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app/main.py

@@ -1,8 +1,5 @@
 
-import threading
-import uvicorn
 import gradio as gr
-import requests
 from fastapi import FastAPI, HTTPException
 from app.schemas import PredictRequest, PredictResponse
 from app import model as ml
@@ -10,14 +7,10 @@ from app import model as ml
 # ── FastAPI ──────────────────────────────────────────────
 app = FastAPI(
     title="PKD Financial Sentiment API",
-    description=(
-        "ALBERT student model trained via Patient Knowledge Distillation "
-        "on scraped financial headlines. Outperforms FinBERT teacher on macro-F1."
-    ),
     version="1.0.0",
 )
 
-@app.get("/")
+@app.get("/api")
 def root():
     return {
         "status": "ok",
@@ -47,7 +40,7 @@ LABEL_EMOJI = {
 def analyze(headline: str):
     if not headline.strip():
         return "Please enter a headline.", "", ""
-    result = ml.predict(headline)  # call directly, no HTTP hop needed
+    result = ml.predict(headline)
     return (
         LABEL_EMOJI[result["label"]],
         f"{result['confidence'] * 100:.1f}%",
@@ -56,20 +49,18 @@ def analyze(headline: str):
 
 with gr.Blocks(title="PKD Financial Sentiment") as demo:
     gr.Markdown("""
-    # 📈 PKD Financial Sentiment API
+    # 📈 PKD Financial Sentiment
     ALBERT student model trained via **Patient Knowledge Distillation** on scraped
     financial headlines. Outperforms FinBERT teacher on macro-F1 at ~40% parameter count.
 
-    **API endpoint:** `POST /predict` — see [/docs](/docs) for full spec.
+    API endpoint: `POST /predict` — see [/docs](/docs) for full spec.
     """)
 
-    with gr.Row():
-        text_input = gr.Textbox(
-            label="Financial Headline",
-            placeholder="e.g. Apple beats Q3 earnings expectations by wide margin",
-            lines=2,
-            scale=4,
-        )
+    text_input = gr.Textbox(
+        label="Financial Headline",
+        placeholder="e.g. Apple beats Q3 earnings expectations by wide margin",
+        lines=2,
+    )
 
     analyze_btn = gr.Button("Analyze Sentiment", variant="primary")
 
@@ -95,5 +86,5 @@ with gr.Blocks(title="PKD Financial Sentiment") as demo:
         outputs=[label_out, confidence_out, latency_out],
     )
 
-# Mount Gradio onto FastAPI at root
+# Gradio takes over "/" — FastAPI routes still work at /predict, /docs, /health
 app = gr.mount_gradio_app(app, demo, path="/")