3 Commits

Author	SHA1	Message	Date
CoreRasurae	227e2feece	feat(agents): implement multi-turn tool-call loop and sandbox improvements ... Implements the complete LLM agent tool-calling pipeline — the tool-calling path was broken in multiple ways: tools from agent config were not passed to the LLM, tool execution was single-pass (the model could not see tool results or make follow-up calls), tool errors were discarded, and shell/ python_exec tools were never registered. Key changes: - Multi-turn tool-call loop: passes tools to the LLM via ainvoke(tools=...) and re-invokes after each batch of ToolResults, with a configurable round limit (tool_max_rounds config / TOOL_MAX_ROUNDS env var, default 20). - Tool schema module (llm_tools.py): normalize_tool_entry() converts string tool names and config dicts to OpenAI function-calling format with full parameter schemas and LLM-facing guidance (max_chars for file_read, sandbox builtins for python_exec, etc.). - file_read enhancements: directory listing with file sizes and type indicators, max_chars truncation to prevent context overflow, shell command detection with redirect to shell tool, file-not-found recovery hints with parent directory listing. - python_exec sandbox: stdout capture so print() produces visible output, NameError guidance directing LLM to file_read/file_write instead of using open(). - shell/python_exec tool registration in builtin_tools when allow_shell / exec_python is enabled. - create_subprocess_shell for shell commands (was create_subprocess_exec, which blocks pipes/redirections/chains). - Tool error propagation: ExecutionError/ConfigurationError details included in ToolMessages for LLM self-correction. - Stuck-model recovery: injects synthesizing prompt when model exhausts tool rounds without producing content. - LLM provider error details preserved in ExecutionError messages instead of generic "LLM processing failed". - Empty message filtering in _prepare_conversation_history() prevents whitespace-only messages from polluting downstream conversation history in multi-agent pipelines. Closes #59	2026-06-23 12:39:20 +01:00
hurui200320	ed9c4dc95d	fix(llmagent): do not close shared cached httpx clients in cleanup() ... LLMAgent.cleanup() previously iterated over hard-coded provider SDK client attributes (root_async_client, root_client, _async_client, _client) and called close() on each. Recent langchain-anthropic and langchain-openai versions cache their default httpx clients via module-level lru_cache functions. Closing those clients poisoned the cache: every subsequent ChatAnthropic/ChatOpenAI instance in the same process received the same closed httpx client and failed with a connection error. Fix: cleanup() now only releases the agent's own reference to the chat model (self._chat_model = None). The removed _KNOWN_CLIENT_ATTRS class variable has been deleted and ClassVar removed from the typing import. The concurrent-idempotency guarantee is preserved: the lock is still acquired before nulling _chat_model, so two concurrent cleanup() calls cannot both see a non-None model and attempt conflicting operations. The four provider SDK client-closing scenarios in credential_injection.feature and llm_missing_coverage.feature are removed as they tested the old (buggy) behaviour. Their step definitions are removed from credential_cleanup_steps.py (now only carries the resolve_class_ref patch step) and llm_missing_coverage_steps.py is updated with the corrected assertions. Six new regression BDD scenarios tagged @tdd_issue @tdd_issue_57 are added in features/llm_cleanup_shared_client.feature, covering all four provider SDK client attribute paths (Anthropic _async_client/_client, OpenAI root_async_client/root_client) and two end-to-end two-agent scenarios that prove a second agent can run successfully after the first is cleaned up. ISSUES CLOSED: #57	2026-06-17 17:19:44 +00:00
CoreRasurae	9753b31c7e	test: add coverage gap tests improving coverage from 81.4% to 96.90% ... Add 13 BDD scenarios covering previously uncovered code paths: - SAFE_BUILTINS validation (sandbox.py: 0% → 100%) - ConfigurationError re-raise path (config.py: 99.3% → 100%) - CLI hello/main functions (cli.py: 72.7% → 90.9%) - GraphState message truncation (state.py: 98.7% → 100%) - ProgressBarManager update/context rendering (progress.py: 0% → 87.7%) - MessageRouter regex/exact/contains routing (message_router.py: 0% → 59.4%) - RoutingAdapter parse_routing_command (routing_adapter.py) - DynamicRouterNode pattern-based routing (dynamic_router.py) - EnhancedTemplateRegistry unknown template type (enhanced_registry.py: 99.2%) - CompositeAgent null-graph error path (composite.py: 97.8% → 98.6%) Cover routing_adapter.py (17% → 100%): all GOTO/ROUTE patterns, create_routing_node, create_conditional_router, dynamic config conversion. Cover dynamic_router.py (21% → 87%): execute with empty/dict/string messages, extract_message with colon parsing, config creation, graph extension with edge generation. Cover message_router.py (59% → 78%): regex, exact, contains, prefix, suffix match types, invalid regex handling, non-string message, set_state. Exercise Node._prepare_conversation_history with invalid configs, _runtime error paths, _execute_message_router with rules, _execute_agent with current_message and metadata propagation, _execute_function with dynamic_router, and _execute_conditional with content_contains/content_not_contains/content_starts_with and custom condition types. Improves nodes.py from 71.3% to 72.5%. Exercise PureGraphConfig, PureLangGraph init with dict/config, RxPyLangGraphBridge registration/connection/lookup, ReactiveStreamRouter operator creation and condition functions, ReactiveConfigParser config/route/graph parsing, ToolAgent tool execution with JSON, space-separated, single, file_read, progress_bar invocations, and ReactiveCleverAgentsApp init/dispose/visualization.	2026-06-02 20:02:01 +01:00