Update app.py

app.py

@@ -1,122 +1,113 @@
-import os
-import re
-import gradio as gr
-from deep_translator import GoogleTranslator
-from sentence_transformers import SentenceTransformer, util
-
-embed_model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L6-v2")
-
-def clean(s):
-    if not s:
-        return ""
-    return re.sub(r"\s+", " ", s).strip()
-
-def ko2en(text):
-    return GoogleTranslator(source="ko", target="en").translate(text)
-
-def en2ko(text):
-    return GoogleTranslator(source="en", target="ko").translate(text)
-
-def sim_ko(a, b):
-    if not a or not b:
-        return 0.0
-    v = embed_model.encode([a, b], convert_to_tensor=True)
-    return float(util.cos_sim(v[0], v[1]).item()) * 100.0
-
-def tone_en(text, tone):
-    t = clean(text)
-    if tone == "����":
-        t = re.sub(r"\b(very|really|so|truly)\b\s*", "", t, flags=re.I)
-        t = re.sub(r"\b(Thank you so much|Thanks a lot)\b", "Thank you", t, flags=re.I)
-    elif tone == "����":
-        if re.search(r"\b(Thank you|Thanks)\b", t, re.I) and not re.search(r"\bappreciat(e|ion)\b", t, re.I):
-            t += " I sincerely appreciate your support."
-        if not re.search(r"\bplease\b", t, re.I) and t:
-            t = "Please " + t[0].lower() + t[1:]
-    elif tone == "����Ͻ���":
-        if not t.endswith("."):
-            t += "."
-        if not re.search(r"\b(Please let me know|I look forward to)\b", t, re.I):
-            t += " Please let me know if you need any further information."
-    return t
-
-def tone_ko(text, tone):
-    t = clean(text)
-    if tone == "����":
-        t = re.sub(r"(����|��������|�ʹ�|�ſ�)\s*", "", t)
-        t = re.sub(r"(��Ź�帳�ϴ�|����帳�ϴ�)", "�����մϴ�", t)
-    elif tone == "����":
-        if "����" in t and "����" not in t:
-            t = t.replace("�����մϴ�", "�������� �����մϴ�")
-        if not re.search(r"(��Ź�帳�ϴ�|�����ֽø� �����ϰڽ��ϴ�)", t):
-            t += " �����ֽø� �����ϰڽ��ϴ�."
-    elif tone == "����Ͻ���":
-        t = re.sub(r"(��������|������|�����ؿ�)", "�����մϴ�", t)
-        if not (t.endswith("���ϴ�.") or t.endswith("�帳�ϴ�.") or t.endswith("��.")):
-            t += " �����մϴ�."
-    return t
-
-def td_translate(ko_text, tone, target=98.2):
-    ko_text = clean(ko_text)
-    if not ko_text:
-        return "������ �Է��ϼ���.", "", "", "", "", 0.0, ""
-    try:
-        en = ko2en(ko_text)
-        back = en2ko(en)
-    except Exception as e:
-        return f"[���� ����] {e}", "", "", "", "", 0.0, ""
-
-    sim = sim_ko(ko_text, back)
-    en_tuned = tone_en(en, tone)
-    ko_tuned = tone_ko(back, tone)
-    ok = sim >= float(target)
-    flag = "���� ���� ✅" if ok else "���� �̴� ⚠️ (ǥ���� ��üȭ�� ������)"
-    final = f"{en_tuned}\n\n{flag} (���絵: {sim:.2f}%, ����: {float(target):.1f}%)"
-    guide = f"��: {tone} | KO��EN��KO ����� ��� �ǹ� ������ ����"
-    return "", en, back, en_tuned, ko_tuned, sim, final + "\n" + guide
-
-with gr.Blocks(title="Tha Deeply Translator — �溰 ������") as app:
-    gr.Markdown(
-        "## Tha Deeply — �� ����ġ / ����� / ���絵 �м���\n"
-        "- �⺻��: ����Ͻ���, ���絵 98.2%, ���� ���� ������\n"
-        "- ���� �ٲ㰡�� �������� ��� ������ ���� ������."
-    )
-
-    default_tone = "����Ͻ���"
-    default_threshold = 98.2
-    default_text = "���� �������ϴ�. ���� �������� ȸ�� ��Ź�帳�ϴ�."
-
-    with gr.Row():
-        tone = gr.Radio(["����", "����", "����Ͻ���"], value=default_tone, label="�� ����")
-        thres = gr.Slider(0, 100, value=default_threshold, step=0.1, label="���絵 ����(%)")
-    ko_in = gr.Textbox(lines=4, label="����(�ѱ���)", value=default_text, placeholder="�ѱ��� ������ �Է��ϼ���")
-    run = gr.Button("����")
-
-    en_out = gr.Textbox(lines=4, label="�� ���� ����(EN)")
-    ko_back = gr.Textbox(lines=4, label="�� �����(KO)")
-    en_tone = gr.Textbox(lines=4, label="�� �� ���� ����(EN)")
-    ko_tone = gr.Textbox(lines=4, label="�� �� ���� �ѱ�(KO)")
-    sim = gr.Number(label="�ǹ� ���絵(%)", precision=2)
-    final = gr.Textbox(lines=6, label="�� ������ ���� ���� + ����")
-
-    examples = gr.Examples(
-        examples=[
-            ["���� �ּż� �����մϴ�. ���� �� �����ϱ��� ȸ�� ��Ź�帳�ϴ�.", "����Ͻ���", 98.2],
-            ["�˼��մϴ�. ���� ������ �ʿ��մϴ�. ������ �ð��� �˷��ּ���.", "����", 97.0],
-            ["���� �����ؿ�! �̹� ������Ʈ �Բ��� �� �־� ��޴ϴ�.", "����", 98.5],
-        ],
-        inputs=[ko_in, tone, thres],
-        label="���� �ҷ�����"
-    )
-
-    def _run(ko_text, t, thr):
-        msg, en, back, en_tuned, ko_tuned, simv, fin = td_translate(ko_text, t, thr)
-        if msg:
-            return "", "", "", "", 0.0, msg
-        return en, back, en_tuned, ko_tuned, simv, fin
-
-    run.click(_run, [ko_in, tone, thres], [en_out, ko_back, en_tone, ko_tone, sim, final])
-
-if __name__ == "__main__":
-    port = int(os.getenv("PORT", "7860"))
+# -*- coding: utf-8 -*-
+
+import os
+import re
+import gradio as gr
+from deep_translator import GoogleTranslator
+from sentence_transformers import SentenceTransformer, util
+
+# model load (first run may take 1-2 minutes)
+embed_model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L6-v2")
+
+def clean(s: str) -> str:
+    if not s:
+        return ""
+    return re.sub(r"\s+", " ", s).strip()
+
+def ko2en(text: str) -> str:
+    return GoogleTranslator(source="ko", target="en").translate(text)
+
+def en2ko(text: str) -> str:
+    return GoogleTranslator(source="en", target="ko").translate(text)
+
+def sim_ko(a: str, b: str) -> float:
+    if not a or not b:
+        return 0.0
+    v = embed_model.encode([a, b], convert_to_tensor=True)
+    return float(util.cos_sim(v[0], v[1]).item()) * 100.0
+
+# tone rules (EN / KO)
+def tone_en(text: str, tone: str) -> str:
+    t = clean(text)
+    if tone == "쿨톤":
+        t = re.sub(r"\b(very|really|so|truly)\b\s*", "", t, flags=re.I)
+        t = re.sub(r"\b(Thank you so much|Thanks a lot)\b", "Thank you", t, flags=re.I)
+    elif tone == "웜톤":
+        if re.search(r"\b(Thank you|Thanks)\b", t, re.I) and not re.search(r"\bappreciat(e|ion)\b", t, re.I):
+            t += " I sincerely appreciate your support."
+        if not re.search(r"\bplease\b", t, re.I) and t:
+            t = "Please " + t[0].lower() + t[1:]
+    elif tone == "비즈니스톤":
+        if not t.endswith("."):
+            t += "."
+        if not re.search(r"\b(Please let me know|I look forward to)\b", t, re.I):
+            t += " Please let me know if you need any further information."
+    return t
+
+def tone_ko(text: str, tone: str) -> str:
+    t = clean(text)
+    if tone == "쿨톤":
+        t = re.sub(r"(정말|진심으로|너무|매우)\s*", "", t)
+        t = re.sub(r"(부탁드립니다|감사드립니다)", "감사합니다", t)
+    elif tone == "웜톤":
+        if "감사" in t and "진심" not in t:
+            t = t.replace("감사합니다", "진심으로 감사합니다")
+        if not re.search(r"(부탁드립니다|도와주시면 감사하겠습니다)", t):
+            t += " 도와주시면 감사하겠습니다."
+    elif tone == "비즈니스톤":
+        t = re.sub(r"(고마워요|고마워|감사해요)", "감사합니다", t)
+        if not (t.endswith("습니다.") or t.endswith("드립니다.") or t.endswith("요.")):
+            t += " 감사합니다."
+    return t
+
+def td_translate(ko_text: str, tone: str, target: float = 98.2):
+    ko_text = clean(ko_text)
+    if not ko_text:
+        return "원문을 입력하세요.", "", "", "", "", 0.0, ""
+    try:
+        en = ko2en(ko_text)
+        back = en2ko(en)
+    except Exception as e:
+        return f"[번역 오류] {e}", "", "", "", "", 0.0, ""
+
+    sim = sim_ko(ko_text, back)
+    en_tuned = tone_en(en, tone)
+    ko_tuned = tone_ko(back, tone)
+    ok = sim >= float(target)
+    flag = "기준 충족" if ok else "기준 미달 (표현을 구체화해 보세요)"
+    final = f"{en_tuned}\n\n{flag} (유사도: {sim:.2f}%, 기준: {float(target):.1f}%)"
+    guide = f"톤: {tone} | KO->EN->KO 재번역 기반 의미 검증"
+    return "", en, back, en_tuned, ko_tuned, sim, final + "\n" + guide
+
+with gr.Blocks(title="Tha Deeply Translator") as app:
+    gr.Markdown("Tha Deeply — 톤 스위치 / 재번역 / 유사도 분석기")
+
+    default_tone = "비즈니스톤"
+    default_threshold = 98.2
+    default_text = "정말 고맙습니다. 내일 오전까지 회신 부탁드립니다."
+
+    with gr.Row():
+        tone = gr.Radio(["쿨톤", "웜톤", "비즈니스톤"], value=default_tone, label="톤 선택")
+        thres = gr.Slider(0, 100, value=default_threshold, step=0.1, label="유사도 기준(%)")
+    ko_in = gr.Textbox(lines=4, label="원문(한국어)", value=default_text, placeholder="한국어 문장을 입력하세요")
+    run = gr.Button("실행")
+
+    en_out = gr.Textbox(lines=4, label="1) 영문 번역(EN)")
+    ko_back = gr.Textbox(lines=4, label="2) 재번역(KO)")
+    en_tone = gr.Textbox(lines=4, label="3) 톤 보정 영문(EN)")
+    ko_tone = gr.Textbox(lines=4, label="4) 톤 보정 한글(KO)")
+    sim = gr.Number(label="의미 유사도(%)", precision=2)
+    final = gr.Textbox(lines=6, label="완전한 영어 제안 + 상태")
+
+    def _run(ko_text, t, thr):
+        msg, en, back, en_tuned, ko_tuned, simv, fin = td_translate(ko_text, t, thr)
+        if msg:
+            return "", "", "", "", 0.0, msg
+        return en, back, en_tuned, ko_tuned, simv, fin
+
+    run.click(_run, [ko_in, tone, thres],
+              [en_out, ko_back, en_tone, ko_tone, sim, final])
+
+if __name__ == "__main__":
+    port = int(os.getenv("PORT", "7860"))
     app.launch(server_name="0.0.0.0", server_port=port)