Update app.py

app.py

@@ -1,41 +1,84 @@
+import os
+import warnings
 import gradio as gr
+from transformers import pipeline
+import re
 
 
-def ask(txt):
-    print("Asked!")
-    return "Fun", "Times"
 
+# Initialize the speech recognition pipeline and transliterator
+ 
+#p1 = pipeline(task="automatic-speech-recognition", model="cdactvm/w2v-bert-2.0-odia_v1")
+#p2 = pipeline(task="automatic-speech-recognition", model="cdactvm/w2v-bert-2.0-hindi_v1")
 
-desc = "Description"
-article_text = "Article Text!"
+HF_TOKEN = os.getenv('HW_TOKEN')
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "save_audio")
+
+
+cur_line=0
+
+def readFile():
+    f=open('prompt.txt')
+    line_num=0
+    lines=f.readlines()
+    line_num = len(lines)
+    return  line_num,lines
+
+totlines,file_content=readFile()
 
 callback = gr.CSVLogger()
+        
+def readPromt():
+    global cur_line
+    cur_line+=1
+    global file_content
+    print (cur_line)
+    return file_content[cur_line]
+    
+def readNext():
+    
+    global totlines
+    print(totlines)
+    global cur_line
+    if cur_line<totlines-1:
+        cur_line+=1
+        global file_content
+        print (cur_line)
+    return [file_content[cur_line],None]
+
+def readPrevious():
+    global cur_line
+    if cur_line>=0:
+        cur_line-=1
+    #cur_line=current_line
+        global file_content
+        print (cur_line)
+    return [file_content[cur_line],None]
 
+demo = gr.Blocks()
 
-with gr.Blocks() as demo:
-    gr.Markdown(
-        """
-    # Maryland Kids Law!
-    Start typing below to see the output.
-    """)
-    txt = gr.Textbox(label="Ask your question:", lines=5,
-                     placeholder="Is it ok to punch a kid?")
-    txt_2 = gr.Textbox(placeholder="Your Question will appear here.",
-                       label="Output", lines=5)
-    txt_3 = gr.Textbox(
-        placeholder="The references cited to answer your question will appear here.", label="References", lines=5)
-    btn = gr.Button(value="Ask!")
-    btn.click(ask, inputs=[txt], outputs=[txt_2, txt_3])
-
-    gr.examples = [
-        ["What a beautiful morning for a walk!"],
-        ["It was the best of times, it was the worst of times."]
-    ]
-    gr.HTML("hello world!")
-
-    callback.setup([txt, txt_2, txt_3], "flagged_data_points")
-    # We can choose which components to flag -- in this case, we'll flag all of them
-    btn.click(lambda *args: callback.flag(args),
-              [txt, txt_2, txt_3], None, preprocess=False)
-
-demo.launch()
+with demo:
+    #dr=gr.Dropdown(["Hindi","Odiya"],value="Odiya",label="Select Language")
+    #audio_file = gr.Audio(sources=["microphone","upload"],type="filepath")
+    text = gr.Textbox(readPromt())
+    upfile =  gr.Audio(
+        sources=["microphone","upload"], type="filepath",  label="Record"
+    )
+    #upfile =  gr.inputs.Audio(source="upload", type="filepath", label="Upload")
+    
+    with gr.Row():
+        b1 = gr.Button("Save")
+        b2 = gr.Button("Next")
+        b3 = gr.Button("Previous")
+        #b4=gr.Button("Clear")
+        b2.click(readNext,inputs=None,outputs=[text,upfile])
+        b3.click(readPrevious,inputs=None,outputs=[text,upfile])
+        #b4.click(lambda: None, outputs=upfile)
+   # b1.click(sel_lng, inputs=[dr,mic,upfile], outputs=text)
+    #b2.click(text_to_sentiment, inputs=text, outputs=label)
+    #callback.setup([text, upfile], "flagged_data_points")
+    #callback.setup([text, upfile], hf_writer)
+    #b1.click(lambda *args: callback.flag(args), [text, upfile], None, preprocess=False)
+    flagging_callback=hf_writer
+    b1.click(lambda *args:  flagging_callback, [text, upfile], None, preprocess=False)
+demo.launch()