BioLM AI
Python client and SDK for BioLM
Install the package:
pip install biolmaiBasic usage:
from biolmai import biolm
# Encode a single sequence
result = biolm(entity="esm2-8m", action="encode", type="sequence", items="MSILVTRPSPAGEEL")
# Predict a batch of sequences
result = biolm(entity="esmfold", action="predict", type="sequence", items=["SEQ1", "SEQ2"])
# Write results to disk
biolm(entity="esmfold", action="predict", type="sequence", items=["SEQ1", "SEQ2"], output='disk', file_path="results.jsonl")Asynchronous usage:
from biolmai.core.http import BioLMApiClient
import asyncio
async def main():
model = BioLMApiClient("esmfold")
result = await model.predict(items=[{"sequence": "MDNELE"}])
print(result)
asyncio.run(main())Overview
The BioLM Python client provides a high-level, user-friendly interface for interacting with the BioLM API. It supports both synchronous and asynchronous usage, automatic batching, flexible error handling, and efficient processing of biological data.
Main features:
High-level BioLM constructor for quick requests
Sync and async interfaces
Automatic or custom rate limiting/throttling
Schema-based batch size detection
Flexible input formats (single key + list, or list of dicts)
Low memory usage via generators
Flexible error handling (raise, continue, or stop on error)
Universal HTTP client for both sync and async
Features
High-level constructor: Instantly run an API call with a single line.
Sync and async: Use BioLM for sync, or BioLMApiClient for async.
Flexible rate limiting: Use API throttle, disable, or set your own (e.g., ‘1000/second’).
Schema-based batching: Automatically queries API for max batch size.
Flexible input: Accepts a single key and list, or list of dicts, or list of lists for advanced batching.
Low memory: Uses generators for validation and batching.
Error handling: Raise HTTPX errors, continue on error, or stop on first error.
Disk output: Write results as JSONL to disk.
Universal HTTP client: Efficient for both sync and async.
Direct access to schema and batching: Use BioLMApi for advanced workflows, including .schema(), .call(), and ._batch_call_autoschema_or_manual().
Example endpoints and actions:
esm2-8m/encode: Embedding for protein sequences.
esmfold/predict: Structure prediction for protein sequences.
progen2-oas/generate: Sequence generation from a context string.
dnabert2/predict: Masked prediction for protein sequences.
ablang2/encode: Embeddings for paired-chain antibodies.
Free software: Apache Software License 2.0
Documentation: https://docs.biolm.ai
1 maintainer
Metadata
1 maintainer
Release files for biolmai 0.4.0
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