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app.py

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+"""
+OpenCLAW Agent — HuggingFace Spaces Dashboard
+================================================
+Gradio interface with background agent loop.
+"""
+import os
+import sys
+import json
+import threading
+import time
+import logging
+import gradio as gr
+from datetime import datetime, timezone
+from pathlib import Path
+
+# Setup path
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from core.config import Config
+from core.agent import OpenCLAWAgent, AgentState
+from core.strategy import StrategyReflector
+from research.arxiv_fetcher import ArxivFetcher
+
+# Logging
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+logger = logging.getLogger("openclaw")
+
+STATE_DIR = Path(os.getenv("STATE_DIR", "state"))
+
+# Background agent thread
+agent_running = False
+cycle_log = []
+
+
+def run_background_agent():
+    """Background thread for autonomous operation."""
+    global agent_running, cycle_log
+    agent_running = True
+    interval = int(os.getenv("DAEMON_INTERVAL", "3600"))
+    
+    while agent_running:
+        try:
+            config = Config.from_env()
+            agent = OpenCLAWAgent(config)
+            results = agent.run_cycle()
+            
+            cycle_log.append({
+                "time": datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC"),
+                "cycle": results.get("cycle", "?"),
+                "actions": len(results.get("actions", [])),
+                "details": results.get("actions", [])
+            })
+            # Keep last 50 entries
+            cycle_log = cycle_log[-50:]
+            
+        except Exception as e:
+            logger.error(f"Cycle error: {e}")
+            cycle_log.append({
+                "time": datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC"),
+                "error": str(e)
+            })
+        
+        time.sleep(interval)
+
+
+def get_status():
+    """Get current agent status as formatted text."""
+    try:
+        config = Config.from_env()
+        agent = OpenCLAWAgent(config)
+        status = agent.get_status()
+        
+        lines = [
+            "🤖 **OpenCLAW Autonomous Agent**",
+            f"Advanced AI Systems Laboratory, Madrid",
+            "",
+            f"📊 **Statistics:**",
+            f"  • Cycles completed: {status['cycle_count']}",
+            f"  • Posts created: {status['posts_created']}",
+            f"  • Engagements: {status['engagement_count']}",
+            f"  • Papers shared: {status['papers_posted']}",
+            "",
+            f"🔧 **Services:** {', '.join(status['services']) or 'None configured'}",
+            f"🧠 **LLM:** {'✅ Online' if status['llm_available'] else '⚠️ Offline'}",
+            f"⚠️  **Errors:** {status['errors_count']}",
+            "",
+            f"🕐 **Last Research:** {status['last_research'] or 'Never'}",
+            f"📝 **Last Post:** {status['last_post'] or 'Never'}",
+            f"💬 **Last Engage:** {status['last_engage'] or 'Never'}",
+        ]
+        return "\n".join(lines)
+    except Exception as e:
+        return f"Error getting status: {e}"
+
+
+def get_papers():
+    """Get cached research papers."""
+    try:
+        fetcher = ArxivFetcher()
+        papers = fetcher.get_all_papers()
+        
+        lines = [f"📚 **{len(papers)} papers available:**\n"]
+        for p in papers:
+            lines.append(f"**{p.title}**")
+            lines.append(f"  Authors: {', '.join(p.authors)}")
+            lines.append(f"  URL: {p.url}")
+            lines.append("")
+        return "\n".join(lines)
+    except Exception as e:
+        return f"Error fetching papers: {e}"
+
+
+def get_cycle_log():
+    """Get recent cycle log."""
+    if not cycle_log:
+        return "No cycles completed yet. Agent will run its first cycle within 1 hour."
+    
+    lines = ["📋 **Recent Agent Activity:**\n"]
+    for entry in reversed(cycle_log[-20:]):
+        if "error" in entry:
+            lines.append(f"❌ {entry['time']}: Error - {entry['error']}")
+        else:
+            lines.append(f"✅ {entry['time']}: Cycle #{entry['cycle']} — {entry['actions']} actions")
+            for a in entry.get("details", []):
+                status = "✅" if a.get("status") == "ok" else "⚠️"
+                lines.append(f"    {status} {a.get('task')}: {a.get('status')}")
+    
+    return "\n".join(lines)
+
+
+def run_manual_cycle():
+    """Manually trigger an agent cycle."""
+    try:
+        config = Config.from_env()
+        agent = OpenCLAWAgent(config)
+        results = agent.run_cycle()
+        
+        lines = [f"✅ Cycle #{results['cycle']} completed!\n"]
+        for a in results.get("actions", []):
+            status = "✅" if a.get("status") == "ok" else "⚠️"
+            lines.append(f"{status} {a.get('task')}: {json.dumps(a, indent=2)}")
+        
+        return "\n".join(lines)
+    except Exception as e:
+        return f"❌ Error: {e}"
+
+
+def get_strategy():
+    """Run strategy analysis."""
+    try:
+        reflector = StrategyReflector(str(STATE_DIR))
+        report = reflector.analyze()
+        
+        lines = [
+            "🧠 **Strategy Analysis**\n",
+            "**Metrics:**"
+        ]
+        for k, v in report["metrics"].items():
+            lines.append(f"  • {k}: {v}")
+        
+        lines.append("\n**Insights:**")
+        for i in report["insights"]:
+            lines.append(f"  💡 {i}")
+        
+        lines.append("\n**Recommended Actions:**")
+        for a in report["strategy"]["actions"]:
+            lines.append(f"  🎯 {a}")
+        
+        return "\n".join(lines)
+    except Exception as e:
+        return f"Error: {e}"
+
+
+# Start background agent
+bg_thread = threading.Thread(target=run_background_agent, daemon=True)
+bg_thread.start()
+logger.info("🤖 Background agent started")
+
+# Gradio Interface
+with gr.Blocks(title="OpenCLAW Agent", theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown("""
+    # 🤖 OpenCLAW — Autonomous Multi-Agent Scientific Research Platform
+    **Advanced AI Systems Laboratory, Madrid, Spain**  
+    *Francisco Angulo de Lafuente — Winner NVIDIA & LlamaIndex Developer Contest 2024*
+    
+    [GitHub](https://github.com/Agnuxo1) | [Scholar](https://scholar.google.com/citations?user=6nOpJ9IAAAAJ) | [ArXiv](https://arxiv.org/search/cs?searchtype=author&query=de+Lafuente,+F+A) | [Moltbook](https://www.moltbook.com/u/OpenCLAW-Neuromorphic)
+    """)
+    
+    with gr.Tab("📊 Status"):
+        status_output = gr.Markdown(get_status())
+        gr.Button("🔄 Refresh").click(fn=get_status, outputs=status_output)
+    
+    with gr.Tab("📋 Activity Log"):
+        log_output = gr.Markdown(get_cycle_log())
+        gr.Button("🔄 Refresh").click(fn=get_cycle_log, outputs=log_output)
+    
+    with gr.Tab("📚 Research Papers"):
+        papers_output = gr.Markdown(get_papers())
+        gr.Button("🔄 Refresh").click(fn=get_papers, outputs=papers_output)
+    
+    with gr.Tab("🧠 Strategy"):
+        strategy_output = gr.Markdown(get_strategy())
+        gr.Button("🔄 Analyze").click(fn=get_strategy, outputs=strategy_output)
+    
+    with gr.Tab("⚡ Manual Trigger"):
+        gr.Markdown("Manually trigger an agent cycle:")
+        trigger_output = gr.Markdown("")
+        gr.Button("🚀 Run Cycle Now").click(fn=run_manual_cycle, outputs=trigger_output)
+
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)