Update app.py

app.py

@@ -1,31 +1,37 @@
 import gradio as gr
-from inference import get_evo_response, get_gpt_response
+from inference import evo_rag_response, get_gpt_response
+from retriever import build_index_from_file
 from logger import log_feedback
 
-def advisor_interface(query, context, feedback_choice):
-    evo_output = get_evo_response(query, context)
-    gpt_output = get_gpt_response(query, context)
+def advisor_interface(query, file, feedback_choice):
+    # 🧾 Build RAG index if a file is uploaded
+    if file is not None:
+        build_index_from_file(file.name)
 
+    # 🧠 Get EvoRAG + GPT responses
+    evo_output = evo_rag_response(query)
+    gpt_output = get_gpt_response(query, "")  # GPT optional context
+
+    # 🗳️ Log feedback
     if feedback_choice != "No feedback":
-        log_feedback(query, context, evo_output, feedback_choice)
+        log_feedback(query, "[RAG context]", evo_output, feedback_choice)
 
     return evo_output, gpt_output
 
 with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 EvoAdvisor – Your Adaptive AI Copilot for Finance")
+    gr.Markdown("## 🧠 EvoRAG – Retrieval-Augmented Adaptive AI for Finance")
 
     with gr.Row():
-        query = gr.Textbox(label="📝 Ask a financial question", placeholder="e.g. Should we exit this position?")
-        context = gr.Textbox(label="📂 Related memo or policy context", placeholder="Paste internal strategy or notes here...")
+        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)", file_types=[".pdf", ".txt"])
 
-    with gr.Row():
-        feedback = gr.Radio(["👍 Helpful", "👎 Not Helpful", "No feedback"], label="Was Evo’s answer useful?", value="No feedback")
+    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="🔬 EvoAdvisor's Suggestion")
-        gpt_out = gr.Textbox(label="🤖 GPT-3.5's Suggestion")
+        evo_out = gr.Textbox(label="🔬 EvoRAG Suggestion")
+        gpt_out = gr.Textbox(label="🤖 GPT-3.5 Suggestion")
 
     submit_btn = gr.Button("Run Advisors")
-    submit_btn.click(fn=advisor_interface, inputs=[query, context, feedback], outputs=[evo_out, gpt_out])
+    submit_btn.click(fn=advisor_interface, inputs=[query, file, feedback], outputs=[evo_out, gpt_out])
 
 demo.launch()