Stay tuned for more such interesting posts → @Saboo_Shubham_ I have created 100+ AI Agents and RAG tutorials, 100% free and opensource. P.S: Don't forget to star the repo to show your support
OPEN SOURCE
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Local Knowledge Base Setup with EmbeddingGemma Embeddings
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4. Set Up Knowledge Base with Local Embeddings Create a cached knowledge base using EmbeddingGemma for 100% local processing:
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Install Python Libraries and Ollama AI Models
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1. Install the necessary Python Libraries Run the following command from your terminal. Then pull the required Ollama models:
• ollama pull embeddinggemma:latest
• ollama pull llama3.2:latest -
Building Local RAG Agent with EmbeddingGemma and Ollama
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Let's build a local RAG Agent using Google's EmbeddingGemma and Ollama running locally on your machine. 100% Opensource and works without internet.
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Google Nano Banana Hackathon Project Goes Open Source
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After the Google Nano Banana Hackathon, the project will be open source.
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Kimi K-2.1: Moonshot’s Upgraded Open Weights Model
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My notes on Kimi-K2-Instruct-0905, aka Kimi K-2.1 – an incremental improvement on Moonshot's previous trillion parameter open weights model, now with twice the context length (256k up from 128k)
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DeepMCPAgent: Dynamic MCP Tool Discovery and Agent Development
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DeepMCPAgent A powerful tool for dynamic MCP tool discovery and agent development. Built with LangChain and LangGraph, it streamlines integration over HTTP/SSE while supporting major LLMs. Check it out! https://
github.com/cryxnet/deepmc
pagent
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OpenAI’s Journey from Open Research to Closed Commercial AI
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> be openAI, circa 2017
> do lots of interesting research
> all open source > no one cares that much
> invent chatGPT in 2022
> get too busy to do open research
> everyone gets mad
> wheres the open research
> more like closedAI
> three years pass. now 2025
> finally release an -
Popular Coding Tool Created for Fun Powers AI Agents
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It’s actually crazy how many coding agents use something I made for fun one afternoon
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Efficient AI Model Runs on Less Than 200MB RAM
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Good question! It's small enough to run on less than 200MB of RAM with quantization. You can read more about it here: