8251853cbd
📋 Marketplace Endpoints: • GET /marketplace/listings - List all active marketplace items • POST /marketplace/create - Create new marketplace listing • Demo listings for GPU and compute resources • In-memory storage with active status filtering 🤖 AI Services Endpoints: • POST /ai/submit - Submit AI jobs with payment • GET /ai/stats - AI service statistics and revenue tracking • Support for text, image, and training job types
227 lines
8.0 KiB
Python
227 lines
8.0 KiB
Python
"""AI Services RPC endpoints for AITBC blockchain"""
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from typing import Any, Dict, List, Optional
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from fastapi import HTTPException
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from pydantic import BaseModel, Field
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from datetime import datetime, timedelta
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import uuid
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from ..database import session_scope
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from ..metrics import metrics_registry
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from .router import router
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class AIJobRequest(BaseModel):
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"""AI job submission request"""
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wallet_address: str = Field(..., description="Client wallet address")
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job_type: str = Field(..., description="Type of AI job (text, image, training, etc.)")
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prompt: str = Field(..., description="AI prompt or task description")
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payment: float = Field(..., ge=0, description="Payment in AIT")
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parameters: Optional[Dict[str, Any]] = Field(default=None, description="Additional job parameters")
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class AIJobResponse(BaseModel):
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"""AI job response"""
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job_id: str
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status: str
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wallet_address: str
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job_type: str
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payment: float
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created_at: datetime
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estimated_completion: Optional[datetime] = None
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result: Optional[Dict[str, Any]] = None
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# In-memory storage for demo (in production, use database)
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_ai_jobs: List[Dict[str, Any]] = [
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{
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"job_id": "job_demo_001",
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"wallet_address": "ait1demo_client_123...",
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"job_type": "text",
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"prompt": "Generate a summary of blockchain technology",
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"payment": 100.0,
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"status": "completed",
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"created_at": (datetime.now() - timedelta(hours=1)).isoformat(),
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"completed_at": (datetime.now() - timedelta(minutes=30)).isoformat(),
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"result": {
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"output": "Blockchain is a distributed ledger technology...",
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"tokens_used": 150,
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"processing_time": "2.5 minutes"
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}
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},
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{
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"job_id": "job_demo_002",
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"wallet_address": "ait1demo_client_456...",
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"job_type": "image",
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"prompt": "Create an image of a futuristic blockchain city",
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"payment": 250.0,
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"status": "processing",
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"created_at": (datetime.now() - timedelta(minutes=15)).isoformat(),
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"estimated_completion": (datetime.now() + timedelta(minutes=10)).isoformat()
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}
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]
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@router.post("/ai/submit", summary="Submit AI job", tags=["ai"])
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async def ai_submit_job(request: AIJobRequest) -> Dict[str, Any]:
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"""Submit a new AI job for processing"""
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try:
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metrics_registry.increment("rpc_ai_submit_total")
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# Generate unique job ID
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job_id = f"job_{uuid.uuid4().hex[:8]}"
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# Calculate estimated completion time
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estimated_completion = datetime.now() + timedelta(minutes=30)
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# Create new job
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new_job = {
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"job_id": job_id,
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"wallet_address": request.wallet_address,
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"job_type": request.job_type,
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"prompt": request.prompt,
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"payment": request.payment,
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"parameters": request.parameters or {},
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"status": "queued",
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"created_at": datetime.now().isoformat(),
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"estimated_completion": estimated_completion.isoformat()
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}
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# Add to storage
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_ai_jobs.append(new_job)
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return {
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"job_id": job_id,
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"status": "queued",
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"message": "AI job submitted successfully",
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"estimated_completion": estimated_completion.isoformat(),
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"wallet_address": request.wallet_address,
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"payment": request.payment,
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"job_type": request.job_type
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}
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except Exception as e:
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metrics_registry.increment("rpc_ai_submit_errors_total")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/ai/jobs", summary="List AI jobs", tags=["ai"])
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async def ai_list_jobs(wallet_address: Optional[str] = None, status: Optional[str] = None) -> Dict[str, Any]:
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"""Get list of AI jobs, optionally filtered by wallet address or status"""
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try:
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metrics_registry.increment("rpc_ai_list_total")
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# Filter jobs
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filtered_jobs = _ai_jobs.copy()
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if wallet_address:
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filtered_jobs = [job for job in filtered_jobs if job.get("wallet_address") == wallet_address]
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if status:
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filtered_jobs = [job for job in filtered_jobs if job.get("status") == status]
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# Sort by creation time (newest first)
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filtered_jobs.sort(key=lambda x: x.get("created_at", ""), reverse=True)
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return {
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"jobs": filtered_jobs,
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"total": len(filtered_jobs),
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"filters": {
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"wallet_address": wallet_address,
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"status": status
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},
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"timestamp": datetime.now().isoformat()
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}
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except Exception as e:
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metrics_registry.increment("rpc_ai_list_errors_total")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/ai/job/{job_id}", summary="Get AI job by ID", tags=["ai"])
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async def ai_get_job(job_id: str) -> Dict[str, Any]:
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"""Get a specific AI job by ID"""
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try:
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metrics_registry.increment("rpc_ai_get_total")
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# Find job
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for job in _ai_jobs:
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if job.get("job_id") == job_id:
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return {
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"job": job,
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"found": True
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}
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raise HTTPException(status_code=404, detail="Job not found")
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except HTTPException:
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raise
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except Exception as e:
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metrics_registry.increment("rpc_ai_get_errors_total")
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raise HTTPException(status_code=500, detail=str(e))
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@router.post("/ai/job/{job_id}/cancel", summary="Cancel AI job", tags=["ai"])
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async def ai_cancel_job(job_id: str) -> Dict[str, Any]:
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"""Cancel an AI job"""
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try:
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metrics_registry.increment("rpc_ai_cancel_total")
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# Find and update job
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for job in _ai_jobs:
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if job.get("job_id") == job_id:
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current_status = job.get("status")
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if current_status in ["completed", "cancelled"]:
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raise HTTPException(
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status_code=400,
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detail=f"Cannot cancel job with status: {current_status}"
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)
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job["status"] = "cancelled"
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job["cancelled_at"] = datetime.now().isoformat()
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return {
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"job_id": job_id,
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"status": "cancelled",
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"message": "AI job cancelled successfully"
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}
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raise HTTPException(status_code=404, detail="Job not found")
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except HTTPException:
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raise
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except Exception as e:
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metrics_registry.increment("rpc_ai_cancel_errors_total")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/ai/stats", summary="AI service statistics", tags=["ai"])
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async def ai_stats() -> Dict[str, Any]:
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"""Get AI service statistics"""
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try:
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metrics_registry.increment("rpc_ai_stats_total")
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total_jobs = len(_ai_jobs)
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status_counts = {}
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type_counts = {}
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total_revenue = 0.0
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for job in _ai_jobs:
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# Count by status
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status = job.get("status", "unknown")
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status_counts[status] = status_counts.get(status, 0) + 1
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# Count by type
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job_type = job.get("job_type", "unknown")
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type_counts[job_type] = type_counts.get(job_type, 0) + 1
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# Sum revenue for completed jobs
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if status == "completed":
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total_revenue += job.get("payment", 0.0)
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return {
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"total_jobs": total_jobs,
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"status_breakdown": status_counts,
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"type_breakdown": type_counts,
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"total_revenue": total_revenue,
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"average_payment": total_revenue / max(1, status_counts.get("completed", 0)),
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"timestamp": datetime.now().isoformat()
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}
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except Exception as e:
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metrics_registry.increment("rpc_ai_stats_errors_total")
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raise HTTPException(status_code=500, detail=str(e))
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