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Update app.py
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app.py
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@@ -8,7 +8,6 @@ import secrets
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from pathlib import Path
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from pydub import AudioSegment
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# Initialize the model and tokenizer
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torch.manual_seed(420)
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-Audio-Chat", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-Audio-Chat", device_map="cuda", trust_remote_code=True).eval()
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@@ -45,6 +44,8 @@ def _parse_text(text):
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return text
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def predict(_chatbot, task_history, user_input):
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print("Predict - Start: task_history =", task_history)
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if not isinstance(task_history, list) or not all(isinstance(item, tuple) and len(item) == 2 for item in task_history):
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print("Error: task_history should be a list of tuples of length 2.")
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@@ -107,6 +108,8 @@ def predict(_chatbot, task_history, user_input):
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def regenerate(_chatbot, task_history):
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print("Regenerate - Start: task_history =", task_history)
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if not task_history:
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return _chatbot
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@@ -123,6 +126,8 @@ def regenerate(_chatbot, task_history):
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return predict(_chatbot, task_history)
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def add_text(history, task_history, text):
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print("Add Text - Before: task_history =", task_history)
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if not isinstance(task_history, list):
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task_history = []
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@@ -132,6 +137,8 @@ def add_text(history, task_history, text):
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return history, task_history
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def add_file(history, task_history, file):
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print("Add File - Before: task_history =", task_history)
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history.append(((file.name,), None))
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task_history.append(((file.name,), None))
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@@ -139,6 +146,8 @@ def add_file(history, task_history, file):
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return history, task_history
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def add_mic(history, task_history, file):
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print("Add Mic - Before: task_history =", task_history)
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if file is None:
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return history, task_history
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@@ -153,6 +162,8 @@ def reset_user_input():
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return gr.update(value="")
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def reset_state(task_history):
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print("Reset State - Before: task_history =", task_history)
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task_history = []
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print("Reset State - After: task_history =", task_history)
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@@ -163,11 +174,11 @@ iface = gr.Interface(
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inputs=[
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gr.Audio(label="Audio Input"),
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gr.Textbox(label="Text Query"),
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gr.State(
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],
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outputs=[
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"text",
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gr.State()
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],
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title="Audio-Text Interaction Model",
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description="This model can process an audio input along with a text query and provide a response.",
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from pathlib import Path
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from pydub import AudioSegment
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torch.manual_seed(420)
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-Audio-Chat", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-Audio-Chat", device_map="cuda", trust_remote_code=True).eval()
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return text
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def predict(_chatbot, task_history, user_input):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Predict - Start: task_history =", task_history)
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if not isinstance(task_history, list) or not all(isinstance(item, tuple) and len(item) == 2 for item in task_history):
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print("Error: task_history should be a list of tuples of length 2.")
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def regenerate(_chatbot, task_history):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Regenerate - Start: task_history =", task_history)
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if not task_history:
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return _chatbot
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return predict(_chatbot, task_history)
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def add_text(history, task_history, text):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Add Text - Before: task_history =", task_history)
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if not isinstance(task_history, list):
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task_history = []
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return history, task_history
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def add_file(history, task_history, file):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Add File - Before: task_history =", task_history)
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history.append(((file.name,), None))
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task_history.append(((file.name,), None))
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return history, task_history
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def add_mic(history, task_history, file):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Add Mic - Before: task_history =", task_history)
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if file is None:
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return history, task_history
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return gr.update(value="")
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def reset_state(task_history):
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if task_history is None or not isinstance(task_history, list):
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task_history = []
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print("Reset State - Before: task_history =", task_history)
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task_history = []
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print("Reset State - After: task_history =", task_history)
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inputs=[
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gr.Audio(label="Audio Input"),
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gr.Textbox(label="Text Query"),
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gr.State()
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],
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outputs=[
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"text",
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gr.State()
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],
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title="Audio-Text Interaction Model",
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description="This model can process an audio input along with a text query and provide a response.",
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