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Update app.py
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app.py
CHANGED
@@ -5,7 +5,11 @@ import torch
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# Set max_split_size_mb
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os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:50'
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raven_pipeline = pipeline(
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"text-generation",
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model="Nexusflow/NexusRaven-V2-13B",
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@@ -33,37 +37,21 @@ def create_interface():
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
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""")
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with gr.Row():
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input_text = gr.Textbox(label="Input Text"
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def create_audio_sequence_order(text):
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"""
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Analyzes the text and creates an order for each character and narrator segment.
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Args:
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text (str): The text containing the dialogues and narration.
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Returns:
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list: A list of tuples, each containing the character/narrator name and a segment of their dialogue/narration.
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"""
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Function:
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def convert_text_to_speech_single_voice(text, voice):
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"""
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Converts a given text to speech using a specified voice. This function is used when there is only one character in the text.
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text (str): The text to be converted to speech.
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voice (str): The voice to be used for the audio generation.
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str: The path to the generated speech MP3 file.
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"""
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Function:
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def create_audio_sequence_order(text):
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"""
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@@ -86,15 +74,39 @@ Churchill? – Ah, here’s Miss Woodhouse – Dear Miss Woodhouse, how do you d
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well. This is a meeting quite in fairyland! Such a transformation! – Must not compliment, I know (...) – that would
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be rude, but upon my word, Miss Woodhouse, you do look – how do you like Jane’s hair? (...)
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use either speech to single voice if there's no dialogue or create_audio_sequence_order if there is dialogue<human_end>
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'''
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# Set max_split_size_mb
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os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:50'
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title = """# 🙋🏻♂️Welcome to🌟Tonic's Nexus🐦⬛Raven"""
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description = """You can build with this endpoint using Nexus Raven. The demo is still a work in progress but we hope to add some endpoints for commonly used functions such as intention mappers and audiobook processing.
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You can also use Nexus🐦⬛Raven on your laptop & by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/NexusRaven2?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
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"""
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raven_pipeline = pipeline(
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"text-generation",
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model="Nexusflow/NexusRaven-V2-13B",
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
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""")
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with gr.Row():
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input_text = gr.Textbox(label="Input Text")
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submit_button = gr.Button("Submit")
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output_text = gr.Textbox(label="Nexus🐦⬛Raven")
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submit_button.click(converter.process_text, inputs=input_text, outputs=output_text)
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return app
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if __name__ == "__main__":
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demo = gr.Interface(
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fn=create_interface,
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inputs="text",
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outputs="text",
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examples=[
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['''
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Function:
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def create_audio_sequence_order(text):
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"""
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well. This is a meeting quite in fairyland! Such a transformation! – Must not compliment, I know (...) – that would
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be rude, but upon my word, Miss Woodhouse, you do look – how do you like Jane’s hair? (...)
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use either speech to single voice if there's no dialogue or create_audio_sequence_order if there is dialogue<human_end>
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'''],
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['''
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Function:
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def create_audio_sequence_order(text):
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"""
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Analyzes the text and creates an order for each character and narrator segment.
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Args:
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text (str): The text containing the dialogues and narration.
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Returns:
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list: A list of tuples, each containing the character/narrator name and a segment of their dialogue/narration.
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"""
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Function:
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def convert_text_to_speech_single_voice(text, voice):
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"""
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Converts a given text to speech using a specified voice. This function is used when there is only one character in the text.
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Args:
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text (str): The text to be converted to speech.
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voice (str): The voice to be used for the audio generation.
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Returns:
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str: The path to the generated speech MP3 file.
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"""
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User Query: Currently, one way that the wealthy distinguish themselves from others is through the collection of rare objects. In a Celebration Society, to own an “original” of something will remain significant. However, barring a desire to prevent others from enjoying the experience, it will become possible to have perfect replicas of all manner of objects including paintings and sculptures.
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There will still be pride of ownership in the original. Others will be able to fully enjoy the “same” piece as well.
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use either speech to single voice if there's no dialogue or create_audio_sequence_order if there is dialogue<human_end>
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'''
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]
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],
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title=title,
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description=description
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)
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demo.launch()
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