Update app.py

app.py

@@ -1,10 +1,14 @@
 import gradio as gr
-from evodiff.pretrained import OA_DM_38M, D3PM_UNIFORM_38M
+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
 
+def a3m_file(file):
 
+    return "tmp.a3m"
 
-def make_seq(seq_len, model_type):
+def make_uncond_seq(seq_len, model_type):
     if model_type == "EvoDiff-Seq-OADM 38M":
         checkpoint = OA_DM_38M()
         model, collater, tokenizer, scheme = checkpoint
@@ -17,13 +21,36 @@ def make_seq(seq_len, model_type):
 
     return generated_sequence
 
-# iface = gr.Interface(
-#     fn=make_seq,
-#     inputs=gr.Slider(10, 100),
-#     outputs="text"
-#     )
+def make_cond_seq(seq_len, msa_file, model_type):
+    if model_type == "EvoDiff-MSA":
+        checkpoint = MSA_OA_DM_MAXSUB()
+        model, collater, tokenizer, scheme = checkpoint
+        tokeinzed_sample, generated_sequence  = generate_query_oadm_msa_simple(msa_file, model, tokenizer, n_sequences=64, seq_length=seq_len, device='cpu', selection_type='random')
+
+    return generated_sequence
 
-# iface.launch()
+usg_app = gr.Interface(
+            fn=make_uncond_seq,
+            inputs=[
+                gr.Slider(10, 100, label = "Sequence Length"),
+                gr.Dropdown(["EvoDiff-Seq-OADM 38M", "EvoDiff-D3PM-Uniform 38M"], type="value", label = "Model")
+                ],
+            outputs="text",
+            title = "Unconditional sequence generation",
+            description="Generate a sequence with `EvoDiff-Seq-OADM 38M` (smaller/faster) or `EvoDiff-D3PM-Uniform 38M` (larger/slower) models."
+            )
+
+csg_app = gr.Interface(
+            fn=make_cond_seq,
+            inputs=[
+                gr.Slider(10, 100, label = "Sequence Length"),
+                gr.File(file_types=["a3m"], label = "MSA File"),
+                gr.Dropdown(["EvoDiff-MSA"], type="value", label = "Model")
+                ],
+            outputs="text",
+            title = "Conditional sequence generation",
+            description="Evolutionary guided sequence generation with the `EvoDiff-MSA` model."
+            )
 
 
 with gr.Blocks() as edapp:
@@ -35,23 +62,13 @@ with gr.Blocks() as edapp:
 
             Created By: Microsoft Research [Sarah Alamdari, Nitya Thakkar, Rianne van den Berg, Alex X. Lu, Nicolo Fusi, ProfileAva P. Amini, and Kevin K. Yang]
             
-            Spaces App By: Colby T. Ford
+            Spaces App By: [Colby T. Ford](httos://github.com/colbyford)
             """
         )
     with gr.Row():
-        gr.Markdown(
-            """
-            ## Unconditional sequence generation
-            Generate a sequence with `EvoDiff-Seq-OADM 38M` (smaller) or `EvoDiff-D3PM-Uniform 38M` (larger) models.
-            """)
-        gr.Interface(
-            fn=make_seq,
-            inputs=[
-                gr.Slider(10, 100, label = "Sequence Length"),
-                gr.Dropdown(["EvoDiff-Seq-OADM 38M", "EvoDiff-D3PM-Uniform 38M"], type="value", label = "Model")
-                ],
-            outputs="text"
-            )
+        gr.TabbedInterface([usg_app, csg_app], ["Unconditional sequence generation", "Conditional generation"])
+
+
 
 if __name__ == "__main__":
     edapp.launch()