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Description
Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications.
Observability: Incorporate Langfuse into your app to start ingesting traces.
Langfuse UI : inspect and debug complex logs, user sessions and user sessions
Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse
Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports
Evals: Calculate and collect scores for your LLM completions
Experiments: Track app behavior and test it before deploying new versions
Why Langfuse?
- Open source
- Models and frameworks are agnostic
- Built for production
- Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents
- Use GET to create downstream use cases and export the data
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
Integrations
LiteLLM
Apolo
Aporia
Azure Machine Learning
Databricks Data Intelligence Platform
Determined AI
HoneyHive
Hugging Face
Kedro
Ludwig
Integrations
LiteLLM
Apolo
Aporia
Azure Machine Learning
Databricks Data Intelligence Platform
Determined AI
HoneyHive
Hugging Face
Kedro
Ludwig
Pricing Details
$29/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
Langfuse
Founded
2023
Country
Germany
Website
langfuse.com
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