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Easily log, connect and observe any parts of your AI Systems from experiments to production to prompts to AI system monitoring.
AimStack offers enterprise support that's beyond core AimOS. Contact via [email protected] e-mail.
About β’ Demos β’ Default logging apps β’ Quick Start β’ Documentation β’ Examples β’ Community β’ Blog β’
AimOS is an open-source operating system for logs. With AimOS you can build, run and combine any kind of logging applications - experiment tracking, production monitoring, AI System (LLM-based) monitoring, usage monitoring etc.
The Logging applications are typically a combination of these components:
- The types and relationships of the data being logged
- The observability UI over the data logged
- Automations over the data logged
AimOS comes installed with a number of default logging apps:
- Base App - a basic generic log exploration and the logging primitives
- AI Experiment Tracking App - log and explore your machine learning experiments. Includes integrations with the majority of leading ML frameworks.
- AI Systems Tracing and Debugging Apps - a combination of variety of apps that log from langchain to llamaindex traces all in one place.
Apart from running the logging apps, AimOS comes with explorers and reports.
- Explorers are advanced logs comparison tools for specific kind of logs - they allow to compare 1000s of sessions of metrics, images, text, audio and other types of data.
- Reports are embedded knowledge-base that operate with the apps and explorers seamlessly to enable capture the knowledge built on top of the logged data from the observations through AimOS apps and explorers.
With the rise of AI Systems and the challenges it brings forward, logging apps are going to be a crucial part of the software.
Our mission is to democratize developer tools for building AI.
A general observability over anything logged with AimOS.
Visualize all the logs ever logged with AimOS for the given project πΊοΈ |
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Base types to log common artifacts such as Images, Audio objects, Figures, Metrics |
High-level overview of the logs, the types logged and the respective sessions/ containers |
Deep-dive into each type of the log |
Log Metadata Across Your ML Pipeline πΎ | Visualize & Compare Metadata via UI π |
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Run ML Trainings Effectively β‘ | Organize Your Experiments ποΈ |
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Log Inputs, Outputs and Actions of Executions π€ | Visualize & Compare Executions Steps via UI π |
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Check out live AimOS demos NOW to see it in action.
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AimOS comes pre-installed with a wide variety of apps. Here is the full list:
App Name | Description | Category | Docs | Source |
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base | Base AimOS app for general observability over anything logged with AimOS. Includes base types to log common artifacts, such as Image, Audio object, Figure, Metric. | Base | docs | source |
docs | Use this AimOS app to access AimOS docs. | Docs | - | source |
langchain_debugger | Debugger for LangChain that logs LLMs prompts and generations, tools inputs/outputs, and chains metadata. | AI Systems Tracing | docs | source |
llamaindex_observer | Debugger and observer for LlamaIndex. Logs metadata like retrieval nodes, queries and responses, embeddings chunks, etc. | AI Systems Tracing | docs | source |
experiment_tracker | App for tracking and exploring ML experiments. Integrations with various ML libraries, including Acme, CatBoost, fastai, Hugging Face Transformers, Keras, Keras Tuner, LightGBM, MXNet, Optuna, PaddlePaddle, PyTorch Ignite, SDB3, and XGBoost. | Experiment Tracking | docs | source |
Follow the steps below to get started with AimOS.
pip3 install aimos
from aimstack.base import Run, Metric
# Initialize a new run
run = Run()
# Log run parameters
run["hparams"] = {
"learning_rate": 0.001,
"batch_size": 32,
}
# Init a metric
metric = Metric(run, name='loss', context={'subset': 'training'})
for i in range(1000):
metric.track(i, epoch=1)
aimos server
aimos ui
Add AimOS badge to your README, if you've enjoyed using AimOS in your work:
[![AimOS](https://img.shields.io/badge/powered%20by-AimOS-%231473E6)](https://github.com/aimhubio/aimos)
Considering contibuting to AimOS? To get started, please take a moment to read the CONTRIBUTING.md guide.
Join AimOS contributors by submitting your first pull request. Happy coding! π
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