Update app.py

app.py

@@ -1,3 +1,64 @@
+# import torchaudio
+# import gradio as gr
+# from transformers import pipeline
+# from gtts import gTTS
+# import tempfile
+# import pygame
+# import time
+
+# # Initialize the speech-to-text transcriber
+# transcriber = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-english")
+
+# # Load the pre-trained question answering model
+# model_name = "AVISHKAARAM/avishkaarak-ekta-hindi"
+# qa_model = pipeline("question-answering", model=model_name)
+
+# def answer_question(context, question=None, audio=None):
+#     if audio is not None:
+#         text = transcriber(audio)
+#         question_text = text['text']
+#     else:
+#         question_text = question
+
+#     qa_result = qa_model(question=question_text, context=context)
+#     answer = qa_result["answer"]
+
+#     tts = gTTS(text=answer, lang='en')
+#     audio_path = tempfile.NamedTemporaryFile(suffix=".mp3").name
+#     tts.save(audio_path)
+
+#     return answer, audio_path
+
+# def play_audio(audio_path):
+#     pygame.mixer.init()
+#     pygame.mixer.music.load(audio_path)
+#     pygame.mixer.music.play()
+#     while pygame.mixer.music.get_busy():
+#         time.sleep(0.1)
+
+# # Define the Gradio interface
+# context_input = gr.components.Textbox(label="Context")
+# question_input = gr.components.Textbox(label="Question")
+# audio_input = gr.components.Audio(source="microphone", type="filepath")
+
+# output_text = gr.components.Textbox(label="Answer")
+# output_audio = gr.components.Audio(label="Answer Audio", type="numpy")
+
+# inter = gr.Interface(
+#     fn=answer_question,
+#     inputs=[context_input, question_input, audio_input],
+#     outputs=[output_text, output_audio],
+#     title="Question Answering",
+#     description="Enter a context and a question to get an answer. You can also upload an audio file with the question.",
+#     examples=[
+#         ["The capital of France is Paris.", "What is the capital of France?"],
+#         ["OpenAI is famous for developing GPT-3.", "What is OpenAI known for?"],
+#     ]
+# )
+# # Launch the Gradio interface
+# inter.launch()
+
+
 import torchaudio
 import gradio as gr
 from transformers import pipeline
@@ -9,14 +70,14 @@ import time
 # Initialize the speech-to-text transcriber
 transcriber = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-english")
 
-# Load the pre-trained question answering model
+# Load the pre-trained question-answering model
 model_name = "AVISHKAARAM/avishkaarak-ekta-hindi"
 qa_model = pipeline("question-answering", model=model_name)
 
 def answer_question(context, question=None, audio=None):
     if audio is not None:
-        text = transcriber(audio)
-        question_text = text['text']
+        text = transcriber(audio)["text"]
+        question_text = text
     else:
         question_text = question
 
@@ -37,23 +98,24 @@ def play_audio(audio_path):
         time.sleep(0.1)
 
 # Define the Gradio interface
-context_input = gr.components.Textbox(label="Context")
-question_input = gr.components.Textbox(label="Question")
-audio_input = gr.components.Audio(source="microphone", type="filepath")
+context_input = gr.Textbox(label="Context")
+question_input = gr.Textbox(label="Question")
+audio_input = gr.Audio(type="filepath", label="Question Audio")
 
-output_text = gr.components.Textbox(label="Answer")
-output_audio = gr.components.Audio(label="Answer Audio", type="numpy")
+output_text = gr.Textbox(label="Answer")
+output_audio = gr.Audio(label="Answer Audio")
 
 inter = gr.Interface(
     fn=answer_question,
     inputs=[context_input, question_input, audio_input],
     outputs=[output_text, output_audio],
     title="Question Answering",
-    description="Enter a context and a question to get an answer. You can also upload an audio file with the question.",
+    description="Enter a context and a question to get an answer. You can also record audio with the question.",
     examples=[
         ["The capital of France is Paris.", "What is the capital of France?"],
         ["OpenAI is famous for developing GPT-3.", "What is OpenAI known for?"],
     ]
 )
+
 # Launch the Gradio interface
-inter.launch()
+inter.launch()