Update app/main.py

app/main.py

@@ -1,80 +1,81 @@
 """
-CryptoSentinel AI — FastAPI app entry point
+CryptoSentinel AI — FastAPI app entry point (no /static mount)
 - Fetches live prices from CoinGecko
-- Provides real-time sentiment analysis using Hugging Face Transformers
-- Compatible with Hugging Face Spaces (safe caching)
+- Provides real-time sentiment analysis via SSE
+- Compatible with Hugging Face Spaces
 """
 
-import os
+import json
+import asyncio
 from pathlib import Path
 
 from fastapi import FastAPI, Request, BackgroundTasks
 from fastapi.responses import HTMLResponse, JSONResponse, StreamingResponse
-from fastapi.staticfiles import StaticFiles
 from fastapi.templating import Jinja2Templates
 from apscheduler.schedulers.background import BackgroundScheduler
 
 from price_fetcher import fetch_prices, CURRENT_PRICES
 from sentiment import SentimentCache
-import json
-import asyncio
 
-# ──────────────────────────────────────────────────────────────────────────────
+# ────── Setup ───────────────────────────────────────────────────────────────
 
-# Define paths
 BASE_DIR = Path(__file__).parent
-TEMPLATES_DIR = BASE_DIR / "templates"
-STATIC_DIR = BASE_DIR / "static"
-
-# Create FastAPI app
-app = FastAPI(title="CryptoSentinel AI")
-templates = Jinja2Templates(directory=str(TEMPLATES_DIR))
-app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
+templates = Jinja2Templates(directory=str(BASE_DIR / "templates"))
 
-# ──────────────────────────────────────────────────────────────────────────────
+app = FastAPI(title="CryptoSentinel AI (CDN-only static)")
 
-# Start background job to update prices
+# Start background job to refresh prices every 10s
 scheduler = BackgroundScheduler(daemon=True)
 scheduler.add_job(fetch_prices, trigger="interval", seconds=10)
 scheduler.start()
 
 @app.on_event("shutdown")
-def stop_scheduler():
+def shutdown():
     scheduler.shutdown(wait=False)
 
 @app.on_event("startup")
-def warm_up_model():
-    # Pre-warm Hugging Face model on startup to avoid first-request latency
-    SentimentCache.compute("The market is bullish today!")
+def warmup_model():
+    # Preload the sentiment model once on startup
+    SentimentCache.compute("The market is pumping 🚀")
 
-# ──────────────────────────────────────────────────────────────────────────────
-# ROUTES
+# ────── Routes ──────────────────────────────────────────────────────────────
 
 @app.get("/", response_class=HTMLResponse)
 async def index(request: Request):
+    """
+    Renders index.html which now should reference HTMX via CDN:
+      <script src="https://unpkg.com/[email protected]"></script>
+    """
     return templates.TemplateResponse("index.html", {"request": request})
 
 @app.get("/prices", response_class=JSONResponse)
-async def get_prices():
+async def prices():
+    """Return the latest cached crypto prices."""
     return CURRENT_PRICES
 
 @app.post("/sentiment")
-async def analyze_sentiment(request: Request, background_tasks: BackgroundTasks):
+async def sentiment(request: Request, background_tasks: BackgroundTasks):
+    """
+    Queue sentiment analysis for the given text.
+    Frontend will pick up results via SSE.
+    """
     body = await request.json()
-    text = body.get("text", "")
-    background_tasks.add_task(SentimentCache.compute, text)
-    return {"status": "processing"}
+    background_tasks.add_task(SentimentCache.compute, body.get("text", ""))
+    return {"status": "queued"}
 
 @app.get("/sentiment/stream")
-async def stream_sentiment():
-    """Server-Sent Events stream for pushing sentiment updates."""
-    async def event_stream():
+async def sentiment_stream():
+    """
+    Server-Sent Events endpoint that pushes new sentiment results
+    as they become available in SentimentCache.latest_result.
+    """
+    async def event_generator():
         last_id = 0
         while True:
             if SentimentCache.latest_id != last_id:
                 last_id = SentimentCache.latest_id
-                data = json.dumps(SentimentCache.latest_result)
-                yield f"id:{last_id}\ndata:{data}\n\n"
+                payload = json.dumps(SentimentCache.latest_result)
+                yield f"id:{last_id}\ndata:{payload}\n\n"
             await asyncio.sleep(1)
 
-    return StreamingResponse(event_stream(), media_type="text/event-stream")
+    return StreamingResponse(event_generator(), media_type="text/event-stream")