Create recovery_enrichment_agent.py

recovery_enrichment_agent.py

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+"""
+Recovery/Enrichment Agent
+
+Implements prioritized enrichment source config, rate limiting, retry/backoff, queue/handoff, and full action/decision logging for leads enrichment and recovery workflows.
+"""
+
+import time
+import logging
+from enum import Enum
+from typing import List, Dict, Any, Optional
+
+# Agent config
+class EnrichmentSource(Enum):
+    API = "api"
+    BROWSER_AGENT = "browser_agent"
+    HUMAN_REVIEW = "human_review"
+
+default_agent_config = {
+    "priority_sources": [EnrichmentSource.API, EnrichmentSource.BROWSER_AGENT, EnrichmentSource.HUMAN_REVIEW],
+    "rate_limit_per_minute": 10,
+    "max_retries": 3,
+    "retry_backoff_seconds": 5,
+}
+
+# Audit and log actions/decisions/edge cases
+def log_event(event_type: str, info: dict):
+    logging.info({"event_type": event_type, **info})
+
+# Simulate lead batch handoff and enrichment
+class LeadBatchHandler:
+    def __init__(self, config=default_agent_config):
+        self.config = config
+        self.queue = []
+        self.history = []
+        self.rate_limit_counter = 0
+        self.last_reset = time.time()
+
+    def reset_rate_limit(self):
+        now = time.time()
+        if now - self.last_reset > 60:
+            self.rate_limit_counter = 0
+            self.last_reset = now
+            log_event("rate_limit_reset", {})
+
+    def handle_lead_batch(self, leads: List[Dict[str, Any]]):
+        results = []
+        for lead in leads:
+            result = self._process_lead(lead)
+            results.append(result)
+        return results
+
+    def _process_lead(self, lead: Dict[str, Any]) -> Dict[str, Any]:
+        self.reset_rate_limit()
+        for source in self.config["priority_sources"]:
+            for attempt in range(self.config["max_retries"]):
+                if self.rate_limit_counter >= self.config["rate_limit_per_minute"]:
+                    wait_time = 60 - (time.time() - self.last_reset)
+                    if wait_time > 0:
+                        log_event("rate_limit_wait", {"wait": wait_time})
+                        time.sleep(wait_time)
+                    self.reset_rate_limit()
+                log_event("enrich_attempt", {"source": source.value, "lead": lead, "attempt": attempt+1})
+                self.rate_limit_counter += 1
+                success, data = self._enrich_from_source(source, lead)
+                if success:
+                    log_event("enrich_success", {"source": source.value, "lead": lead})
+                    return {"lead": lead, "enriched": data}
+                else:
+                    log_event("enrich_failure", {"source": source.value, "lead": lead, "attempt": attempt+1})
+                    time.sleep(self.config["retry_backoff_seconds"])
+        self._escalate_to_human(lead)
+        return {"lead": lead, "enriched": None, "escalated": True}
+
+    def _enrich_from_source(self, source: EnrichmentSource, lead: Dict[str, Any]) -> (bool, Optional[dict]):
+        # Simulation logic; replace with real API/browser/human integration
+        if source == EnrichmentSource.API:
+            return False, None  # simulate API failure
+        if source == EnrichmentSource.BROWSER_AGENT:
+            return True, {"company": "Simulated Corp", "status": "Browser enrichment success"}
+        if source == EnrichmentSource.HUMAN_REVIEW:
+            return True, {"company": "Simulated Corp", "status": "Human reviewed"}
+        return False, None
+
+    def _escalate_to_human(self, lead: Dict[str, Any]):
+        self.queue.append(lead)
+        log_event("escalate", {"lead": lead})
+
+    def get_audit_log(self):
+        # Return all logged history (simulate)
+        pass
+
+# Config interface sample
+def get_sample_config() -> dict:
+    return default_agent_config
+
+# Usage sample
+def simulate_lead_handoff():
+    handler = LeadBatchHandler()
+    leads = [{"first_name": "Mila", "company": "Sample Inc"}, {"first_name": "Rob", "company": "Unknown Ltd"}]
+    results = handler.handle_lead_batch(leads)
+    print(results)
+    # add more logic for audit/fallback/escalation as needed
+
+if __name__ == "__main__":
+    simulate_lead_handoff()