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Average Ratings 0 Ratings

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ease
features
design
support

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Description

LLM Gateway is a completely open-source, unified API gateway designed to efficiently route, manage, and analyze requests directed to various large language model providers such as OpenAI, Anthropic, and Gemini Enterprise Agent Platform, all through a single, OpenAI-compatible endpoint. It supports multiple providers, facilitating effortless migration and integration, while its dynamic model orchestration directs each request to the most suitable engine, providing a streamlined experience. Additionally, it includes robust usage analytics that allow users to monitor requests, token usage, response times, and costs in real-time, ensuring transparency and control. The platform features built-in performance monitoring tools that facilitate the comparison of models based on accuracy and cost-effectiveness, while secure key management consolidates API credentials under a role-based access framework. Users have the flexibility to deploy LLM Gateway on their own infrastructure under the MIT license or utilize the hosted service as a progressive web app, with easy integration that requires only a change to the API base URL, ensuring that existing code in any programming language or framework, such as cURL, Python, TypeScript, or Go, remains functional without any alterations. Overall, LLM Gateway empowers developers with a versatile and efficient tool for leveraging various AI models while maintaining control over their usage and expenses.

Description

MLflow is an open-source suite designed to oversee the machine learning lifecycle, encompassing aspects such as experimentation, reproducibility, deployment, and a centralized model registry. The platform features four main components that facilitate various tasks: tracking and querying experiments encompassing code, data, configurations, and outcomes; packaging data science code to ensure reproducibility across multiple platforms; deploying machine learning models across various serving environments; and storing, annotating, discovering, and managing models in a unified repository. Among these, the MLflow Tracking component provides both an API and a user interface for logging essential aspects like parameters, code versions, metrics, and output files generated during the execution of machine learning tasks, enabling later visualization of results. It allows for logging and querying experiments through several interfaces, including Python, REST, R API, and Java API. Furthermore, an MLflow Project is a structured format for organizing data science code, ensuring it can be reused and reproduced easily, with a focus on established conventions. Additionally, the Projects component comes equipped with an API and command-line tools specifically designed for executing these projects effectively. Overall, MLflow streamlines the management of machine learning workflows, making it easier for teams to collaborate and iterate on their models.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure Data Science Virtual Machines
Azure Marketplace
Comet LLM
Cranium
Gemini Enterprise Agent Platform
Google AI Studio
Groq
Keras
LiteLLM
Microsoft 365
OpenMetadata
PHP
Ragas
Ray
Robust Intelligence
Ruby
TypeScript
Unity Catalog
lakeFS
neptune.ai

Integrations

Azure Data Science Virtual Machines
Azure Marketplace
Comet LLM
Cranium
Gemini Enterprise Agent Platform
Google AI Studio
Groq
Keras
LiteLLM
Microsoft 365
OpenMetadata
PHP
Ragas
Ray
Robust Intelligence
Ruby
TypeScript
Unity Catalog
lakeFS
neptune.ai

Pricing Details

$50 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

LLM Gateway

Country

United States

Website

llmgateway.io

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

Product Features

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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