Update app.py

app.py

@@ -143,25 +143,13 @@ def model_inference(
     if output_format == "原始富文本":
         return raw_text
     elif output_format == "纯净文本":
-        return " ".join(re.sub(r"<\|[^>]*>", "", raw_text).split())
+        return add_spacing(" ".join(re.sub(r"<\|[^>]*>", "", raw_text).split()))
     else:
-        return format_str_v3(raw_text)
+        return add_spacing(format_str_v3(raw_text))
 
 
-html_intro = """
-<div style="text-align: center; font-family: var(--font-sans);">
-    <h1 style="font-size: 28px;">SenseVoice-Small 语音识别</h1>
-    <p>SenseVoice 是具有音频理解能力的音频基础模型，包括语音识别（ASR）、语种识别（LID）、语音情感识别（SER）和声学事件分类（AEC）或声学事件检测（AED）。</p>
-    <p style="font-size: small; color: #888;">支持 MP3, WAV, FLAC, M4A 等常见音频格式。</p>
-</div>
-"""
-
-custom_css = """
-body, .gradio-container {
-    font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Open Sans', 'Helvetica Neue', sans-serif;
-}
-"""
-
+html_intro = """<div style="text-align: center; font-family: var(--font-sans);"><h1 style="font-size: 28px;">SenseVoice-Small 语音识别</h1><p>SenseVoice 是具有音频理解能力的音频基础模型，包括语音识别（ASR）、语种识别（LID）、语音情感识别（SER）和声学事件分类（AEC）或声学事件检测（AED）。</p><p style="font-size: small; color: #888;">支持 MP3, WAV, FLAC, M4A 等常见音频格式。</p></div>"""
+custom_css = "body, .gradio-container {font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Open Sans', 'Helvetica Neue', sans-serif;}"
 lang_options = [
     ("自动检测", "auto"),
     ("中文", "zh"),
@@ -172,7 +160,7 @@ lang_options = [
     ("无语音", "nospeech"),
 ]
 
-with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
+with gr.Blocks(theme=gr.themes.Glass(), css=custom_css) as demo:
     gr.HTML(html_intro)
     with gr.Row():
         with gr.Column(scale=2):
@@ -194,7 +182,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as demo:
                 ban_emo_unk_checkbox = gr.Checkbox(value=False, label="强制情感分类")
             fn_button = gr.Button("开始识别", variant="primary")
         with gr.Column(scale=3):
-            text_outputs = gr.Textbox(label="识别结果", lines=20)
+            text_outputs = gr.Textbox(label="识别结果", lines=20, height=520)
     fn_button.click(
         fn=model_inference,
         inputs=[