add polling

Author: Mike Goitia

examples/logging/async_simple_logging.py

@@ -10,7 +10,7 @@
     tags={"model": "gpt-4o", "feature": "customer-support"},
     hallucination_detection=True,
     inconsistency_detection=True,
-    sample_rate=1.0,
+    hallucination_detection_sample_rate=1.0,
 )
 
 
@@ -40,6 +40,37 @@ async def main():
 
     print("Log request sent")
     print("Log ID: ", log_id)
+    print("Log created, waiting for detection results...")
+
+    # Poll for detection results with a timeout of 60 seconds
+    # You can adjust timeout and poll_interval based on your needs
+    detection_results = await quotient_logger.poll_for_detection(
+        log_id=log_id,
+        timeout=60,  # Wait up to 60 seconds for results
+        poll_interval=2.0,  # Check every 2 seconds
+    )
+
+    if detection_results:
+        print("\nDetection Results:")
+        print(f"Status: {detection_results.status}")
+        print(f"Has hallucination: {detection_results.has_hallucination}")
+
+        if detection_results.has_hallucination is not None:
+            print(f"Has hallucinations: {detection_results.has_hallucination}")
+
+        if detection_results.evaluations:
+            print(f"\nFound {len(detection_results.evaluations)} evaluations")
+            for i, eval in enumerate(detection_results.evaluations):
+                print(f"\nEvaluation {i+1}:")
+                print(f"Sentence: {eval.get('sentence', 'N/A')}")
+                print(f"Is hallucinated: {eval.get('is_hallucinated', 'N/A')}")
+    else:
+        print(
+            "\nNo detection results received. The detection might still be in progress or failed."
+        )
+        print("You can try again later with:")
+        print(f"await quotient_logger.get_detection(log_id='{log_id}')")
+
     print("Press Enter to exit...")
 
     # Use asyncio's run_in_executor to handle blocking input() call

examples/logging/simple_logging.py

@@ -3,12 +3,13 @@
 quotient = QuotientAI()
 quotient_logger = quotient.logger.init(
     # Required
-    app_name="test-id-create",
+    app_name="my-app",
     environment="dev",
     # dynamic labels for slicing/dicing analytics e.g. by customer, feature, etc
     tags={"model": "gpt-4o", "feature": "customer-support"},
     hallucination_detection=True,
     inconsistency_detection=True,
+    hallucination_detection_sample_rate=1.0,
 )
 
 # Mock retrieved documents
@@ -35,5 +36,33 @@
 )
 
 print("Log ID: ", log_id)
+print("Log created, waiting for detection results...")
 
-print("Log created")
+# Poll for detection results with a timeout of 60 seconds
+# You can adjust timeout and poll_interval based on your needs
+detection_results = quotient_logger.poll_for_detection(
+    log_id=log_id,
+    timeout=60,  # Wait up to 60 seconds for results
+    poll_interval=2.0,  # Check every 2 seconds
+)
+
+if detection_results:
+    print("\nDetection Results:")
+    print(f"Status: {detection_results.status}")
+    print(f"Has hallucination: {detection_results.has_hallucination}")
+
+    if detection_results.has_hallucination is not None:
+        print(f"Has hallucinations: {detection_results.has_hallucination}")
+
+    if detection_results.evaluations:
+        print(f"\nFound {len(detection_results.evaluations)} evaluations")
+        for i, eval in enumerate(detection_results.evaluations):
+            print(f"\nEvaluation {i+1}:")
+            print(f"Sentence: {eval.get('sentence', 'N/A')}")
+            print(f"Is hallucinated: {eval.get('is_hallucinated', 'N/A')}")
+else:
+    print(
+        "\nNo detection results received. The detection might still be in progress or failed."
+    )
+    print("You can try again later with:")
+    print(f"quotient_logger.get_detection(log_id='{log_id}')")

quotientai/async_client.py

@@ -308,6 +308,37 @@ async def log(
             return log_id
         return None
 
+    async def poll_for_detection(
+        self, log_id: str, timeout: int = 300, poll_interval: float = 2.0
+    ):
+        """
+        Get Detection results for a log asynchronously.
+
+        This method polls the Detection endpoint until the results are ready or the timeout is reached.
+
+        Args:
+            log_id: The ID of the log to get Detection results for
+            timeout: Maximum time to wait for results in seconds (default: 300s/5min)
+            poll_interval: How often to poll the API in seconds (default: 2s)
+
+        Returns:
+            Log object with Detection results if successful, None otherwise
+        """
+        if not self._configured:
+            logger.error(
+                f"Logger is not configured. Please call init() before getting Detection results."
+            )
+            return None
+
+        if not log_id:
+            logger.error("Log ID is required for Detection")
+            return None
+
+        # Call the underlying resource method
+        return await self.logs_resource.poll_for_detection(
+            log_id, timeout, poll_interval
+        )
+
 
 class AsyncQuotientAI:
     """

quotientai/client.py

@@ -1,5 +1,3 @@
-from datetime import datetime, timezone
-import uuid
 import json
 import os
 import random
@@ -310,6 +308,35 @@ def log(
         else:
             return None
 
+    def poll_for_detection(
+        self, log_id: str, timeout: int = 300, poll_interval: float = 2.0
+    ):
+        """
+        Get Detection results for a log.
+
+        This method polls the Detection endpoint until the results are ready or the timeout is reached.
+
+        Args:
+            log_id: The ID of the log to get Detection results for
+            timeout: Maximum time to wait for results in seconds (default: 300s/5min)
+            poll_interval: How often to poll the API in seconds (default: 2s)
+
+        Returns:
+            Log object with Detection results if successful, None otherwise
+        """
+        if not self._configured:
+            logger.error(
+                f"Logger is not configured. Please call init() before getting Detection results."
+            )
+            return None
+
+        if not log_id:
+            logger.error("Log ID is required for Detection")
+            return None
+
+        # Call the underlying resource method
+        return self.logs_resource.poll_for_detection(log_id, timeout, poll_interval)
+
 
 class QuotientAI:
     """