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Top 23 TypeScript prompt-engineering Projects
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langfuse
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
I have been spending a lot of time exploring AI Coding Assistants like Amazon Q Developer to see how they can help open source developers, and Ricardo Tasso came up with a great example in how he is using Q Developer to generate deployment configurations for Kubernetes. He has written this up in his post, Creating Deployment Configurations for EKS with Amazon Q so go check it out (you can get started with Amazon Q Developer for free by registering your Builder ID here). Langfuse is an open source LLM engineering platform that helps teams collaboratively develop, monitor, evaluate, and debug AI applications. AWS Community Builder Matsuda shows you how you can deploy this, using CDK to make it simple. If this sounds like something you are interested in, go read the post Self-Hosting Langfuse v3 on AWS Using CDK.
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SurveyJS
SurveyJS: Build JSON-Driven Surveys and Forms with Full Data Control. Add the SurveyJS UI components to your JS app (React/Angular/Vue3). Securely collect and analyze data without sending it to 3rd-party servers. Fully customizable, works with any backend, and ideal for data-heavy apps. Learn more.
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View the Project on GitHub
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12-factor-agents
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
Project mention: Show HN: Radkit – Build reliable AI agents with Rust | news.ycombinator.com | 2025-11-13We (me and my co-founder) have been working on this library for a while and would love to get your thoughts.
github.com/agents-sh/radkit
radkit.rs/getting-started/
Most of the agent librararies out there just adds a huge prompt, put all the tool definitions and call the LLM on a loop hope and for the best.
This is not a way to build reliable ai agents. A better way to build ai agents is described in 12-factor agents by Dex Horthy here.
https://www.youtube.com/watch?v=8kMaTybvDUw
https://github.com/humanlayer/12-factor-agents
Another limitations of current agentic frameworks is their support for interoperability among agents is very limited.
Google came up with https://a2a-protocol.org/latest/ (now under linux foundation) to address this, but the agent frameworks trying to do as much as possible and keep the end users locked into their "ecosystem" instead of supporting such protocols.
Everyone is so focused on MCP for some reason. (no hate for mcp, radkit supports mcp as well).
We belive in an agentic future where businesses expose ai agents and not mcp servers or rest apis. If you build an agent using radkit, it is a2a-protocol compliant from the get go.
With all of this in mind, we are building `radkit`.
It is still early stages. But we have reached a milestone and wanted to share with the community.
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promptfoo
Test your prompts, agents, and RAGs. AI Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.
Project mention: Ask HN: What Are You Working On? (December 2025) | news.ycombinator.com | 2025-12-14Working on promptfoo, an open-source (MIT) CLI and framework for eval-ing and red-teaming LLM apps. Think of it like pytest but for prompts - you define test cases, run evals against any model (OpenAI, Anthropic, local models, whatever), and catch regressions before they hit prod.
Currently building out support for multi-agent evals, better tracing, voice, and static code analysis for AI security use cases. So many fun sub-problems in this space - LLM testing is deceptively hard.
If you end up checking it out and pick up an issue, I'll happily send swag. We're also hiring if you want to work on this stuff full-time.
https://github.com/promptfoo/promptfoo
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helicone
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
Yes, Java SDKs are critical. But you don't need to rebuild entire orchestration engines just to write agents in Java. The ecosystem already has platforms solving the hard problems: memory (Zep, Mem0, LangMem), tools (specialized platforms), vectors (Pinecone, Weaviate, Qdrant), observability (LangSmith, Helicone, Langfuse). Integrate, don't rebuild.
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pezzo
🕹️ Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more.
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Stream
Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
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OpenPipe | ML & Full-Stack Engineers | Full-time | Seattle, WA (ONSITE) | https://openpipe.ai/ | Highly competitive pay + equity
We've built the world's best fine-tuning platform in just over a year. First to launch self-service preference tuning, integrated evals/data prep/fine-tuning, and self-service learning from human feedback.
Our customers range from fast-growing startups to Fortune 500s. We're growing 40% MoM and have achieved this with a team of just 5 engineers, including the founders.
Seeking:
- ML Engineers: Help advance our fine-tuning capabilities. (We have thousands of datasets and evals; testing new ideas is really easy!)
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langwatch
The open LLM Ops platform - Traces, Analytics, Evaluations, Datasets and Prompt Optimization ✨
Project mention: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production | news.ycombinator.com | 2025-07-30Hey! I work for the LLM Ops platform LangWatch and I've been working on building out our Go support the past few months as a little hobby of mine (I hope more people adopt this, so I can spent more of my working hours on this ).
If you're interested, we're an LLM Ops platform, and our Go SDK has full support for OpenAI, and any OpenAI compatible endpoints, as well as some nice OpenTelemetry tracing support too.
https://github.com/langwatch/langwatch/tree/main/sdk-go
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aide
Conquer Any Code in VSCode: One-Click Comments, Conversions, UI-to-Code, and AI Batch Processing of Files! 在 VSCode 中征服任何代码：一键注释、转换、UI 图生成代码、AI 批量处理文件！💪 (by nicepkg)
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langtrace
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊
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Magick
Magick is a cutting-edge toolkit for a new kind of AI builder. Make Magick with us! (by Oneirocom)
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gateway
The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for calling more than 200+ LLMs. (by adaline)
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prompt-tower
Context management for long-context LLMs, agents, and vibe coding. Instantly build context for an entire repo, selected files, folders, and GitHub issues to generate structured AI-XML context with real-time token counting.
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Raycast-PromptLab
A Raycast extension for creating powerful, contextually-aware AI commands using placeholders, action scripts, selected files, and more.
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- Project mention: Show HN: Open-source AI Retool, where AI does the tooling | news.ycombinator.com | 2025-05-21
- Project mention: JSON River – Parse JSON incrementally as it streams in | news.ycombinator.com | 2025-10-08
Thanks for sharing!
Roughly how does it compare with https://github.com/promplate/partial-json-parser-js ?
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).
TypeScript prompt-engineering discussion
TypeScript prompt-engineering related posts
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Measuring Political Bias in Claude
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Show HN: EchoMode – A stability layer that prevents persona drift in LLMs
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Reproducible LLM Benchmarking: GPT-5 vs Grok-4 with Promptfoo
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Open-sourced my prompt management tool for LLM-powered apps
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Show HN: Open-sourced my prompt management tool for LLM-powered apps
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Revolutionize Your AI Workflow with Prompt Optimizer!
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Mastering AI-Assisted Software Development: From Prompts to Production-Ready Code
- A note from our sponsor - InfluxDB www.influxdata.com | 23 Dec 2025
Index
What are some of the best open-source prompt-engineering projects in TypeScript? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | langfuse | 19,423 |
| 2 | prompt-optimizer | 17,978 |
| 3 | 12-factor-agents | 17,080 |
| 4 | promptfoo | 9,474 |
| 5 | helicone | 4,841 |
| 6 | pezzo | 3,166 |
| 7 | ChainForge | 2,900 |
| 8 | genaiscript | 2,859 |
| 9 | OpenPipe | 2,754 |
| 10 | langwatch | 2,695 |
| 11 | aide | 2,666 |
| 12 | ChatGPT-Free-Prompt-List | 2,267 |
| 13 | langtrace | 1,081 |
| 14 | tutor-gpt | 869 |
| 15 | Magick | 826 |
| 16 | gateway | 567 |
| 17 | prompt-tower | 326 |
| 18 | agentmark | 320 |
| 19 | Raycast-PromptLab | 307 |
| 20 | latent-browser | 274 |
| 21 | oneShotCodeGen | 247 |
| 22 | partial-json-parser-js | 195 |
| 23 | promptclip | 95 |
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