps: Build awesome LLM apps using RAG to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos with simple text prompts. These apps will let you retrieve information, engage in chat, and extract insights directly from content on these platforms.

Hot Takes

1. What will we do with all the GPUs if they turn out to be useless for the next generation of AI? ~
   Pedro Domingos
   
   

2. there’s a specific kind of degrowth lib that has convinced themselves that using chatgpt consumes some Amazon burning amount of energy bc the concept of free lunches or pareto improvements doesn’t exist in their moral landscape

   a very sad way to live. btw as a general rule if it was really so energy hungry it wouldn’t be free to use ~
   roon

That’s all for today! See you tomorrow with more such AI-filled content.

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