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Update app.py
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app.py
CHANGED
@@ -1,5 +1,5 @@
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import gradio as gr
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from inference import evo_chat_predict, get_model_config,
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import pandas as pd
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import csv
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from datetime import datetime
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@@ -37,21 +37,22 @@ with gr.Blocks(theme=gr.themes.Base(), css="body { background-color: #0f0f0f; co
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# π Ask Evo
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def ask_evo(q, opt1, opt2, hist):
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result = evo_chat_predict(hist, q, [opt1, opt2])
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evo_text = f"Answer: {result['answer']} (Confidence: {result['confidence']})\n\nReasoning: {result['reasoning']}"
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gpt_text = get_gpt_response(q)
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stats = get_model_config()
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stats_text = f"Layers: {stats['num_layers']} | Heads: {stats['num_heads']} | FFN: {stats['ffn_dim']} | Memory: {stats['memory_enabled']} | Phase: {stats['phase']} | Accuracy: {stats['accuracy']}"
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#
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new_row = [q, opt1, opt2, result["answer"], result["confidence"], result["reasoning"], result["context_used"]]
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new_row_df = pd.DataFrame([new_row], columns=hist.columns)
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if hist.empty
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return evo_text, gpt_text, stats_text, updated_df
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# π Actual retraining
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@@ -78,7 +79,7 @@ with gr.Blocks(theme=gr.themes.Base(), css="body { background-color: #0f0f0f; co
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return "β οΈ No feedback to export."
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# π Event bindings
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evo_btn.click(fn=ask_evo, inputs=[query, option1, option2, convo], outputs=[evo_box, gpt_box, evo_stats, convo])
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retrain_btn.click(fn=retrain_evo, inputs=[], outputs=[status_box])
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clear_btn.click(fn=clear_fields, inputs=[], outputs=[query, option1, option2, evo_box, gpt_box, convo])
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export_btn.click(fn=log_feedback_to_csv, inputs=[], outputs=[status_box])
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import gradio as gr
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from inference import evo_chat_predict, get_model_config, get_gpt_response, retrain_from_feedback
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import pandas as pd
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import csv
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from datetime import datetime
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)
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# π Ask Evo
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def ask_evo(q, opt1, opt2, hist, selected):
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result = evo_chat_predict(hist, q, [opt1, opt2])
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evo_text = f"Answer: {result['answer']} (Confidence: {result['confidence']})\n\nReasoning: {result['reasoning']}"
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gpt_text = get_gpt_response(q)
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stats = get_model_config()
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stats_text = f"Layers: {stats['num_layers']} | Heads: {stats['num_heads']} | FFN: {stats['ffn_dim']} | Memory: {stats['memory_enabled']} | Phase: {stats['phase']} | Accuracy: {stats['accuracy']}"
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# Update history
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new_row = [q, opt1, opt2, result["answer"], result["confidence"], result["reasoning"], result["context_used"]]
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new_row_df = pd.DataFrame([new_row], columns=hist.columns)
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updated_df = new_row_df if hist.empty else pd.concat([hist, new_row_df], ignore_index=True)
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# Log feedback
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if selected in ["Evo", "GPT"]:
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feedback_log.append(new_row)
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return evo_text, gpt_text, stats_text, updated_df
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# π Actual retraining
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return "β οΈ No feedback to export."
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# π Event bindings
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evo_btn.click(fn=ask_evo, inputs=[query, option1, option2, convo, feedback], outputs=[evo_box, gpt_box, evo_stats, convo])
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retrain_btn.click(fn=retrain_evo, inputs=[], outputs=[status_box])
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clear_btn.click(fn=clear_fields, inputs=[], outputs=[query, option1, option2, evo_box, gpt_box, convo])
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export_btn.click(fn=log_feedback_to_csv, inputs=[], outputs=[status_box])
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