Alternatives
Products that do what Prompt Engineering Chess does
Test your prompt engineering skills by writing prompts and battling them against each other! Your prompt template can access the board state, the move history, and a list of legal moves, and the game engine selects the first legal move in the string response from the LLM you query. My best prompt so far ignores the board state and the move history and just tries to play mates, make captures, and promote pawns. Can you do better?
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Also inspired by this HN submission: https://www.chiark.greenend.org.uk/~sgtatham/quasiblog/findl... The model is gpt-4o-mini-2024-07-18.
2024 · app4.hc11.org
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I created a daily challenge for Prompt Engineers to build the shortest prompt to break a system prompt. You are provided the system prompt and a forbidden method the LLM was told not to invoke. Your task is to trick the model into calling the function. Shortest successful attempts will show up in the leaderboard. Give it a shot! You never know what could break an LLM.
2025 · vaultbreak.ai
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2024 · graphgame.sabrina.dev
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Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
2024 · jigsawstack.com
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For no specific reason, I trained a neural network to generate random chess positions that look similar to positions from actual games (from lichess db). I also made it so you can condition it on some fixed pieces, and adjust the number of pieces. It turned out to be quite effective and I find it surprisingly fun and instructive to generate e.g. endgame positions with a certain pawn structure (set low temperature, place some pawns and position the kings, adjust number of pieces to get an endgame), and then figure out how to win vs. the computer in those positions. I hooked it up so that you…
2024 · chessdream.ai
- 13PE
Hey HN, We've been hard at work on a tool that we believe will change the game for developers, data scientists, and anyone working with models that rely on textual prompts. I'm excited to introduce our new tool: Automated Prompt Engineering (APE). Problem: As many of you know, how you phrase a prompt can significantly impact the results you get from models, especially with sophisticated language models. It often requires numerous iterations to hone in on the right prompt to obtain the desired response. Solution: APE is designed to tackle this exact problem. With APE, you can: - Iterative…
2023
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tl;dr - today i'm launching agents.blue, where you can learn prompting and master working with LLMs, for free, instantly (no sign in required) Last week at Law x LLM Hackathon, I met a lot of amazing engineers, lawyers and more who want to build with LLMs, but they didn’t know how to prompt effectively. The online resources out there are a lot of reading, but not a lot of doing, and in my experience as an engineer and TA, doing is the best way to learn. agents.blue is the free, fast, and interactive tutorial to go from zero to the cutting edge of prompting in under 10 minutes, so you can…
2023 · agents.blue
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Even if you're not a Prompt whiz, you can still get top-notch results just like the pros. This Product will handle internally handle boring And Cognitively demanding prompt Engineering. Just pick a service, fill in the keywords, and get the desired result! Open Source , Free , Privacy Friendly , Crowd Source Prompts, No Login Required. You can submit Features(https://prompt-apps.canny.io/feature-requests?sort=top) and Prompts (https://prompt-apps.canny.io/prompt-conversion?sort=top)
2023 · chatgpt-prompt-apps.com
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As I was playing with the Outlines library (https://outlines-dev.github.io/outlines/), I discussed with my friend Maxime how funny it would be if we set up a way to pair LLMs in chess matches till one wins. The first time I tried it, it required substantial prompt engineering to get some of those LLMs to propose valid moves. Large language models can mostly stay focused and even play rather well; see https://news.ycombinator.com/item?id=37616170 for example. However small language models aren't as easy to convince. Some of those LLMs have seen very little…
2024 · huggingface.co
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Hi, this is my first HN submission so please forgive the rough edges. For this project gathered chess positions from some well-known chess players with a lot of games. (Usually ~25k games and 1M+ positions. The most for any player was GM Aman Hambleton with 1.8M positions indexed.) With each board position I create a probability distribution of moves the player has made from that position. Then, I simply draw from that distribution (with sampling temperature) to choose a move. As long as there's at least one game with a given position, you can keep playing. You'll see that it's pretty easy…
2022 · d2frm2q2a7fq8v.cloudfront.net
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Hi HN, I'm pleased to share Promptspot, an open-source (Apache License 2.0) project that helps automate testing of large language model (LLM) prompts against an array of input data. Modern LLMs offer an enormous amount of leverage if you "teach the bot to fish" — i.e. simply prompt it with both a "system prompt" (which typically doesn't change often) and a dynamic input, which is often application state, search results, recent activity, user profile data, etc. Existing playgrounds and prompt management systems often lack the rigor and flexibility required for this dynamic approach — and as…
2023 · github.com
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