Unit Tests for LangChain aps in 3 lines of code

Hacker News

Everyone who has ever tried to tweak a prompt knows that changing the prompt to make it work on one scenario can lead to break another. Up until now there was no easy solution for this. PromptWatch is a LangChain tracing on steroids and now introducing also Unit tests! Based on annotated previous sessions or prompts, it allows you to replay these inputs with new prompt / model. And just 3 lines of code (more/less) to set it up.

Visit product View on Hacker NewsMay 19, 2023

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, code · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Standardising 'Unit Tests' for Prompts33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Standardising 'Unit Tests' for Prompts

Hacker News3

Writing unit tests in Golang33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Writing unit tests in Golang

Hacker News1

CodeBeaver65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unit tests on autopilot

Product Hunt+109

Own MobX in 65 lines of code51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Own MobX in 65 lines of code

Hacker News12

Implement MFA in two lines of code58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Implement MFA in two lines of code

Hacker News8

Dynamically generate self-signed certs for Go unit tests41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Dynamically generate self-signed certs for Go unit tests

Hacker News1

Writing modern C unit tests with Criterion46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Writing modern C unit tests with Criterion

Hacker News34

Opunit Simple unit tests for servers and containers43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Opunit Simple unit tests for servers and containers

Hacker News15

Writing Maintainable Unit Tests Course39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Writing Maintainable Unit Tests Course

Hacker News2

Wasted hours on Unit tests, so I built VS Code ext for AI tests40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Wasted hours on Unit tests, so I built VS Code ext for AI tests

Hacker News15

Browse all products Analyze your launch