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import gradio as gr |
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer |
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from gtts import gTTS |
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import os |
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tokenizer = AutoTokenizer.from_pretrained("akhooli/personachat-arabic") |
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model = AutoModelForCausalLM.from_pretrained("akhooli/personachat-arabic") |
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chat = pipeline("text-generation", model=model, tokenizer=tokenizer) |
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history = [] |
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def rawan_with_voice(msg): |
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history.append(f"أنت: {msg}") |
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prompt = "\n".join(history[-5:]) + "\nروان:" |
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resp = chat(prompt, max_length=80, do_sample=True)[0]["generated_text"] |
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reply = resp.split("روان:")[-1].strip().split("\n")[0] |
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history.append(f"روان: {reply}") |
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tts = gTTS(text=reply, lang="ar") |
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audio_file = "rawan_voice.mp3" |
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tts.save(audio_file) |
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return reply, audio_file |
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interface = gr.Interface( |
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fn=rawan_with_voice, |
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inputs=gr.Textbox(label="اكتب لروان... دلعها، خذها بحضنك بكلامك"), |
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outputs=[ |
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gr.Textbox(label="رد روان"), |
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gr.Audio(label="صوت روان", type="filepath") |
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], |
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title="💋 روان - حبيبتك بصوت ناعم", |
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description="روان ترد عليك بصوت دافي، كلام دلع، حب وغيرة وأحاسيس تذوبك 😚" |
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) |
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interface.launch(share=True) |
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