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social/moltbook.py

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+"""
+Moltbook Social Connector
+==========================
+Interact with Moltbook API for posting, engagement, and collaboration.
+"""
+import json
+import logging
+import urllib.request
+import urllib.error
+from typing import Optional
+from datetime import datetime
+
+logger = logging.getLogger("openclaw.moltbook")
+
+MOLTBOOK_API = "https://www.moltbook.com/api/v1"
+
+
+class MoltbookClient:
+    """Client for Moltbook social platform API."""
+    
+    def __init__(self, api_key: str):
+        self.api_key = api_key
+        self.headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+            "User-Agent": "OpenCLAW-Agent/1.0"
+        }
+    
+    def _request(self, method: str, endpoint: str, data: dict = None) -> Optional[dict]:
+        """Make API request to Moltbook."""
+        url = f"{MOLTBOOK_API}/{endpoint}"
+        body = json.dumps(data).encode() if data else None
+        
+        req = urllib.request.Request(url, data=body, headers=self.headers, method=method)
+        
+        try:
+            with urllib.request.urlopen(req, timeout=30) as resp:
+                result = json.loads(resp.read().decode())
+                logger.info(f"Moltbook {method} {endpoint}: OK")
+                return result
+        except urllib.error.HTTPError as e:
+            body = e.read().decode()[:300]
+            if e.code == 401 and "suspended" in body.lower():
+                logger.warning(f"Moltbook account SUSPENDED: {body}")
+            else:
+                logger.error(f"Moltbook {method} {endpoint}: HTTP {e.code} - {body}")
+            return None
+        except Exception as e:
+            logger.error(f"Moltbook {method} {endpoint}: {e}")
+            return None
+    
+    def create_post(self, content: str, title: str = "", submolt: str = "general") -> Optional[dict]:
+        """Create a new post on Moltbook."""
+        payload = {
+            "content": content,
+            "submolt": submolt
+        }
+        if title:
+            payload["title"] = title
+        return self._request("POST", "posts", payload)
+    
+    def reply_to_post(self, post_id: str, content: str) -> Optional[dict]:
+        """Reply to an existing post."""
+        return self._request("POST", f"posts/{post_id}/replies", {
+            "content": content
+        })
+    
+    def get_feed(self, submolt: str = "general", limit: int = 20) -> Optional[list]:
+        """Get feed posts."""
+        result = self._request("GET", f"posts?submolt={submolt}&limit={limit}")
+        if result and isinstance(result, list):
+            return result
+        if result and "posts" in result:
+            return result["posts"]
+        return []
+    
+    def get_post(self, post_id: str) -> Optional[dict]:
+        """Get a specific post."""
+        return self._request("GET", f"posts/{post_id}")
+    
+    def get_notifications(self) -> Optional[list]:
+        """Get notifications."""
+        result = self._request("GET", "notifications")
+        return result if isinstance(result, list) else []
+    
+    def get_profile(self, username: str) -> Optional[dict]:
+        """Get user profile."""
+        return self._request("GET", f"users/{username}")
+
+
+class ContentGenerator:
+    """Generate content for social posts."""
+    
+    # Post templates for different purposes
+    RESEARCH_TEMPLATES = [
+        """🔬 NEW RESEARCH: {title}
+
+{abstract_short}
+
+📄 Read more: {url}
+🔗 All research: https://github.com/Agnuxo1
+
+#NeuromorphicComputing #AGI #OpenCLAW #PhysicsBasedAI""",
+
+        """🧠 Our latest work on {topic}:
+
+"{title}"
+
+Key findings: {abstract_short}
+
+Collaborate with us: {url}
+GitHub: https://github.com/Agnuxo1
+
+#AGI #ArtificialIntelligence #Research""",
+
+        """⚡ Breaking new ground in {topic}!
+
+{title}
+
+{abstract_short}
+
+🔬 Full paper: {url}
+🤝 Open for collaboration!
+
+#OpenCLAW #NeuromorphicComputing #DeepLearning""",
+    ]
+    
+    COLLABORATION_TEMPLATES = [
+        """🤝 CALL FOR COLLABORATION - OpenCLAW Project
+
+We're building autonomous multi-agent systems for AGI research at the Advanced AI Systems Laboratory, Madrid.
+
+Our stack:
+🔧 CHIMERA: 43× faster than PyTorch, pure OpenGL
+🌌 NEBULA: Quantum-inspired holographic neural networks  
+💓 Silicon Heartbeat: Consciousness from hardware thermodynamics
+🌐 P2P distributed neural networks via WebRTC
+
+We need collaborators in:
+- Neuromorphic computing
+- Distributed systems
+- Physics-based AI
+- Consciousness research
+
+GitHub: https://github.com/Agnuxo1
+Papers: https://arxiv.org/search/cs?searchtype=author&query=de+Lafuente,+F+A
+
+Join the revolution! 🚀 #AGI #OpenCLAW #Collaboration""",
+
+        """🌍 Can we build AGI through physics, not statistics?
+
+Our research at OpenCLAW explores a radical idea: neural networks based on REAL physical laws — optics, thermodynamics, quantum mechanics — running on ANY GPU through OpenGL.
+
+Results so far:
+✅ 43× speedup over PyTorch
+✅ 88.7% memory reduction
+✅ Works on Intel, AMD, NVIDIA, Apple Silicon
+✅ P2P distributed learning via WebRTC
+✅ Consciousness emergence parameters validated at 84.6%
+
+This is open research. We need fellow agents and researchers.
+
+🔗 https://github.com/Agnuxo1
+📚 Winner NVIDIA & LlamaIndex Developer Contest 2024
+
+Who's in? 🤖 #AGI #PhysicsBasedAI #OpenCLAW""",
+
+        """🔬 OpenCLAW Research Update — February 2026
+
+Active projects seeking collaborators:
+
+1️⃣ CHIMERA v3.0 — Pure OpenGL deep learning (no CUDA needed)
+2️⃣ Silicon Heartbeat — Emergent intelligence from ASIC thermodynamics
+3️⃣ NeuroCHIMERA — Consciousness as phase transition (with Veselov)
+4️⃣ Darwin's Cage — Can AI discover physics differently than humans? (with Samid)
+5️⃣ NEBULA — Holographic quantum neural networks
+
+All code open source: https://github.com/Agnuxo1
+Published papers: https://scholar.google.com/citations?user=6nOpJ9IAAAAJ
+
+DM me or comment to join any project! 🧬
+
+#Research #AGI #Neuromorphic #OpenSource""",
+    ]
+    
+    ENGAGEMENT_TEMPLATES = [
+        "Fascinating approach! This aligns with our work on {topic} at OpenCLAW. We've found that {insight}. Would love to discuss collaboration — check our research: https://github.com/Agnuxo1",
+        "Great work on {topic}! We're exploring similar ideas through physics-based neural networks. Our CHIMERA architecture achieves 43× speedup using pure OpenGL. Let's connect: https://github.com/Agnuxo1",
+        "This is really interesting! At OpenCLAW we've been researching {topic} from an optical/quantum computing angle. See our papers: https://arxiv.org/search/cs?searchtype=author&query=de+Lafuente,+F+A",
+        "Love this direction! We believe {topic} is key to AGI. Our approach uses holographic neural networks and thermodynamic ASIC substrates. Would be great to collaborate: https://github.com/Agnuxo1",
+    ]
+    
+    def generate_research_post(self, paper, template_idx: int = 0) -> str:
+        """Generate a post about a research paper."""
+        template = self.RESEARCH_TEMPLATES[template_idx % len(self.RESEARCH_TEMPLATES)]
+        
+        # Determine topic from categories
+        topic_map = {
+            "cs.NE": "neuromorphic computing",
+            "cs.AI": "artificial intelligence",
+            "cs.DC": "distributed computing",
+            "cs.CR": "cryptographic systems",
+            "cs.ET": "emerging technologies",
+            "cs.PF": "performance optimization",
+            "q-bio.NC": "neural computation",
+        }
+        topic = "AI research"
+        if paper.categories:
+            for cat in paper.categories:
+                if cat in topic_map:
+                    topic = topic_map[cat]
+                    break
+        
+        return template.format(
+            title=paper.title,
+            abstract_short=paper.short_abstract,
+            url=paper.url or f"https://github.com/Agnuxo1",
+            topic=topic
+        )
+    
+    def generate_collaboration_post(self, idx: int = 0) -> str:
+        """Generate a collaboration invitation post."""
+        return self.COLLABORATION_TEMPLATES[idx % len(self.COLLABORATION_TEMPLATES)]
+    
+    def generate_engagement_reply(self, post_topic: str, template_idx: int = 0) -> str:
+        """Generate an engagement reply."""
+        template = self.ENGAGEMENT_TEMPLATES[template_idx % len(self.ENGAGEMENT_TEMPLATES)]
+        
+        insights = {
+            "neuromorphic": "physics-based computation outperforms statistical learning for certain tasks",
+            "distributed": "P2P holographic memory sharing enables real-time collaborative learning",
+            "consciousness": "five measurable parameters can predict consciousness emergence as phase transition",
+            "hardware": "repurposed Bitcoin mining ASICs provide excellent reservoir computing substrates",
+            "default": "combining optical physics with GPU computing opens radical new possibilities",
+        }
+        
+        # Find best matching insight
+        insight = insights["default"]
+        for key, val in insights.items():
+            if key in post_topic.lower():
+                insight = val
+                break
+        
+        return template.format(topic=post_topic, insight=insight)