try hard with api
Browse files- .gitignore +2 -0
- app.py +5 -2
- requirements.txt +2 -1
.gitignore
ADDED
@@ -0,0 +1,2 @@
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venv/
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.env
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app.py
CHANGED
@@ -4,7 +4,7 @@ import io
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import numpy as np
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import os
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import traceback
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import spaces
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from esm.sdk import client
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from esm.sdk.api import ESM3InferenceClient, ESMProtein, GenerationConfig
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from esm.utils.structure.protein_chain import ProteinChain
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@@ -13,6 +13,9 @@ import biotite.structure as bs
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from biotite.structure.io import pdb
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from esm.utils import residue_constants as RC
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# Initialize the model
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token = os.environ.get("ESM_API_TOKEN")
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if not token:
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@@ -165,7 +168,7 @@ def visualize_after_pred(protein: ESMProtein, aligned: ESMProtein):
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view.zoomTo()
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return view
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@spaces.GPU()
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def run_prediction(pdb_file, num_runs, noise_level, num_frames):
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try:
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if pdb_file is None:
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import numpy as np
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import os
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import traceback
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# import spaces
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from esm.sdk import client
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from esm.sdk.api import ESM3InferenceClient, ESMProtein, GenerationConfig
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from esm.utils.structure.protein_chain import ProteinChain
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from biotite.structure.io import pdb
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from esm.utils import residue_constants as RC
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from dotenv import load_dotenv
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load_dotenv()
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# Initialize the model
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token = os.environ.get("ESM_API_TOKEN")
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if not token:
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view.zoomTo()
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return view
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# @spaces.GPU()
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def run_prediction(pdb_file, num_runs, noise_level, num_frames):
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try:
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if pdb_file is None:
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requirements.txt
CHANGED
@@ -7,4 +7,5 @@ pandas
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torch
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numpy
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esm
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biotite
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torch
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numpy
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esm
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biotite
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python-dotenv
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