Open Source AI Tools and Frameworks

I think it is essential for Data Analysts to become skilled in the use of top-tier AI tools. But what if you don't have access to a GPT-4 subscription? Great news! - you can build a very comparable system entirely for free... Currently, Open AI's GPT4 model represents the state-of-the-art. At $20 per month, I think it represents a tremendous value. However, not everyone has the ability or willingness to pay for a subscription. With the advent of great, easy to use open source AI tools you can now assemble your own AI toolbox, close to the power and capabilities you would get from a GPT 4 subscription, and in some ways actually better. Here's how to do it: 🔸 Jan AI - Open Source Alternative to Chat GPT Jan AI is an entirely free, open-source environment for running AI Large Language Models (LLMs). It is super easy to install, runs on Windows, Mac and Linux, and unlike Chat GPT it can run entirely locally and off-line. It lets you install different models either from the Jan AI site, or from other open-source repositories, as well as incorporate any existing models you have an API key to. Currently, the best-performing open-source model seems to be the Mistral 7 billion parameter model, which many benchmarks evaluate as outperforming GPT 3.5, though not yet at the level of GPT 4. I have loaded the Mistral 7B model into my local Jan implementation, and I find it works really well, with an interface very similar to Open AI's. 🔸 Free AI Image Generation You have a number of great options here. Bing Image Creator incorporates the same DALLE-3 engine as GPT 4, and will give you 150 free credits every day. Leonardo.AI is another top-quality AI image generator with a free tier. While both of the above run in the cloud with limitations on the number of free generations per day, Stable Diffusion offers a free, powerful and unlimited local AI image generation model. The downside to this is that I found it difficult to install and use, although it does have some strong adherents. For AI image upscaling (to increase the resolution of your generated images), I strongly recommend Upscayl, an incredibly powerful, free local AI upscaling tool that I now use on almost all my images. 🔸 Code Interpreter/Advanced Data Analysis Capabilities The open-source equivalent of ADA is Open Interpreter. This is a very ambitious open-source project, the goal which is to provides a natural-language interface between AI models and your computer's general-purpose capabilities, allowing you to do things like: - Create and edit photos, videos, PDFs, etc. - Control a browser to perform research - Plot, clean, and analyze large datasets Open Interpreter also now has the ability to take control of your computer's keyboard and mouse, opening the door to all sorts of AI automation. Within the next few weeks a polished graphical user interface is expected to become publicly available (it currently runs via text input, same as ADA). #AI #opensource

I found the missing piece for building AI agent teams that actually collaborate! Common Ground is an open-source framework for creating teams of AI agents that tackle complex research and analysis tasks through true collaboration. Think of it as simulating a real consulting team: a Partner agent handles user interaction, a Principal agent breaks down complex problems, and specialized Associate agents execute the work. Key Features: • Advanced multi-agent architecture with Partner-Principal-Associate roles • Full observability with real-time Flow, Kanban, and Timeline views • Model agnostic with built-in Gemini integration via LiteLLM • Extensible tooling through Model Context Protocol (MCP) • Built-in project management and auto-updating RAG system The breakthrough? It transforms you from a passive prompter into an active "pilot in the cockpit" with deep visibility into not just what agents are doing, but why they're doing it. Perfect for building agents that handle multi-step workflows and strategic collaboration beyond simple command-response chains. It's 100% open-source. Link to the repo in the comments! ___ Connect with me → Shubham Saboo I share daily AI tips and opensource tutorials on AI Agents, RAG and MCP.

If you have been following any topics around AI development, you have probably heard about LangChain, one of the most popular open source tools for building AI applications. LangChain was launched in October 2022 as an open source project by Harrison Chase while working at the machine learning startup Robust Intelligence. The project quickly gained popularity on GitHub, Twitter, YouTube, etc., with hundreds of developers' contributions. LangChain Inc. was incorporated as a startup by Harrison Chase and co-founder Ankush Johar Gola. They raised over $20 million in funding within a week of announcing a $10 million seed investment. On January 8th, LangChain released its first stable version v0.1.0. 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 LangChain is a software framework designed to facilitate the development of advanced AI applications, particularly those that involve processing and generating human language. It serves as a comprehensive toolkit for developers, streamlining the creation of language-based AI solutions. Here's how LangChain can be helpful: Facilitates Language Understanding and Generation: LangChain enables AI applications to understand and generate human language better, making interactions with AI more natural and effective. Integrates Various AI Services: It acts as a middleware, connecting different AI tools and services. This integration allows for more robust and versatile AI applications. Customization and Flexibility: Developers can tailor AI solutions to specific needs, thanks to LangChain's modular design. This flexibility ensures that a wide range of language-based tasks can be addressed effectively. Simplifies AI Development: LangChain abstracts the complexities of developing language AI, making it more accessible for developers to create sophisticated AI tools without needing deep expertise in every underlying technology. Enhances AI Application Performance: By providing a structured framework and toolkit, LangChain helps build more efficient and reliable AI applications, improving performance in tasks like language understanding, conversation, and data processing. 𝗦𝘂𝗺𝗺𝗮𝗿𝘆 𝗼𝗳 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 𝗮𝗻𝗱 𝗜𝘁𝘀 𝗨𝘁𝗶𝗹𝗶𝘁𝘆 In summary, LangChain is a valuable tool for developers looking to harness the power of AI in language processing and generation, offering a blend of integration, customization, and ease of use.

Great news for the Open-source LLM community!!! 🤩🚀 Allen Institute for AI (AI2) has released OLMo 7B, a truly open, state-of-the-art large language model, alongside the pre-training data and training code. The framework features a suite of completely open AI development tools, including: Full pretraining data: The model is built on AI2’s Dolma set, which features a three trillion token open corpus for language model pretraining, including code that produces the training data. Training code and model weights: The OLMo framework includes full model weights for four model variants at the 7B scale, each trained to at least 2T tokens. Inference code, training metrics and training logs are all provided. Evaluation: We’ve released the evaluation suite used in development, complete with 500+ checkpoints per model, from every 1000 steps during the training process and evaluation code under the umbrella of the Catwalk project. As Professor Yann LeCun said, "Open-source AI models will soon become unbeatable. Period." Great job Allen Institute for AI (AI2)! #ai #largelanguagemodels #opensourceai #opensource