In LLM world, the prompt is the input to the LLM and the output is generated text/image/audio/video. But when it comes to automation using the prompts, there are many problems faced by developers in Production Environments.
- Accuracy: Prompt on generalised LLMs like OpenAI, llama2 offers lower accuracy from 50-90% depends on what kind of prompts.
- Cost: Increasing the accuracy of prompt takes time, data and gpu, and its iterative and costly affair
- Interoperability: Upgrading the underlying llm or moving to differing variants break the prompt accuracy, so maintainnance become a major headache for enginnering teams
- Reusability: Since there is no way to package and share a prompt, developers around the world are reinventing the wheel.
- Knowledge Upgradation: Base LLMs offers have 6-12 old months information.
Overall 80% of developer bandwith and server cost is spend in fighting LLM Selection, Prompt Fine tunning and achieving production level accuracy.
Sugarcane AI is a Prompt IDE that helps solves all of the problems by bringing the Micro Services architecture in the LLM World. Sugarcane AI offers Open source Prompt IDE to build, version, backtest, deploy, share high performance, and ready to use prompts based packages which are available over APIs. All the prompt executions are logged for further dataset creation and It further enables the train the Task Specific LLMs AKA Micro LLms, based on the prompt Package data. These Micro LLMs helps achieve better performance and accuracy at much lower cost. Similar to npm, a prompt package can be listed on registry and can even be sold on marketplace, enables faster development of LLMs apps in a reliable way.
Sugarcane AI is on a mission to upskill/educate 10 million future prompt developers and which will contribute in the prompt package creationa and maintainance. Using these prompt packages, a LLM can be build upto 20x faster.
With a developer-centric approach, the opensource project focuses on solving prompt accuracy problems and enhancing developer productivity by adopting a microservices and collaborative approach for LLM application development. It will ensure performance and reliability through the open-source community of prompt developers worldwide.
*Prompt Package: An npm-like package containing LLM configs, prompt templates, and underlying datasets and examples.
**Micro LLMs: Task-specific Fine-Tuned LLMs trained on smaller and targeted datasets.
Track: AI in education: With this project, we are offering a Prompt IDE which is easy to use playground for prompt enginners beginners and they can create their first prompt App just by writing a prompt.
Github: Prompt IDE: https://github.com/sugarcane-ai/sugarcane-ai/
Demo Video https://sugarcaneai.dev/demo/
Live Demo: https://play.sugarcaneai.dev/
username: demo
pass: demo123
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