Blockchain Enthusiast | Web3 enthusiast & NFT Enjoyoor
Metaverse
Joined May 2021
- Tweets4.9K
- Following840
- Followers640
- Likes2.8K
Satwik Samanta retweeted
از طریق این آدرس میتونید یه آدرس .tech رایگان بگیرید.
من یکی گرفتم همین الان :)
hacktoberfest.com/my/promos/
Satwik Samanta retweeted
The web is free for humans. Agents shouldn't have to pay to read it.
Our free Search and Fetch (30 searches a minute, no card) now power the first call in @treg_ai 's open source WebAccess.
Try it: treg.to/web-access
Introducing OpenSource Free WebAccess
- 100% FREE Web search & fetch @Tiny_Fish
- Any web page & data, agent can access
- Routing each request to the vendor best at that task
- Benchmark on cost/speed/token-efficiency
Try it at treg.to/web-access
Repo link below 👇
Satwik Samanta retweeted
老哥们，又冒出来个把我整得直呼邪门的开源神器😅
有人把 PDF 解析器干到了每秒 100 页转 Markdown，要命的是分文不取，纯靠 CPU 就能扛，GPU 不用、云端不沾、连 API key 都省下了。
叫 OpenDataLoader，一路横扫各家跑分榜，径直坐上头把交椅
拎几个对比你就门儿清了：
1️⃣ docling 分儿还凑合，可速度慢它 15 倍
2️⃣ marker 既得要 GPU，又慢出 1000 倍
3️⃣ Pymupdf4llm 是够快，可表格分只摸到 0.40
github.com/opendataloader-pr…
Satwik Samanta retweeted
I just tried out that Reverse Engineer Anything trending git repo.
It decompiled a steam game I had previously purchased and launched it in Unity in less than 30 minutes using OPUS 5.5 on medium reasoning.
Absolutely cracked tbh…. Fully decompiled to C#
Satwik Samanta retweeted
Finally my script to auto mint nfts in public phase against other bots is here with a video explanation :
🔗 Link : github.com/morsyxbt/nft-publ…
- visit my repo and follow step by step
- prefer burner wallets to mint
- you can mint unlimited nfts in public stage
almost 99% public stage RH nft is doing 5-6x ($1 to $6-7) by sniping multiple via this script you can make 10-100x ($70-$700)
but always dyor before minting
current chains supported :
eth
base
robinhood
so, whats next ?
fcfs script ?
Satwik Samanta retweeted
Searching 32 million records in 30 milliseconds is insane!
@typesense is a crazy fast open-source search engine that supports natural language search. It's like Elasticsearch but much easier to set up, configure, and use.
You can do all of this with Typesense:
• Fuzzy search: Typo-tolerant fuzzy search-as-you-type
• Vector search: Return records that are similar to each other
• Semantic search: Return records that are conceptually related
• Geo Search: Return records that are close to a given lat/long
Typesense's Natural Language Search is pretty cool:
It turns a sentence into a structured search query, then runs it against your data. For example:
The query "Find me a BMW under $40,000, newer than 2020, with the lowest mileage first" will produce the following:
• Filters: brand = BMW, price < 40000, year > 2020
• Sort: mileage ascending
Typesense will then apply these filters and sorting rules to the data.
They offer client libraries in Python, JavaScript, PHP, Ruby, Go, Rust, Swift, .NET, Java, and pretty much any other programming language.
You can start searching in less than a minute:
1. Run their Docker image (or one of their native binaries)
2. Import your data
3. Start searching!
GitHub repository: fandf.co/4ytzmmE
I recorded a quick video to show you a demo. I promise you haven't seen anything this fast!
Thanks to the team for partnering with me on this post.
Satwik Samanta retweeted
What if an AI browser didn’t render pixels unless it actually needed them?
That’s the idea behind Moli.
A production-ready headless browser built in Rust for AI agents.
And its architecture is seriously interesting.
Most browser automation keeps a fully rendered visual world alive.
Moli takes the opposite approach:
Structure first.
Pixels on demand.
Need HTML, Markdown, DOM, JavaScript, network data or storage?
→ No layout.
→ No paint.
→ Just read the browser state directly.
Need coordinates or a screenshot?
→ Build the layout.
Need another screenshot?
→ Render a fresh frame.
The visual state doesn't sit there consuming resources when the agent doesn't need it.
And Moli isn't some tiny HTML fetcher.
It has:
→ V8 JavaScript
→ Native DOM + CSS
→ WebSockets & Fetch/XHR
→ Cookies & storage
→ Screenshots & PDFs
→ CDP + WebDriver Classic + BiDi
→ Playwright support
→ MCP/WebMCP capabilities
The benchmark numbers get even crazier.
On one mixed public-web crawl:
Moli: 73 MiB median RSS
Chrome Headless: 773 MiB
And in its reported Lexbench run:
Moli: 81.9% task success
Chrome: 99.8%
while Moli used roughly 13% of Chrome's peak memory in the reported resource comparison.
So the goal isn't to beat Chrome at being Chrome.
It's to build a browser around what AI agents actually need.
Because an AI agent doesn't need a GPU-rendered webpage sitting there 24/7.
Sometimes it just needs:
DOM → understand → act
And when vision is actually required:
Layout → pixels → act
That architecture could make browser agents dramatically more efficient.
Structure first.
Pixels on demand.
REPOO👇
Satwik Samanta retweeted
I got accepted into Claude's Startup Program!
You may not get an emai, check this link to see if you got accepted: platform.claude.com/offers/s…
Satwik Samanta retweeted
数字羊毛第二弹：Freestyle 云电脑，Free 档永久免费。
据官方定价页：每月含 200 vCPU 小时、400 GiB·小时内存、60000 GiB·小时存储，10 并发 VM。超额部分按 0.04032 美元/vCPU·小时计费。
行动指引：给 agent 跑长任务、挂脚本，免费档基本够用。提醒一句：Free 档不含 Persistent VM，重要数据做好备份。freestyle.sh 定价页可查。
Satwik Samanta retweeted
Chrome uses hundreds of MB just to open a webpage.
This browser does it in around 30 MB.
And somehow… it can still run JavaScript, render pages, take screenshots, generate PDFs and control websites.
Meet Obscura.
An open-source headless browser written in Rust for AI agents and web scraping.
No Chromium.
No Node.js.
No massive browser stack.
Obscura embeds V8 directly and comes with its own rendering engine.
It supports:
→ Real JavaScript execution
→ CSS layout & rendering
→ Puppeteer + Playwright
→ Chrome DevTools Protocol
→ Screenshots, PDFs & screencasts
→ Parallel scraping
→ Network interception
→ MCP for AI agents
And then it gets even crazier.
Obscura has a stealth mode.
It can randomize browser fingerprints, hide "navigator.webdriver", mask native functions and block 3,520 tracker domains.
So your AI agent can actually operate a browser without needing to launch Chrome.
It can:
→ Navigate
→ Click
→ Fill forms
→ Execute JavaScript
→ Read pages
→ Inspect network requests
→ Take screenshots
→ Generate PDFs
All from an open-source Rust browser.
The goal isn't to make another Chrome clone.
It's to build a browser small enough for machines and powerful enough for AI agents.
REPOO👇
Satwik Samanta retweeted
🤯 $324M Backed New Layer 1 Blockchain
@hashed_official is building a new Layer 1 blockchain called @maroo_io
Hashed has raised $324M+ across its venture funds to back and invest in Web3 projects.
Maroo is an EVM-compatible Layer 1 built for Korea's $KRW stablecoin ecosystem, with compliance built into the protocol.
Testnet isn’t fully live yet, but you can still explore it early by claiming faucet tokens and deploying a contract.
🔗 Faucet: faucet.maroo.io/en
– Connect your EVM wallet
– Claim $tOKRW test tokens
Deploy a Contract
🔗 Create: wizard.openzeppelin.com
– Connect your EVM wallet
– Deploy your contract (follow the video)
Also, claim as much faucet as you can now.
Once ecosystem projects go live, I’ll make guides covering them.
So, after Arc, we’ve got another Layer 1 backed by big VCs. 🫡
Did you deploy a contract?
Post your screenshot below 👇
Like, Repost & Share ❤️🩹
Satwik Samanta retweeted
OnionClaw 🧅
Provide AI agents with full Tor network access and dark web data through a zero-config OpenClaw skill or standalone tool.
Source/Credit: github.com/christinminor459/…
Satwik Samanta retweeted
GitHub is becoming f...cking dangerous for AI agents
10 open-source repos that turn one powerful model into an entire autonomous system
01 LangGraph
▸ github.com/langchain-ai/lang…
→ stateful agent orchestration
02 PydanticAI
▸ github.com/pydantic/pydantic…
→ typed agents + structured outputs
BUILD THE CONTROL LAYER
03 Mastra
▸ github.com/mastra-ai/mastra
→ agents + workflows + memory
04 Agno
▸ github.com/agno-agi/agno
→ multi-agent systems
GIVE IT CONTEXT
05 Cognee
▸ github.com/topoteretes/cogne…
→ data → knowledge → agent memory
06 Graphiti
▸ github.com/getzep/graphiti
→ knowledge that changes over time
GIVE IT A COMPUTER
07 Browser Use
▸ github.com/browser-use/brows…
→ AI agents that operate websites
08 E2B
▸ github.com/e2b-dev/E2B
→ isolated environments for execution
KEEP IT ALIVE
09 Langfuse
▸ github.com/langfuse/langfuse
→ traces + evals + observability
10 DeepEval
▸ github.com/confident-ai/deep…
→ test agent behavior before production
the architecture:
model → context → planner → memory → tools → execution → eval → retry
that's the shift happening on GitHub
the best repos aren't making another chatbot
they're building everything the model needs around it ⭣
Satwik Samanta retweeted
Introducing pdfcn
Build beautiful PDFs like you build your UI.
Powered by Takumi + Forme.
Pick from 10+ themes, 40+ components & blocks, then customize everything.
One command to get started. shadcn/ui compatible.
100% Free. Open source.
Satwik Samanta retweeted
🚨 FREE LINUX VM IN 1 COMMAND - NO SIGNUP, NO CARD
Railway just opened free Linux VMs that you can launch directly from your terminal.
Run: ssh railway.new
and you get:
> 2 vCPU
> 2 GB RAM
Ready in ~1.4 seconds
> No account required
> No credit card
> No dashboard needed
Claude Code, Codex, OpenCode and other coding tools pre-installed
Live preview URL for your app (railway.new)
You get 60 minutes to build on the free VM. If you want to keep it, claim it within 24 hours. (Railway)
This is basically:
Terminal → Linux VM → Coding Agent → Live App
> No cloud setup.
> No server configuration.
Just: ssh railway.new
FREE CLOUD VM + AI CODING AGENTS IN ONE COMMAND.
Satwik Samanta retweeted
🚨 GOOGLE IS BUILDING KUBERNETES FOR AI AGENTS.
Google just open-sourced AX — a high-throughput orchestrator designed to run autonomous agent workloads at massive scale.
Think:
Kubernetes → containers
AX → AI agents
→ Run agents inside isolated sandboxes
→ Pre-wire Git repos, MCP servers, and skills with Workspaces
→ Restrict network access with Gateways
→ Configure LLM providers with Models
→ ax watch to monitor agents live
→ ax ssh to look inside a running sandbox
→ Suspend + resume agents without losing their state
→ Declarative YAML for the entire workflow
The crazy part?
You can define the whole agent environment in YAML:
Task + Workspace + Gateway + Model
Then:
ax apply -f task.yaml
And AX handles the orchestration.
Google says it's designed to run billions of autonomous agent workloads in a cluster.
This feels less like another AI agent framework…
and more like infrastructure for an entire agent fleet.
#Google #AIAgents #AI #Kubernetes #DevOps #CloudNative #OpenSource #AgentInfrastructure #LLM #Developers
Satwik Samanta retweeted
hmm... try installing these
Graphify, Obsidian, Codegraph and Ponytail ... it will make a diff
Satwik Samanta retweeted
Meta just put $1M on the table for builders.
Meta Global AI Developer Hackathon:
- 10 days to build
- Access to Meta's newest models
- $1M in prizes
- 100% virtual, open worldwide
- Free to enter
apply: dev.meta.ai/events/global-ha…
No visa. No flight. No fee.
Just a laptop and 10 days to ship.
Bookmark this + tag the builder you'd team up with.
