Build, Publish, and Monetize your AI Agents

Today’s top AI Highlights:

1. Open-source platform to build and monetize swarm of AI agents

2. Microsoft releases GraphRAG 1.0 with better CLI and simpler setup

3. OpenAI just held a mini DevDay with o1 API and more

4. Build and deploy web apps in pure Python - no Javascript required

5. Open-source drag-and-drop tool for building AI agents

& so much more!

Read time: 3 mins

AI Tutorials

Building powerful RAG applications has often meant trading off between model performance, cost, and speed. Today, we're changing that by using Cohere's newly released Command R7B model - their most efficient model that delivers top-tier performance in RAG, tool use, and agentic behavior while keeping API costs low and response times fast.

In this tutorial, we'll build a production-ready RAG agent that combines Command R7B's capabilities with Qdrant for vector storage, Langchain for RAG pipeline management, and LangGraph for orchestration. You'll create a system that not only answers questions from your documents but intelligently falls back to web search when needed.

Command R7B brings an impressive 128k context window and leads the HuggingFace Open LLM Leaderboard in its size class. What makes it particularly exciting for our RAG application is its native in-line citation capabilities and strong performance on enterprise RAG use-cases, all with just 7B parameters.

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 leveling 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

Build, Monitor, and Monetize AI Agents With One Platform 🤖🤖

SwarmZero is an open-source platform to build and monetize AI agents on a unified platform, with both SDK and no-code options for building AI agents. The platform handles the complexities of agent deployment and marketplace distribution, letting developers focus on creating capable AI solutions.

Beyond standard agent features, SwarmZero lets you create agent swarms for handling complex multi-step workflows, and integrates with 1000+ tools through its built-in connections. The platform also provides a marketplace where you can publish and monetize their agents, making it easier to reach users looking for specific AI solutions.

Key Highlights:

1. Agent Enhancement - Extend agent capabilities by connecting multiple ML models, integrating APIs, and uploading knowledge files. Agents can be embedded within other agents, enabling modular design patterns. The platform includes built-in support for common agent tasks like file operations and data analysis.

2. Production-Ready Infrastructure - Built-in features for state management, conversation history, and error handling eliminate common deployment hurdles. The platform handles authentication, API rate limiting, and monitoring out of the box, with detailed logs and metrics for debugging and optimization.

3. Observability - The platform is integrated with Langtrace for monitoring agent performance, evaluating prompts, and comparing the performance of different models. You can even track LLM metrics through this feature.

4. Monetization - Direct publishing to the Agent Hub marketplace with built-in pricing and usage tracking. Developers can set custom pricing models and access analytics on agent usage, while users can easily discover and purchase agents that match their needs.

5. Development Options - Build agents using the Python SDK for full customization or use the no-code Agent Builder for quick prototyping. The platform supports multiple LLM providers including OpenAI, Anthropic, and MistralAI, with comprehensive documentation and example implementations to speed up development.

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GraphRAG 1.0 Reduces Storage Needs by 80% 🕸️

Microsoft's GraphRAG, their most popular graph-based RAG system, has just hit version 1.0, bringing a host of changes. This release is a significant overhaul to make the tool easier to use and more performant, with key changes in setup, data management, and code structure.

Faster indexing, simpler configurations, and a more straightforward API for smoother integrations with your applications. This new release tackles some of the biggest hurdles developers have faced with earlier versions, and is designed to streamline your AI development workflows.

Key Highlights:

1. Setup with init Command - The new init command generates a basic settings.yml file pre-populated with core configurations. You can now get started with just an OpenAI API key, significantly lowering the initial setup barrier and getting to coding faster.

2. Streamlined CLI and Dedicated API Layer - The CLI has been overhauled with a richer experience powered by Typer, making it a primary interface for GraphRAG, with startup times dropping from over 2 minutes to just 2 seconds on average. Plus, a standalone API layer means you can now directly integrate GraphRAG functionality into your own applications, the API acting as a documented example for you.

3. Data Model and Vector Storage - Disk usage has seen an 80% reduction in parquet outputs due to changes in how embeddings are handled. Embeddings are now placed into vector stores like LanceDB or Azure AI Search, avoiding the unnecessary loading of large embedding files during each query. The result is a smaller storage footprint and faster data access.

4. Incremental Ingest with update Command - You can now update existing knowledge indexes with new data using the update command, which will compute the changes and merge them instead of rebuilding the index entirely. The update also utilizes LLM caching to save time and resources and provides better quality answers for better managing evolving datasets.

Quick Bites

Google has released updated versions of their video and image generation models, Veo 2 and Imagen 3, along with a new experimental tool called Whisk. These models boast state-of-the-art results and are now available in Google Labs.

1. Veo 2 - Achieves top performance in video generation with improved realism, physics and cinematic understanding, up to 4K resolution, and extended durations to minutes, now accessible through VideoFX.

2. Imagen 3 - Enhances image generation with improved composition, diverse art style rendering, prompt fidelity, and richer detail, rolling out globally in ImageFX.

3. Whisk - A novel Labs experiment, lets users combine and remix images using Gemini's visual understanding and Imagen 3, for flexible creation via subject, scene, and style prompts, currently available in the US.

Wrapping up the 9th day of the 12-day announcement series, OpenAI made a slew of announcements for developers. Here’s everything you need to know:

1. o1 model out of preview is now generally available in the API with function calling, structured outputs, a new type of system message called Developer Messages for more precise model steering, a Reasoning Effort parameter for cost and time optimization on tasks of varying complexity, and Vision inputs. Rollout is starting with tier 5 customers and will take a few weeks to reach all users.

2. A new fine-tuning method called Preference Fine-Tuning is now available for GPT-4o that uses pairs of responses, with one preferred over the other. This allows the model to learn differences in factors like response format, style, and abstract qualities (like helpfulness).

3. New SDKs for Go and Java are out. Similar to the existing Python and Node SDKs, these new SDKs fully support all API endpoints.

4. The Realtime API now supports WebRTC, drastically reducing the amount of code needed to build real-time, low-latency voice applications.

5. There are major price reductions for audio tokens in Realtime API. GPT-4o audio tokens are now 60% cheaper and GPT-4o-mini tokens are now 10x cheaper.

UAE’s Technology Innovation Institute released Falcon 3, a family of powerful small language models - Falcon3 1B, 3B, 7B, and 10B. The models impressively outperform others in their size class, while running efficiently on laptops. These open-source models, available on Hugging Face now, are designed for easy integration with existing tools and include base and instruct versions for varied tasks.

Tools of the Trade

1. CerebrasCoder: Open-source app to build fully functional websites from simple text prompts, using Llama 3.3-70b from Cerebras Systems as fast as you can type. 100% free and open-source.

2. Reflex: Python library for building full-stack web applications entirely in Python, without any JavaScript. You can define both frontend UI and backend logic, then deploy with a single command. It comes with built-in components, flexible customizations, and more.

3. PySpur: Open-source, drag-and-drop tool for building AI agents with modular components, deployable as an API. It supports adding custom tools with Python, exporting configurations as JSON for version control, and integrating with existing codebases via Python and TypeScript SDKs.

4. Awesome LLM Apps: Build awesome LLM apps with RAG, AI agents, and more to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos, and automate complex work.

Hot Takes

1. I think it’s time for everyone to state their AGI definitions. Otherwise we will just keep moving goalposts.
   (For the record, I think AGI is effectively already here. Note: AGI != ASI) ~
   Dylan Field
   
   

2. > intelligence too cheap to meter
   > what if we charge $2k/month
   open source must win (otherwise many will just be priced out) ~
   anton

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

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