Update app.py

app.py

@@ -1,7 +1,3 @@
-# التثبيت (لو مش مثبت)
-!pip install rdkit-pypi py3Dmol transformers selfies biopython gradio -q
-
-# الاستيراد
 from Bio import PDB
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from rdkit import Chem
@@ -18,18 +14,15 @@ torch.manual_seed(int(time.time()))
 if torch.cuda.is_available():
     torch.cuda.manual_seed_all(int(time.time()))
 
-# تحميل النموذج
 model_name = "ncfrey/ChemGPT-1.2B"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-# تحميل ملف PDB
 def load_pdb(file_obj):
     parser = PDB.PDBParser(QUIET=True)
     structure = parser.get_structure('protein', file_obj)
     return structure
 
-# عرض البروتين ثلاثي الأبعاد
 def get_protein_3d_html(pdb_str):
     view = py3Dmol.view(width=600, height=400)
     view.addModel(pdb_str, "pdb")
@@ -37,7 +30,6 @@ def get_protein_3d_html(pdb_str):
     view.zoomTo()
     return view._make_html()
 
-# تنظيف وتحويل SELFIES إلى SMILES
 def clean_and_decode_selfies(raw_output):
     tokens = re.findall(r'\[[^\[\]]+\]', raw_output)
     valid_tokens = [t for t in tokens if all(x not in t for x in ['Branch', 'Ring', 'expl'])]
@@ -50,7 +42,6 @@ def clean_and_decode_selfies(raw_output):
     except:
         return None
 
-# توليد SMILES
 def generate_multiple_valid_smiles(prompt, n=10, max_length=100):
     valid_smiles = set()
     tries = 0
@@ -71,15 +62,9 @@ def generate_multiple_valid_smiles(prompt, n=10, max_length=100):
         tries += 1
     return list(valid_smiles)
 
-# الوظيفة الرئيسية
 def generate_from_pdb(pdb_file):
     try:
-        if isinstance(pdb_file, (str, bytes)):
-            pdb_str = pdb_file if isinstance(pdb_file, str) else pdb_file.decode('utf-8', errors='ignore')
-        else:
-            pdb_bytes = pdb_file.read()
-            pdb_str = pdb_bytes.decode('utf-8', errors='ignore')
-
+        pdb_str = pdb_file.read().decode('utf-8', errors='ignore')
         if len(pdb_str.strip()) == 0:
             return "❌ الملف فارغ أو غير صالح", None, None
 
@@ -90,7 +75,6 @@ def generate_from_pdb(pdb_file):
             return f"❌ خطأ أثناء تحليل ملف PDB:\n{str(e)}", None, None
 
         html_3d = get_protein_3d_html(pdb_str)
-
         prompt = "Generate a molecule in SELFIES that binds to the mutated KRAS protein"
         smiles_list = generate_multiple_valid_smiles(prompt, n=10)
 
@@ -103,17 +87,14 @@ def generate_from_pdb(pdb_file):
             f.write(smiles_txt)
 
         return "✅ تم توليد المركبات بنجاح", html_3d, smiles_file_path
-
     except Exception as e:
         return f"❌ حدث خطأ:\n{str(e)}", None, None
 
-# CSS لتجميل الواجهة
 css = """
 body {background-color: #f0f9ff;}
 h1 {color: #004d66; text-align: center;}
 """
 
-# واجهة Gradio
 with gr.Blocks(css=css) as demo:
     gr.Markdown("<h1>🔬 Drug-like Molecule Generation from PDB using ChemGPT</h1>")
     gr.Markdown("🧪 Upload a PDB file containing mutations in the KRAS protein. The system will generate suitable SMILES drug candidates.")
@@ -123,10 +104,6 @@ with gr.Blocks(css=css) as demo:
     status = gr.Textbox(label="📢 Status")
     view3d = gr.HTML(label="🧬 3D Structure Viewer")
     file_output = gr.File(label="📄 Download SMILES File")
-    run_btn.click(
-        fn=generate_from_pdb,
-        inputs=pdb_input,
-        outputs=[status, view3d, file_output]
-    )
+    run_btn.click(fn=generate_from_pdb, inputs=pdb_input, outputs=[status, view3d, file_output])
 
-demo.launch(share=True)  # خليها True لو عايز لينك عام
+demo.launch()