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Update app.py
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app.py
CHANGED
@@ -9,6 +9,7 @@ from datasets import Dataset
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from huggingface_hub import HfApi, login
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import time
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from gradio_modal import Modal
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import huggingface_hub
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import datasets
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@@ -131,7 +132,7 @@ def submit_research_feedback(conversation_history, satisfaction, feedback_text):
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# Get token from environment variable
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env_token = os.environ.get("HF_TOKEN")
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# Use environment token
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push_success = push_feedback_to_hub(env_token)
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if push_success:
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@@ -141,9 +142,8 @@ def submit_research_feedback(conversation_history, satisfaction, feedback_text):
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return status_msg
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#
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=3):
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chatbot = gr.ChatInterface(
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@@ -155,13 +155,6 @@ with gr.Blocks() as demo:
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type="messages"
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)
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# Update conversation_state with each new message
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chatbot.submit_btn.click(
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lambda history: history,
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inputs=[chatbot.chat_history],
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outputs=[conversation_state]
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)
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with gr.Column(scale=1):
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report_button = gr.Button("Share Feedback", variant="primary")
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@@ -171,7 +164,6 @@ with gr.Blocks() as demo:
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gr.Markdown("## Research Preview Feedback")
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gr.Markdown("Thank you for testing our research model. Your feedback (positive or negative) helps us improve!")
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# Remove HF token input as we're using environment variables
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satisfaction = gr.Radio(
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["Very satisfied", "Satisfied", "Neutral", "Unsatisfied", "Very unsatisfied"],
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label="How would you rate your experience with this research model?",
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@@ -187,17 +179,17 @@ with gr.Blocks() as demo:
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submit_button = gr.Button("Submit Research Feedback", variant="primary")
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response_text = gr.Textbox(label="Status", interactive=False)
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# Connect the "
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report_button.click(
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lambda: Modal(visible=True),
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None,
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feedback_modal
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)
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# Connect the submit button to the submit_research_feedback function
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submit_button.click(
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submit_research_feedback,
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inputs=[
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outputs=response_text
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)
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from huggingface_hub import HfApi, login
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import time
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# Install required packages if not present
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from gradio_modal import Modal
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import huggingface_hub
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import datasets
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# Get token from environment variable
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env_token = os.environ.get("HF_TOKEN")
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# Use environment token
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push_success = push_feedback_to_hub(env_token)
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if push_success:
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return status_msg
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# Create the Gradio interface
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=3):
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chatbot = gr.ChatInterface(
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type="messages"
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)
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with gr.Column(scale=1):
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report_button = gr.Button("Share Feedback", variant="primary")
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gr.Markdown("## Research Preview Feedback")
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gr.Markdown("Thank you for testing our research model. Your feedback (positive or negative) helps us improve!")
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satisfaction = gr.Radio(
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["Very satisfied", "Satisfied", "Neutral", "Unsatisfied", "Very unsatisfied"],
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label="How would you rate your experience with this research model?",
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submit_button = gr.Button("Submit Research Feedback", variant="primary")
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response_text = gr.Textbox(label="Status", interactive=False)
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# Connect the "Share Feedback" button to show the modal
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report_button.click(
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lambda: Modal(visible=True),
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None,
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feedback_modal
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)
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# Connect the submit button to the submit_research_feedback function with the current chat history
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submit_button.click(
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lambda satisfaction, feedback_text: submit_research_feedback(chatbot.value, satisfaction, feedback_text),
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inputs=[satisfaction, feedback_text],
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outputs=response_text
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)
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