fix: implement runtime support for widened type hints in Agent init

- Add string preset handling in _init_autonomy() for autonomy='full_auto' etc.
- Add str/dict support in context_manager property for context='summarize' etc.
- Add dict-to-ApprovalConfig conversion for approval={'backend': ..., 'all_tools': True}
- Add string mode handling in learn parameter for learn='agentic' etc.
- Fix AUTONOMY_PRESETS to use 'level' field (not 'mode') per AutonomyConfig

Resolves type hint/implementation mismatches identified by code reviewers.
All new type hints now have proper runtime support.

Co-authored-by: Mervin Praison <[email protected]>

src/praisonai-agents/praisonaiagents/agent/agent.py

@@ -1076,6 +1076,18 @@ class Agent(ToolExecutionMixin, ChatHandlerMixin, SessionManagerMixin, ChatMixin
                 _learn_config = learn
             elif isinstance(learn, dict):
                 _learn_config = LearnConfig(**learn)
+            elif isinstance(learn, str):
+                # String mode: "disabled", "agentic", "propose"
+                from ..memory.learn.protocols import LearnMode
+                if learn == "disabled":
+                    _learn_config = None
+                elif learn == "agentic":
+                    _learn_config = LearnConfig(mode=LearnMode.AGENTIC)
+                elif learn == "propose":
+                    _learn_config = LearnConfig(mode=LearnMode.PROPOSE)
+                else:
+                    # Unknown string mode, disable learning
+                    _learn_config = None
             else:
                 _learn_config = learn  # Pass through
         elif _memory_config is not None and isinstance(_memory_config, MemoryConfig):
@@ -1651,6 +1663,12 @@ Your Goal: {self.goal}
             self._approval_backend = approval.backend
             self._approve_all_tools = approval.all_tools
             self._approval_timeout = approval.timeout  # None = indefinite, 0 = backend default
+        elif isinstance(approval, dict):
+            # Dict config: convert to ApprovalConfig
+            approval_config = ApprovalConfig(**approval)
+            self._approval_backend = approval_config.backend
+            self._approve_all_tools = approval_config.all_tools
+            self._approval_timeout = approval_config.timeout
         else:
             # Plain backend object — dangerous tools only, backend default timeout
             self._approval_backend = approval
@@ -1958,6 +1976,64 @@ Your Goal: {self.goal}
         elif hasattr(self._context_param, 'process'):
             # Already a ContextManager instance
             self._context_manager = self._context_param
+        elif isinstance(self._context_param, str):
+            # String preset: "sliding_window", "summarize", "truncate"
+            from ..config.presets import CONTEXT_PRESETS
+            preset_config = CONTEXT_PRESETS.get(self._context_param)
+            if preset_config is not None:
+                # Convert preset to ContextConfig, then to ManagerConfig
+                try:
+                    from ..context.models import ContextConfig as _ContextConfig
+                    context_config = _ContextConfig(**preset_config)
+                    manager_config = ManagerConfig(
+                        auto_compact=context_config.auto_compact,
+                        compact_threshold=context_config.compact_threshold,
+                        strategy=context_config.strategy,
+                        output_reserve=context_config.output_reserve,
+                        default_tool_output_max=context_config.tool_output_max,
+                        protected_tools=list(context_config.protected_tools),
+                        keep_recent_turns=context_config.keep_recent_turns,
+                        monitor_enabled=context_config.monitor.enabled if context_config.monitor else False,
+                    )
+                    self._context_manager = ContextManager(
+                        model=self.llm if isinstance(self.llm, str) else "gpt-4o-mini",
+                        config=manager_config,
+                        agent_name=self.name or "Agent",
+                        session_cache=self._session_dedup_cache,
+                        llm_summarize_fn=None,
+                    )
+                except Exception as e:
+                    logging.debug(f"Context preset conversion failed: {e}")
+                    self._context_manager = None
+            else:
+                # Unknown string preset, disable
+                self._context_manager = None
+        elif isinstance(self._context_param, dict):
+            # Dict config: convert to ContextConfig, then to ManagerConfig
+            try:
+                from ..context.models import ContextConfig as _ContextConfig
+                context_config = _ContextConfig(**self._context_param)
+                manager_config = ManagerConfig(
+                    auto_compact=context_config.auto_compact,
+                    compact_threshold=context_config.compact_threshold,
+                    strategy=context_config.strategy,
+                    output_reserve=context_config.output_reserve,
+                    default_tool_output_max=context_config.tool_output_max,
+                    protected_tools=list(context_config.protected_tools),
+                    keep_recent_turns=context_config.keep_recent_turns,
+                    monitor_enabled=context_config.monitor.enabled if context_config.monitor else False,
+                )
+                llm_summarize_enabled = self._context_param.get('llm_summarize', False)
+                self._context_manager = ContextManager(
+                    model=self.llm if isinstance(self.llm, str) else "gpt-4o-mini",
+                    config=manager_config,
+                    agent_name=self.name or "Agent",
+                    session_cache=self._session_dedup_cache,
+                    llm_summarize_fn=self._create_llm_summarize_fn() if llm_summarize_enabled else None,
+                )
+            except Exception as e:
+                logging.debug(f"Context dict conversion failed: {e}")
+                self._context_manager = None
         else:
             # Unknown type, disable
             self._context_manager = None
@@ -2174,6 +2250,25 @@ Summary:"""
             # Extract verification_hooks from AutonomyConfig if provided
             if autonomy.verification_hooks and not verification_hooks:
                 self._verification_hooks = autonomy.verification_hooks
+        elif isinstance(autonomy, str):
+            # String preset: "suggest", "auto_edit", "full_auto"
+            from ..config.presets import AUTONOMY_PRESETS
+            preset_config = AUTONOMY_PRESETS.get(autonomy)
+            if preset_config is not None:
+                config = AutonomyConfig.from_dict(preset_config)
+            else:
+                # Unknown string preset — disable autonomy
+                self.autonomy_enabled = False
+                self.autonomy_config = {}
+                self._autonomy_trigger = None
+                self._doom_loop_tracker = None
+                self._file_snapshot = None
+                self._snapshot_stack = []
+                self._redo_stack = []
+                self._autonomy_turn_tool_count = 0
+                self._consecutive_no_tool_turns = 0
+                self._doom_recovery_active = False
+                return
         else:
             self.autonomy_enabled = False
             self.autonomy_config = {}

src/praisonai-agents/praisonaiagents/config/presets.py

@@ -300,9 +300,9 @@ CONTEXT_PRESETS: Dict[str, Dict[str, Any]] = {
 # =============================================================================
 
 AUTONOMY_PRESETS: Dict[str, Dict[str, Any]] = {
-    "suggest": {"mode": "suggest"},
-    "auto_edit": {"mode": "auto_edit"},
-    "full_auto": {"mode": "full_auto"},
+    "suggest": {"level": "suggest"},
+    "auto_edit": {"level": "auto_edit"},
+    "full_auto": {"level": "full_auto"},
 }