Implement all 6 phases of missing functionality
Phase 1: Agent SDK Marketplace Integration - Implement _submit_to_marketplace() with HTTP client to coordinator API - Implement _update_marketplace_offer() with HTTP client - Implement assess_capabilities() with GPU detection using nvidia-smi - Add coordinator_url parameter and AITBCHTTPClient integration Phase 2: Agent SDK Network Registration - Implement register_with_network() with HTTP client to coordinator API - Implement get_reputation() with HTTP client to fetch from API - Implement get_earnings() with HTTP client to fetch from API - Implement signature verification in send_message() and receive_message() - Add coordinator_url parameter and AITBCHTTPClient integration Phase 3: Coordinator API Enterprise Integration - Implement generic ERPIntegration base class methods with mock implementations - Implement generic CRMIntegration base class methods with mock implementations - Add BillingIntegration base class with generic mock implementations - Add ComplianceIntegration base class with generic mock implementations - No third-party integration as requested Phase 4: Coordinator API Key Management - Add MockHSMStorage class with in-memory key storage - Add HSMProviderInterface with mock HSM connection methods - FileKeyStorage already had all abstract methods implemented Phase 5: Blockchain Node Multi-Chain Operations - Implement start_chain() with Ethereum-specific chain startup - Implement stop_chain() with Ethereum-specific chain shutdown - Implement sync_chain() with Ethereum consensus (longest-chain rule) - Add database, RPC server, P2P service, and consensus initialization Phase 6: Settlement Bridge - Implement EthereumBridge class extending BridgeAdapter - Implement _encode_payload() with Ethereum transaction encoding - Implement _get_gas_estimate() with Web3 client integration - Add Web3 client initialization and gas estimation with safety buffer
This commit is contained in:
aitbc
@@ -3,12 +3,13 @@ Compute Provider Agent - for agents that provide computational resources
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import httpx
|
||||
from typing import Dict, List, Optional, Any
|
||||
from datetime import datetime, timedelta
|
||||
from dataclasses import dataclass
|
||||
from dataclasses import dataclass, asdict
|
||||
from .agent import Agent, AgentCapabilities
|
||||
|
||||
from aitbc import get_logger
|
||||
from aitbc import get_logger, AITBCHTTPClient, NetworkError
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
@@ -43,7 +44,7 @@ class JobExecution:
|
||||
class ComputeProvider(Agent):
|
||||
"""Agent that provides computational resources"""
|
||||
|
||||
def __init__(self, *args: Any, **kwargs: Any) -> None:
|
||||
def __init__(self, *args: Any, coordinator_url: Optional[str] = None, **kwargs: Any) -> None:
|
||||
super().__init__(*args, **kwargs)
|
||||
self.current_offers: List[ResourceOffer] = []
|
||||
self.active_jobs: List[JobExecution] = []
|
||||
@@ -51,6 +52,8 @@ class ComputeProvider(Agent):
|
||||
self.utilization_rate: float = 0.0
|
||||
self.pricing_model: Dict[str, Any] = {}
|
||||
self.dynamic_pricing: Dict[str, Any] = {}
|
||||
self.coordinator_url = coordinator_url or "http://localhost:8001"
|
||||
self.http_client = AITBCHTTPClient(base_url=self.coordinator_url)
|
||||
|
||||
@classmethod
|
||||
def create_provider(
|
||||
@@ -291,23 +294,149 @@ class ComputeProvider(Agent):
|
||||
"current_offers": len(self.current_offers),
|
||||
}
|
||||
|
||||
async def _submit_to_marketplace(self, offer: ResourceOffer) -> None:
|
||||
"""Submit resource offer to marketplace (placeholder)"""
|
||||
# TODO: Implement actual marketplace submission
|
||||
await asyncio.sleep(0.1)
|
||||
async def _submit_to_marketplace(self, offer: ResourceOffer) -> str:
|
||||
"""Submit resource offer to marketplace"""
|
||||
try:
|
||||
offer_data = {
|
||||
"provider_id": offer.provider_id,
|
||||
"compute_type": offer.compute_type,
|
||||
"gpu_memory": offer.gpu_memory,
|
||||
"supported_models": offer.supported_models,
|
||||
"price_per_hour": offer.price_per_hour,
|
||||
"availability_schedule": offer.availability_schedule,
|
||||
"max_concurrent_jobs": offer.max_concurrent_jobs,
|
||||
"quality_guarantee": offer.quality_guarantee,
|
||||
}
|
||||
|
||||
response = await self.http_client.post(
|
||||
"/v1/marketplace/offers",
|
||||
json=offer_data
|
||||
)
|
||||
|
||||
if response.status_code == 201:
|
||||
result = response.json()
|
||||
offer_id = result.get("offer_id")
|
||||
logger.info(f"Offer submitted successfully: {offer_id}")
|
||||
return offer_id
|
||||
else:
|
||||
logger.error(f"Failed to submit offer: {response.status_code}")
|
||||
raise NetworkError(f"Marketplace submission failed: {response.status_code}")
|
||||
except NetworkError:
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"Error submitting to marketplace: {e}")
|
||||
raise
|
||||
|
||||
async def _update_marketplace_offer(self, offer: ResourceOffer) -> None:
|
||||
"""Update existing marketplace offer (placeholder)"""
|
||||
# TODO: Implement actual marketplace update
|
||||
await asyncio.sleep(0.1)
|
||||
"""Update existing marketplace offer"""
|
||||
try:
|
||||
offer_data = {
|
||||
"provider_id": offer.provider_id,
|
||||
"compute_type": offer.compute_type,
|
||||
"gpu_memory": offer.gpu_memory,
|
||||
"supported_models": offer.supported_models,
|
||||
"price_per_hour": offer.price_per_hour,
|
||||
"availability_schedule": offer.availability_schedule,
|
||||
"max_concurrent_jobs": offer.max_concurrent_jobs,
|
||||
"quality_guarantee": offer.quality_guarantee,
|
||||
}
|
||||
|
||||
response = await self.http_client.put(
|
||||
f"/v1/marketplace/offers/{offer.provider_id}",
|
||||
json=offer_data
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
logger.info(f"Offer updated successfully: {offer.provider_id}")
|
||||
else:
|
||||
logger.error(f"Failed to update offer: {response.status_code}")
|
||||
raise NetworkError(f"Marketplace update failed: {response.status_code}")
|
||||
except NetworkError:
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating marketplace offer: {e}")
|
||||
raise
|
||||
|
||||
@classmethod
|
||||
def assess_capabilities(cls) -> Dict[str, Any]:
|
||||
"""Assess available computational capabilities"""
|
||||
# TODO: Implement actual capability assessment
|
||||
return {
|
||||
"gpu_memory": 24,
|
||||
"supported_models": ["llama3.2", "mistral", "deepseek"],
|
||||
"performance_score": 0.95,
|
||||
"max_concurrent_jobs": 3,
|
||||
import subprocess
|
||||
import re
|
||||
|
||||
capabilities = {
|
||||
"gpu_memory": 0,
|
||||
"supported_models": [],
|
||||
"performance_score": 0.0,
|
||||
"max_concurrent_jobs": 1,
|
||||
"gpu_count": 0,
|
||||
"compute_capability": "unknown",
|
||||
}
|
||||
|
||||
try:
|
||||
# Try to detect GPU using nvidia-smi
|
||||
result = subprocess.run(
|
||||
["nvidia-smi", "--query-gpu=memory.total,name,compute_cap", "--format=csv,noheader"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=5
|
||||
)
|
||||
|
||||
if result.returncode == 0:
|
||||
gpu_lines = result.stdout.strip().split("\n")
|
||||
capabilities["gpu_count"] = len(gpu_lines)
|
||||
|
||||
total_memory = 0
|
||||
for line in gpu_lines:
|
||||
parts = line.split(", ")
|
||||
if len(parts) >= 3:
|
||||
# Parse memory (e.g., "8192 MiB")
|
||||
memory_str = parts[0].strip()
|
||||
memory_match = re.search(r'(\d+)', memory_str)
|
||||
if memory_match:
|
||||
total_memory += int(memory_match.group(1))
|
||||
|
||||
# Get compute capability
|
||||
capabilities["compute_capability"] = parts[2].strip()
|
||||
|
||||
capabilities["gpu_memory"] = total_memory
|
||||
capabilities["max_concurrent_jobs"] = min(len(gpu_lines), 4)
|
||||
|
||||
# Estimate performance score based on GPU memory and compute capability
|
||||
if total_memory >= 24000:
|
||||
capabilities["performance_score"] = 0.95
|
||||
elif total_memory >= 16000:
|
||||
capabilities["performance_score"] = 0.85
|
||||
elif total_memory >= 8000:
|
||||
capabilities["performance_score"] = 0.75
|
||||
else:
|
||||
capabilities["performance_score"] = 0.65
|
||||
|
||||
# Determine supported models based on GPU memory
|
||||
if total_memory >= 24000:
|
||||
capabilities["supported_models"] = ["llama3.2", "mistral", "deepseek", "gpt-j", "bloom"]
|
||||
elif total_memory >= 16000:
|
||||
capabilities["supported_models"] = ["llama3.2", "mistral", "deepseek"]
|
||||
elif total_memory >= 8000:
|
||||
capabilities["supported_models"] = ["llama3.2", "mistral"]
|
||||
else:
|
||||
capabilities["supported_models"] = ["llama3.2"]
|
||||
|
||||
logger.info(f"GPU capabilities detected: {capabilities}")
|
||||
else:
|
||||
logger.warning("nvidia-smi not available, using CPU-only capabilities")
|
||||
capabilities["supported_models"] = ["llama3.2-quantized"]
|
||||
capabilities["performance_score"] = 0.3
|
||||
capabilities["max_concurrent_jobs"] = 1
|
||||
|
||||
except (subprocess.TimeoutExpired, FileNotFoundError) as e:
|
||||
logger.warning(f"GPU detection failed: {e}, using CPU-only capabilities")
|
||||
capabilities["supported_models"] = ["llama3.2-quantized"]
|
||||
capabilities["performance_score"] = 0.3
|
||||
capabilities["max_concurrent_jobs"] = 1
|
||||
except Exception as e:
|
||||
logger.error(f"Error assessing capabilities: {e}")
|
||||
capabilities["supported_models"] = ["llama3.2-quantized"]
|
||||
capabilities["performance_score"] = 0.3
|
||||
capabilities["max_concurrent_jobs"] = 1
|
||||
|
||||
return capabilities
|
||||
|
||||
Reference in New Issue
Block a user