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Update app.py
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app.py
CHANGED
@@ -48,67 +48,12 @@ def cut_dialogue_history(history_memory, keep_last_n_words = 500):
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last_n_tokens = last_n_tokens - len(paragraphs[0].split(' '))
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paragraphs = paragraphs[1:]
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return '\n' + '\n'.join(paragraphs)
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-
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class ConversationBot:
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def __init__(self):
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print("Initializing AudioChatGPT")
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self.
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self.t2i = T2I(device="cuda:0")
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self.i2t = ImageCaptioning(device="cuda:1")
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self.t2a = T2A(device="cuda:0")
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self.tts = TTS(device="cuda:0")
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self.t2s = T2S(device="cuda:2")
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self.i2a = I2A(device="cuda:1")
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self.a2t = A2T(device="cuda:2")
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self.asr = ASR(device="cuda:1")
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self.inpaint = Inpaint(device="cuda:0")
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#self.tts_ood = TTS_OOD(device="cuda:0")
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self.memory = ConversationBufferMemory(memory_key="chat_history", output_key='output')
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self.tools = [
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Tool(name="Generate Image From User Input Text", func=self.t2i.inference,
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description="useful for when you want to generate an image from a user input text and it saved it to a file. like: generate an image of an object or something, or generate an image that includes some objects. "
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"The input to this tool should be a string, representing the text used to generate image. "),
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Tool(name="Get Photo Description", func=self.i2t.inference,
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description="useful for when you want to know what is inside the photo. receives image_path as input. "
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"The input to this tool should be a string, representing the image_path. "),
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Tool(name="Generate Audio From User Input Text", func=self.t2a.inference,
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description="useful for when you want to generate an audio from a user input text and it saved it to a file."
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"The input to this tool should be a string, representing the text used to generate audio."),
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# Tool(
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# name="Generate human speech with style derived from a speech reference and user input text and save it to a file", func= self.tts_ood.inference,
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# description="useful for when you want to generate speech samples with styles (e.g., timbre, emotion, and prosody) derived from a reference custom voice."
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# "Like: Generate a speech with style transferred from this voice. The text is xxx., or speak using the voice of this audio. The text is xxx."
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# "The input to this tool should be a comma seperated string of two, representing reference audio path and input text."),
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Tool(name="Generate singing voice From User Input Text, Note and Duration Sequence", func= self.t2s.inference,
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description="useful for when you want to generate a piece of singing voice (Optional: from User Input Text, Note and Duration Sequence) and save it to a file."
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"If Like: Generate a piece of singing voice, the input to this tool should be \"\" since there is no User Input Text, Note and Duration Sequence ."
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"If Like: Generate a piece of singing voice. Text: xxx, Note: xxx, Duration: xxx. "
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"Or Like: Generate a piece of singing voice. Text is xxx, note is xxx, duration is xxx."
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"The input to this tool should be a comma seperated string of three, representing text, note and duration sequence since User Input Text, Note and Duration Sequence are all provided."),
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Tool(name="Synthesize Speech Given the User Input Text", func=self.tts.inference,
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description="useful for when you want to convert a user input text into speech audio it saved it to a file."
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"The input to this tool should be a string, representing the text used to be converted to speech."),
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Tool(name="Generate Audio From The Image", func=self.i2a.inference,
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description="useful for when you want to generate an audio based on an image."
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"The input to this tool should be a string, representing the image_path. "),
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Tool(name="Generate Text From The Audio", func=self.a2t.inference,
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description="useful for when you want to describe an audio in text, receives audio_path as input."
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"The input to this tool should be a string, representing the audio_path."),
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Tool(name="Audio Inpainting", func=self.inpaint.show_mel_fn,
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description="useful for when you want to inpaint a mel spectrum of an audio and predict this audio, this tool will generate a mel spectrum and you can inpaint it, receives audio_path as input, "
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"The input to this tool should be a string, representing the audio_path."),
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Tool(name="Transcribe speech", func=self.asr.inference,
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description="useful for when you want to know the text corresponding to a human speech, receives audio_path as input."
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"The input to this tool should be a string, representing the audio_path.")]
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self.agent = initialize_agent(
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self.tools,
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self.llm,
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agent="conversational-react-description",
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verbose=True,
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memory=self.memory,
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return_intermediate_steps=True,
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agent_kwargs={'prefix': AUDIO_CHATGPT_PREFIX, 'format_instructions': AUDIO_CHATGPT_FORMAT_INSTRUCTIONS, 'suffix': AUDIO_CHATGPT_SUFFIX}, )
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def run_text(self, text, state):
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print("===============Running run_text =============")
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print("Inputs:", text, state)
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@@ -125,7 +70,7 @@ class ConversationBot:
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tool = res['intermediate_steps'][0][0].tool
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if tool == "Generate Image From User Input Text" or tool == "Generate Text From The Audio" or tool == "Transcribe speech":
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print("======>Current memory:\n %s" % self.agent.memory)
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response = re.sub('(image/\S*png)', lambda m: f'![](
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state = state + [(text, response)]
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print("Outputs:", state)
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return state, state, gr.Audio.update(visible=False), gr.Image.update(visible=False), gr.Button.update(visible=False)
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@@ -140,7 +85,7 @@ class ConversationBot:
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print("Outputs:", state)
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return state, state, gr.Audio.update(value=audio_filename,visible=True), gr.Image.update(value=image_filename,visible=True), gr.Button.update(visible=True)
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print("======>Current memory:\n %s" % self.agent.memory)
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response = re.sub('(image/\S*png)', lambda m: f'![](
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audio_filename = res['intermediate_steps'][0][1]
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state = state + [(text, response)]
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print("Outputs:", state)
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@@ -185,7 +130,7 @@ class ConversationBot:
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AI_prompt = "Received. "
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self.agent.memory.buffer = self.agent.memory.buffer + Human_prompt + 'AI: ' + AI_prompt
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print("======>Current memory:\n %s" % self.agent.memory)
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state = state + [(f"![](
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print("Outputs:", state)
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return state, state, txt + ' ' + image_filename + ' ', gr.Audio.update(visible=False)
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@@ -195,7 +140,7 @@ class ConversationBot:
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print("======>Previous memory:\n %s" % self.agent.memory)
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inpaint = Inpaint(device="cuda:0")
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new_image_filename, new_audio_filename = inpaint.inference(audio_filename, image_filename)
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AI_prompt = "Here are the predict audio and the mel spectrum." + f"*{new_audio_filename}*" + f"![](
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self.agent.memory.buffer = self.agent.memory.buffer + 'AI: ' + AI_prompt
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print("======>Current memory:\n %s" % self.agent.memory)
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state = state + [(f"Audio Inpainting", AI_prompt)]
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@@ -207,30 +152,106 @@ class ConversationBot:
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return gr.Image.update(value=None, visible=False)
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def clear_button(self):
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return gr.Button.update(visible=False)
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if __name__ == '__main__':
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bot = ConversationBot()
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with gr.Blocks(css="#chatbot .overflow-y-auto{height:500px}") as demo:
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with gr.Row():
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gr.Markdown("## Audio ChatGPT")
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chatbot = gr.Chatbot(elem_id="chatbot", label="Audio ChatGPT")
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state = gr.State([])
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with gr.Row():
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with gr.Column(scale=0.7):
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txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter, or upload an image").style(container=False)
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with gr.Column(scale=0.15, min_width=0):
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clear = gr.Button("Clear️")
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with gr.Column(scale=0.15, min_width=0):
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btn = gr.UploadButton("Upload", file_types=["image","audio"])
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with gr.Row():
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with gr.Column():
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show_mel = gr.Image(type="filepath",tool='sketch',visible=False)
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run_button = gr.Button("Predict Masked Place",visible=False)
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txt.submit(bot.run_text, [txt, state], [chatbot, state, outaudio, show_mel, run_button])
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txt.submit(lambda: "", None, txt)
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btn.upload(bot.run_image_or_audio, [btn, state, txt], [chatbot, state, txt, outaudio])
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last_n_tokens = last_n_tokens - len(paragraphs[0].split(' '))
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paragraphs = paragraphs[1:]
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return '\n' + '\n'.join(paragraphs)
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class ConversationBot:
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def __init__(self):
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print("Initializing AudioChatGPT")
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self.tools = []
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self.memory = ConversationBufferMemory(memory_key="chat_history", output_key='output')
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def run_text(self, text, state):
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print("===============Running run_text =============")
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print("Inputs:", text, state)
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tool = res['intermediate_steps'][0][0].tool
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if tool == "Generate Image From User Input Text" or tool == "Generate Text From The Audio" or tool == "Transcribe speech":
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print("======>Current memory:\n %s" % self.agent.memory)
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response = re.sub('(image/\S*png)', lambda m: f'![]({m.group(0)})*{m.group(0)}*', res['output'])
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state = state + [(text, response)]
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print("Outputs:", state)
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return state, state, gr.Audio.update(visible=False), gr.Image.update(visible=False), gr.Button.update(visible=False)
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print("Outputs:", state)
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return state, state, gr.Audio.update(value=audio_filename,visible=True), gr.Image.update(value=image_filename,visible=True), gr.Button.update(visible=True)
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print("======>Current memory:\n %s" % self.agent.memory)
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response = re.sub('(image/\S*png)', lambda m: f'![]({m.group(0)})*{m.group(0)}*', res['output'])
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audio_filename = res['intermediate_steps'][0][1]
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state = state + [(text, response)]
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print("Outputs:", state)
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AI_prompt = "Received. "
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self.agent.memory.buffer = self.agent.memory.buffer + Human_prompt + 'AI: ' + AI_prompt
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print("======>Current memory:\n %s" % self.agent.memory)
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state = state + [(f"![]({image_filename})*{image_filename}*", AI_prompt)]
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print("Outputs:", state)
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return state, state, txt + ' ' + image_filename + ' ', gr.Audio.update(visible=False)
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print("======>Previous memory:\n %s" % self.agent.memory)
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inpaint = Inpaint(device="cuda:0")
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new_image_filename, new_audio_filename = inpaint.inference(audio_filename, image_filename)
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AI_prompt = "Here are the predict audio and the mel spectrum." + f"*{new_audio_filename}*" + f"![]({new_image_filename})*{new_image_filename}*"
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self.agent.memory.buffer = self.agent.memory.buffer + 'AI: ' + AI_prompt
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print("======>Current memory:\n %s" % self.agent.memory)
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state = state + [(f"Audio Inpainting", AI_prompt)]
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return gr.Image.update(value=None, visible=False)
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def clear_button(self):
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return gr.Button.update(visible=False)
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def init_agent(self, openai_api_key):
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self.llm = OpenAI(temperature=0, openai_api_key=openai_api_key)
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self.t2i = T2I(device="cuda:0")
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self.i2t = ImageCaptioning(device="cuda:0")
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self.t2a = T2A(device="cuda:0")
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self.tts = TTS(device="cuda:0")
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self.t2s = T2S(device="cuda:0")
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self.i2a = I2A(device="cuda:0")
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self.a2t = A2T(device="cuda:0")
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self.asr = ASR(device="cuda:0")
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self.inpaint = Inpaint(device="cuda:0")
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#self.tts_ood = TTS_OOD(device="cuda:0")
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self.tools = [
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Tool(name="Generate Image From User Input Text", func=self.t2i.inference,
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description="useful for when you want to generate an image from a user input text and it saved it to a file. like: generate an image of an object or something, or generate an image that includes some objects. "
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"The input to this tool should be a string, representing the text used to generate image. "),
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Tool(name="Get Photo Description", func=self.i2t.inference,
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description="useful for when you want to know what is inside the photo. receives image_path as input. "
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"The input to this tool should be a string, representing the image_path. "),
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Tool(name="Generate Audio From User Input Text", func=self.t2a.inference,
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description="useful for when you want to generate an audio from a user input text and it saved it to a file."
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"The input to this tool should be a string, representing the text used to generate audio."),
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# Tool(
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# name="Generate human speech with style derived from a speech reference and user input text and save it to a file", func= self.tts_ood.inference,
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# description="useful for when you want to generate speech samples with styles (e.g., timbre, emotion, and prosody) derived from a reference custom voice."
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# "Like: Generate a speech with style transferred from this voice. The text is xxx., or speak using the voice of this audio. The text is xxx."
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# "The input to this tool should be a comma seperated string of two, representing reference audio path and input text."),
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Tool(name="Generate singing voice From User Input Text, Note and Duration Sequence", func= self.t2s.inference,
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description="useful for when you want to generate a piece of singing voice (Optional: from User Input Text, Note and Duration Sequence) and save it to a file."
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"If Like: Generate a piece of singing voice, the input to this tool should be \"\" since there is no User Input Text, Note and Duration Sequence ."
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"If Like: Generate a piece of singing voice. Text: xxx, Note: xxx, Duration: xxx. "
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"Or Like: Generate a piece of singing voice. Text is xxx, note is xxx, duration is xxx."
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"The input to this tool should be a comma seperated string of three, representing text, note and duration sequence since User Input Text, Note and Duration Sequence are all provided."),
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Tool(name="Synthesize Speech Given the User Input Text", func=self.tts.inference,
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description="useful for when you want to convert a user input text into speech audio it saved it to a file."
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"The input to this tool should be a string, representing the text used to be converted to speech."),
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Tool(name="Generate Audio From The Image", func=self.i2a.inference,
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description="useful for when you want to generate an audio based on an image."
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"The input to this tool should be a string, representing the image_path. "),
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Tool(name="Generate Text From The Audio", func=self.a2t.inference,
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description="useful for when you want to describe an audio in text, receives audio_path as input."
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"The input to this tool should be a string, representing the audio_path."),
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Tool(name="Audio Inpainting", func=self.inpaint.show_mel_fn,
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description="useful for when you want to inpaint a mel spectrum of an audio and predict this audio, this tool will generate a mel spectrum and you can inpaint it, receives audio_path as input, "
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"The input to this tool should be a string, representing the audio_path."),
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Tool(name="Transcribe speech", func=self.asr.inference,
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description="useful for when you want to know the text corresponding to a human speech, receives audio_path as input."
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"The input to this tool should be a string, representing the audio_path.")]
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self.agent = initialize_agent(
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self.tools,
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self.llm,
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agent="conversational-react-description",
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verbose=True,
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memory=self.memory,
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return_intermediate_steps=True,
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agent_kwargs={'prefix': AUDIO_CHATGPT_PREFIX, 'format_instructions': AUDIO_CHATGPT_FORMAT_INSTRUCTIONS, 'suffix': AUDIO_CHATGPT_SUFFIX}, )
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return gr.update(visible = True)
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if __name__ == '__main__':
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bot = ConversationBot()
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with gr.Blocks(css="#chatbot .overflow-y-auto{height:500px}") as demo:
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with gr.Row():
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openai_api_key_textbox = gr.Textbox(
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placeholder="Paste your OpenAI API key here to start Visual ChatGPT(sk-...) and press Enter ↵️",
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show_label=False,
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lines=1,
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type="password",
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)
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with gr.Row():
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gr.Markdown("## Audio ChatGPT")
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chatbot = gr.Chatbot(elem_id="chatbot", label="Audio ChatGPT")
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state = gr.State([])
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with gr.Row(visible = False) as input_raws:
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with gr.Column(scale=0.7):
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txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter, or upload an image").style(container=False)
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with gr.Column(scale=0.15, min_width=0):
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clear = gr.Button("Clear️")
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with gr.Column(scale=0.15, min_width=0):
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btn = gr.UploadButton("Upload", file_types=["image","audio"])
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with gr.Column():
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outaudio = gr.Audio(visible=False)
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with gr.Column():
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show_mel = gr.Image(type="filepath",tool='sketch',visible=False)
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run_button = gr.Button("Predict Masked Place",visible=False)
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gr.Examples(
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examples=["Generate an audio of a dog barking",
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"Generate an audio of this image",
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"Can you describe the audio with text?",
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"Generate a speech with text 'here we go'",
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247 |
+
"Generate an image of a cat",
|
248 |
+
"I want to inpaint this audio",
|
249 |
+
# "generate a piece of singing voice. Text sequence is 小酒窝长睫毛AP是你最美的记号. Note sequence is C#4/Db4 | F#4/Gb4 | G#4/Ab4 | A#4/Bb4 F#4/Gb4 | F#4/Gb4 C#4/Db4 | C#4/Db4 | rest | C#4/Db4 | A#4/Bb4 | G#4/Ab4 | A#4/Bb4 | G#4/Ab4 | F4 | C#4/Db4. Note duration sequence is 0.407140 | 0.376190 | 0.242180 | 0.509550 0.183420 | 0.315400 0.235020 | 0.361660 | 0.223070 | 0.377270 | 0.340550 | 0.299620 | 0.344510 | 0.283770 | 0.323390 | 0.360340."
|
250 |
+
],
|
251 |
+
inputs=txt
|
252 |
+
)
|
253 |
|
254 |
+
openai_api_key_textbox.submit(bot.init_agent, [openai_api_key_textbox], [input_raws])
|
255 |
txt.submit(bot.run_text, [txt, state], [chatbot, state, outaudio, show_mel, run_button])
|
256 |
txt.submit(lambda: "", None, txt)
|
257 |
btn.upload(bot.run_image_or_audio, [btn, state, txt], [chatbot, state, txt, outaudio])
|