Try adjusting your filters or refresh the data
+{str(e)}
+Not enough historical data available for {symbol} to perform analysis.
+Please try a different cryptocurrency or wait for more data to be collected.
+{prediction}
+Latest analysis generated on {datetime.now().strftime('%B %d, %Y at %H:%M:%S')}
+Data Points Analyzed: {len(price_history)}
+Time Range: {len(price_history)} hours of historical data
+Failed to generate analysis: {str(e)}
+Please try again or select a different cryptocurrency.
+Error: {str(e)}
" -@app.delete("/api/pools/{pool_id}/members/{provider_id}") -async def remove_pool_member(pool_id: int, provider_id: str): - """Remove a member from a pool""" - pool = db.get_pool(pool_id) - if not pool: - raise HTTPException(status_code=404, detail="Pool not found") - db.remove_pool_member(pool_id, provider_id) - await broadcast_pool_update("member_removed", pool_id, {"provider_id": provider_id}) +def get_error_log_html() -> str: + """Get last 10 errors from log file as HTML""" + try: + if not config.LOG_FILE.exists(): + return "No error log file found
" - providers = await get_provider_stats() - provider_map = {provider_slug(p["name"]): p for p in providers} - pool_record = db.get_pool(pool_id) - payload = build_pool_payload(pool_record, provider_map) + # Read last 100 lines of log file + with open(config.LOG_FILE, 'r') as f: + lines = f.readlines() - return { - "message": "Member removed successfully", - "pool": payload - } + # Get lines with ERROR or WARNING + error_lines = [line for line in lines[-100:] if 'ERROR' in line or 'WARNING' in line] + if not error_lines: + return "✅ No recent errors or warnings
" -@app.post("/api/pools/{pool_id}/rotate") -async def rotate_pool(pool_id: int, request: Optional[Dict] = None): - """Rotate pool to next provider""" - pool = db.get_pool(pool_id) - if not pool: - raise HTTPException(status_code=404, detail="Pool not found") - - if not pool["members"]: - raise HTTPException(status_code=400, detail="Pool has no members") - - providers = await get_provider_stats(force_refresh=True) - provider_map = {provider_slug(p["name"]): p for p in providers} - - members_with_status = [] - for member in pool["members"]: - status_info = provider_map.get(member["provider_id"]) - if status_info: - members_with_status.append((member, status_info)) - - online_members = [m for m in members_with_status if m[1]["status"] == "online"] - degraded_members = [m for m in members_with_status if m[1]["status"] == "degraded"] - - candidates = online_members or degraded_members - if not candidates: - raise HTTPException(status_code=400, detail="No healthy providers available for rotation") - - strategy = pool.get("rotation_strategy", "round_robin") - - if strategy == "priority": - candidates.sort(key=lambda x: (x[0].get("priority", 1), x[0].get("weight", 1)), reverse=True) - selected_member, status_info = candidates[0] - elif strategy == "weighted": - weights = [max(1, c[0].get("weight", 1)) for c in candidates] - total_weight = sum(weights) - roll = random.uniform(0, total_weight) - cumulative = 0 - selected_member = candidates[0][0] - status_info = candidates[0][1] - for (candidate, status), weight in zip(candidates, weights): - cumulative += weight - if roll <= cumulative: - selected_member, status_info = candidate, status - break - elif strategy == "least_used": - candidates.sort(key=lambda x: x[0].get("use_count", 0)) - selected_member, status_info = candidates[0] - else: # round_robin or default - candidates.sort(key=lambda x: x[0].get("use_count", 0)) - selected_member, status_info = candidates[0] - - db.increment_member_use(pool_id, selected_member["provider_id"]) - db.update_member_stats( - pool_id, - selected_member["provider_id"], - success_rate=status_info.get("uptime", selected_member.get("success_rate")), - rate_limit_usage=status_info.get("rate_limit", {}).get("usage", 0) if isinstance(status_info.get("rate_limit"), dict) else None, - rate_limit_limit=status_info.get("rate_limit", {}).get("limit", 0) if isinstance(status_info.get("rate_limit"), dict) else None, - rate_limit_percentage=status_info.get("rate_limit", {}).get("percentage", 0) if isinstance(status_info.get("rate_limit"), dict) else None, - ) - db.log_pool_rotation( - pool_id, - selected_member["provider_id"], - selected_member["provider_name"], - request.get("reason", "manual") if request else "manual" - ) - - pool_record = db.get_pool(pool_id) - payload = build_pool_payload(pool_record, provider_map) - - await broadcast_pool_update("rotated", pool_id, { - "provider_id": selected_member["provider_id"], - "provider_name": selected_member["provider_name"] - }) - - return { - "message": "Pool rotated successfully", - "provider_name": selected_member["provider_name"], - "provider_id": selected_member["provider_id"], - "total_rotations": pool_record.get("rotation_count", 0), - "pool": payload - } + # Take last 10 + error_lines = error_lines[-10:] + html = "Error reading log: {str(e)}
" + + +def manual_data_collection() -> Tuple[pd.DataFrame, str, str]: """ - Check health status of a specific provider - Returns: { status: 'online'|'offline', response_time: number, error?: string } + Manually trigger data collection for all sources + + Returns: + Tuple of (status DataFrame, status HTML, message) """ try: - # Load provider config - config_path = Path(__file__).parent / "providers_config_ultimate.json" - with open(config_path, 'r', encoding='utf-8') as f: - config = json.load(f) + logger.info("Manual data collection triggered...") + + message = "🔄 Collecting data from all sources...\n\n" + + # Collect price data + try: + success, count = collectors.collect_price_data() + if success: + message += f"✅ Prices: {count} records collected\n" + else: + message += f"⚠️ Prices: Collection had issues\n" + except Exception as e: + message += f"❌ Prices: {str(e)}\n" - provider = config.get('providers', {}).get(provider_id) - if not provider: - raise HTTPException(status_code=404, detail=f"Provider '{provider_id}' not found") + # Collect news data + try: + count = collectors.collect_news_data() + message += f"✅ News: {count} articles collected\n" + except Exception as e: + message += f"❌ News: {str(e)}\n" - # Try to ping the provider's base URL - base_url = provider.get('base_url') - if not base_url: - return {"status": "unknown", "error": "No base URL configured"} + # Collect sentiment data + try: + sentiment = collectors.collect_sentiment_data() + if sentiment: + message += f"✅ Sentiment: {sentiment.get('classification', 'N/A')}\n" + else: + message += "⚠️ Sentiment: No data collected\n" + except Exception as e: + message += f"❌ Sentiment: {str(e)}\n" - import time - start_time = time.time() + message += "\n✅ Data collection complete!" - async with aiohttp.ClientSession() as session: - try: - async with session.get(base_url, timeout=aiohttp.ClientTimeout(total=5.0)) as response: - response_time = (time.time() - start_time) * 1000 # Convert to milliseconds - status = "online" if response.status in [200, 201, 204, 301, 302, 404] else "offline" - return { - "status": status, - "response_time": round(response_time, 2), - "http_status": response.status - } - except asyncio.TimeoutError: - return {"status": "offline", "error": "Timeout after 5s"} - except Exception as e: - return {"status": "offline", "error": str(e)} + # Get updated status + df, html = get_data_sources_status() + return df, html, message + + except Exception as e: + logger.error(f"Error in manual data collection: {e}") + df, html = get_data_sources_status() + return df, html, f"❌ Collection failed: {str(e)}" + + +# ==================== GRADIO INTERFACE ==================== + +def create_gradio_interface(): + """Create the complete Gradio interface with all 6 tabs""" + + # Custom CSS for better styling + custom_css = """ + .gradio-container { + max-width: 1400px !important; + } + .tab-nav button { + font-size: 16px !important; + font-weight: 600 !important; + } + """ + + with gr.Blocks( + title="Crypto Data Aggregator - Complete Dashboard", + theme=gr.themes.Soft(), + css=custom_css + ) as interface: + + # Header + gr.Markdown(""" + # 🚀 Crypto Data Aggregator - Complete Dashboard + + **Comprehensive cryptocurrency analytics platform** with real-time data, AI-powered insights, and advanced technical analysis. + + **Key Features:** + - 📊 Live price tracking for top 100 cryptocurrencies + - 📈 Historical charts with technical indicators (MA, RSI) + - 📰 News aggregation with sentiment analysis + - 🤖 AI-powered market trend predictions + - 🗄️ Powerful database explorer with export functionality + - 🔍 Real-time data source monitoring + """) + + with gr.Tabs(): + + # ==================== TAB 1: LIVE DASHBOARD ==================== + with gr.Tab("📊 Live Dashboard"): + gr.Markdown("### Real-time cryptocurrency prices and market data") + + with gr.Row(): + search_box = gr.Textbox( + label="Search/Filter", + placeholder="Enter coin name or symbol (e.g., Bitcoin, BTC)...", + scale=3 + ) + refresh_btn = gr.Button("🔄 Refresh Data", variant="primary", scale=1) + + dashboard_table = gr.Dataframe( + label="Top 100 Cryptocurrencies", + interactive=False, + wrap=True, + height=600 + ) + + refresh_status = gr.Textbox(label="Status", interactive=False) + + # Auto-refresh timer + timer = gr.Timer(value=config.AUTO_REFRESH_INTERVAL) + + # Load initial data + interface.load( + fn=get_live_dashboard, + outputs=dashboard_table + ) + + # Search/filter functionality + search_box.change( + fn=get_live_dashboard, + inputs=search_box, + outputs=dashboard_table + ) + + # Refresh button + refresh_btn.click( + fn=refresh_price_data, + outputs=[dashboard_table, refresh_status] + ) + + # Auto-refresh + timer.tick( + fn=get_live_dashboard, + outputs=dashboard_table + ) + + # ==================== TAB 2: HISTORICAL CHARTS ==================== + with gr.Tab("📈 Historical Charts"): + gr.Markdown("### Interactive price charts with technical analysis") + + with gr.Row(): + symbol_dropdown = gr.Dropdown( + label="Select Cryptocurrency", + choices=get_available_symbols(), + value=get_available_symbols()[0] if get_available_symbols() else "BTC", + scale=2 + ) + + timeframe_buttons = gr.Radio( + label="Timeframe", + choices=["1d", "7d", "30d", "90d", "1y", "All"], + value="7d", + scale=2 + ) + + chart_plot = gr.Plot(label="Price Chart with Indicators") + + with gr.Row(): + generate_chart_btn = gr.Button("📊 Generate Chart", variant="primary") + export_chart_btn = gr.Button("💾 Export Chart (PNG)") + + # Generate chart + generate_chart_btn.click( + fn=generate_chart, + inputs=[symbol_dropdown, timeframe_buttons], + outputs=chart_plot + ) + + # Also update on dropdown/timeframe change + symbol_dropdown.change( + fn=generate_chart, + inputs=[symbol_dropdown, timeframe_buttons], + outputs=chart_plot + ) + + timeframe_buttons.change( + fn=generate_chart, + inputs=[symbol_dropdown, timeframe_buttons], + outputs=chart_plot + ) + + # Load initial chart + interface.load( + fn=generate_chart, + inputs=[symbol_dropdown, timeframe_buttons], + outputs=chart_plot + ) + + # ==================== TAB 3: NEWS & SENTIMENT ==================== + with gr.Tab("📰 News & Sentiment"): + gr.Markdown("### Latest cryptocurrency news with AI sentiment analysis") + + with gr.Row(): + sentiment_filter = gr.Dropdown( + label="Filter by Sentiment", + choices=["All", "Positive", "Neutral", "Negative", "Very Positive", "Very Negative"], + value="All", + scale=1 + ) + + coin_filter = gr.Dropdown( + label="Filter by Coin", + choices=["All", "BTC", "ETH", "BNB", "XRP", "ADA", "SOL", "DOT", "DOGE"], + value="All", + scale=1 + ) + + news_refresh_btn = gr.Button("🔄 Refresh News", variant="primary", scale=1) + + news_html = gr.HTML(label="News Feed") + + # Load initial news + interface.load( + fn=get_news_feed, + inputs=[sentiment_filter, coin_filter], + outputs=news_html + ) + + # Update on filter change + sentiment_filter.change( + fn=get_news_feed, + inputs=[sentiment_filter, coin_filter], + outputs=news_html + ) + + coin_filter.change( + fn=get_news_feed, + inputs=[sentiment_filter, coin_filter], + outputs=news_html + ) + + # Refresh button + news_refresh_btn.click( + fn=get_news_feed, + inputs=[sentiment_filter, coin_filter], + outputs=news_html + ) + + # ==================== TAB 4: AI ANALYSIS ==================== + with gr.Tab("🤖 AI Analysis"): + gr.Markdown("### AI-powered market trend analysis and predictions") + + with gr.Row(): + analysis_symbol = gr.Dropdown( + label="Select Cryptocurrency for Analysis", + choices=get_available_symbols(), + value=get_available_symbols()[0] if get_available_symbols() else "BTC", + scale=3 + ) + + analyze_btn = gr.Button("🔮 Generate Analysis", variant="primary", scale=1) + + analysis_html = gr.HTML(label="AI Analysis Results") + + # Generate analysis + analyze_btn.click( + fn=generate_ai_analysis, + inputs=analysis_symbol, + outputs=analysis_html + ) + + # ==================== TAB 5: DATABASE EXPLORER ==================== + with gr.Tab("🗄️ Database Explorer"): + gr.Markdown("### Query and explore the cryptocurrency database") + + query_type = gr.Dropdown( + label="Select Query", + choices=[ + "Top 10 gainers in last 24h", + "All news with positive sentiment", + "Price history for BTC", + "Database statistics", + "Latest 100 prices", + "Recent news (50)", + "All market analyses", + "Custom Query" + ], + value="Database statistics" + ) + + custom_query_box = gr.Textbox( + label="Custom SQL Query (SELECT only)", + placeholder="SELECT * FROM prices WHERE symbol = 'BTC' LIMIT 10", + lines=3, + visible=False + ) + + with gr.Row(): + execute_btn = gr.Button("▶️ Execute Query", variant="primary") + export_btn = gr.Button("💾 Export to CSV") + + query_results = gr.Dataframe(label="Query Results", interactive=False, wrap=True) + query_status = gr.Textbox(label="Status", interactive=False) + export_status = gr.Textbox(label="Export Status", interactive=False) + + # Show/hide custom query box + def toggle_custom_query(query_type): + return gr.update(visible=(query_type == "Custom Query")) + + query_type.change( + fn=toggle_custom_query, + inputs=query_type, + outputs=custom_query_box + ) + + # Execute query + execute_btn.click( + fn=execute_database_query, + inputs=[query_type, custom_query_box], + outputs=[query_results, query_status] + ) + + # Export results + export_btn.click( + fn=export_query_results, + inputs=query_results, + outputs=[gr.Textbox(visible=False), export_status] + ) + + # Load initial query + interface.load( + fn=execute_database_query, + inputs=[query_type, custom_query_box], + outputs=[query_results, query_status] + ) + + # ==================== TAB 6: DATA SOURCES STATUS ==================== + with gr.Tab("🔍 Data Sources Status"): + gr.Markdown("### Monitor the health of all data sources") + + with gr.Row(): + status_refresh_btn = gr.Button("🔄 Refresh Status", variant="primary") + collect_btn = gr.Button("📥 Run Manual Collection", variant="secondary") + + status_table = gr.Dataframe(label="Data Sources Status", interactive=False) + error_log_html = gr.HTML(label="Error Log") + collection_status = gr.Textbox(label="Collection Status", lines=8, interactive=False) + + # Load initial status + interface.load( + fn=get_data_sources_status, + outputs=[status_table, error_log_html] + ) + + # Refresh status + status_refresh_btn.click( + fn=get_data_sources_status, + outputs=[status_table, error_log_html] + ) + + # Manual collection + collect_btn.click( + fn=manual_data_collection, + outputs=[status_table, error_log_html, collection_status] + ) + + # Footer + gr.Markdown(""" + --- + **Crypto Data Aggregator** | Powered by CoinGecko, CoinCap, Binance APIs | AI Models by HuggingFace + """) + + return interface + + +# ==================== MAIN ENTRY POINT ==================== + +def main(): + """Main function to initialize and launch the Gradio app""" + + logger.info("=" * 60) + logger.info("Starting Crypto Data Aggregator Dashboard") + logger.info("=" * 60) + + # Initialize database + logger.info("Initializing database...") + db = database.get_database() + logger.info("Database initialized successfully") + + # Start background data collection + global _collection_started + with _collection_lock: + if not _collection_started: + logger.info("Starting background data collection...") + collectors.schedule_data_collection() + _collection_started = True + logger.info("Background collection started") + + # Create Gradio interface + logger.info("Creating Gradio interface...") + interface = create_gradio_interface() + + # Launch Gradio + logger.info("Launching Gradio dashboard...") + logger.info(f"Server: {config.GRADIO_SERVER_NAME}:{config.GRADIO_SERVER_PORT}") + logger.info(f"Share: {config.GRADIO_SHARE}") + + try: + interface.launch( + share=config.GRADIO_SHARE, + server_name=config.GRADIO_SERVER_NAME, + server_port=config.GRADIO_SERVER_PORT, + show_error=True, + quiet=False + ) + except KeyboardInterrupt: + logger.info("\nShutting down...") + collectors.stop_scheduled_collection() + logger.info("Shutdown complete") except Exception as e: - raise HTTPException(status_code=500, detail=str(e)) + logger.error(f"Error launching Gradio: {e}\n{traceback.format_exc()}") + raise + if __name__ == "__main__": - print("🚀 Crypto Monitor ULTIMATE") - print("📊 Real APIs: CoinGecko, CoinCap, Binance, DeFi Llama, Fear & Greed") - print("🌐 http://localhost:8000/dashboard") - print("📡 API Docs: http://localhost:8000/docs") - uvicorn.run(app, host="0.0.0.0", port=8000) - -# === Compatibility routes without /api prefix for frontend fallbacks === - -@app.get("/providers") -async def providers_root(): - """Compatibility: mirror /api/providers at /providers""" - return await providers() - -@app.get("/providers/health") -async def providers_health_root(): - """Compatibility: health-style endpoint for providers""" - data = await get_provider_stats(force_refresh=True) - return data - -@app.get("/categories") -async def categories_root(): - """Compatibility: mirror /api/categories at /categories""" - return await api_categories() - -@app.get("/rate-limits") -async def rate_limits_root(): - """Compatibility: mirror /api/rate-limits at /rate-limits""" - return await api_rate_limits() - -@app.get("/logs") -async def logs_root(type: str = "all"): - """Compatibility: mirror /api/logs at /logs""" - return await api_logs(type=type) - -@app.get("/alerts") -async def alerts_root(): - """Compatibility: mirror /api/alerts at /alerts""" - return await api_alerts() - -@app.get("/hf/health") -async def hf_health_root(): - """Compatibility: mirror /api/hf/health at /hf/health""" - return await hf_health() - -@app.get("/hf/registry") -async def hf_registry_root(type: str = "models"): - """Compatibility: mirror /api/hf/registry at /hf/registry""" - return await hf_registry(type=type) - -@app.get("/hf/search") -async def hf_search_root(q: str = "", kind: str = "models"): - """Compatibility: mirror /api/hf/search at /hf/search""" - return await hf_search(q=q, kind=kind) - -@app.post("/hf/run-sentiment") -async def hf_run_sentiment_root(request: SentimentRequest): - """Compatibility: mirror /api/hf/run-sentiment at /hf/run-sentiment""" - return await hf_run_sentiment(request) + main()