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Lemon AI - Local General AI Agent Framework Like Manus & Genspark AI!
In this video, you’ll learn how to run Lemon AI—a full-stack, open-source, general AI agent —entirely on your local machine using Docker and WSL2 on Windows. We walk through the complete setup process, from installing Ubuntu via WSL2 and configuring Docker Desktop to integrating local language models like Qwen3 Coder via Ollama, and even connecting cloud-based models through OpenRouter. You’ll see Lemon AI in action: autonomously planning multi-step tasks, generating marketing websites, creating AI video storylines, and adapting to your feedback mid-process. This tutorial is ideal for developers, AI enthusiasts, content creators, and tech-savvy professionals who want to explore agentic AI without relying on cloud subscriptions. Understanding and running general AI agents locally matters because it gives you full control, privacy, and the ability to customize intelligent automation for your own workflows—today, not years from now.
Lemon AI is the first Full-stack Open-source Self-Evolving General AI Agent
https://lemonai.ai/
GitHub:
https://github.com/hexdocom/lemonai
Installation
https://lemon-11.gitbook.io/le....monai/development-de
Local Workstation GPU : https://amzn.to/3XfXsAO
If You Like tutorial like this, You Can Support Our Work In Patreon:
https://www.patreon.com/c/aifuturetech
#generalAIagent #LemonAI #artificialintelligence #aiagent
Advanced RAG 101 - build agentic RAG with llama3
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🔗 Links
- Join my community: https://2ly.link/1zq90
- Follow me on twitter: https://twitter.com/jasonzhou1993
- Join my AI email list: https://www.ai-jason.com/
- My discord: https://discord.gg/eZXprSaCDE
- Corrective RAG agent: https://github.com/langchain-a....i/langgraph/blob/mai
- LlamaParse: https://github.com/run-llama/llama_parse
- Firecrawl: https://www.firecrawl.dev/
- Jerry Liu build production-ready RAG: https://www.youtube.com/watch?v=TRjq7t2Ms5I
⏱️ Timestamps
0:00 Intro
1:33 How to give LLM knowledge
3:05 Problem with simple RAG
5:55 Better Parser
9:01 Chunk size
11:40 Rerank
12:39 Hybrid search
13:10 Agentic RAG - Query translation
14:35 Agentic RAG - metadata filtering
15:52 Agentic RAG - Corrective RAG agent
17:33 Install LLama3
18:00 Code walkthrough
👋🏻 About Me
My name is Jason Zhou, a product designer who shares interesting AI experiments & products. Email me if you need help building AI apps! ask@ai-jason.com
#llama3 #rag #llamaparse #llamaindex #gpt5 #autogen #gpt4 #autogpt #ai #artificialintelligence #tutorial #stepbystep #openai #llm #chatgpt #largelanguagemodels #largelanguagemodel #bestaiagent #chatgpt #agentgpt #agent #babyagi
Learn more about Types of AI agents here → https://ibm.biz/BdnZTE
Can a drone deliver packages safely and efficiently? 🤖 Martin Keen breaks down the 5 types of AI agents—from reflex to learning models—and their role in robotics, decision-making, and automation. Learn how goal-driven and utility-based AI adapt to workflows and complex environments.
Intro - 0:00
Simple Reflex Agent - 0:50
Model-Based Reflex Agent - 2:49
Goal-Based AI Agent - 4:20
Utility Based AI Agent- 5:43
Learning AI Agent - 6:55
Use Cases - 8:22
AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdnZTX
#aiagents #machinelearning #ai
Traditional RAG systems only scratch the surface of what's possible. This advanced AI agent combines vector search with knowledge graphs to create a system that understand relationships, track changes over time, and reason about complex connections. Built with PostgreSQL + pgvector and Neo4j + Graphiti, it automatically chooses between vector search, graph traversal, or hybrid approaches based on what will answer your question the best.
I built the full package here - a complete implementation including semantic chunking, a vector database/knowledge graph pipeline, a FastAPI backend with streaming responses, and a CLI tool to chat with the agent.
Full source code (linked below!) included with support for multiple LLM providers. This is production-ready RAG.
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Neon's free tier is more than enough to cover what you'll need in this guide! But if you do decide that you need to upgrade, you can sign up through this link and get a $100 credit:
https://get.neon.com/2scm
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Code and instructions for this Agentic RAG Agent here:
https://github.com/coleam00/ot....tomator-agents/tree/
I did test the downloaded LLM and it worked perfectly on a computer that was not connected to the internet. Please be responsible and use the offline uncensored LLM for good rather than evil. Uncensored LLMs can be beneficial if used properly.
Consider Supporting the Global Science Network.
Ko-fi (Preferred as there is zero platform fee for the transactions)
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External Drive Options.
Sandisk 128GB Flash Drive
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Larger Sandisk SSD
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Blue-ray disks
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Here is a link to the article with code and commands that need to be used.
https://www.gsnetwork.com/how-....to-use-the-dolphin-l
Zhipu AI just dropped the first real open source AI agent, and the entire industry felt it instantly. GLM four point six V delivers native multimodal tool-calling, full visual reasoning, pixel-accurate UI automation, and a massive one hundred twenty eight thousand token context window that handles documents, videos, charts, and screenshots in one pass. It is the first open source model that matches capabilities previously locked inside OpenAI and Google, and its Flash version runs locally for free. This release sent a shockwave through every major lab and pushed the open source race into a new era.
👉 Join the waitlist for the 2026 AI Playbook: https://tinyurl.com/AI-Playbook-2026
📩 Brand Deals & Partnerships: me@faiz.mov
✉ General Inquiries: airevolutionofficial@gmail.com
🧠 What You’ll See:
• The first real open source AI agent with native multimodal tool calling — https://www.marktechpost.com/2....025/12/09/zhipu-ai-r
• GLM four point six V building full UI layouts and verifying changes visually — https://binaryverseai.com/glm-....4-6v-review-benchmar
• The Flash model running locally with fast multimodal reasoning — https://huggingface.co/zai-org/GLM-4.6V-Flash
• How visual search, frame extraction, and interleaved reasoning work inside GLM four point six V — https://stable-learn.com/en/gl....m-46v-multimodal-vis
🚨 Why It Matters:
AI just moved into a new phase: open source models that understand screens, parse massive documents, run real tools, rewrite frontends, and reason across video in a single context window. GLM four point six V brings capabilities once exclusive to closed labs directly into the open ecosystem. This changes agents, automation, search, research, and software development, while OpenAI and Google face real pressure from a model anyone can run, study, or build on.
#ai #opensource #ainews
Try Flow Pro free for 14 days: https://ref.wisprflow.ai/tinahuang
👉 AND get an extra month free with my code TINAHUANG
In this video I explain every way to run open source AI models!
🐙 Free 28-Day AI Sprint Roadmap: pick your goal to get a clear, day-by-day path forward 👉 https://www.lonelyoctopus.com/ai-sprint-roadmap
🤖 Want to get ahead in your career using AI? Join the waitlist for my AI Agent Bootcamp: https://www.lonelyoctopus.com/ai-agent-bootcamp
🤝 Business Inquiries: https://tally.so/r/mRDV99
🖱️Links mentioned in video
========================
🔗Affiliates
========================
My SQL for data science interviews course (10 full interviews):
https://365datascience.com/lea....rn-sql-for-data-scie
365 Data Science:
https://365datascience.pxf.io/WD0za3 (link for 57% discount for their complete data science training)
Check out StrataScratch for data science interview prep:
https://stratascratch.com/?via=tina
🎥 My filming setup
========================
📷 camera: https://amzn.to/3LHbi7N
🎤 mic: https://amzn.to/3LqoFJb
🔭 tripod: https://amzn.to/3DkjGHe
💡 lights: https://amzn.to/3LmOhqk
⏰Timestamps
========================
00:00 Intro
01:40 Run Open Source Models Locally
07:47 Browser/Hosted Playgrounds
10:44 Managed Inference API
11:57 VPS (Virtual Private Server)
15:20 Managed Cloud
16:01 On-device/Edge
📲Socials
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linkedin: https://www.linkedin.com/in/tinaw-h/
tiktok: https://www.tiktok.com/@hellotinahuang
discord: https://discord.gg/5mMAtprshX
🎥Other videos you might be interested in
========================
How I consistently study with a full time job:
https://www.youtube.com/watch?v=INymz5VwLmk
How I would learn to code (if I could start over):
https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s
🐈⬛🐈⬛About me
========================
Hi, my name is Tina and I'm an ex-Meta data scientist turned internet person!
📧Contact
========================
youtube: youtube comments are by far the best way to get a response from me!
linkedin: https://www.linkedin.com/in/tinaw-h/
email for business inquiries only: tina@smoothmedia.co
========================
Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :)
OpenClaw can be run for free forever using local ai models through Ollama. Models like qwen 3.5 can be setup to connect directly to Open Claw, so you won't be charged per token use like with Clade or ChatGPT.
In this video I'll show you how to setup Local Models, how to connect them to OpenClaw, and how to setup things like MCP to reduce the cost of doing large context queries or API calls.
🔶 Install MCP Tools via Zapier:
https://bit.ly/4ccnm0G
🦙 Install Ollama Setup
https://ollama.com/
The model I used for openclaw here was Qwen 3.5 however there are many other models you can use from Google, Meta, etc.
#openclaw #ollama #ai
Want to learn web design? ⭐ Check out my course! ⭐
📘 Teach Me Design - Course: https://www.enhanceui.com/
To run openclaw local models, you need to install openclaw local llm setup. This lets openclaw llm charge you only what electricity you use for your mahcine!
🖥️ Download the free AI Agents Playbook: https://clickhubspot.com/f865c2
More from Futurepedia:
👉 Join the fastest-growing AI education platform! Try it free and explore 20+ top-rated courses in AI: https://bit.ly/futurepediaSL
Summary:
AI Agents seem overwhelming, but in 2026, we've gotten to the point that any non-technical person can create and manage their own AI agents to accomplish tasks. I cover everything simply: what an agent actually is, what to automate, how to start, and build two agents step by step using two of the leading platforms. Then dive into common pitfalls and how to avoid them. This is everything you need to get started with building AI agents in 2026, no coding required.
Chapters
0:00 Intro
0:50 What is an agent?
1:37 Where we're at right now
2:08 What to automate first
4:58 How to start
7:01 Time to build
7:24 Build 1
14:04 Build 2
20:43 More complex agents
22:03 Zapier vs n8n
22:40 Common Pitfalls (and how to avoid them)
24:44 The real skill
Get the 10-Step Security PDF Checklist here: https://danieljindoo.substack.com/
Join Our Semi-Private Community: https://discord.gg/HmbPtVy6Eq
Join Operators: https://www.youtube.com/channe....l/UCz21u_dPpYlJ-XyLc
Your local AI agents setup is leaking data right now, and you probably don't even know it. Running an LLM locally doesn't automatically make it private & safe. If your machine connects to the internet, you’ve basically bought your own house and left every single window open.
In this video, I break down the 7 vulnerabilities hiding in plain sight in your local AI stack-from browser extensions reading your chats to OS telemetry and exposed servers. Whether you're using Ollama, LM Studio, or vLLM, if you handle client data or sensitive business info, you need to lock this down.
No enterprise BS. Just real implementation and the exact 10-step security checklist I use.
⏳ TIMESTAMPS:
00:00 - The "Local = Safe" Myth Debunked
00:14 - Renting vs. Owning: Levels of AI Ownership
01:09 - Why You Are Probably at Level 1 (Exposed)
01:45 - Leak 1: Exposed AI Servers & APIs
03:00 - Leak 2: Browser Extensions Reading Everything
04:10 - Leak 3: Cloud Sync Auto-Uploading Chats
05:16 - Leak 4: Malicious AI Models & Poisoned Weights
06:30 - Leak 5: OS Telemetry (Windows Recall & Mac)
07:36 - Leak 6: Legal Obligations (GDPR, HIPAA, CCPA)
09:01 - The 10-Step Local AI Security Checklist
10:07 - Download the Free Setup Guide
Got questions about securing your specific SMB stack? Drop a comment below and let's troubleshoot.
Subscribe for outcome-based AI use cases. Information is free. Trust is rare. I only show you what I've actually built.
FIND ME ON SOCIALX/Twitter:
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https://www.linkedin.com/in/hy....oungjin-doo-a1939423
Newsletter: https://danieljindoo.substack.com/
Website: / https://doomade.com/
Local AI models/LLMs are the future. Here's how they work and how to set them up on ANY device.
FULL local LLM bootcamp in the Vibe Coding Academy: https://vibecodingacademy.dev
Sign up for my free newsletter: https://www.alexfinn.ai/subscribe
Follow my X: https://x.com/AlexFinn
My $300k/yr AI app: https://www.creatorbuddy.io/
OpenClaw:
https://openclaw.ai/
Hugging Face:
https://huggingface.co
Timestamps:
0:00 Intro
0:50 What are local models
6:16 Which computer you need
11:30 Which local models to use
13:54 Local models demos
In this video, I show you how to run a fully unrestricted and private, offline LLM directly on your own machine. If you are a cybersecurity professional, Red Teamer, or Pentester, you know the pain of getting the "I cannot help with that" error when working on legitimate security simulations or code analysis. I also show you how to set up a full private AI with RAG!
https://docs.privategpt.dev/ov....erview/welcome/intro
https://dev.to/docteurrs/insta....lling-privategpt-on-
*00:00* - Introduction to Private AI and Setup Guide
*00:56* - Understanding AI Models and Exploring Hugging Face
*01:24* - Installing Ollama for Local AI Models
*02:00* - Running Your First Local AI Model
*04:15* - Understanding what is RAG in AI
*05:05* - Setting Up Windows Subsystem for Linux (WSL) for AI
*05:24* - Private AI Setup and Installation
*10:04* - Fine-Tuning AI with Your Own Data
*10:37* - Setting Up Your Own Private GPT with RAG
Setting up Private AI on your computer
Offline AI models like ChatGPT
Enhancing job performance with Private AI
Fine-tuning AI models for specific needs
Running AI without internet
Privacy concerns with AI technologies
Surviving a zombie apocalypse with AI
Connecting knowledge bases to Private GPT
Retrieval Augmented Generation (RAG) with AI
Installing WSL for AI projects
Running LLMs on personal devices
VMware deep learning VMs
Customizing AI with VMware and Nvidia
Private GPT project setup
Leveraging GPUs for AI processing
Consulting databases with AI for accurate answers
Running local private AI in companies
Guide to private AI
Future of technology with private and fine-tuned AI
Here is the actual uncensored prompt explaining it: https://www.linkedin.com/posts/maddyhivemind_been-messing-around-with-local-uncensored-activity-7418024051081797632-myHZ?utm_source=share&utm_medium=member_desktop&rcm=ACoAADXr8m0B6M1r3WOYZgX9cWPwo96f9XA-XPk
Video Idea: https://www.youtube.com/@UC9x0AN7BWHpCDHSm9NiJFJQ
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Join the Discord: https://discord.com/servers/th....ehivemind-1235399448
Want to actually learn Linux, not just commands? Take my training: https://hivemindacademy.org/catalog
Hack The Box Cybersecurity Training: https://hacktheboxltd.sjv.io/Cyb3rMaddy
My Other Links: https://linktr.ee/Cyb3rMaddy
Local AI finally got good. Google's new Gemma 4 runs on a MacBook (and even on a phone) and performs about as well as the best frontier model from a year ago. Free & Offline!
In this video, I break down why local AI suddenly matters, walk through Gemma 4's real specs (not the cherry-picked charts), and test it on my M4 Pro MacBook using OpenCode, OpenClaw, and the Pi coding agent. I also rented an 80GB GPU on RunPod to try the biggest version of Gemma 4 on a more complex coding task - my own YouTube Copilot app.
If you've been wondering if it's finally time to take local AI more seriously - this video is worth a watch!
⏱ Timestamps
00:00 - How we got here
01:30 - Gemma 4
03:30 - Testing (OpenCode / OpenClaw / Pi Agent)
08:00 - Future Takeaway
🔗 Tools mentioned:
Ollama — https://ollama.com
LM Studio — https://lmstudio.ai
Google AI Edge Gallery (iOS / Android)
OpenCode, OpenClaw, Pi coding agent
RunPod (for renting GPUs)
💬 Got a more powerful machine? Running your own local setup? Drop your experience in the comments - I'd love to hear what's working for you.
👍 If this helped, smash that like button and subscribe for more hands-on AI experiments.
#LocalAI #Gemma4 #Ollama #OpenSourceAI #LLM #AI #GoogleGemma
