Update app.py

app.py

@@ -126,6 +126,13 @@ with gr.Blocks() as blocks:
         sampling_steps = gr.Slider(value=200, minimum=0, label="Sampling steps")
         diffusion_samples = gr.Slider(value=1, label="Diffusion samples")
 
+    gr.Examples([
+            ("TOP7",{"chains": [{"class": "protein","sequence": "MGDIQVQVNIDDNGKNFDYTYTVTTESELQKVLNELMDYIKKQGAKRVRISITARTKKEAEKFAAILIKVFAELGYNDINVTFDGDTVTVEGQLEGGSLEHHHHHH","chain": "A"}], "covMods":[]}), 
+            ("ApixacabanBinder", {"chains": [{"class": "protein","sequence": "SVKSEYAEAAAVGQEAVAVFNTMKAAFQNGDKEAVAQYLARLASLYTRHEELLNRILEKARREGNKEAVTLMNEFTATFQTGKSIFNAMVAAFKNGDDDSFESYLQALEKVTAKGETLADQIAKAL","chain": "A"}, {"class":"ligand", "smiles":"COc1ccc(cc1)n2c3c(c(n2)C(=O)N)CCN(C3=O)c4ccc(cc4)N5CCCCC5=O", "chain": "A"}], "covMods":[]}) 
+        ],
+    inputs = [jobname, inp]     
+    )
+
     btn = gr.Button("predict")
 
     btn.click(fn=predict, inputs=[jobname,inp, recycling_steps, sampling_steps, diffusion_samples], outputs=[out],  api_name="predict")