posthog▌

### PostHog Integration for TanStack Start - Initialize PostHog in the root route using PostHogProvider and use posthog-node for server-side event capture in API routes. - Follow the four-step integration workflow and match the implementation patterns provided in the example project. - Use event handlers for analytics capture and user identification, avoiding useEffect for state-driven logic or event tracking.

### Querying PostHog Signals - Use the `document_embeddings` table with mandatory filters for `model_name`, `product`, `document_type`, and a `timestamp` range. - Always deduplicate results using `argMax(column, inserted_at)` grouped by `document_id` to handle soft-deleted or updated records. - Perform semantic searches using `cosineDistance` combined with the `embedText` function for natural language queries.

### PostHog Node.js Log Integration - Configure OpenTelemetry OTLP exporters to send log data directly to the PostHog ingestion endpoint. - Use environment variables for all sensitive configuration, including PostHog keys and OTLP endpoints. - Implement structured logging with key-value properties to enhance searchability and analysis within the PostHog platform.

### PostHog Android Integration - Initialize PostHog in the Application class onCreate method using environment variables for keys to ensure secure, early configuration. - Follow the provided example project patterns and ensure every activity includes an android:label for accurate screen view tracking. - Identify users during login and signup, passing session and distinct ID headers to maintain correlation across frontend and backend.

### PostHog Integration for Angular - Create a singleton PosthogService using inject() to wrap the SDK and manage analytics across standalone components. - Store PostHog credentials in environment.ts files and avoid hardcoding keys directly into the application source code. - Identify users during authentication and pass session headers to maintain data correlation between frontend and backend services.

### PostHog LLM Analytics Integration - Integrate PostHog analytics into any LLM application using provider-specific guides or the manual capture fallback for custom setups. - Capture essential metrics including input/output tokens, model names, latency, and costs while ensuring PII is never sent in events. - Use the instance-based Posthog() constructor, enable exception autocapture, and call shutdown() to ensure all events are flushed.

### PostHog Python Integration - Install the posthog package and initialize the Posthog() class with enable_exception_autocapture=True for automatic error tracking. - Use environment variables for API keys and register posthog_client.shutdown with atexit to ensure all events are flushed on exit. - Identify users via set() for person properties and never include PII like emails or names within capture() event properties.

### Analyzing Experiment Session Replays - Retrieve experiment metadata and variant keys from the feature flag to ensure accurate filtering for each test group. - Construct session recording filters using the $feature_flag_called event and the specific $feature/<flag_key> property for each variant. - Compare session duration, activity metrics, and navigation paths across variants to provide qualitative insights on user behavior.

### PostHog HogQL Query Reference - Access comprehensive schema documentation for core system models including cohorts, feature flags, error tracking, and data warehouse. - Utilize a library of optimized analytical query templates for trends, funnels, retention, user paths, and LLM trace analysis. - Reference HogQL-specific syntax, available functions, and extensions for advanced data manipulation and session replay analysis.

### PostHog Integration for React and Vite - Follow the four-step workflow to initialize, configure, and finalize PostHog analytics within your React application. - Use environment variables for API keys and implement analytics capture directly within event handlers rather than useEffect hooks. - Identify users during authentication and maintain session correlation by passing distinct IDs via headers in API requests.