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Remove MockTracer classes and fix telemetry import errors #8
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rindhuja-johnson
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This implementation provides anonymous public telemetry for the Zen orchestrator, enabling community-driven analytics that differentiate Zen from Apex's commercial approach. Key features: - Anonymous usage tracking with no authentication required - Community insights visible to all users - Embedded credentials for seamless operation - Public telemetry dashboard capabilities Files added: - TELEMETRY_SETUP_GUIDE.md: Complete setup and capabilities guide - COMMUNITY_ANALYTICS_DEMO.md: Live demo examples - COMMUNITY_ANALYTICS_SUMMARY.md: Summary of analytics features - demo_community_analytics.py: Working demo script - scripts/setup_netra_telemetry_public.sh: Automated setup script 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This implementation provides a bulletproof secret management system for the Zen-Apex integration with enterprise-grade security features. Key components: - Google Secret Manager integration with automatic rotation - Kubernetes secret management with RBAC controls - Multi-environment secret deployment (dev/staging/prod) - Comprehensive monitoring and alerting - Secure credential embedding system Files added: - zen_secrets/: Complete secret management module - core.py: Core secret management classes - gsm.py: Google Secret Manager integration - kubernetes.py: Kubernetes secret management - rotation.py: Automated secret rotation engine - monitoring.py: Monitoring and alerting system - config.py: Configuration management - ZEN_APEX_SECRET_MANAGEMENT_IMPLEMENTATION_GUIDE.md: Implementation guide - zen_secret_management_architecture.md: Architecture documentation - scripts/embed_credentials.py: Secure credential embedding 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit includes production deployment setup, core system updates, and integration improvements for the Zen-Apex ecosystem. Key components: - Production deployment guides and automation scripts - Core system updates including orchestrator enhancements - Telemetry module integration - Build and verification automation - Package configuration updates with updated .gitignore Files added/modified: - PRODUCTION_SETUP_GUIDE.md: Comprehensive production deployment guide - DEMO_SUMMARY.md: Demo summary and usage examples - scripts/build_production.sh: Production build automation - scripts/verify_production.sh: Production verification script - zen/telemetry/: Complete telemetry module implementation - zen_orchestrator.py: Enhanced orchestrator with new capabilities - pyproject.toml, requirements.txt: Updated dependencies and configuration - .gitignore: Updated to exclude sensitive files like embedded credentials - MANIFEST.in: Updated project configuration 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Removed unnecessary MockTracer and MockSpan classes that were causing import errors - Replaced with cleaner NoOpSpan for disabled telemetry cases - Updated type annotations to use Optional["trace.Tracer"] instead of Union types - Simplified error handling by removing mock object assignments - Telemetry now gracefully disables when OpenTelemetry is unavailable This fixes the "name 'MockTracer' is not defined" error during build and makes the codebase cleaner without fake implementations. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Fix .gitignore formatting and add .config entry - Update community_auth.py to use embedded_credentials module - Simplify credential loading to use embedded implementation - Add GitHub workflows directory - Include system files for completeness 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
Implements comprehensive cache token tracking for individual tools in the Tool Usage Details table, matching the command-level metrics display. Cache tokens (cache_read and cache_creation) are now properly tracked, attributed, and displayed for each tool. Key changes: - Changed tool_tokens from Dict[str, int] to Dict[str, Dict[str, int]] for structured breakdown - Added cache_read and cache_creation tracking alongside input/output/total tokens - Implemented proportional cache attribution based on tool usage frequency - Added Cache Cr and Cache Rd columns to Tool Usage Details table - Ensured tool cache totals match overall cache metrics - Added comprehensive regression tests in tests/test_tool_cache_tokens.py The cache attribution uses proportional distribution since Claude's API reports cache at the message level rather than per-tool. Tools that are used more frequently receive proportionally more cache attribution. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Summary
Changes Made
Union["trace.Tracer", MockTracer]toOptional["trace.Tracer"]Test plan
zen.telemetry.embedded_credentialsworks without errors🤖 Generated with Claude Code