This repository contains multiple PyPI-publishable packages organized and orchestrated using Nx workspace management.
Sign in to like and favorite skills
This repository contains multiple PyPI-publishable packages organized and orchestrated using Nx workspace management.
# Run tests across all packages nx run-many -t test # Run linting across all packages nx run-many -t lint # Update lock files across all packages nx run-many -t lock # Run specific targets on specific packages nx run <package-name>:test nx run <package-name>:lint # Show project graph nx graph # Show what's affected by changes nx affected:test nx affected:lint
All packages use uv as the package manager. Always execute commands through uv:
uv run <command>
Tests utilize VCR cassettes for API calls.
# Run tests normally (uses existing cassettes) uv run pytest tests/ # Re-record all cassettes (requires API keys) uv run pytest tests/ --record-mode=all # Record only new test episodes uv run pytest tests/ --record-mode=new_episodes # Record cassettes once (if they don't exist) uv run pytest tests/ --record-mode=once # Run tests without recording (fails if cassettes missing) uv run pytest tests/ --record-mode=none # Run specific test files uv run pytest tests/test_agents.py --record-mode=once
Re-record cassettes when API interactions change to ensure test accuracy. Never commit secrets or PII. Scrub them using VCR filters (e.g., filter_headers, before_record) or your test framework's equivalent. Store API keys only in environment variables/secure vaults; never in code or cassettes. Typical record modes you may use: once, new_episodes, all, none (choose per test needs). Creating new cassettes requires valid API keys (OpenAI, Anthropic, etc.); ask the user to provide them if needed.
For debugging OpenTelemetry spans and hierarchy issues, use the console exporter:
from opentelemetry.sdk.trace.export import ConsoleSpanExporter from traceloop.sdk import Traceloop Traceloop.init( app_name="debug-app", exporter=ConsoleSpanExporter(), # other config... )
This outputs all spans to console in JSON format, showing trace IDs, span IDs, parent relationships, and attributes for debugging span hierarchy issues.
The semantic convention package follows the OpenTelemetry GenAI specification: https://opentelemetry.io/docs/specs/semconv/gen-ai/
Instrumentation packages should leverage the semantic conventions package. Their purpose is to instrument AI-related libraries and generate spans and tracing data compliant with OpenTelemetry semantic conventions.
Ruff is used for code linting. Configuration is in each package's pyproject.toml under
[tool.ruff]