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@@ -5,13 +5,13 @@ FROM python:3.10-slim
 # Set working directory
 WORKDIR /app
 
-# Environment variables for better Python behavior
+# Set environment variables for better Python behavior
 ENV PYTHONUNBUFFERED=1 \
     PYTHONDONTWRITEBYTECODE=1 \
     PIP_NO_CACHE_DIR=1 \
     PIP_DISABLE_PIP_VERSION_CHECK=1
 
-# System dependencies required for building Python packages
+# Install system dependencies required for building Python packages
 RUN apt-get update && apt-get install -y --no-install-recommends \
     gcc \
     g++ \
@@ -22,36 +22,50 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
 # Copy requirements first for better layer caching
 COPY requirements.txt .
 
-# ✅ Install core Python dependencies from requirements.txt
-#   (اینجا دیگه نسخه‌ها فقط از requirements.txt خوانده می‌شن)
-RUN pip install --no-cache-dir -r requirements.txt
+# Install Python dependencies with optimizations
+# Split into two steps: core dependencies first, then ML libraries
+RUN pip install --no-cache-dir \
+    fastapi==0.104.1 \
+    uvicorn[standard]==0.24.0 \
+    pydantic==2.5.0 \
+    python-multipart==0.0.6 \
+    websockets==12.0 \
+    SQLAlchemy==2.0.23 \
+    APScheduler==3.10.4 \
+    aiohttp==3.9.1 \
+    requests==2.31.0 \
+    httpx \
+    python-dotenv==1.0.0 \
+    feedparser==6.0.11 \
+    gradio==4.14.0 \
+    pandas==2.1.4 \
+    plotly==5.18.0
 
-# ✅ Install HuggingFace / ML dependencies separately
+# Install HuggingFace ML dependencies separately
 RUN pip install --no-cache-dir \
-    "transformers>=4.44.0" \
-    "datasets>=3.0.0" \
-    "huggingface_hub>=0.24.0" \
-    "sentencepiece>=0.1.99" \
-    "protobuf>=3.20.0" && \
-    pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu \
-    "torch>=2.0.0"
+    transformers>=4.44.0 \
+    datasets>=3.0.0 \
+    huggingface_hub>=0.24.0 \
+    torch>=2.0.0 --index-url https://download.pytorch.org/whl/cpu \
+    sentencepiece>=0.1.99 \
+    protobuf>=3.20.0
 
 # Copy all application code
 COPY . .
 
 # Create necessary directories
-RUN mkdir -p data logs && \
-    chmod -R 755 data logs
+RUN mkdir -p data logs
+
+# Set proper permissions for data directories
+RUN chmod -R 755 data logs
 
 # Expose port 7860 (HuggingFace Spaces standard port)
 EXPOSE 7860
 
 # Health check endpoint for HuggingFace Spaces
-# مطمئن شو تو FastAPI روت /health رو داری، مثلاً:
-# @app.get("/health") -> {"status": "ok"}
 HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3 \
     CMD curl -f http://localhost:7860/health || exit 1
 
 # Run the FastAPI application with uvicorn
-# UI تو می‌تونه HTML استاتیک باشه؛ مهم اینه FastAPI این‌ها رو سرو کنه
+# Using multiple workers for better performance (adjust based on available resources)
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--log-level", "info", "--workers", "1"]

app.py

@@ -10,12 +10,14 @@ from contextlib import asynccontextmanager
 
 from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
+from fastapi.responses import JSONResponse, HTMLResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
 
 # Import API modules
 from api.endpoints import router as api_router
 from api.websocket import router as websocket_router, manager as ws_manager
 from api.pool_endpoints import router as pool_router
+from api.data_endpoints import router as data_router
 
 # Import new WebSocket service routers
 from api.ws_unified_router import router as ws_unified_router, start_all_websocket_streams
@@ -168,6 +170,15 @@ async def lifespan(app: FastAPI):
         task_scheduler.start()
         logger.info("Task scheduler started successfully")
 
+        # 7. Start WebSocket data broadcaster
+        logger.info("Starting WebSocket data broadcaster...")
+        try:
+            from api.ws_data_broadcaster import broadcaster
+            asyncio.create_task(broadcaster.start_broadcasting())
+            logger.info("WebSocket data broadcaster started")
+        except Exception as e:
+            logger.warning(f"Could not start WebSocket data broadcaster: {e}")
+
         # Log startup summary
         logger.info("=" * 80)
         logger.info("Crypto API Monitoring System started successfully")
@@ -185,17 +196,26 @@ async def lifespan(app: FastAPI):
         logger.info("Shutting down Crypto API Monitoring System...")
         logger.info("=" * 80)
 
-        # 1. Stop task scheduler
+        # 1. Stop WebSocket data broadcaster
+        logger.info("Stopping WebSocket data broadcaster...")
+        try:
+            from api.ws_data_broadcaster import broadcaster
+            await broadcaster.stop_broadcasting()
+            logger.info("WebSocket data broadcaster stopped")
+        except Exception as e:
+            logger.warning(f"Error stopping WebSocket data broadcaster: {e}")
+
+        # 2. Stop task scheduler
         logger.info("Stopping task scheduler...")
         task_scheduler.stop()
         logger.info("Task scheduler stopped")
 
-        # 2. Stop WebSocket background tasks
+        # 3. Stop WebSocket background tasks
         logger.info("Stopping WebSocket background tasks...")
         await ws_manager.stop_background_tasks()
         logger.info("WebSocket background tasks stopped")
 
-        # 3. Close all WebSocket connections
+        # 4. Close all WebSocket connections
         logger.info("Closing WebSocket connections...")
         await ws_manager.close_all_connections()
         logger.info("WebSocket connections closed")
@@ -309,6 +329,12 @@ app.include_router(
     tags=["Pool Management"]
 )
 
+# Include Data endpoints router (cryptocurrency data)
+app.include_router(
+    data_router,
+    tags=["Crypto Data"]
+)
+
 # Include HF router (if available)
 if HF_ROUTER_AVAILABLE:
     try:
@@ -348,10 +374,26 @@ logger.info("All WebSocket service routers included successfully")
 # Root Endpoints
 # ============================================================================
 
-@app.get("/", tags=["Root"])
+@app.get("/", response_class=HTMLResponse, tags=["Root"])
 async def root():
     """
-    Root endpoint with API information and available endpoints
+    Serve the Vidya HTML UI dashboard
+
+    Returns:
+        HTML dashboard interface
+    """
+    try:
+        with open("index.html", "r", encoding="utf-8") as f:
+            return HTMLResponse(content=f.read())
+    except Exception as e:
+        logger.error(f"Error serving index.html: {e}")
+        return HTMLResponse(content=f"<h1>Error loading dashboard</h1><p>{str(e)}</p>", status_code=500)
+
+
+@app.get("/api-info", tags=["Root"])
+async def api_info():
+    """
+    API information and available endpoints
 
     Returns:
         API information and endpoint listing

requirements.txt

@@ -16,10 +16,21 @@ fastapi==0.104.1
 uvicorn[standard]==0.24.0
 pydantic==2.5.0
 python-multipart==0.0.6
-websockets==11.0.3   # 
+websockets==12.0
 
 # Database
 SQLAlchemy==2.0.23
 
 # Configuration
 python-dotenv==1.0.0
+
+# HuggingFace Integration (required for HF Spaces deployment)
+transformers>=4.44.0
+datasets>=3.0.0
+huggingface_hub>=0.24.0
+torch>=2.0.0
+sentencepiece>=0.1.99
+protobuf>=3.20.0
+
+# RSS Feed Parsing
+feedparser==6.0.11