Spaces:
Sleeping
Sleeping
aaaaa
Browse files- app.py +9 -5
- app_interface.py +141 -0
app.py
CHANGED
@@ -37,7 +37,7 @@ def respond(
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messages.append({"role": "user", "content": message})
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response = ""
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-
for
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messages,
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max_tokens=max_tokens,
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stream=True,
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@@ -45,14 +45,17 @@ def respond(
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top_p=top_p,
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):
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if stop_inference:
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-
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-
yield history
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break
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-
token =
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response += token
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-
history
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yield history
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def cancel_inference():
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global stop_inference
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stop_inference = True
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@@ -124,6 +127,7 @@ with gr.Blocks(css=custom_css) as demo:
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cancel_button = gr.Button("Cancel Inference", variant="danger")
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def chat_fn(message, history):
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return respond(
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message,
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history,
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messages.append({"role": "user", "content": message})
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response = ""
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+
for message_chunk in client.chat_completion(
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messages,
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max_tokens=max_tokens,
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stream=True,
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top_p=top_p,
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):
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if stop_inference:
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response = "Inference cancelled."
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break
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token = message_chunk.choices[0].delta.content
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response += token
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history[-1] = (message, response)
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yield history
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# Finalize response in history
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history.append((message, response))
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yield history
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+
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def cancel_inference():
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global stop_inference
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stop_inference = True
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cancel_button = gr.Button("Cancel Inference", variant="danger")
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def chat_fn(message, history):
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history.append((message, "")) # Initialize with empty response
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return respond(
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message,
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history,
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app_interface.py
ADDED
@@ -0,0 +1,141 @@
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import gradio as gr
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from huggingface_hub import InferenceClient
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import time
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# Inference client setup
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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# Global flag to handle cancellation
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stop_inference = False
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def respond(
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message,
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history: list[tuple[str, str]],
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system_message,
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max_tokens,
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temperature,
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top_p,
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use_local_model,
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):
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global stop_inference
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stop_inference = False # Reset cancellation flag
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if use_local_model:
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# Simulate local inference
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time.sleep(2) # simulate a delay
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response = "This is a response from the local model."
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history.append((message, response))
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yield history
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else:
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# API-based inference
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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if val[0]:
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messages.append({"role": "user", "content": val[0]})
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if val[1]:
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=max_tokens,
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stream=True,
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temperature=temperature,
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top_p=top_p,
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):
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if stop_inference:
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history.append((message, "Inference cancelled."))
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yield history
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break
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token = message.choices[0].delta.content
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response += token
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history.append((message, response))
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yield history
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def cancel_inference():
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global stop_inference
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stop_inference = True
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# Custom CSS for a fancy look
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custom_css = """
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#main-container {
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background-color: #f0f0f0;
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font-family: 'Arial', sans-serif;
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}
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.gradio-container {
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max-width: 700px;
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margin: 0 auto;
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padding: 20px;
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background: white;
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
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border-radius: 10px;
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}
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.gr-button {
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background-color: #4CAF50;
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color: white;
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border: none;
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border-radius: 5px;
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padding: 10px 20px;
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cursor: pointer;
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transition: background-color 0.3s ease;
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}
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.gr-button:hover {
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background-color: #45a049;
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}
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.gr-slider input {
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color: #4CAF50;
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}
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.gr-chat {
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font-size: 16px;
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}
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#title {
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text-align: center;
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font-size: 2em;
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margin-bottom: 20px;
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color: #333;
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}
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"""
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# Define the interface
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with gr.Blocks(css=custom_css) as demo:
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gr.Markdown("<h1 style='text-align: center;'>🌟 Fancy AI Chatbot 🌟</h1>")
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gr.Markdown("Interact with the AI chatbot using customizable settings below.")
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with gr.Row():
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system_message = gr.Textbox(value="You are a friendly Chatbot.", label="System message", interactive=True)
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use_local_model = gr.Checkbox(label="Use Local Model", value=False)
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with gr.Row():
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max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
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temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
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top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
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chat_history = gr.Chatbot(label="Chat")
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user_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
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cancel_button = gr.Button("Cancel Inference", variant="danger")
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def chat_fn(message, history):
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return respond(
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message,
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history,
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system_message.value,
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max_tokens.value,
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temperature.value,
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top_p.value,
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use_local_model.value,
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)
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user_input.submit(chat_fn, [user_input, chat_history], chat_history)
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cancel_button.click(cancel_inference)
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if __name__ == "__main__":
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demo.launch(share=True)
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