Conversation logs provide detailed visibility into every interaction with your AI application. Use them to debug specific issues, understand user behavior patterns, and collect feedback for continuous improvement.
What Gets Logged
All User Interactions
Every conversation through your web app or API is logged with complete input/output history, timing data, and system metadata.
User Feedback
Thumbs up/down ratings and user comments are captured alongside the conversations they reference.
System Context
Model used, token consumption, response times, and any errors or warnings during processing.
Exclusions: Debugging sessions and prompt testing are not included in logs.
Using the Logs Console
Access logs from your application’s navigation menu. The interface shows:
- Conversation Timeline: Chronological list of user interactions
- Message Details: Full conversation context with AI responses
- Performance Data: Response times and token usage per interaction
- User Feedback: Ratings and comments from users and team members
Debugging with Logs
Failed Interactions
Quickly identify conversations where the AI provided poor responses, failed to understand user intent, or encountered errors.
Performance Issues
Spot slow responses, high token usage, or system errors that affect user experience.
User Journey Analysis
Follow individual users through multiple conversations to understand usage patterns and pain points.
Feedback Collection
User Ratings
Users can provide thumbs up/down feedback on AI responses. Track satisfaction trends over time.
Team Annotations
Team members can add internal notes and improved responses directly in the log interface.
Feedback Analysis
Identify common complaint patterns, successful interaction types, and areas needing improvement.
Data Retention
Ensure your application complies with local data privacy regulations. Publish a privacy policy and obtain user consent where required.
Improving Applications with Logs
Pattern Recognition
Look for recurring user questions that your application handles poorly. These indicate opportunities for prompt improvements or knowledge base updates.
Response Quality
Use feedback patterns to identify which types of responses work well and which need refinement.
Performance Optimization
Track response times and token usage to identify inefficient prompts or model configurations.
Content Gaps
Spot topics or question types where your application consistently struggles, indicating areas for knowledge base expansion.
Privacy Considerations
Logs contain complete user conversations and may include sensitive information. Implement appropriate access controls and ensure compliance with applicable data protection regulations.
Consider configuring shorter retention periods for applications handling sensitive data or implement log anonymization where appropriate. 
