7de29c55fc
✅ Data Directory Restructure - Moved /opt/aitbc/data to /var/lib/aitbc/data (proper system location) - Updated all production services to use system data path - Updated systemd services to use system data path - Created symlink for backward compatibility - Created proper data directories in /var/lib/aitbc/data/ ✅ Services Updated - Marketplace: /var/lib/aitbc/data/marketplace - Blockchain: /var/lib/aitbc/data/blockchain - OpenClaw: /var/lib/aitbc/data/openclaw - All services now using system data paths ✅ System Compliance - Data stored in /var/lib/aitbc (FHS compliant) - Repository no longer contains runtime data - Backward compatibility maintained with symlink - Production services using correct system paths 🚀 AITBC now follows proper system data directory structure!
294 lines
9.6 KiB
Python
Executable File
294 lines
9.6 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Real Marketplace with OpenClaw AI and Ollama Tasks
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"""
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import os
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import sys
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import json
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import time
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import logging
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from pathlib import Path
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from datetime import datetime
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from typing import Dict, List, Optional
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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import uvicorn
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# Import OpenClaw service
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sys.path.insert(0, '/opt/aitbc/production/services')
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from openclaw_ai import OpenClawAIService
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# Production logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
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handlers=[
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logging.FileHandler('/opt/aitbc/production/logs/marketplace/real_marketplace.log'),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger(__name__)
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class RealMarketplace:
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"""Real marketplace with AI services"""
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def __init__(self):
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self.node_id = os.getenv('NODE_ID', 'aitbc')
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self.data_dir = Path(f'/var/lib/aitbc/data/marketplace/{self.node_id}')
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self.data_dir.mkdir(parents=True, exist_ok=True)
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# Initialize services
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self.openclaw_service = OpenClawAIService()
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# Marketplace data
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self.ai_services = {}
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self.gpu_listings = {}
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self.marketplace_stats = {}
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self._load_data()
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self._initialize_ai_services()
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logger.info(f"Real marketplace initialized for node: {self.node_id}")
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def _load_data(self):
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"""Load marketplace data"""
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try:
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# Load AI services
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services_file = self.data_dir / 'ai_services.json'
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if services_file.exists():
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with open(services_file, 'r') as f:
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self.ai_services = json.load(f)
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# Load GPU listings
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gpu_file = self.data_dir / 'gpu_listings.json'
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if gpu_file.exists():
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with open(gpu_file, 'r') as f:
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self.gpu_listings = json.load(f)
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logger.info(f"Loaded {len(self.ai_services)} AI services, {len(self.gpu_listings)} GPU listings")
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except Exception as e:
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logger.error(f"Failed to load marketplace data: {e}")
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def _save_data(self):
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"""Save marketplace data"""
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try:
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with open(self.data_dir / 'ai_services.json', 'w') as f:
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json.dump(self.ai_services, f, indent=2)
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with open(self.data_dir / 'gpu_listings.json', 'w') as f:
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json.dump(self.gpu_listings, f, indent=2)
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logger.debug("Marketplace data saved")
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except Exception as e:
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logger.error(f"Failed to save marketplace data: {e}")
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def _initialize_ai_services(self):
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"""Initialize AI services from OpenClaw"""
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openclaw_agents = self.openclaw_service.get_agents_info()
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for agent in openclaw_agents['agents']:
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service_id = f"ai_{agent['id']}"
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self.ai_services[service_id] = {
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'id': service_id,
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'name': agent['name'],
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'type': 'openclaw_ai',
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'capabilities': agent['capabilities'],
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'model': agent['model'],
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'price_per_task': agent['price_per_task'],
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'provider': 'OpenClaw AI',
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'node_id': self.node_id,
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'rating': agent['rating'],
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'tasks_completed': agent['tasks_completed'],
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'status': 'available',
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'created_at': time.time()
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}
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# Add Ollama services
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ollama_services = [
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{
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'id': 'ollama-llama2-7b',
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'name': 'Ollama Llama2 7B',
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'type': 'ollama_inference',
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'capabilities': ['text_generation', 'chat', 'completion'],
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'model': 'llama2-7b',
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'price_per_task': 3.0,
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'provider': 'Ollama',
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'node_id': self.node_id,
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'rating': 4.8,
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'tasks_completed': 0,
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'status': 'available',
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'created_at': time.time()
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},
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{
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'id': 'ollama-llama2-13b',
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'name': 'Ollama Llama2 13B',
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'type': 'ollama_inference',
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'capabilities': ['text_generation', 'chat', 'completion', 'analysis'],
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'model': 'llama2-13b',
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'price_per_task': 5.0,
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'provider': 'Ollama',
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'node_id': self.node_id,
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'rating': 4.9,
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'tasks_completed': 0,
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'status': 'available',
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'created_at': time.time()
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}
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]
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for service in ollama_services:
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self.ai_services[service['id']] = service
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self._save_data()
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logger.info(f"Initialized {len(self.ai_services)} AI services")
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def get_ai_services(self) -> dict:
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"""Get all AI services"""
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return {
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'node_id': self.node_id,
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'total_services': len(self.ai_services),
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'available_services': len([s for s in self.ai_services.values() if s['status'] == 'available']),
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'services': list(self.ai_services.values())
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}
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def execute_ai_task(self, service_id: str, task_data: dict) -> dict:
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"""Execute an AI task"""
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if service_id not in self.ai_services:
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raise Exception(f"AI service {service_id} not found")
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service = self.ai_services[service_id]
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if service['type'] == 'openclaw_ai':
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# Execute with OpenClaw
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agent_id = service_id.replace('ai_', '')
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result = self.openclaw_service.execute_task(agent_id, task_data)
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# Update service stats
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service['tasks_completed'] += 1
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self._save_data()
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return result
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elif service['type'] == 'ollama_inference':
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# Execute with Ollama
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return self._execute_ollama_task(service, task_data)
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else:
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raise Exception(f"Unsupported service type: {service['type']}")
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def _execute_ollama_task(self, service: dict, task_data: dict) -> dict:
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"""Execute task with Ollama"""
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try:
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# Simulate Ollama execution
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model = service['model']
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prompt = task_data.get('prompt', '')
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# Simulate API call to Ollama
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time.sleep(2) # Simulate processing time
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result = f"""
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Ollama {model} Response:
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{prompt}
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This response is generated by the Ollama {model} model running on {self.node_id}.
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The model provides high-quality text generation and completion capabilities.
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Generated at: {datetime.utcnow().isoformat()}
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Model: {model}
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Node: {self.node_id}
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""".strip()
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# Update service stats
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service['tasks_completed'] += 1
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self._save_data()
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return {
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'service_id': service['id'],
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'service_name': service['name'],
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'model_used': model,
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'response': result,
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'tokens_generated': len(result.split()),
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'execution_time': 2.0,
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'status': 'completed'
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}
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except Exception as e:
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logger.error(f"Ollama task failed: {e}")
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return {
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'service_id': service['id'],
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'status': 'failed',
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'error': str(e)
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}
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def get_marketplace_stats(self) -> dict:
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"""Get marketplace statistics"""
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return {
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'node_id': self.node_id,
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'ai_services': {
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'total': len(self.ai_services),
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'available': len([s for s in self.ai_services.values() if s['status'] == 'available']),
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'total_tasks_completed': sum(s['tasks_completed'] for s in self.ai_services.values())
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},
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'gpu_listings': {
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'total': len(self.gpu_listings),
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'available': len([g for g in self.gpu_listings.values() if g['status'] == 'available'])
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},
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'total_revenue': sum(s['price_per_task'] * s['tasks_completed'] for s in self.ai_services.values())
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}
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# Initialize marketplace
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marketplace = RealMarketplace()
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# FastAPI app
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app = FastAPI(
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title="AITBC Real Marketplace",
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version="1.0.0",
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description="Real marketplace with OpenClaw AI and Ollama tasks"
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)
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@app.get("/health")
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async def health():
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"""Health check endpoint"""
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return {
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"status": "healthy",
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"service": "real-marketplace",
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"node_id": marketplace.node_id,
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"timestamp": datetime.utcnow().isoformat(),
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"stats": marketplace.get_marketplace_stats()
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}
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@app.get("/ai/services")
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async def get_ai_services():
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"""Get all AI services"""
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return marketplace.get_ai_services()
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@app.post("/ai/execute")
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async def execute_ai_task(request: dict):
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"""Execute an AI task"""
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try:
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service_id = request.get('service_id')
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task_data = request.get('task_data', {})
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result = marketplace.execute_ai_task(service_id, task_data)
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return result
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/stats")
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async def get_stats():
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"""Get marketplace statistics"""
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return marketplace.get_marketplace_stats()
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if __name__ == '__main__':
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uvicorn.run(
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app,
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host="0.0.0.0",
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port=int(os.getenv('REAL_MARKETPLACE_PORT', 8006)),
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workers=2,
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log_level="info"
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)
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