Add application file

app.py

@@ -1,7 +1,63 @@
 import gradio as gr
+from modeling_llama_seq2seq import LlamaCrossAttentionEncDec
+from transformers import AutoTokenizer, AutoConfig
+from PIL import Image
 
-def greet(name):
-    return "Hello " + name + "!!"
+# 模型路径和初始化
+def load_model(model_name_or_path):
+    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+    config = AutoConfig.from_pretrained(model_name_or_path, trust_remote_code=True)
+    model = LlamaCrossAttentionEncDec.from_pretrained(model_name_or_path, config=config)
+    return tokenizer, model
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+tokenizer, model = load_model('path_to_your_model')
+
+# 翻译函数
+def translate_text(src_text, src_lang, tgt_lang, task_type, term_text=None, mt_text=None):
+    if task_type == "常规翻译":
+        prompt = f"Translate the following text from {src_lang} into {tgt_lang}.\n{src_lang}: {src_text}\n{tgt_lang}: "
+    elif task_type == "术语受限翻译":
+        prompt = f"Translate the following text from {src_lang} into {tgt_lang} using the provided terminology pairs.\nTerminology pairs: {term_text}\n{src_lang}: {src_text}\n{tgt_lang}: "
+    elif task_type == "自动后期编辑":
+        prompt = f"Improve the following machine-generated translation from {src_lang} to {tgt_lang}.\n{src_lang}: {src_text}\n{tgt_lang}: {mt_text}\n{tgt_lang}: "
+    else:
+        return "请选择正确的任务类型"
+
+    input_ids = tokenizer(prompt, return_tensors="pt")
+    outputs_tokenized = model.generate(**input_ids, num_beams=5, do_sample=False)
+    outputs = tokenizer.batch_decode(outputs_tokenized, skip_special_tokens=True)
+    return outputs[0]
+
+# 构建 Gradio UI
+def create_interface():
+    logo_image = Image.open('path_to_your_logo/logo.png')
+
+    with gr.Blocks() as demo:
+        gr.Image(logo_image, elem_id="logo", label="Logo")
+        gr.Markdown("## 🌎 AI 翻译助手")
+        
+        with gr.Row():
+            src_text = gr.Textbox(label="输入文本", placeholder="请输入需要翻译的文本")
+        
+        with gr.Row():
+            src_lang = gr.Dropdown(["English", "Chinese", "French", "German"], label="源语言")
+            tgt_lang = gr.Dropdown(["Chinese", "English", "French", "German"], label="目标语言")
+        
+        with gr.Row():
+            task_type = gr.Radio(["常规翻译", "术语受限翻译", "自动后期编辑"], label="任务类型")
+            term_text = gr.Textbox(label="术语表（术语受限翻译）", visible=False)
+            mt_text = gr.Textbox(label="机器翻译结果（自动后期编辑）", visible=False)
+        
+        def show_extra_fields(task_type):
+            return (task_type == "术语受限翻译", task_type == "自动后期编辑")
+        
+        task_type.change(show_extra_fields, inputs=[task_type], outputs=[term_text, mt_text])
+        output_text = gr.Textbox(label="翻译结果")
+
+        translate_button = gr.Button("翻译")
+        translate_button.click(translate_text, inputs=[src_text, src_lang, tgt_lang, task_type, term_text, mt_text], outputs=output_text)
+
+    demo.launch(server_name="0.0.0.0", server_port=8080, share=True)
+
+if __name__ == "__main__":
+    create_interface()