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AI · alternatives · 2026

24 alternatives to ChainForge, a visual tool for prompt engineering and LLM evaluation

Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)

ChainForge is a visual, low-code tool designed for prompt engineering and LLM evaluation. It enables users to rapidly discover effective prompts, test their robustness, and evaluate language model performance across… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. ChainForge, a visual tool for prompt engineering and LLM evaluation launched in 2023; newer entries below may have overtaken it.

  1. 1

    PromptForge: Open-source AI prompt engineering workbench with systematic evaluation I built PromptForge after getting frustrated with the manual trial-and-error approach to prompt engineering. Most tools are just text editors, but I wanted something that brings software engineering discipline to prompt development. Key technical features: - AI-assisted prompt generation (stop starting from scratch) - Systematic evaluation engine that auto-generates test suites - Multi-model support (Claude, GPT-4, Azure OpenAI) - Go backend with SQLite for performance and simplicity - One-line Docker…

    2025 · github.com · its alternatives →

  2. 2

    Hey HN! We’re Kevin and Steve. We’re building PromptTools (https://github.com/hegelai/prompttools): open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. Evaluating prompts, LLMs, and vector databases is a painful, time-consuming but necessary part of the product engineering process. Our tools allow engineers to do this in a lot less time. By “evaluating” we mean checking the quality of a model's response for a given use case, which is a combination of testing and benchmarking. As examples: - For generated…

    2023 · github.com · its alternatives →

  3. 3

    Free & fast chain of prompts generator

    2024 · mindpal.space · its alternatives →

  4. 4

    Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…

    2023 · perplexity.vercel.app · its alternatives →

  5. 5

    The low-code platform for testing AI apps

    2024 · langtail.com · its alternatives →

  6. 6

    Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…

    2025 · github.com · its alternatives →

  7. 7

    ErisForge is a Python library designed to modify Large Language Models (LLMs) by applying transformations to their internal layers. Named after Eris, the goddess of strife and discord, ErisForge allows you to alter model behavior in a controlled manner, creating both ablated and augmented versions of LLMs that respond differently to specific types of input. It is also quite useful to perform studies on propaganda and bias in LLMs (planning to experiment with deepseek). Features - Modify internal layers of LLMs to produce altered behaviors. - Ablate or enhance model responses with the…

    2025 · github.com · its alternatives →

  8. 8

    Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…

    2024 · github.com · its alternatives →

  9. 9

    Find your best LLM for a local inference

    2023 · its alternatives →

  10. 10AP

    2023 · promptperfect.jina.ai · its alternatives →

  11. 11

    G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…

    2023 · github.com · its alternatives →

  12. 12
    Twigg▲157

    Hi HN, we’re Jamie and Matti, co-founders of Twigg. During our master’s we continually found the same pain points cropping up when using LLMs. The linear nature of typical LLMs interfaces - like ChatGPT and Claude - made it really easy to get lost without any easy way to visualise or navigate your project. Worst of all, none of them are well suited for long term projects. We found ourselves spending days using the same chat, only for it to eventually break. Transferring context from one chat to another is also cumbersome. We decided to build something more intuitive to the ways humans think.…

    Oct 2025 · twigg.ai · its alternatives →

  13. 13

    One-shot Prompt Engineering Toolkit

    2023 · promptmetheus.com · its alternatives →

  14. 14

    We developed a new framework that enables flexible control of generated text in language models. By combining several models and&#x2F;or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2311.14479. Feedback and potential applications are welcome.

    2023 · github.com · its alternatives →

  15. 15

    The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  16. 16

    The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  17. 17IG

    Data automation and visualization platform for spreadsheet users.

    2024 · columns.ai · its alternatives →

  18. 18RA

    Hey everyone! Along with my team, I've developed a reinforcement learning system that automatically optimizes LLM prompts, complete with a visualization feature to track both prompt structure and learning progress over time. Take a look here: https:&#x2F;&#x2F;nomadic-ml.github.io&#x2F;nomadic&#x2F;cookbooks&#x2F;Nomadic_Promp... Check out our website too:https:&#x2F;&#x2F;www.nomadicml.com&#x2F; In terms of how this visualization works: The RL Prompt Optimizer employs a reinforcement learning framework to iteratively improve prompts used for language model evaluations. At each episode, the…

    2024 · nomadic-ml.github.io · its alternatives →

  19. 19

    Hi HN! Over the last several weekends, I've been building LLMFlows as an alternative to langchain. There's been a lot of discussion on the shortcomings of langchain in the past few weeks, but when I first tried it in March, I thought there are 3 main problems: 1. Too many abstractions 2. Hidden prompts and opinionated logic in chains which makes it hard to customize 3. Hard to debug This inspired me to try and build a framework that solves these 3 issues, and therefore I started building LLFlows with the "philosophy" of being "simple, explicit, and transparent." A few weekends later, I think…

    2023 · github.com · its alternatives →

  20. 20

    Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!

    2023 · github.com · its alternatives →

  21. 21

    Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.

    2024 · github.com · its alternatives →

  22. 22

    A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub

    2023 · github.com · its alternatives →

  23. 23

    It’s written in Python and I call it GoalChain. It lets you build a conversation flow graph that the user traverses. When there’s enough input it spits out a dictionary with the defined fields. Otherwise it will jump state to state as led by the user. It was fun to write, and it’s surprisingly effective if you keep in mind you’re prompt-engineering every string and field name. README.md has a mini-tutorial. Would be cool to get some ideas for how to build it further and what improvements I could make.

    2024 · github.com · its alternatives →

  24. 24

    Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them &#x2F; eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…

    2025 · github.com · its alternatives →

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