Update app.py

app.py

@@ -1,23 +1,22 @@
 import gradio as gr
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-import torch
+import os
 from datetime import datetime
 from functools import lru_cache
+import torch
+import requests
 
-# ---------------------------
-# Translator Tool Components
-# ---------------------------
-
+# Language Codes
 LANGUAGE_CODES = {
     "English": "eng_Latn", "Korean": "kor_Hang", "Japanese": "jpn_Jpan", "Chinese": "zho_Hans",
     "Spanish": "spa_Latn", "French": "fra_Latn", "German": "deu_Latn", "Russian": "rus_Cyrl",
     "Portuguese": "por_Latn", "Italian": "ita_Latn", "Burmese": "mya_Mymr", "Thai": "tha_Thai"
 }
 
+# Translation History
 class TranslationHistory:
     def __init__(self):
         self.history = []
-
     def add(self, src, translated, src_lang, tgt_lang):
         self.history.insert(0, {
             "source": src, "translated": translated,
@@ -26,65 +25,123 @@ class TranslationHistory:
         })
         if len(self.history) > 100:
             self.history.pop()
-
     def get(self):
         return self.history
-
     def clear(self):
         self.history = []
 
 history = TranslationHistory()
 
+# Load Translation Model
 model_name = "facebook/nllb-200-distilled-600M"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
 
+# Translation Function
 @lru_cache(maxsize=512)
 def cached_translate(text, src_lang, tgt_lang, max_length=128, temperature=0.7):
-    if not text.strip():
-        return ""
+    if not text.strip(): return ""
     src_code = LANGUAGE_CODES.get(src_lang, src_lang)
     tgt_code = LANGUAGE_CODES.get(tgt_lang, tgt_lang)
     input_tokens = tokenizer(text, return_tensors="pt", padding=True)
     input_tokens = {k: v.to(device) for k, v in input_tokens.items()}
     forced_bos_token_id = tokenizer.convert_tokens_to_ids(tgt_code)
-    output = model.generate(
-        **input_tokens,
+    output = model.generate(**input_tokens,
         forced_bos_token_id=forced_bos_token_id,
-        max_length=max_length,
-        temperature=temperature,
-        num_beams=5,
-        early_stopping=True
+        max_length=max_length, temperature=temperature,
+        num_beams=5, early_stopping=True
     )
     result = tokenizer.decode(output[0], skip_special_tokens=True)
     history.add(text, result, src_lang, tgt_lang)
     return result
 
-# ---------------------------
-# Gradio App with Tabs
-# ---------------------------
+def translate_file(file, src_lang, tgt_lang, max_length, temperature):
+    try:
+        lines = file.decode("utf-8").splitlines()
+        translated = [cached_translate(line, src_lang, tgt_lang, max_length, temperature) for line in lines if line.strip()]
+        return "\n".join(translated)
+    except Exception as e:
+        return f"File translation error: {e}"
+
+# Summarization
+API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
+HF_API_KEY = os.environ.get("HF_API_KEY", "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")
+headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+
+def summarize_text(text, max_length):
+    if not text.strip(): return ""
+    min_length = max(10, max_length // 4)
+    response = requests.post(API_URL, headers=headers, json={
+        "inputs": text,
+        "parameters": {"min_length": min_length, "max_length": max_length}
+    })
+    result = response.json()
+    return result[0]["summary_text"] if isinstance(result, list) else "Error: " + str(result)
+
+# UI Styling
+gradio_style = """
+.gr-button { border-radius: 12px !important; padding: 10px 20px !important; font-weight: bold; }
+textarea, input[type=text] { border: 2px solid #00ADB5 !important; border-radius: 10px; transition: 0.2s; }
+textarea:focus, input[type=text]:focus { border-color: #FF5722 !important; box-shadow: 0 0 8px #FF5722 !important; }
+"""
+
+with gr.Blocks(css=gradio_style, theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🤖 AI Toolbox: Translate & Summarize")
+
+    with gr.Tab("🌐 Text Translator"):
+        with gr.Row():
+            src_lang = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="🌐 From", value="English")
+            swap = gr.Button("⇄")
+            tgt_lang = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="🎯 To", value="Korean")
+        with gr.Row():
+            input_text = gr.Textbox(lines=3, label="✍️ Input Text")
+            output_text = gr.Textbox(lines=3, label="📤 Translated Output", interactive=False)
+        with gr.Row():
+            translate = gr.Button("🚀 Translate", variant="primary")
+            clear = gr.Button("🧽 Clear")
+        with gr.Accordion("⚙️ Advanced Settings", open=False):
+            max_length = gr.Slider(10, 512, value=128, step=1, label="Max Length")
+            temperature = gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature")
+        with gr.Accordion("📜 Translation History", open=False):
+            history_json = gr.JSON(label="Recent Translations")
+            with gr.Row():
+                refresh = gr.Button("🔄 Refresh")
+                clear_history = gr.Button("🧹 Clear History")
 
-def create_demo():
-    with gr.Blocks(theme=gr.themes.Soft(), fill_height=True) as demo:
-        gr.Markdown("## 🤖 Smart AI Tools – Translate, Summarize, and More")
+        with gr.Tab("📁 File Translator"):
+            file_input = gr.File(label="📂 Upload .txt File", file_types=[".txt"])
+            file_src = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="📌 From", value="English")
+            file_tgt = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="📌 To", value="Korean")
+            file_translate = gr.Button("📄 Translate File", variant="primary")
+            file_result = gr.Textbox(label="📑 File Output", lines=10, interactive=False)
+            with gr.Accordion("⚙️ Advanced Settings", open=False):
+                f_max_length = gr.Slider(10, 512, value=128, step=1, label="Max Length")
+                f_temp = gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature")
 
-        with gr.Tab("🌐 Translator"):
-            src_lang = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="From", value="English")
-            tgt_lang = gr.Dropdown(list(LANGUAGE_CODES.keys()), label="To", value="Korean")
-            input_text = gr.Textbox(label="Input Text", lines=4)
-            output_text = gr.Textbox(label="Translated Output", lines=4, interactive=False)
-            translate_btn = gr.Button("Translate")
-            clear_btn = gr.Button("Clear")
-            translate_btn.click(cached_translate, [input_text, src_lang, tgt_lang], output_text)
-            clear_btn.click(lambda: ("", ""), None, [input_text, output_text])
+    with gr.Tab("📝 Text Summarizer"):
+        summary_input = gr.Textbox(lines=5, label="📚 Enter text to summarize")
+        summary_length = gr.Slider(32, 512, value=128, step=8, label="📏 Max Length")
+        summary_output = gr.Textbox(label="🧾 Summary", lines=5, interactive=False)
+        summary_btn = gr.Button("🧠 Summarize")
 
-        with gr.Tab("📝 Summarizer"):
-            gr.Markdown("### This tool summarizes long content using `facebook/bart-large-cnn`")
-            gr.load("models/facebook/bart-large-cnn", provider="huggingface", label="Summarizer")
+    # Button events
+    translate.click(cached_translate, [input_text, src_lang, tgt_lang, max_length, temperature], output_text)
+    clear.click(lambda: ("", ""), None, [input_text, output_text])
+    swap.click(lambda s, t: (t, s), [src_lang, tgt_lang], [src_lang, tgt_lang])
+    refresh.click(lambda: history.get(), None, history_json)
+    clear_history.click(lambda: history.clear() or [], None, history_json)
+    file_translate.click(lambda file, src, tgt, ml, t: translate_file(file.read(), src, tgt, ml, t),
+                         [file_input, file_src, file_tgt, f_max_length, f_temp], file_result)
+    summary_btn.click(summarize_text, [summary_input, summary_length], summary_output)
 
-    return demo
+    gr.Markdown(f"""
+    ### 🔍 Info
+    - Translator Model: `{model_name}` on `{device}`
+    - Summarizer Model: `facebook/bart-large-cnn`
+    - HF API Key: {'Loaded ✅' if HF_API_KEY else 'Missing ❌'}
+    """)
 
-demo = create_demo()
-demo.launch(share=False)
+if __name__ == "__main__":
+    demo.launch(share=True)