airalogy
The world's first universal framework for data digitization and automation
Key Features
Airalogy lets you create fully custom protocols (Airalogy Protocols) for defining how data is collected, validated, and processed.
| Area | Highlights |
|---|---|
| Airalogy Markdown (AIMD) | Define rich, custom data fields directly in Markdown—variables ({{var}}), procedural steps ({{step}}), checkpoints ({{check}}), and more. |
| Model-based Data Validation | Attach a model to every protocol for strict type checking—supports datetime, enums, nested models, lists, etc.; and Airalogy-specific built-in types (UserName, CurrentTime, AiralogyMarkdown, file IDs, ...). |
| Assigner for Auto-Computation | Use the declarative @assigner decorator to compute field values automatically. |
Requirements
Python ≥ 3.13
Installation
pip install airalogy
Release and PyPI publishing steps for maintainers are documented in RELEASING.md.
Quick Start
Use one typed AIMD
protocol.aimd
# Serum sample collection
Participant: {{var|subject_name: UserName, title="Participant name"}}
Collection time: {{var|collected_at: CurrentTime}}
Serum volume (mL): {{var|serum_volume: float, gt=0}}
Ice-bath time (min): {{var|ice_time: int = 0, ge=0}}
Sample photo: {{var|sample_photo: FileIdPNG, description="Upload collection photo"}}
{{step|collect}} Collect serum sample as per standard procedure.
{{step|verify_labels, 2}} Verify labels and IDs.
{{step|ice_hold, 2, duration="10m", timer="countdown"}} Immediately place sample on ice.
{{check|info_confirmed}} Confirm details and metadata.
- Run
airalogy checkto validate the AIMD and use it directly. - Need an explicit model file?
airalogy generate_model protocol.aimd -o model.pyauto-generates the Pydantic model that matches these types.
Extended: add model and assigner
protocol/
├─ protocol.aimd # Airalogy Markdown
├─ model.py # Optional: Define data validation model
└─ assigner.py # Optional: Define auto-computation logic
protocol.aimd
# Reagent preparation
Solvent name: {{var|solvent_name}}
Target solution volume (L): {{var|target_solution_volume}}
Solute name: {{var|solute_name}}
Solute molar mass (g/mol): {{var|solute_molar_mass}}
Target molar concentration (mol/L): {{var|target_molar_concentration}}
Required solute mass (g): {{var|required_solute_mass}}
model.py
from pydantic import BaseModel, Field
class VarModel(BaseModel):
solvent_name: str
target_solution_volume: float = Field(gt=0)
solute_name: str
solute_molar_mass: float = Field(gt=0)
target_molar_concentration: float = Field(gt=0)
required_solute_mass: float = Field(gt=0)
assigner.py
from airalogy.assigner import AssignerResult, assigner
@assigner(
assigned_fields=["required_solute_mass"],
dependent_fields=[
"target_solution_volume",
"solute_molar_mass",
"target_molar_concentration",
],
mode="auto",
)
def calculate_required_solute_mass(dependent_fields: dict) -> AssignerResult:
target_solution_volume = dependent_fields["target_solution_volume"]
solute_molar_mass = dependent_fields["solute_molar_mass"]
target_molar_concentration = dependent_fields["target_molar_concentration"]
required_solute_mass = (
target_solution_volume * target_molar_concentration * solute_molar_mass
)
return AssignerResult(
assigned_fields={
"required_solute_mass": required_solute_mass,
},
)
Load packaged protocol examples
Official Airalogy Protocol examples are included in the Python package so downstream apps can reuse them without depending on a local clone of the Airalogy repository:
from airalogy.examples.protocols import get_protocol_example
example = get_protocol_example("meeting_notes_en")
metadata = example.load_metadata()
aimd = example.read_aimd()
Command Line Interface
Airalogy provides a CLI tool for common operations. After installation, you can use the airalogy command:
$ airalogy --help
usage: airalogy [-h] [-v] {check,c,generate_model,gm,generate_assigner,ga,pack,unpack,inspect,validate,import-records,ir} ...
Airalogy CLI - Tools for Airalogy
positional arguments:
{check,c,generate_model,gm,generate_assigner,ga,pack,unpack,inspect,validate,import-records,ir}
Available commands
check (c) Check AIMD syntax
generate_model (gm)
Generate models
generate_assigner (ga)
Generate Assigner
pack Pack protocol directories or record JSON files into a single-file archive
unpack Unpack an Airalogy archive
inspect Inspect an Airalogy archive
validate Validate an Airalogy archive
import-records (ir)
Import batch data into Airalogy Record JSON
options:
-h, --help show this help message and exit
-v, --version show program's version number and exit
Syntax Checking
Check AIMD syntax:
# Check default protocol.aimd file
airalogy check
# Check specific AIMD file
airalogy check my_protocol.aimd
# Using alias
airalogy c my_protocol.aimd
Model Generation
Generate VarModel from AIMD file:
# Generate model.py from protocol.aimd
airalogy generate_model
# Generate with custom output file
airalogy generate_model my_protocol.aimd -o my_model.py
# Using alias
airalogy gm my_protocol.aimd -o custom_model.py
Assigner Extraction
Extract inline assigner code blocks into assigner.py:
# Generate assigner.py from protocol.aimd (and strip inline blocks)
airalogy generate_assigner
# Using alias
airalogy ga my_protocol.aimd -o assigner.py
Single-file Archives
Airalogy uses one unified archive suffix, .aira. The concrete payload type is stored in the internal manifest as kind, for example protocol or records.
Pack a protocol directory into a shareable .aira file:
airalogy pack ./my_protocol -o my_protocol.aira
Pack multiple protocol directories into one protocol bundle without records:
airalogy pack ./protocol_a ./protocol_b -o protocols.aira
Pack one or more record JSON files into a .aira file:
airalogy pack ./record.json ./record-history.json -o records.aira
If you want the record bundle to carry the related protocol definition as well, embed the protocol directory:
airalogy pack ./record.json -o record_bundle.aira --protocol-dir ./my_protocol
If Records reference local file payloads, embed them through a file payload spec:
airalogy pack ./record.json -o record_bundle.aira --file-payload ./files.json
Relative path, local_path, or file_path values inside files.json are resolved relative to that spec file.
Unpack either archive type:
airalogy unpack ./my_protocol.aira -o ./extracted_protocol
airalogy unpack ./record_bundle.aira -o ./extracted_bundle
Inspect or validate an archive without extracting it:
airalogy inspect ./record_bundle.aira
airalogy inspect ./record_bundle.aira --json
airalogy validate ./record_bundle.aira
airalogy validate ./record_bundle.aira --json
Inspect or validate Record JSON before packaging:
airalogy record inspect ./record.json
airalogy record validate ./record.json
airalogy record validate ./record.json --protocol-dir ./my_protocol
Notes:
- Protocol archives preserve the original protocol directory layout, including
files/. - Protocol bundle archives can contain multiple Protocol directories without requiring any Record payloads.
- Record archives accept JSON files containing either one record object or a list of record objects.
- All archive kinds use the same
.airasuffix; inspect_airalogy_archive/manifest.jsonto determine whether the payload is a single protocol archive, a protocols bundle, or a record bundle. - New archives include SHA-256 hashes for packed records and protocol files so readers can detect tampering.
- Protocol packing excludes
.envand common cache artifacts by default so local secrets are not bundled accidentally. - Record archives bundle JSON records, optional embedded protocol directories, and optional local file payloads under
blobs/. - Remote Airalogy file IDs or OSS objects are not downloaded automatically; exporters should download those bytes first, then pass local paths through
--file-payload. - The public manifest schema is available at
schemas/aira/manifest.v1.schema.json. - The public Record schema is available at
schemas/aira/record.v1.schema.json. - Browser users can open
.airafiles locally with the Airalogy Reader app inapps/aira-reader; it parses the archive in the browser and does not upload file content. - Ready-to-open example archives for Reader testing live in
examples/aira/.
Document Conversion (MarkItDown)
Airalogy provides a unified API to convert documents into Markdown.
pip install "airalogy[markitdown]"
# or (uv)
uv add "airalogy[markitdown]"
from airalogy.convert import to_markdown
print(to_markdown("report.pdf", backend="markitdown").text)
See docs: docs/airalogy/en/apis/convert.md / docs/airalogy/zh/apis/convert.md.
Development Setup
We use uv for environment management and build, ruff for lint/format.
setup project environment:
uv sync
Install all optional backends (extras) as well:
uv sync --all-extras
Or install a specific extra (example: markitdown):
uv sync --extra markitdown
Testing
uv run pytest
License
Apache 2.0
Cite This Framework
@misc{yang2025airalogyaiempowereduniversaldata,
title={Airalogy: AI-empowered universal data digitization for research automation},
author={Zijie Yang and Qiji Zhou and Fang Guo and Sijie Zhang and Yexun Xi and Jinglei Nie and Yudian Zhu and Liping Huang and Chou Wu and Yonghe Xia and Xiaoyu Ma and Yingming Pu and Panzhong Lu and Junshu Pan and Mingtao Chen and Tiannan Guo and Yanmei Dou and Hongyu Chen and Anping Zeng and Jiaxing Huang and Tian Xu and Yue Zhang},
year={2025},
eprint={2506.18586},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2506.18586},
}
Metadata
Release files for airalogy 0.17.0
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| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| airalogy-0.17.0-py3-none-any.whl | Python 3 | none | any | Details for airalogy-0.17.0-py3-none-any.whl |
Total release size: 500.6 kB
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