[QUO-2301] Update Log and Detection Params

.gitignore

@@ -25,4 +25,7 @@ coverage/
 
 # Logs
 logs/
-*.log 
+*.log
+
+# Comprehensive testing examples internal use only
+examples/comprehensive-testing.ts 

README.md

@@ -4,7 +4,7 @@
 
 ## Overview
 
-`quotientai` is an SDK and CLI for logging data to [Quotient](https://quotientai.co), running hallucination and document attribution detections for retrieval and search-augmented AI systems, and **automatically tracing AI/ML applications**.
+`quotientai` is an SDK and CLI for logging data to [Quotient](https://quotientai.co), running hallucination and document relevancy detections for retrieval and search-augmented AI systems, and **automatically tracing AI/ML applications**.
 
 ## Installation
 
@@ -14,14 +14,14 @@ npm install quotientai
 
 ## Usage
 
-### Logging and Hallucination Detection
+### Logging and Detection
 
 Create an API key on [Quotient](https://app.quotientai.co) and set it as an environment variable called `QUOTIENT_API_KEY`. Then follow the examples below or see our [docs](https://docs.quotientai.co) for a more comprehensive walkthrough.
 
-Send your first log and detect hallucinations. Run the code below and see your Logs and Detections on your [Quotient Dashboard](https://app.quotientai.co/dashboard).
+Send your first log and run detections (hallucination detection, document relevancy). Run the code below and see your Logs and Detections on your [Quotient Dashboard](https://app.quotientai.co/dashboard).
 
 ```typescript
-import { QuotientAI } from 'quotientai';
+import { QuotientAI, DetectionType } from 'quotientai';
 
 const quotient = new QuotientAI(apiKey?: string);
 
@@ -30,12 +30,12 @@ const quotientLogger = quotient.logger.init({
   appName: 'my-app',
   environment: 'dev',
   sampleRate: 1.0,
-  hallucinationDetection: true,
-  hallucinationDetectionSampleRate: 1.0,
+  detections: [DetectionType.HALLUCINATION, DetectionType.DOCUMENT_RELEVANCY],
+  detectionSampleRate: 1.0,
 });
 
 // create a log
-const logId = await quotientLogger.log({
+const logId = await quotient.log({
   userQuery: 'How do I cook a goose?',
   modelOutput: 'The capital of France is Paris',
   documents: ['Here is an excellent goose recipe...'],

examples/example_logs.ts

@@ -1,17 +1,17 @@
-import { QuotientAI } from 'quotientai';
+import { QuotientAI, DetectionType } from 'quotientai';
 
 async function main() {
   const quotient = new QuotientAI();
   console.log('QuotientAI client initialized');
 
   // configure the logger
-  const quotientLogger = quotient.logger.init({
+  quotient.logger.init({
     appName: 'my-app',
     environment: 'dev',
     sampleRate: 1.0,
     tags: { model: 'gpt-4o', feature: 'customer-support' },
-    hallucinationDetection: true,
-    hallucinationDetectionSampleRate: 1.0,
+    detections: [DetectionType.HALLUCINATION, DetectionType.DOCUMENT_RELEVANCY],
+    detectionSampleRate: 1.0,
   });
 
   console.log('Logger initialized');
@@ -38,13 +38,11 @@ async function main() {
         'You are a helpful assistant that answers questions about the world.',
         "Answer the question in a concise manner. If you are not sure, say 'I don't know'.",
       ],
-      hallucinationDetection: true,
-      inconsistencyDetection: true,
     });
     console.log('pollForDetections with logId: ', logId);
 
     // poll for the detection results
-    const detectionResults = await quotientLogger.pollForDetections(logId);
+    const detectionResults = await quotientLogger.pollForDetection(logId);
     console.log('detectionResults', detectionResults);
   } catch (error) {
     console.error(error);

quotientai/index.ts

@@ -53,18 +53,27 @@ export class QuotientAI {
   }
 
   /**
+   * Log the model interaction.
+   *
    * Args:
-   *     user_query: The user's input query
-   *     model_output: The model's response
+   *     # New detection parameters (recommended):
+   *     detections: List of detection types to run (replaces hallucinationDetection/inconsistencyDetection)
+   *     detectionSampleRate: Sample rate for all detections 0-1 (replaces hallucinationDetectionSampleRate)
+   *
+   *     # Deprecated detection parameters:
+   *     hallucinationDetection: [DEPRECATED in 0.0.9] Use detections=[DetectionType.HALLUCINATION] instead
+   *     inconsistencyDetection: [DEPRECATED in 0.0.9] Use detections=[DetectionType.INCONSISTENCY] instead
+   *
+   *     # Common input parameters:
+   *     userQuery: The user's input query
+   *     modelOutput: The model's response
    *     documents: Optional list of documents (strings or LogDocument objects)
-   *     message_history: Optional conversation history
+   *     messageHistory: Optional conversation history
    *     instructions: Optional list of instructions
    *     tags: Optional tags to attach to the log
-   *     hallucination_detection: Override hallucination detection setting
-   *     inconsistency_detection: Override inconsistency detection setting
    *
    * Returns:
-   *     Log ID if successful, None otherwise
+   *     Log ID if successful, null otherwise
    */
   async log(params: Omit<LogEntry, 'appName' | 'environment'>): Promise<any> {
     return this.logger._internalLog(params);
@@ -92,3 +101,4 @@ export class QuotientAI {
 
 // Export types that users need
 export { TracingConfig } from './tracing';
+export { DetectionType } from './types';