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import gradio as gr |
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from transformers import pipeline |
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import os |
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import torch |
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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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torch_dtype="auto", |
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device_map="auto", |
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) |
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class DialogueToSpeechConverter: |
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def __init__(self): |
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self.raven_pipeline = raven_pipeline |
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def process_text(self, input_text: str) -> str: |
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prompt = f"User Query: {input_text}<human_end>" |
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result = self.raven_pipeline(prompt, max_new_tokens=2048, return_full_text=False, do_sample=False, temperature=0.001)[0]["generated_text"] |
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torch.cuda.empty_cache() |
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return result |
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def create_interface(): |
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converter = DialogueToSpeechConverter() |
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with gr.Blocks() as app: |
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gr.Markdown("""# 🙋🏻♂️Welcome to🌟Tonic's Nexus🐦⬛Raven""") |
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gr.Markdown("""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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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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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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User Query: Thank you, my mother is remarkably well. Gone to Mr. Woodhouse’s. I made her take her shawl – for the |
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evenings are not warm – her large new shawl – Mrs. Dixon’s wedding present. So kind of her to think of my |
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mother! Bought at Weymouth, you know – Mr. Dixon’s choice. There were three others, Jane says, which they |
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hesitated about some time. Colonel Campbell rather preferred an olive. My dear Jane, are you sure you did not |
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wet your feet? – It was but a drop or two, but I am so afraid: but Mr. Frank Churchill was so extremely – and |
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there was a mat to step upon – I shall never forget his extreme politeness. (…) Do we not often talk of Mr. Frank |
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Churchill? – Ah, here’s Miss Woodhouse – Dear Miss Woodhouse, how do you do? Very well, I thank you, quite |
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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() |
