2 Commits

Author	SHA1	Message	Date
hurui200320	91691750ed	fix(reactive): forward actor options block in ToolCallingLLMCaller._resolve_llm ... Port the options-block merging logic from SimpleLLMAgent._resolve_llm() (stream_router.py, added in PR #11225 / commit b3851693) to the parallel resolution path ToolCallingLLMCaller._resolve_llm() in tool_caller.py. Without this fix, running an actor with --skill would ignore the options block in the actor YAML, causing openai_api_base and openai_api_key to be silently dropped. The provider registry then fell back to OPENAI_API_KEY from the environment, routing requests to api.openai.com instead of the configured local llama-swap/llama.cpp backend (HTTP 401). Changes: - tool_caller.ToolCallingLLMCaller._resolve_llm: read actor_config.options; extract openai_api_key -> __api_key_sentinel; forward allowed keys (openai_api_base, timeout, top_p, frequency_penalty, presence_penalty); reject reserved keys (provider_type, model_id) and unknown keys with logger.warning, matching SimpleLLMAgent behaviour exactly. - features/actor_run_tool_calling.feature: add five BDD regression scenarios (section V, tagged @tdd_issue @tdd_issue_11243) covering api_base+key forwarding, allowed extra keys, reserved key rejection, unknown key rejection, and top-level precedence over options. - features/steps/actor_run_tool_calling_steps.py: add corresponding step definitions for all five scenarios. All nox quality gates pass (lint, typecheck, unit_tests 15822/0 fail, integration_tests 1999/0 fail, coverage_report 97%). ISSUES CLOSED: #11243	2026-05-27 12:14:04 -04:00
hurui200320	0c5724c2f6	feat(actor-run): wire ToolCallingRuntime into actor run for skill-based tool calling ... Implements the full tool-calling path for `agents actor run --skill` so that LLM actors can actually invoke tools through the ToolCallingRuntime loop when a skill is attached. Core changes: - reactive/tool_caller.py (new): ToolCallingLLMCaller implements the LLMCaller protocol; binds tool schemas via bind_tools(), threads SystemMessage+HumanMessage on first call and AIMessage+ToolMessages on subsequent calls, extracts tool calls from LangChain responses following the LangChainSessionCaller pattern. - reactive/tool_caller.py: bidirectional tool name encoding via uppercase sentinels (_encode_tool_name / _decode_tool_name) to make CleverAgents namespaced tool names ("builtin/file-read", "server:local/tool") compatible with Anthropic's tool name pattern ^[a-zA-Z0-9_-]{1,128}$. Uses _C_ for ":" and _S_ for "/" — uppercase sentinels are safe because valid CleverAgents tool names forbid uppercase letters. Encoding applied in _resolve_llm() before bind_tools(); decoding applied in invoke() when extracting tool calls from the LLM response. - reactive/tool_agent.py (new): ToolCallingAgent builds a per-run local ToolRegistry from resolved skill tool entries by looking up names in the shared builtin_registry; drives ToolCallingRuntime.run_tool_loop(); exposes last_result for tool_calls surfacing. - reactive/application.py: (ST-1) _make_agent_instance() now always merges skill tools instead of silently dropping them when actor has no base tools list; routes tools+llm→ToolCallingAgent, tools+non-llm→SimpleToolAgent, no-tools+llm→SimpleLLMAgent; (ST-4) _builtin_registry created at startup with register_file_tools/git/subplan; (ST-6) _tally_tool_calls() + last_run_tool_calls property. - reactive/graph_executor.py: (ST-5) ToolCallingAgent added to isinstance check in _invoke_agent() so context dict is forwarded for Jinja2 rendering. - cli/commands/actor_run.py: prints "Tool Calls: {n}" when > 0. Test fixes: - features/steps/actor_cli_run_steps.py: _make_app() sets last_run_tool_calls=0 to avoid MagicMock>int TypeError in Python 3.13. - features/steps/actor_run_signature_resolve_steps.py: same fix. - robot/helper_actor_run_signature.py: same fix. - features/reactive_application_coverage_boost.feature: updated scenario to verify new correct behavior (LLM+skills → ToolCallingAgent, not silently kept as SimpleLLMAgent). BDD coverage: 34 scenarios in features/actor_run_tool_calling.feature covering tool call success, multi-turn loop, no-skill regression, silent-drop fix, LLMCaller internals, _build_tool_registry edge cases, last_run_tool_calls tallying, tool name encoding/decoding, and LLM response decoding. ISSUES CLOSED: #11211	2026-05-18 06:05:54 +00:00