Update app.py

app.py

@@ -1,36 +1,53 @@
 import gradio as gr
-from inference import get_evo_response, get_gpt_response, get_context_from_file
+from inference import get_evo_response, get_gpt_response
 from logger import log_feedback
+import retrain
+import pandas as pd
+import os
 
-def advisor_interface(query, file, feedback_choice):
-    context = None
-    if file is not None:
-        context = get_context_from_file(file)
-
-    evo_output = get_evo_response(query, file)
-    gpt_output = get_gpt_response(query, file)
+def advisor_interface(query, context, feedback_choice):
+    evo_output, evo_reasoning = get_evo_response(query, context)
+    gpt_output = get_gpt_response(query, context)
 
     if feedback_choice != "No feedback":
-        log_feedback(query, context, evo_output, feedback_choice)
+        label = 1 if feedback_choice == "👍 Helpful" else 0
+        log_feedback(query, context, evo_output, label)
+
+    return evo_reasoning, gpt_output, load_history()
+
+def retrain_evo():
+    retrain.fine_tune_on_feedback()
+    return "✅ Evo retrained on feedback.", load_history()
 
-    return evo_output, gpt_output
+def load_history():
+    if os.path.exists("feedback_log.csv"):
+        df = pd.read_csv("feedback_log.csv")
+        return df.tail(10).to_markdown(index=False)
+    return "No history available yet."
 
 with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 EvoRAG – Retrieval-Augmented Adaptive AI for Finance")
+    gr.Markdown("## 🧠 EvoRAG – Retrieval-Augmented Adaptive AI")
 
     with gr.Row():
         query = gr.Textbox(label="📝 Ask a financial question", placeholder="e.g. Should we reduce exposure to Fund A?")
-    
-    file = gr.File(label="📂 Upload policy or memo (.pdf or .txt)", type="file")
+        context = gr.Textbox(label="📂 Paste memo, news, or background", placeholder="e.g. Tech Fund A underperformed 3.2%...")
 
     with gr.Row():
         feedback = gr.Radio(["👍 Helpful", "👎 Not Helpful", "No feedback"], label="Was Evo’s answer useful?", value="No feedback")
 
     with gr.Row():
-        evo_out = gr.Textbox(label="🔬 EvoRAG Suggestion")
+        evo_out = gr.Textbox(label="🔬 EvoRAG Suggestion (with reasoning)")
         gpt_out = gr.Textbox(label="🤖 GPT-3.5 Suggestion")
 
-    submit_btn = gr.Button("Run Advisors")
-    submit_btn.click(fn=advisor_interface, inputs=[query, file, feedback], outputs=[evo_out, gpt_out])
+    run_button = gr.Button("Run Advisors")
+    run_button.click(fn=advisor_interface, inputs=[query, context, feedback], outputs=[evo_out, gpt_out, gr.Textbox(label="📜 Recent History")])
+
+    gr.Markdown("---")
+    gr.Markdown("### 🔁 Retrain Evo from Feedback")
+    retrain_button = gr.Button("📚 Retrain Evo")
+    retrain_output = gr.Textbox(label="🛠️ Retrain Status")
+    history_output = gr.Textbox(label="📜 Recent History")
+
+    retrain_button.click(fn=retrain_evo, inputs=[], outputs=[retrain_output, history_output])
 
 demo.launch()