Update app.py

app.py

@@ -1,12 +1,18 @@
+import re
+from pathlib import Path
 import gradio as gr
+
 from evodiff.pretrained import OA_DM_38M, D3PM_UNIFORM_38M, MSA_OA_DM_MAXSUB
 from evodiff.generate import generate_oaardm, generate_d3pm
 from evodiff.generate_msa import generate_query_oadm_msa_simple
-import re
+
 import py3Dmol
+from colabfold.download import download_alphafold_params, default_data_dir
+from colabfold.utils import setup_logging
+from colabfold.batch import get_queries, run, set_model_type
+from colabfold.plot import plot_msa_v2
 
 def a3m_file(file):
-
     return "tmp.a3m"
 
 def make_uncond_seq(seq_len, model_type):
@@ -59,6 +65,41 @@ def display_pdb(path_to_pdb):
                             allowpaymentrequest="" frameborder="0" srcdoc='{x}'></iframe>"""
 '''
 
+def predict_protein(sequence):
+    model_type = "alphafold2_ptm"
+    download_alphafold_params(model_type, Path("."))
+    results = run(
+        queries=queries,
+        result_dir=result_dir,
+        use_templates=use_templates,
+        custom_template_path=custom_template_path,
+        num_relax=0,
+        msa_mode=msa_mode,
+        model_type=model_type,
+        num_models=1,
+        num_recycles=1,
+        recycle_early_stop_tolerance=recycle_early_stop_tolerance,
+        num_seeds=num_seeds,
+        use_dropout=use_dropout,
+        model_order=[1],
+        is_complex=False,
+        data_dir=Path("."),
+        keep_existing_results=False,
+        rank_by="auto",
+        pair_mode=pair_mode,
+        pairing_strategy=pairing_strategy,
+        stop_at_score=float(100),
+        prediction_callback=prediction_callback,
+        dpi=dpi,
+        zip_results=False,
+        save_all=save_all,
+        max_msa=max_msa,
+        use_cluster_profile=use_cluster_profile,
+        input_features_callback=input_features_callback,
+        save_recycles=save_recycles,
+        user_agent="colabfold/google-colab-main",
+    )
+
 usg_app = gr.Interface(
             fn=make_uncond_seq,
             inputs=[