Update app.py

app.py

@@ -439,51 +439,7 @@ def toggle_secondary_structure(choice):
     elif choice == "explicit":
         return gr.update(visible=False, value=None),gr.update(visible=False, value=None),gr.update(visible=False, value=None),gr.update(visible=True, value=None)
 
-def generate_hero(name, strength, flexibility, speed, defense, size, abilities):
-    try:
-        # protein_diffusion_model 호출하여 마지막 결과 얻기
-        generator = protein_diffusion_model(
-            sequence=None,
-            seq_len=size,
-            helix_bias=flexibility,
-            strand_bias=strength,
-            loop_bias=speed,
-            secondary_structure=None,
-            aa_bias=None,
-            aa_bias_potential=None,
-            num_steps="25",
-            noise="normal",
-            hydrophobic_target_score=str(-defense),
-            hydrophobic_potential="2",
-            contigs=None,
-            pssm=None,
-            seq_mask=None,
-            str_mask=None,
-            rewrite_pdb=None
-        )
-        
-        # 마지막 결과만 가져오기
-        final_result = None
-        for result in generator:
-            final_result = result
-            
-        if final_result is None:
-            raise Exception("생성 결과가 없습니다")
-            
-        # 능력치 계산
-        stats = calculate_hero_stats(flexibility, strength, speed, defense)
-        
-        # 결과 반환 (3D 구조 제외)
-        return (
-            create_radar_chart(stats),  # 능력치 차트
-            generate_hero_description(name, stats, abilities)  # 히어로 설명
-        )
-    except Exception as e:
-        print(f"Error in generate_hero: {str(e)}")
-        return (
-            None,
-            f"에러: {str(e)}"
-        )
+
 
 def create_radar_chart(stats):
     # 레이더 차트 생성 로직
@@ -522,173 +478,64 @@ def generate_hero_description(name, stats, abilities):
     """
     return description
 
-# Gradio 인터페이스 수정
-with gr.Blocks(theme='ParityError/Interstellar') as demo:
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("# 🦸‍♂️ 슈퍼히어로 단백질 만들기")
+def combined_generation(name, strength, flexibility, speed, defense, size, abilities,
+                       sequence, seq_len, helix_bias, strand_bias, loop_bias, 
+                       secondary_structure, aa_bias, aa_bias_potential, 
+                       num_steps, noise, hydrophobic_target_score, hydrophobic_potential,
+                       contigs, pssm, seq_mask, str_mask, rewrite_pdb):
+    try:
+        # protein_diffusion_model 실행
+        generator = protein_diffusion_model(
+            sequence=None,
+            seq_len=size,  # 히어로 크기를 seq_len으로 사용
+            helix_bias=flexibility,  # 히어로 유연성을 helix_bias로 사용
+            strand_bias=strength,    # 히어로 강도를 strand_bias로 사용
+            loop_bias=speed,         # 히어로 스피드를 loop_bias로 사용
+            secondary_structure=None,
+            aa_bias=None,
+            aa_bias_potential=None,
+            num_steps="25",
+            noise="normal",
+            hydrophobic_target_score=str(-defense),  # 히어로 방어력을 hydrophobic score로 사용
+            hydrophobic_potential="2",
+            contigs=None,
+            pssm=None,
+            seq_mask=None,
+            str_mask=None,
+            rewrite_pdb=None
+        )
+        
+        # 마지막 결과 가져오기
+        final_result = None
+        for result in generator:
+            final_result = result
             
-            with gr.Tabs():
-                with gr.TabItem("히어로 디자인"):
-                    # 히어로 기본 정보
-                    hero_name = gr.Textbox(label="히어로 이름", placeholder="당신의 히어로 이름을 지어주세요!")
-                    
-                    # 능력치 설정
-                    gr.Markdown("### 💪 히어로 능력치 설정")
-                    with gr.Row():
-                        strength = gr.Slider(minimum=0.0, maximum=0.05, label="💪 초강력(근력)", value=0.02)
-                        flexibility = gr.Slider(minimum=0.0, maximum=0.05, label="🤸‍♂️ 유연성", value=0.02)
-                    
-                    with gr.Row():
-                        speed = gr.Slider(minimum=0.0, maximum=0.20, label="⚡ 스피드", value=0.1)
-                        defense = gr.Slider(minimum=-10, maximum=10, label="🛡️ 방어력", value=0)
-                    
-                    # 히어로 크기 설정
-                    hero_size = gr.Slider(minimum=50, maximum=200, label="히어로 크기", value=100)
-                    
-                    # 특수 능력 설정
-                    with gr.Accordion("🌟 특수 능력", open=False):
-                        special_ability = gr.CheckboxGroup(
-                            choices=["자가 회복", "원거리 공격", "방어막 생성"],
-                            label="���수 능력 선택"
-                        )
-                    
-                    # 생성 버튼
-                    create_btn = gr.Button("히어로 생성!", variant="primary")
-
-                with gr.TabItem("Inputs"):
-                    gr.Markdown("""## INPUTS""")
-                    gr.Markdown("""#### Start Sequence
-                                Specify the protein length for complete unconditional generation, or scaffold a motif (or your name) using the custom sequence input""")
-                    seq_opt = gr.Radio(["protein length","custom sequence"], label="How would you like to specify the starting sequence?", value='protein length')
-
-                    sequence = gr.Textbox(label="custom sequence", lines=1, placeholder='AMINO ACIDS: A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y\n  MASK TOKEN: X', visible=False)
-                    seq_len = gr.Slider(minimum=5.0, maximum=250.0, label="protein length", value=100, visible=True)
-                    
-                    seq_opt.change(fn=toggle_seq_input,
-                                            inputs=[seq_opt],
-                                            outputs=[seq_len, sequence],
-                                            queue=False)
-
-                    gr.Markdown("""### Optional Parameters""")
-                    with gr.Accordion(label='Secondary Structure',open=True):
-                        gr.Markdown("""Try changing the sliders or inputing explicit secondary structure conditioning for each residue""")
-                        sec_str_opt = gr.Radio(["sliders","explicit"], label="How would you like to specify secondary structure?", value='sliders')
-
-                        secondary_structure = gr.Textbox(label="secondary structure", lines=1, placeholder='HELIX = H  STRAND = S  LOOP = L  MASK = X(must be the same length as input sequence)', visible=False)
-                        
-                        with gr.Column():
-                            helix_bias = gr.Slider(minimum=0.0, maximum=0.05, label="helix bias", visible=True)
-                            strand_bias = gr.Slider(minimum=0.0, maximum=0.05, label="strand bias", visible=True)
-                            loop_bias = gr.Slider(minimum=0.0, maximum=0.20, label="loop bias", visible=True)
-                    
-                        sec_str_opt.change(fn=toggle_secondary_structure,
-                                                inputs=[sec_str_opt],
-                                                outputs=[helix_bias,strand_bias,loop_bias,secondary_structure],
-                                                queue=False)
-                        
-                    with gr.Accordion(label='Amino Acid Compositional Bias',open=False):
-                        gr.Markdown("""Bias sequence composition for particular amino acids by specifying the one letter code followed by the fraction to bias. This can be input as a list for example: W0.2,E0.1""")
-                        with gr.Row():
-                            aa_bias = gr.Textbox(label="aa bias", lines=1, placeholder='specify one letter AA and fraction to bias, for example W0.1 or M0.1,K0.1' )
-                            aa_bias_potential = gr.Textbox(label="aa bias scale", lines=1, placeholder='AA Bias potential scale (recomended range 1.0-5.0)')
-
-                    with gr.Accordion(label='Hydrophobic Bias',open=False):
-                        gr.Markdown("""Bias for or against hydrophobic composition, to get more soluble proteins, bias away with a negative target score (ex. -5)""")
-                        with gr.Row():
-                            hydrophobic_target_score = gr.Textbox(label="hydrophobic score", lines=1, placeholder='hydrophobic score to target (negative score is good for solublility)')
-                            hydrophobic_potential = gr.Textbox(label="hydrophobic potential scale", lines=1, placeholder='hydrophobic potential scale (recomended range 1.0-2.0)')
-                    
-                    with gr.Accordion(label='Diffusion Params',open=False):
-                        gr.Markdown("""Increasing T to more steps can be helpful for harder design challenges, sampling from different distributions can change the sequence and structural composition""")
-                        with gr.Row():
-                            num_steps = gr.Textbox(label="T", lines=1, placeholder='number of diffusion steps (25 or less will speed things up)')
-                            noise = gr.Dropdown(['normal','gmm2 [-1,1]','gmm3 [-1,0,1]'], label='noise type', value='normal')
-
-                with gr.TabItem("Motif Selection"):
-                    gr.Markdown("""### Motif Selection Preview""")
-                    gr.Markdown('Contigs explained: to grab residues (seq and str) on a pdb chain you will provide the chain letter followed by a range of residues as indexed in the pdb file for example (A3-10) is the syntax to select residues 3-10 on chain A (the chain always needs to be specified). To add diffused residues to either side of this motif you can specify a range or discrete value without a chain letter infront. To add 15 residues before the motif and 20-30 residues (randomly sampled) after use the following syntax: 15,A3-10,20-30 commas are used to separate regions selected from the pdb and designed (diffused) resiudes which will be added. ')
-                    pdb_id_code = gr.Textbox(label="PDB ID", lines=1, placeholder='INPUT PDB ID TO FETCH (ex. 1DPX)', visible=True)
-                    contigs = gr.Textbox(label="contigs", lines=1, placeholder='specify contigs to grab particular residues from pdb ()', visible=True)
-                    gr.Markdown('Using the same contig syntax, seq or str of input motif residues can be masked, allowing the model to hold strucutre fixed and design sequence or vice-versa')
-                    with gr.Row():
-                        seq_mask = gr.Textbox(label='seq mask',lines=1,placeholder='input residues to mask sequence')
-                        str_mask = gr.Textbox(label='str mask',lines=1,placeholder='input residues to mask structure')
-                    preview_viewer = gr.HTML()
-                    rewrite_pdb = gr.File(label='PDB file')
-                    preview_btn = gr.Button("Preview Motif")
-
-                with gr.TabItem("MSA to PSSM"):
-                    gr.Markdown("""### MSA to PSSM Generation""")
-                    gr.Markdown('input either an MSA or PSSM to guide the model toward generating samples within your family of interest')
-                    with gr.Row():
-                        fasta_msa = gr.File(label='MSA')
-                        input_pssm = gr.File(label='PSSM (.csv)')
-                    pssm = gr.File(label='Generated PSSM')
-                    pssm_view = gr.Plot(label='PSSM Viewer')
-                    pssm_gen_btn = gr.Button("Generate PSSM")
-
-        with gr.Column():
-            gr.Markdown("## 🦸‍♂️ 히어로 프로필")
-    
-    # 히어로 시각화 부분 제거 (hero_structure 삭제)
-    
-    # 능력치 레이더 차트
-            hero_stats = gr.Plot(label="능력치 분석")
-    
-    # 히어로 설명
-            hero_description = gr.Textbox(label="히어로 특성", lines=3)
-    
-    # 다운로드 버튼
-            download_btn = gr.Button("히어로 데이터 다운로드")
-
-            gr.Markdown("""## OUTPUTS""")
-            gr.Markdown("""#### Confidence score for generated structure at each timestep""")
-            plddt_plot = gr.Plot(label='plddt at step t')
-            gr.Markdown("""#### Output protein sequnece""")
-            output_seq = gr.Textbox(label="sequence")
-            gr.Markdown("""#### Download PDB file""")
-            output_pdb = gr.File(label="PDB file")
-            gr.Markdown("""#### Structure viewer""")
-            output_viewer = gr.HTML()
-
-
-
-    # 이벤트 연결
-    preview_btn.click(get_motif_preview,[pdb_id_code, contigs],[preview_viewer, rewrite_pdb])
-    pssm_gen_btn.click(get_pssm,[fasta_msa,input_pssm],[pssm_view, pssm])
-
-
-    create_btn.click(
-        generate_hero,
-        inputs=[hero_name, strength, flexibility, speed, defense, hero_size, special_ability],
-        outputs=[hero_stats, hero_description]  # hero_structure 제거
-    )
+        if final_result is None:
+            raise Exception("생성 결과가 없습니다")
+            
+        output_seq, output_pdb, structure_view, plddt_plot = final_result
+        
+        # 히어로 능력치 계산
+        stats = calculate_hero_stats(flexibility, strength, speed, defense)
+        
+        # 모든 결과 반환
+        return (
+            create_radar_chart(stats),  # 능력치 차트
+            generate_hero_description(name, stats, abilities),  # 히어로 설명
+            output_seq,  # 단백질 서열
+            output_pdb,  # PDB 파일
+            structure_view,  # 3D 구조
+            plddt_plot  # 신뢰도 차트
+        )
+    except Exception as e:
+        print(f"Error in combined_generation: {str(e)}")
+        return (
+            None,
+            f"에러: {str(e)}",
+            None,
+            None,
+            gr.HTML("에러가 발생했습니다"),
+            None
+        )
 
-    
-    btn = gr.Button("GENERATE")
-    btn.click(protein_diffusion_model, 
-                [sequence, 
-                 seq_len, 
-                 helix_bias, 
-                 strand_bias, 
-                 loop_bias, 
-                 secondary_structure, 
-                 aa_bias, 
-                 aa_bias_potential, 
-                 num_steps, 
-                 noise, 
-                 hydrophobic_target_score, 
-                 hydrophobic_potential,
-                 contigs,
-                 pssm,
-                 seq_mask, 
-                 str_mask,
-                 rewrite_pdb], 
-                [output_seq,
-                 output_pdb,
-                 output_viewer,
-                 plddt_plot])
-
-demo.queue()
-demo.launch(debug=True)
+with gr.Blocks(theme='ParityError/Interstellar') as demo: