Initial commit

app.py

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+import bz2
+import shutil
+import tempfile
+from pathlib import Path
+
+import gradio as gr
+import pypythia.msa
+import pypythia.prediction
+import pypythia.predictor
+import pypythia.raxmlng
+
+
+def get_default_raxmlng():
+    version = "1.1.0"
+    uncompressed_raxmlng = Path.home() / f"raxml-ng-v{version}-linux-64"
+    if not uncompressed_raxmlng.exists():
+        compressed_raxmlng = Path(__file__).parent / f"raxml-ng-v{version}-linux-64.bz2"
+        with bz2.BZ2File(compressed_raxmlng) as bz, uncompressed_raxmlng.open(
+            "wb"
+        ) as rax:
+            shutil.copyfileobj(bz, rax)
+    return uncompressed_raxmlng
+
+
+def predict_difficulty(uploaded_file):
+    predictor_file = (
+        Path(pypythia.__file__).parent / "predictors" / "predictor_lgb_v1.0.0.pckl"
+    )
+    predictor = pypythia.predictor.DifficultyPredictor(predictor_file.open("rb"))
+    raxmlng = pypythia.raxmlng.RAxMLNG(
+        shutil.which("raxml-ng") or get_default_raxmlng()
+    )
+    with tempfile.NamedTemporaryFile() as msa_file:
+        uploaded_file.seek(0)
+        shutil.copyfileobj(uploaded_file, msa_file)
+        msa_file.flush()
+        msa = pypythia.msa.MSA(msa_file.name)
+        msa_features = pypythia.prediction.get_all_features(raxmlng, msa)
+        difficulty = predictor.predict(msa_features)
+
+    return difficulty, msa_features
+
+
+pythia_demo = gr.Interface(
+    predict_difficulty,
+    gr.File(label="MSA file (.phy or .msa)"),
+    [
+        gr.Number(label="Difficulty", precision=5),
+        gr.JSON(label="Features used for prediction"),
+    ],
+)
+pythia_demo.launch()

raxml-ng-v1.1.0-linux-64.bz2

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2c246fec86cbc1820b8f9f240adf372c03a39779203821e9e23d8579e2c7ec6a
+size 2287022

requirements.txt

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+git+https://github.com/tschuelia/PyPythia