Update app.py

app.py

@@ -10,18 +10,11 @@ import torch
 import nltk
 from functools import lru_cache
 
-
-code_mapping = dict(sorted(code_mapping.items(), key=lambda item: item[0]))
-flores_codes = list(code_mapping.keys())
-target_languages = flores_codes  # 简化列表
-
 # 假设openai_client已定义，例如：
 
 device = "cuda"
 MODEL_NAME = "ByteDance-Seed/Seed-X-PPO-7B"
 
-
-
 def load_model():
     model = AutoModelForCausalLM.from_pretrained(MODEL_NAME,torch_dtype="bfloat16").to(device)
     print(f"Model loaded in {device}")
@@ -30,12 +23,10 @@ def load_model():
 
 model = load_model()
 
-
 # Loading the tokenizer once, because re-loading it takes about 1.5 seconds each time
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 
 
-
 @lru_cache(maxsize=100)
 def translate(text: str, src_lang: str, tgt_lang: str):
     if not src_lang:
@@ -56,7 +47,7 @@ def _translate(text: str, src_lang: str, tgt_lang: str):
     )
     translated_chunk = model.generate(
         input_ids=torch.tensor([input_tokens]).to(device),
-        max_length=len(input_tokens) + 1000,
+        max_length=len(input_tokens) + 2048,
         num_return_sequences=1,
     )
     full_output = tokenizer.decode(translated_chunk[0], skip_special_tokens=True).strip()
@@ -82,16 +73,13 @@ description = """
     <img src="https://github.com/user-attachments/assets/c42e675e-497c-4508-8bb9-093ad4d1f216" alt="UNESCO Meta Hugging Face Banner" style="max-width: 800px; width: 100%; margin: 0 auto;">
     <h1 style="color: #0077be; font-size: 3em;">Seed-X, powered by Bytedance</h1>
 </div>
-We are excited to introduce Seed-X, a powerful series of open-source multilingual translation language models, including an instruction model, a reinforcement learning model, and a reward model. It pushes the boundaries of translation capabilities within 7 billion parameters. We develop Seed-X as an accessible, off-the-shelf tool to support the community in advancing translation research and applications:
+Seed-X, a powerful series of open-source multilingual translation language models, including an instruction model, a reinforcement learning model, and a reward model. It pushes the boundaries of translation capabilities within 7 billion parameters. We develop Seed-X as an accessible, off-the-shelf tool to support the community in advancing translation research and applications:
 """
 
 examples_inputs = [["Seed-X is indeed a good translation model ","English","Chinese"],]
 
 with gr.Blocks() as demo:
     gr.Markdown(description)
-    with gr.Row():
-        src_lang = gr.Dropdown(label="Source Language", choices=flores_codes)
-        target_lang = gr.Dropdown(label="Target Language", choices=target_languages)
     with gr.Row():
         input_text = gr.Textbox(label="Input Text", lines=6)
     with gr.Row():