Upload app.py

app.py

@@ -1,58 +1,56 @@
-
-import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-
-# Cargar el modelo solo una vez
-model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2")
-tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2")
-tokenizer.pad_token = tokenizer.eos_token
-
-# Traducción entre moléculas
-def transcode_phrase(phrase, src, dst):
-    if src == dst:
-        return "⚠️ Source and target are the same."
-    if src == "DNA" and dst == "RNA":
-        return phrase.replace("~d:", ":r:").replace("Exon", "Ex").replace("Intr", "removed")
-    elif src == "RNA" and dst == "Protein":
-        return phrase.replace(":r:", "^p:").replace("Ex1", "Dom(Kin)").replace("Ex2", "Mot(NLS)")
-    elif src == "Protein" and dst == "DNA":
-        return phrase.replace("^p:", "~d:").replace("Dom(Kin)", "Exon1").replace("Mot(NLS)", "Exon2")
-    else:
-        return "❌ Translation not implemented."
-
-# Generar proteína a partir de frase
-semillas = {
-    "^p:Dom(Kin)-Mot(NLS)*AcK@147=Localize(Nucleus)": "MKKK",
-    "^p:Mot(NLS)-Mot(PEST)*P@120": "MKSP",
-    "^p:Dom(ZnF)-Mot(NLS)*UbK@42": "MKHG",
-}
-
-def generar_desde_frase(frase):
-    semilla = semillas.get(frase, "MKKK")
-    inputs = tokenizer(semilla, return_tensors="pt", padding=True)
-    outputs = model.generate(**inputs, max_length=200, do_sample=True, top_k=950, temperature=1.5, num_return_sequences=1)
-    secuencia = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return f"🧪 Seed: {semilla}"
-🧬 Generated Protein:
-{secuencia}"
-
-# Interfaz Gradio
-with gr.Blocks() as demo:
-    with gr.Tab("Phrase → Protein"):
-        gr.Markdown("### Generate Protein Sequence from GeneForgeLang Phrase")
-        input_frase = gr.Textbox(label="Input Phrase")
-        output_prot = gr.Textbox(label="Generated Protein")
-        boton_gen = gr.Button("Generate")
-        boton_gen.click(fn=generar_desde_frase, inputs=input_frase, outputs=output_prot)
-
-    with gr.Tab("Transcode Across Molecules"):
-        gr.Markdown("### Convert between DNA, RNA, and Protein symbolic phrases")
-        input_phrase = gr.Textbox(label="Input GeneForgeLang Phrase")
-        src_select = gr.Radio(choices=["DNA", "RNA", "Protein"], label="Translate From", value="DNA")
-        dst_select = gr.Radio(choices=["DNA", "RNA", "Protein"], label="Translate To", value="RNA")
-        output = gr.Textbox(label="Translated Phrase")
-        trans_btn = gr.Button("Translate")
-        trans_btn.click(fn=transcode_phrase, inputs=[input_phrase, src_select, dst_select], outputs=output)
-
-demo.launch()
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Cargar el modelo solo una vez
+model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2")
+tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2")
+tokenizer.pad_token = tokenizer.eos_token
+
+# Traducción entre moléculas
+def transcode_phrase(phrase, src, dst):
+    if src == dst:
+        return "⚠️ Source and target are the same."
+    if src == "DNA" and dst == "RNA":
+        return phrase.replace("~d:", ":r:").replace("Exon", "Ex").replace("Intr", "removed")
+    elif src == "RNA" and dst == "Protein":
+        return phrase.replace(":r:", "^p:").replace("Ex1", "Dom(Kin)").replace("Ex2", "Mot(NLS)")
+    elif src == "Protein" and dst == "DNA":
+        return phrase.replace("^p:", "~d:").replace("Dom(Kin)", "Exon1").replace("Mot(NLS)", "Exon2")
+    else:
+        return "❌ Translation not implemented."
+
+# Generar proteína a partir de frase
+semillas = {
+    "^p:Dom(Kin)-Mot(NLS)*AcK@147=Localize(Nucleus)": "MKKK",
+    "^p:Mot(NLS)-Mot(PEST)*P@120": "MKSP",
+    "^p:Dom(ZnF)-Mot(NLS)*UbK@42": "MKHG",
+}
+
+def generar_desde_frase(frase):
+    semilla = semillas.get(frase, "MKKK")
+    inputs = tokenizer(semilla, return_tensors="pt", padding=True)
+    outputs = model.generate(**inputs, max_length=200, do_sample=True, top_k=950, temperature=1.5, num_return_sequences=1)
+    secuencia = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return f"🧪 Seed: {semilla}\n🧬 Generated Protein:\n{secuencia}"
+
+# Interfaz Gradio
+with gr.Blocks() as demo:
+    with gr.Tab("Phrase → Protein"):
+        gr.Markdown("### Generate Protein Sequence from GeneForgeLang Phrase")
+        input_frase = gr.Textbox(label="Input Phrase")
+        output_prot = gr.Textbox(label="Generated Protein")
+        boton_gen = gr.Button("Generate")
+        boton_gen.click(fn=generar_desde_frase, inputs=input_frase, outputs=output_prot)
+
+    with gr.Tab("Transcode Across Molecules"):
+        gr.Markdown("### Convert between DNA, RNA, and Protein symbolic phrases")
+        input_phrase = gr.Textbox(label="Input GeneForgeLang Phrase")
+        src_select = gr.Radio(choices=["DNA", "RNA", "Protein"], label="Translate From", value="DNA")
+        dst_select = gr.Radio(choices=["DNA", "RNA", "Protein"], label="Translate To", value="RNA")
+        output = gr.Textbox(label="Translated Phrase")
+        trans_btn = gr.Button("Translate")
+        trans_btn.click(fn=transcode_phrase, inputs=[input_phrase, src_select, dst_select], outputs=output)
+
+demo.launch()