0.1.9

✅ Key New Features

• Added chunk-processing pipeline under content_processing.chunk_processing with map_chunks and map_paragraphs modes (provider: semchunks), including overlap and output limits.
• Added preprocessing-only execution behavior for empty agent bodies (chain, instructions, and system_prompt all empty), returning sampled/chunked content without an LLM call.
• Added execution logging entries with call-site context and cURL reconstruction support for request debugging.
• Added tool-call dependency memory (state + memory) and model profile/tool-mode options to support smaller tool-calling model setups.

🛠️ Improvements & Stabilization

• Renamed model setting max_tokens to max_completion_tokens across runtime/spec usage.
• Added orchestrator agent-state retention (orchestrator.agent) and optional injected OpenAI client pass-through.
• Improved agent loading validation with clearer missing-agent errors and YAML ParserError handling.
• Added CLI validation for missing user agents directory before run.
• Expanded output handling to support list outputs (including chunked result arrays) and handoff return propagation.

🧪 Testing & Quality

• Added dedicated chunking test suite: src/tests/test_map_chunking.py.
• Expanded orchestrator tests for chunk/sample execution paths, execution logging behavior, memory deps, and handoff return behavior.
• Updated HTTP/tooling tests and integration tests for new model parameter naming and runtime behavior.

📚 Documentation & Templates

• Added chunking documentation: docs/chunking.md.
• Added large-context examples under examples/large_context/ (map_chunks, map_paragraphs, sample_then_chunk, and summary agent examples).
• Updated docs/advanced.md with preprocessing-only run behavior and sample/chunk-only examples.
• Updated README.md docs index to include chunking docs and refreshed template/example references.

Full Changelog: 0.1.8...0.1.9