Update app.py
Browse files
app.py
CHANGED
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@@ -437,7 +437,7 @@ with gr.Blocks() as demo:
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outputs=gr.Textbox(label="Fine-tuning Status", interactive=False),
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title="⚙️ Fine-tuning (Optional)",
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description="This section allows you to fine-tune the custom R1 model on a small subset of the ServiceNow dataset. This step is optional but can potentially improve the model's performance on ServiceNow-related tasks. **Note:** This process may take up to 5 minutes.",
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),
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gr.Interface(
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fn=predict,
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@@ -451,7 +451,7 @@ with gr.Blocks() as demo:
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outputs=gr.Textbox(label="Custom R1 Output", lines=8, interactive=False),
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title="✍️ Direct Generation",
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description="Enter a prompt to generate text directly using the custom R1 model. This is standard text generation without retrieval augmentation.",
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),
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gr.Interface(
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fn=compare_models,
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@@ -468,26 +468,25 @@ with gr.Blocks() as demo:
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],
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title="🆚 Model Comparison",
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description="Enter a prompt to compare the text generation of your fine-tuned custom R1 model with the official DeepSeek-R1-Distill-Llama-8B model.",
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),
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# Corrected gr.ChatInterface - inputs are NOT passed here
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gr.ChatInterface(
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fn=chat_rag,
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chatbot=gr.Chatbot(label="RAG Chatbot"),
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textbox=gr.Textbox(placeholder="Ask a question to the RAG Chatbot...", lines=2, show_label=False),
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title="💬 RAG Chat",
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description="Chat with the custom R1 model, enhanced with retrieval-augmented memory. The model retrieves relevant info for informed responses.",
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submit_button="➡️ Send",
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clear_btn=None
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)
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# Sliders defined OUTSIDE ChatInterface, but within the gr.Blocks() for the RAG Chat Tab
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with gr.Row():
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temperature_chat = gr.Slider(0.0, 1.5, step=0.1, value=0.7, label="Temperature", visible=False) # Initially hidden, can be shown if needed
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top_p_chat = gr.Slider(0.0, 1.0, step=0.05, value=0.9, label="Top-p", visible=False) # Initially hidden, can be shown if needed
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min_tokens_chat = gr.Slider(1, 2500, value=50, step=10, label="Min New Tokens", visible=False) # Initially hidden, can be shown if needed
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max_tokens_chat = gr.Slider(1, 2500, value=200, step=50, label="Max New Tokens", visible=False) # Initially hidden, can be shown if needed
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-
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]
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).render():
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pass # No need for extra elements outside the tabs now
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outputs=gr.Textbox(label="Fine-tuning Status", interactive=False),
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title="⚙️ Fine-tuning (Optional)",
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description="This section allows you to fine-tune the custom R1 model on a small subset of the ServiceNow dataset. This step is optional but can potentially improve the model's performance on ServiceNow-related tasks. **Note:** This process may take up to 5 minutes.",
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# submit_button_text="🚀 Start Fine-tuning (QLoRA)" # REMOVE THIS LINE
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),
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gr.Interface(
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fn=predict,
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outputs=gr.Textbox(label="Custom R1 Output", lines=8, interactive=False),
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title="✍️ Direct Generation",
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description="Enter a prompt to generate text directly using the custom R1 model. This is standard text generation without retrieval augmentation.",
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# submit_button_text="✨ Generate Text" # REMOVE THIS LINE
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),
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gr.Interface(
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fn=compare_models,
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],
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title="🆚 Model Comparison",
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description="Enter a prompt to compare the text generation of your fine-tuned custom R1 model with the official DeepSeek-R1-Distill-Llama-8B model.",
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# submit_button_text="⚖️ Compare Models" # REMOVE THIS LINE
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),
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gr.ChatInterface(
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fn=chat_rag,
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chatbot=gr.Chatbot(label="RAG Chatbot"),
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textbox=gr.Textbox(placeholder="Ask a question to the RAG Chatbot...", lines=2, show_label=False),
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inputs=[
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"textbox",
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gr.State([]), # chat_state
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gr.Slider(0.0, 1.5, step=0.1, value=0.7, label="Temperature"),
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gr.Slider(0.0, 1.0, step=0.05, value=0.9, label="Top-p"),
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gr.Slider(1, 2500, value=50, step=10, label="Min New Tokens"),
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gr.Slider(1, 2500, value=200, step=50, label="Max New Tokens")
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],
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title="💬 RAG Chat",
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description="Chat with the custom R1 model, enhanced with retrieval-augmented memory. The model retrieves relevant info for informed responses.",
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submit_button="➡️ Send",
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clear_btn=None # Optional: You can add a clear button if needed
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)
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]
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).render():
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pass # No need for extra elements outside the tabs now
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