v0.5.0

[0.5.0] - 2026-11-07
Added

Typed messages: Message can carry tool_calls, a tool result (role="tool" with tool_call_id and name) and a stored tool_trace; ToolCall and LLMResponse (new tool_calls field) serialise them. New fields are written only when set, so plain messages and old snapshots are unchanged
LLMBackend.chat_turn(messages, tool_specs, system=, config=): one tool-aware round over typed messages that returns an LLMResponse with tool_calls (every call gets an id, invented when the provider has none) and real token counts on tool rounds. Implemented by the Ollama, OpenAI, OpenRouter, llama.cpp, vLLM and Anthropic backends (supports_typed_messages, to_wire_messages); the dict-based chat_with_tools / append_tool_results still work for custom backends
The agent's native tool loop runs on typed messages for those backends, and a FallbackBackend of typed backends hands a half-finished tool loop to the next backend as it is (no flattening to text)
MemoryPolicy(tool_history=True) (needs history_mode="messages"): the tool calls and results behind each answer are remembered, clipped to tool_result_chars, counted against the token budget, replayed ahead of that answer and described to the summariser. Also settable under memory: in agent YAML
Conformance suite: typed-turn contract tests for every backend adapter; live typed tool-round and tool-history checks against Ollama and OpenRouter

Changed

Tool-call rounds are now counted in agent.usage (they were not before: only text answers were)
With a typed backend, AgentCallback.on_model_start receives typed Message objects instead of provider dicts, and on_model_end receives the response (with token counts) on tool rounds instead of None
The agent's closing round after ToolPolicy.max_rounds now offers the tools with tool_choice="none" (Anthropic insists on tool definitions while the history holds tool blocks) and carries a short "answer now" instruction, because some local models return nothing when simply asked to continue after a tool exchange (seen with gemma4). The instruction is not stored in the remembered trace
The async per-agent gate also works on event loop implementations that cannot be weakly referenced
Anthropic: an empty tool result is sent as "(no output)" because empty tool_result content is not reliably accepted
Remembered tool-call arguments are clipped to tool_result_chars like results, so a large write is not replayed whole
Anthropic: the text of a response is the join of its text blocks (a response that opens with a tool_use or thinking block no longer raises)