Create scratch.py

scratch.py

@@ -0,0 +1,56 @@
+
+# >>>>>>   Adapted/frankensteined from these scripts:   <<<<<<<
+#                 for Summary Interface:
+# >>>> https://huggingface.co/spaces/khxu/pegasus-text-summarizers/blob/main/app.py
+#                      Audio Interface
+# >>>> https://huggingface.co/spaces/iSky/Speech-audio-to-text-with-grammar-correction/blob/main/app.py
+#                      Gramar
+# >>>> https://huggingface.co/deep-learning-analytics/GrammarCorrector/blob/main/README.md
+
+
+import gradio as gr
+from transformers import pipeline
+from gradio.mix import Parallel, Series
+
+# >>>>>>>>>>>>>>>>>>>> Danger Below <<<<<<<<<<<<<<<<<<<<<<
+# Load Interfaces:
+s2t = gr.Interface.load('huggingface/hf-internal-testing/processor_with_lm')
+grammar = gr.Interface.load('huggingface/deep-learning-analytics/GrammarCorrector')
+sum_it = gr.Interface.load('huggingface/SamuelMiller/lil_sum_sum') 
+
+# Audio Functions:
+def out(audio):
+  flag = True
+  if audio==None:
+    return "no audio" 
+  
+  elif flag:               
+    a = s2t(audio)
+    #g = grammar(a)
+    #s = sum_it(g)                              # Summarize Audio with sum_it
+    return a #grammar(a, num_return_sequences=1) # grammar(s),                       # Grammar Filter 
+
+  else:
+    return "something is wrong in the function?"
+
+
+# Construct Interfaces:
+iface = gr.Interface(
+  fn=out, 
+  title="Speech Audio to text (with corrected grammar)",
+  description="Let's Hear It!! This app transforms your speech (input) to text with corrected grammar after (output)!",
+  inputs= gr.inputs.Audio(source="microphone", type="filepath", label=None, optional=True),
+  outputs= 'text'
+)
+
+# Launch Interface
+iface.launch(enable_queue=True,show_error=True)
+
+  # From Original Code:
+# gr.inputs.Audio(source="upload", type="filepath", label=None, optional=True),  
+# examples=[["Grammar-Correct-Sample.mp3"], ["Grammar-Wrong-Sample.mp3"],],
+
+#def speech_to_text(inp):
+    #pass  # speech recognition model defined here
+
+#gr.Interface(speech_to_text, inputs="mic", outputs=gr.Textbox(label="Predicted text", lines=4))