Spaces:
Runtime error
Runtime error
File size: 1,971 Bytes
2e5db77 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
import random
import datetime
from components.sentiment_analysis import EnhancedSentimentAnalyzer
from components.real_time_data import RealTimeDataIntegrator
from components.self_improving_ai import SelfImprovingAI
class FederatedAI:
"""
Real federated AI aggregator using sentiment, real-time data, and self-improvement feedback loops.
"""
def __init__(self):
self.nodes = {
"sentiment_node": EnhancedSentimentAnalyzer(),
"realtime_node": RealTimeDataIntegrator(),
"self_reflect_node": SelfImprovingAI()
}
self.last_feedback_log = []
async def get_latest_data(self) -> dict:
"""
Perform distributed AI analysis from multiple perspectives.
"""
sentiment_result = self.nodes["sentiment_node"].detailed_analysis(
"Global mental health patterns show growing concern in post-COVID behavior."
)
try:
realtime_data = await self.nodes["realtime_node"].fetch_and_integrate([
"https://api.coindesk.com/v1/bpi/currentprice.json",
"https://api.exchangerate-api.com/v4/latest/USD"
])
except Exception as e:
realtime_data = {"error": str(e)}
feedback = random.choice([
"Response missed cultural context.",
"Model adaptation needed.",
"Excellent contextual interpretation.",
"Too generic, lacking actionable advice."
])
self.nodes["self_reflect_node"].improve(feedback)
self.last_feedback_log.append(feedback)
return {
"federated_summary": {
"timestamp": datetime.datetime.utcnow().isoformat(),
"sentiment_insight": sentiment_result,
"real_time_data": realtime_data,
"last_feedback": feedback,
"feedback_history": self.last_feedback_log[-3:] # keep recent 3
}
} |