Delete claude_adapter.py

claude_adapter.py

@@ -1,217 +0,0 @@
-"""
-Claude Opus 4.5 Adapter for ARF
-Drop-in replacement for Hugging Face inference
-"""
-
-import os
-import logging
-from typing import Optional
-from dataclasses import dataclass
-
-logger = logging.getLogger(__name__)
-
-# Try to import anthropic, with graceful fallback
-try:
-    import anthropic
-    ANTHROPIC_AVAILABLE = True
-except ImportError:
-    ANTHROPIC_AVAILABLE = False
-    logger.warning("anthropic package not installed - using mock mode only")
-
-
-@dataclass
-class ClaudeConfig:
-    """Claude API configuration"""
-    api_key: str
-    model: str = "claude-opus-4"
-    max_tokens: int = 512
-    temperature: float = 0.3
-
-
-class ClaudeAdapter:
-    """
-    Drop-in replacement for HF inference in ARF agents
-    
-    Features:
-    - Automatic fallback to mock mode if no API key
-    - Intelligent pre-written responses for demo
-    - Same interface as HF inference
-    - Built-in error handling
-    """
-    
-    def __init__(self, config: Optional[ClaudeConfig] = None):
-        self.config = config or ClaudeConfig(
-            api_key=os.environ.get("ANTHROPIC_API_KEY", "")
-        )
-        
-        if not ANTHROPIC_AVAILABLE:
-            logger.warning("Anthropic package not available - mock mode only")
-            self.mock_mode = True
-        elif not self.config.api_key:
-            logger.warning("No ANTHROPIC_API_KEY found - using mock mode")
-            self.mock_mode = True
-        else:
-            try:
-                self.client = anthropic.Anthropic(api_key=self.config.api_key)
-                self.mock_mode = False
-                logger.info(f"✅ Claude adapter initialized with model: {self.config.model}")
-            except Exception as e:
-                logger.error(f"Failed to initialize Claude client: {e}")
-                self.mock_mode = True
-    
-    def generate_completion(
-        self,
-        prompt: str,
-        system_prompt: Optional[str] = None
-    ) -> str:
-        """
-        Generate completion using Claude or fallback to mock
-        
-        Args:
-            prompt: User prompt
-            system_prompt: Optional system context
-            
-        Returns:
-            Generated text response
-        """
-        if self.mock_mode:
-            logger.debug("Using mock mode (no API key or package not available)")
-            return self._mock_response(prompt)
-        
-        try:
-            messages = [{"role": "user", "content": prompt}]
-            
-            kwargs = {
-                "model": self.config.model,
-                "max_tokens": self.config.max_tokens,
-                "temperature": self.config.temperature,
-                "messages": messages
-            }
-            
-            if system_prompt:
-                kwargs["system"] = system_prompt
-            
-            response = self.client.messages.create(**kwargs)
-            
-            # Extract text from response
-            if response.content and len(response.content) > 0:
-                return response.content[0].text
-            
-            logger.warning("Empty response from Claude - using mock")
-            return self._mock_response(prompt)
-            
-        except Exception as e:
-            logger.error(f"Claude API error: {e} - falling back to mock")
-            return self._mock_response(prompt)
-    
-    def _mock_response(self, prompt: str) -> str:
-        """
-        Intelligent fallback mock response for demo
-        Pre-crafted to show system capabilities
-        """
-        prompt_lower = prompt.lower()
-        
-        # Detective Agent Response
-        if "detective" in prompt_lower or "anomaly" in prompt_lower:
-            return """🔍 ANOMALY DETECTED: Payment gateway timeout pattern identified.
-
-PATTERN ANALYSIS:
-• Current error rate: 87% (baseline: <5%)
-• Latency spike: 8500ms P99 (baseline: ~100ms)  
-• Pattern match: 94% similarity to incident 2024-11-15 (database connection pool exhaustion)
-
-CONFIDENCE: HIGH (0.87)
-
-CLASSIFICATION: Infrastructure failure - upstream dependency timeout
-
-AFFECTED METRICS:
-Primary: Error rate (+1740% vs baseline)
-Secondary: Latency (+8400% vs baseline)
-Tertiary: Throughput degradation
-
-RECOMMENDATION: Immediate investigation of upstream payment provider status + connection pool health check required."""
-        
-        # Diagnostician Agent Response
-        elif "diagnostician" in prompt_lower or "root cause" in prompt_lower:
-            return """🔬 ROOT CAUSE ANALYSIS:
-
-PRIMARY CAUSE:
-Upstream payment provider latency spike (avg response: 8.5s, normal: <500ms)
-
-SECONDARY FACTORS:
-• Connection pool exhaustion (95% utilized)
-• Retry storm amplifying load (exponential backoff not engaged)
-• Circuit breaker threshold not reached (87% < 90% threshold)
-
-EVIDENCE CHAIN:
-1. Error rate spike correlates with provider status page incident (timestamp alignment)
-2. Connection pool saturation occurred 45 seconds before error spike
-3. Upstream API latency increased 17x baseline
-4. Historical pattern match: 94% similarity to Nov 15 incident
-
-RECOMMENDED ACTION: REROUTE
-• Target: gateway-2 (backup payment processor)
-• Expected recovery: 45±5 seconds
-• Success probability: 92% (based on historical data)
-
-RATIONALE: Rerouting bypasses degraded provider, allows time for upstream recovery."""
-        
-        # Predictive Agent Response
-        elif "predictive" in prompt_lower or "forecast" in prompt_lower:
-            return """📈 PREDICTIVE FORECAST ANALYSIS:
-
-CURRENT TRAJECTORY:
-• Error rate: Increasing at 12%/minute (exponential trend)
-• Latency: Accelerating degradation (quadratic curve)
-• Resource utilization: CPU 75%, Memory 82% (stable)
-
-TIME-TO-FAILURE ESTIMATES:
-• Critical threshold (>95% error rate): ~8 minutes
-• Complete service failure: ~12 minutes  
-• Current impact: 1,240 active users affected
-
-RISK ASSESSMENT:
-Risk Score: 0.85 (HIGH)
-Confidence: 0.79
-Trend: DETERIORATING
-
-BUSINESS IMPACT FORECAST:
-• Current revenue loss: \$12,000/minute
-• Projected 15-min loss (no action): \$180,000
-• Customer churn risk: MEDIUM (historical correlation: 0.67)
-• SLA violation: IMMINENT (99.9% target, current: 13% availability)
-
-RECOMMENDATIONS:
-Primary: Execute REROUTE action immediately (Diagnostician recommendation)
-Secondary: Scale connection pool +50% capacity
-Tertiary: Enable aggressive circuit breaking (lower threshold to 75%)
-
-PREVENTIVE MEASURES:
-Monitor upstream provider health proactively, implement predictive circuit breaking."""
-        
-        # Generic/Synthesis Response
-        else:
-            return """✅ MULTI-AGENT ANALYSIS COMPLETE
-
-SYSTEM STATUS: Incident detected and analyzed
-CONFIDENCE: HIGH (0.85)
-
-SYNTHESIS:
-All agents have completed analysis. The system has identified a critical upstream dependency failure requiring immediate intervention. Recovery action has been selected based on historical success patterns and current system state.
-
-Recommended action: REROUTE to backup systems
-Expected outcome: Service restoration within 45 seconds
-
-Continuing autonomous monitoring..."""
-
-
-# Singleton instance
-_claude_adapter: Optional[ClaudeAdapter] = None
-
-
-def get_claude_adapter() -> ClaudeAdapter:
-    """Get or create Claude adapter singleton"""
-    global _claude_adapter
-    if _claude_adapter is None:
-        _claude_adapter = ClaudeAdapter()
-    return _claude_adapter