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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

BudgetML is an ideal solution for professionals looking to swiftly launch their models to an endpoint without investing excessive time, money, or effort into mastering the complex end-to-end process. We developed BudgetML in response to the challenge of finding a straightforward and cost-effective method to bring a model into production promptly. Traditional cloud functions often suffer from memory limitations and can become expensive as usage scales, while Kubernetes clusters are unnecessarily complex for deploying a single model. Starting from scratch also requires navigating a myriad of concepts such as SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, and backend servers, which can be overwhelming for the average data scientist. BudgetML directly addresses these hurdles, prioritizing speed, simplicity, and accessibility for developers. It is not intended for comprehensive production environments but serves as a quick and economical way to set up a server efficiently. Ultimately, BudgetML empowers users to focus on their models without the burden of unnecessary complications.

Description

Literal AI is a collaborative platform crafted to support engineering and product teams in the creation of production-ready Large Language Model (LLM) applications. It features an array of tools focused on observability, evaluation, and analytics, which allows for efficient monitoring, optimization, and integration of different prompt versions. Among its noteworthy functionalities are multimodal logging, which incorporates vision, audio, and video, as well as prompt management that includes versioning and A/B testing features. Additionally, it offers a prompt playground that allows users to experiment with various LLM providers and configurations. Literal AI is designed to integrate effortlessly with a variety of LLM providers and AI frameworks, including OpenAI, LangChain, and LlamaIndex, and comes equipped with SDKs in both Python and TypeScript for straightforward code instrumentation. The platform further facilitates the development of experiments against datasets, promoting ongoing enhancements and minimizing the risk of regressions in LLM applications. With these capabilities, teams can not only streamline their workflows but also foster innovation and ensure high-quality outputs in their projects.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Docker Yes 
Google Cloud Platform Yes 
APIFuzzer Yes 
ChatGPT No 
Codestral No 
Codestral Mamba No 
Gemini 2.0 No 
Gemini Enterprise No 
Gemini Nano No 
Gunicorn Yes 
Kubernetes Yes 
Mathstral No 
Ministral 8B No 
Mistral Large No 
Mistral Small No 
OpenAI No 
Pixtral Large No 
Python No 
TypeScript No 

Integrations

Docker Yes 
Google Cloud Platform Yes 
APIFuzzer No 
ChatGPT Yes 
Codestral Yes 
Codestral Mamba Yes 
Gemini 2.0 Yes 
Gemini Enterprise Yes 
Gemini Nano Yes 
Gunicorn No 
Kubernetes No 
Mathstral Yes 
Ministral 8B Yes 
Mistral Large Yes 
Mistral Small Yes 
OpenAI Yes 
Pixtral Large Yes 
Python Yes 
TypeScript Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

ebhy

Website

github.com/ebhy/budgetml

Vendor Details

Company Name

Literal AI

Country

United States

Website

www.literalai.com

Product Features

Alternatives

Alternatives