Product Overview - Sim is a 100% open-source alternative to n8n, designed as a drag-and-drop platform for building and deploying Agentic workflows [1] - Sim allows easy feature additions without disrupting existing functionality [3] Functionality and Integration - Sim can be used to build a finance assistance app and connect it to Telegram [2] - Sim agents support integration with MCP to connect with APIs like Alpha Vantage for stock data [2][3] - Sim works with any local LLM and runs 100% locally [3] Workflow and Components - The workflow involves an Intent Classifier to determine if a question is finance-related [3] - A Finance Agent uses Firecrawl for web searches and accesses stock data [2] - A Response Agent compiles the information and delivers it [2]

Open-Source Platform - Sim is presented as a 100% open-source alternative to n8n for building and deploying Agentic workflows [1] - Sim is a drag-and-drop platform [1] Application and Functionality - The platform was used to build a finance assistance app and connected to Telegram [2] - The workflow is simple and runs 100% locally [2] - It works with any local LLM [2]

Link to @simdotai GitHub repo: https://t.co/mnBXIe28JX(don't forget to star 🌟) ...

Core Functionality & Architecture - Sim is a 100% open-source alternative to n8n, designed as a drag-and-drop platform for building and deploying Agentic workflows [1] - The platform allows users to connect tools or agents as blocks on a canvas [2] - Sim agents support integration with MCP, facilitating connections with APIs like Alpha Vantage [3] - The architecture includes an Intent Classifier to determine if a user question is finance-related, redirecting if not [3] Finance Application & Use Case - A finance assistance app was built and connected to Telegram using Sim [2] - The Finance Agent utilizes Firecrawl for web searches and Alpha Vantage's API via MCP servers to access stock data [2] - A Response Agent compiles the information and delivers it to the user [2] - The platform supports easy feature additions, such as tracking crypto or portfolio analysis, without disrupting existing functionality [3] Deployment & Customization - Sim runs 100% locally [3] - It works with any local LLM (Large Language Model) [3] - The platform is easily extendable, allowing users to add agents for specific needs [3]

RT Avi Chawla (@_avichawla)You're in a Research Scientist interview at OpenAI.The interviewer asks:"Our investors want us to contribute to open-source.o3 crushed benchmarks.But we can lose a competitive edge by open-sourcing it.What do we do?"You: "Release the research paper."Interview over.You forgot that LLMs don't just learn from raw text; they also learn from each other.For example:- Llama 4 Scout & Maverick were trained using Llama 4 Behemoth.- Gemma 2 and 3 were trained using Gemini.Distillation helps ...

You're in a Research Scientist interview at OpenAI.The interviewer asks:"Our investors want us to contribute to open-source.o3 crushed benchmarks.But we can lose a competitive edge by open-sourcing it.What do we do?"You: "Release the research paper."Interview over.You forgot that LLMs don't just learn from raw text; they also learn from each other.For example:- Llama 4 Scout & Maverick were trained using Llama 4 Behemoth.- Gemma 2 and 3 were trained using Gemini.Distillation helps us do so, and the visual e ...

RT Avi Chawla (@_avichawla)11 plots that data scientists use 90% of the time: https://t.co/9f5RD23rkK ...

11 plots that data scientists use 90% of the time: https://t.co/9f5RD23rkK ...

RT Avi Chawla (@_avichawla)I just built my own multi-agent deep researcher!It uses a 100% local LLM and MCP.Here's an overview of how it works:- User submits a query- Web agent searches with Bright Data MCP tool- Research agents generate insights using platform-specific tools- Response agent crafts a coherent answer with citationsTech stack:- Bright Data MCP for real-time web access- CrewAI for multi-agent orchestration- Ollama to locally serve GPT-OSSWhy Bright Data MCP?To build this workflow, we needed to ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. ...