Show HN: Which is faster? Puppeteer, Playwright or Selenium https://ift.tt/frxLcB2

Show HN: Which is faster? Puppeteer, Playwright or Selenium Hey Everyone, I just ran a [rather silly] race between Puppeteer (JS), Playwright (Python) and Selenium (Python) to see which one would be fastest on a simple scrape (using Google Colab so you can also run it) Far from a comprehensive benchmark, this race is 100% free from advanced configurations, multi-threading or anything complicated. It just opens Wallapop (a second hand marketplace in Spain) and times how long it takes to extract the first 2000 results of a search. If you like this simple format, have any ideas on how to improve a race like this or have a strong urge to prove Ward Cunningham wright, let me know in the comments! https://ift.tt/Fs5qY6I September 9, 2023 at 04:54PM

Show HN: Convert Youtube Video to Pdf https://ift.tt/SPFNxwo

Show HN: Convert Youtube Video to Pdf https://www.u2docs.com September 9, 2023 at 08:12AM

Show HN: Mkwhl – Python wheel creation utility https://ift.tt/j3mEs6k

Show HN: Mkwhl – Python wheel creation utility https://ift.tt/OjieZno September 9, 2023 at 03:38AM

Show HN: What an 8-bit computer can do [video] https://ift.tt/gdMuS0F

Show HN: What an 8-bit computer can do [video] Most under-evaluated 8bit: The plus/4 https://www.youtube.com/watch?v=dgm2eZMFuXw September 9, 2023 at 02:27AM

Show HN: New AI Dataset Based on LibGen and Sci-Hub https://ift.tt/Mci1tnd

Show HN: New AI Dataset Based on LibGen and Sci-Hub We recently began extracting the text layers of scholarly publications and books to include in our database. This encompasses sources such as scimag, libgen, and the latest zlib leaks. Our project, named the Standard Template Construct, also features a distributed search engine and incorporates various AI routines to handle the text corpus. Today we have releases our first dataset, STC230908. This dataset contains approximately 75,000 book texts, 1.3 million scholarly paper texts, and 24 million abstracts, including the years from 2021 to 2023. We're currently in the process of preparing the next version of the dataset, which will include an additional 300,000 books. How to Access Short Instructions: Install IPFS and launch it. pip3 install stc-geck && geck - documents More details: the dataset is released in IPFS and replicated to multiple nodes. It is in format of database for the search engine that we use in STC. GECK is the library that embeds this search engine and allows to stream all contained data in easy way. Even more detailed Instructions: https://ift.tt/tqxnvlc https://ift.tt/DSIv4Ek September 9, 2023 at 02:11AM

Show HN: Find jobs at top AI startups https://ift.tt/j2DPkNx

Show HN: Find jobs at top AI startups Hello HN, I am one of the creators of WorkInAI, and I'm excited to share our project with the community and gather valuable feedback. WorkInAI is a job aggregation platform for positions at leading AI startups. We have compiled over 350 job listings from more than 20 top AI startups, including companies like OpenAI, Anthropic, Cohere, and more. We created this platform in response to a friend's frustration with trying to find suitable AI startup roles in London. He used to check various company career pages frequently to see if any new opportunities had arisen -- so we built this to aggregate jobs in a single place. We're launching this MVP early to gather feedback, whether it's feature requests or suggestions for adding new startups to our list. We value your thoughts and input on our product and idea. Thanks! https://workinai.xyz/ September 8, 2023 at 09:51PM

Show HN: Rivet – open-source AI Agent dev env with real-world applications https://ift.tt/n5BNrCc

Show HN: Rivet – open-source AI Agent dev env with real-world applications We just launched Rivet, the open-source visual AI programming environment! We built Rivet, because we were building complex AI Agent applications at Ironclad. It unlocked our abilities here, and we're excited to make available to the entire community. Backstory: A few months ago, inspired by things like LangChain and LlamaIndex, we started building an AI agent that could work with legal contracts. Unfortunately, we couldn't just use retrieval augmented generation (RAG), because a lot of contracts are basically identical (many chunks with near-identical embeddings), except for a few key details. So, we turned to things like ReAct and AutoGPT for inspiration. At first, things went great. We were adding agent capabilities, doing chain-of-thought prompting. But then we hit a wall. The agent became too complex. We had debugger breakpoints on almost every line of code, but we still had no idea where the agent was breaking. Every change we made destabilized something else. After two weeks of fumbling, I decided to end the project. But one of my teammates, Andy, didn't give up. The following week, he showed me v0 of Rivet. He'd used it to refactor and improve our existing agent. I was skeptical... it just seemed like a visual programming environment, and I was not a fan. But I gave it a shot, and suddenly found myself able to add new skills to the agent, debug brittle areas with ease, and update prompts with confidence. Rivet is a game-changer. And more than that, it makes building with LLMs super fun. What exactly makes it different? First, the debugger is incredible. You have to experience it to believe it. You can update a graph, and then immediately run it, and see where it succeeded or failed. Even better: you can attach Rivet as a remote debugger, and watch your agent graphs execute in your app. Second, visual programming is actually a game-changer for prompting LLMs. I don't know why exactly, but it's way easier to understand and organize your work when you have an extra dimension to work with. Finally, Rivet is built to be embedded into a larger application (TypeScript for now, but we've also found a way to run it in Python). Beyond importing Rivet as a dependency, you can also define "external functions" dynamically at run-time. It feels pretty sketchy to give a LLM a key and unfettered access to an API. With Rivet, you can give it access to a specific set of defined functions, potentially pre-scoped to the access level you want. ...Sorry that was long. If you read this whole thing, thank you! We're really excited to hear what you think! We just launched our first Rivet-based application at Ironclad, and we've been working with companies like Sourcegraph, Attentive, AssemblyAI, Bento, and Willow to make Rivet useful for others. https://ift.tt/ExMoCTb September 8, 2023 at 06:59PM