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Update voice_chat.py
Browse files- voice_chat.py +2 -2
voice_chat.py
CHANGED
@@ -21,7 +21,7 @@ tokenizer = spm.SentencePieceProcessor(hf_hub_download(model_name, "tokenizer.sp
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# Mistral Model Configuration
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client1 = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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system_instructions1 = "
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def resample(audio_fp32, sr):
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return soxr.resample(audio_fp32, sr, sample_rate)
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@@ -50,7 +50,7 @@ def transcribe(audio_path):
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return text
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def model(text):
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formatted_prompt = system_instructions1 + text + "[
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stream = client1.text_generation(formatted_prompt, max_new_tokens=512, stream=True, details=True, return_full_text=False)
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return "".join([response.token.text for response in stream if response.token.text != "</s>"])
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# Mistral Model Configuration
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client1 = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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system_instructions1 = "[SYSTEM] Answer as Real OpenGPT 4o, Made by 'KingNish', Keep conversation very short, clear, friendly and concise. The text provided is a request for a specific type of response from you, the virtual assistant. You will avoid introductions and start answering the query directly, elaborating on all aspects of the request. As an AI-powered assistant, your task is to generate responses that appear as if they are created by the user and not an AI-powered assistant. [USER]"
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def resample(audio_fp32, sr):
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return soxr.resample(audio_fp32, sr, sample_rate)
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return text
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def model(text):
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formatted_prompt = system_instructions1 + text + "[OpenGPT 4o]"
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stream = client1.text_generation(formatted_prompt, max_new_tokens=512, stream=True, details=True, return_full_text=False)
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return "".join([response.token.text for response in stream if response.token.text != "</s>"])
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