Alternatives
Products that do what LLM prompt template to build backend APIs faster does
- 1FB
2019 · fastapi.tiangolo.com
- 2PR
2017 · github.com
- 3AS
2025 · github.com
- 4GO
2016 · grapesjs.com
- 5CA
2020 · canonic.dev
- 6

- 7PS
2024 · promptql.hasura.io
- 8IM
2022 · getquickbase.com
- 9IB
2025 · interlify.com
- 10LL
2023 · github.com
- 11BF
2023 · e2b.dev
- 12LS
2023 · github.com
- 13KA
Knit was created to solve pains of other LLM playgrounds. Some of the highlights: - Smart prompt builder, create prompt with simple requirement and few shot learning, fast and effortlessly. - Function call simulation, visualize the function callings and you can also setup a mocked value to return. - Support OpenAI/Anthropic/Azure models. - Manage prompts with projects and members. - And so much more! I have been developing Knit by myself for over 4 months now, and am looking for ways to improve it. Any feedback is appreciated.
2023 · promptknit.com
- 14AS
2025 · github.com
- 15LB
For the past few months I've been building a lot of things with LLMs (GPT-3, Codex, etc.) as I've been trying to push them to their limits (especially towards applying them to the tabular data domain) When working on this, I've found there are some common patterns for solving problems (templating, chaining, functional-programming style operations, etc.) As I've iterated, I've come to believe that a functional style interface is likely going to power a new wave of systems I'm calling "prompt-machines"(systems where the core new unit of work is a "named" LLM prompt, extending the "function"…
2022 · github.com
- 16JF
2020 · turbovar.com
- 17IM
2019 · github.com
- 18PL
2023 · github.com
- 19AT
2020 · specstemplate.com
- 20QT
2017 · hasura.github.io
- 21HP
Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai
- 22PN
2018 · github.com
- 23SF
2024 · github.com
- 24LB
2025 · github.com
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