Add lightweight onTrace callback to OrchestratorConfig that emits
structured span events (llm_call, tool_call, task, agent) with timing,
token usage, and runId correlation. Zero overhead when not subscribed.
Closes#18
- Merge examples 08 (runTasks) and 09 (runTeam) into a single Gemma 4 example
- Renumber: structured output → 09, task retry → 10
- Move Author and Contributors sections to bottom in both READMEs
- Add Author section to English README
Add examples/09-gemma4-auto-orchestration.ts demonstrating runTeam()
with Gemma 4 as the coordinator — the framework's key feature running
fully local. The coordinator successfully decomposes goals into JSON
task arrays, schedules dependencies, and synthesises results.
Verified on gemma4:e2b (5.1B params) with Ollama 0.20.0-rc1.
Add examples/08-gemma4-local.ts demonstrating a pure-local multi-agent
team using Gemma 4 via Ollama — zero API cost. Two agents (researcher +
summarizer) collaborate through a task pipeline with bash, file_write,
and file_read tools. Verified on gemma4:e2b with Ollama 0.20.0-rc1.
Update both READMEs: add example 08 to the examples table and note
Gemma 4 as a verified local model with tool-calling support.
- Add Supported Providers table with 4 verified providers (Anthropic, OpenAI,
Copilot, Ollama) and note that other OpenAI-compatible providers are unverified
- Update Contributing to distinguish baseURL verification (#25) from new adapters
- Note that local models via Ollama require no API key in Quick Start
Remove ~160 lines of duplicated code snippets from both READMEs.
Link to the runnable scripts in examples/ instead — single source of truth,
type-checked by npm run lint.
- Add Ollama/local model agent example in multi-model teams section
- Update "Model Agnostic" description to mention local models and baseURL
- Update contributing section to reflect built-in OpenAI-compatible support
- Add author block with Xiaohongshu link in Chinese README