agents

%% cognitive_workflow_orchestrator.erl
%% Advanced gen_statem workflow orchestration with cognitive capabilities
%% Handles complex multi-agent workflows with adaptive execution
-module(cognitive_workflow_orchestrator).
-behaviour(gen_statem).

-export([
    start_link/1,
    create_workflow/2,
    execute_workflow/2,
    pause_workflow/1,
    resume_workflow/1,
    abort_workflow/1,
    add_dynamic_step/3,
    branch_workflow/3,
    merge_workflows/2,
    adapt_execution_strategy/2,
    monitor_progress/1,
    handle_exception/2
]).

-export([init/1, callback_mode/0, terminate/3]).
-export([
    idle/3,
    planning/3,
    executing/3,
    monitoring/3,
    adapting/3,
    paused/3,
    error_handling/3,
    completing/3,
    reflecting/3
]).

-record(workflow_data, {
    workflow_id,
    workflow_spec,
    execution_plan,
    current_step = 1,
    step_results = #{},
    execution_context = #{},
    resource_allocations = #{},
    adaptive_parameters = #{},
    monitoring_data = #{},
    error_recovery_stack = [],
    branch_history = [],
    performance_metrics = #{},
    learning_data = #{},
    reflection_insights = []
}).

-record(workflow_step, {
    step_id,
    step_type, % sequential, parallel, conditional, loop, human_intervention
    agent_assignments = [],
    dependencies = [],
    resources_required = #{},
    success_criteria = #{},
    failure_handling = #{},
    timeout = 30000,
    retry_policy = #{},
    adaptive_weights = #{},
    monitoring_hooks = []
}).

-record(execution_context, {
    environment_state = #{},
    available_agents = [],
    resource_pool = #{},
    external_dependencies = [],
    constraints = #{},
    optimization_goals = [],
    adaptation_history = [],
    cognitive_state = #{},
    meta_reasoning_active = false
}).

%% Public API

start_link(WorkflowConfig) ->
    gen_statem:start_link(?MODULE, WorkflowConfig, []).

create_workflow(WorkflowSpec, InitialContext) ->
    gen_statem:start_link(?MODULE, {WorkflowSpec, InitialContext}, []).

execute_workflow(WorkflowPid, ExecutionParams) ->
    gen_statem:call(WorkflowPid, {execute, ExecutionParams}).

pause_workflow(WorkflowPid) ->
    gen_statem:call(WorkflowPid, pause).

resume_workflow(WorkflowPid) ->
    gen_statem:call(WorkflowPid, resume).

abort_workflow(WorkflowPid) ->
    gen_statem:call(WorkflowPid, abort).

add_dynamic_step(WorkflowPid, StepSpec, InsertionPoint) ->
    gen_statem:call(WorkflowPid, {add_step, StepSpec, InsertionPoint}).

branch_workflow(WorkflowPid, BranchCondition, BranchSpec) ->
    gen_statem:call(WorkflowPid, {branch, BranchCondition, BranchSpec}).

merge_workflows(WorkflowPid1, WorkflowPid2) ->
    gen_statem:call(WorkflowPid1, {merge, WorkflowPid2}).

adapt_execution_strategy(WorkflowPid, AdaptationRules) ->
    gen_statem:call(WorkflowPid, {adapt, AdaptationRules}).

monitor_progress(WorkflowPid) ->
    gen_statem:call(WorkflowPid, get_progress).

handle_exception(WorkflowPid, Exception) ->
    gen_statem:call(WorkflowPid, {exception, Exception}).

%% Gen_statem callbacks

init({WorkflowSpec, InitialContext}) ->
    WorkflowId = generate_workflow_id(),
    
    Data = #workflow_data{
        workflow_id = WorkflowId,
        workflow_spec = WorkflowSpec,
        execution_context = create_execution_context(InitialContext),
        adaptive_parameters = initialize_adaptive_parameters(),
        monitoring_data = initialize_monitoring(),
        performance_metrics = initialize_performance_metrics()
    },
    
    {ok, idle, Data}.

callback_mode() ->
    state_functions.

%% State: idle - Workflow created but not started
idle({call, From}, {execute, Params}, Data) ->
    % Transition to planning phase
    NewData = Data#workflow_data{execution_context = merge_execution_params(Params, Data)},
    {next_state, planning, NewData, [{reply, From, {ok, planning}}]};

idle({call, From}, get_progress, Data) ->
    Progress = #{
        state => idle,
        workflow_id => Data#workflow_data.workflow_id,
        progress => 0.0,
        steps_completed => 0,
        total_steps => count_workflow_steps(Data#workflow_data.workflow_spec)
    },
    {keep_state_and_data, [{reply, From, Progress}]};

idle(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, idle).

%% State: planning - Analyzing workflow and creating execution plan
planning(enter, _OldState, Data) ->
    % Analyze workflow complexity and create execution plan
    spawn(fun() -> 
        Plan = create_execution_plan(Data#workflow_data.workflow_spec, Data#workflow_data.execution_context),
        gen_statem:cast(self(), {plan_ready, Plan})
    end),
    {keep_state_and_data, [{state_timeout, 10000, planning_timeout}]};

planning(cast, {plan_ready, Plan}, Data) ->
    % Execution plan is ready, validate and proceed
    case validate_execution_plan(Plan, Data#workflow_data.execution_context) of
        {ok, ValidatedPlan} ->
            NewData = Data#workflow_data{execution_plan = ValidatedPlan},
            {next_state, executing, NewData};
        {error, ValidationError} ->
            % Re-plan with adjusted parameters
            AdaptedSpec = adapt_workflow_spec(Data#workflow_data.workflow_spec, ValidationError),
            NewData = Data#workflow_data{workflow_spec = AdaptedSpec},
            {repeat_state, NewData}
    end;

planning(state_timeout, planning_timeout, Data) ->
    % Planning took too long, use simplified execution plan
    SimplifiedPlan = create_simplified_plan(Data#workflow_data.workflow_spec),
    NewData = Data#workflow_data{execution_plan = SimplifiedPlan},
    {next_state, executing, NewData};

planning({call, From}, pause, Data) ->
    {next_state, paused, Data, [{reply, From, {ok, paused}}]};

planning(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, planning).

%% State: executing - Active execution of workflow steps
executing(enter, _OldState, Data) ->
    % Start execution monitoring and begin first step
    start_execution_monitoring(Data),
    execute_next_step(Data),
    {keep_state_and_data, []};

executing(cast, {step_completed, StepId, Result}, Data) ->
    % Process step completion
    UpdatedData = record_step_result(StepId, Result, Data),
    
    case determine_next_action(UpdatedData) of
        {continue, NextStep} ->
            execute_step(NextStep, UpdatedData),
            {keep_state, UpdatedData};
        {branch, BranchSpec} ->
            BranchedData = execute_workflow_branch(BranchSpec, UpdatedData),
            {keep_state, BranchedData};
        {adapt, AdaptationReason} ->
            {next_state, adapting, UpdatedData#workflow_data{
                adaptive_parameters = maps:put(reason, AdaptationReason, UpdatedData#workflow_data.adaptive_parameters)
            }};
        {complete} ->
            {next_state, completing, UpdatedData};
        {error, ErrorReason} ->
            ErrorData = UpdatedData#workflow_data{
                error_recovery_stack = [ErrorReason | UpdatedData#workflow_data.error_recovery_stack]
            },
            {next_state, error_handling, ErrorData}
    end;

executing(cast, {step_failed, StepId, Reason}, Data) ->
    % Handle step failure
    FailureData = record_step_failure(StepId, Reason, Data),
    
    case should_retry_step(StepId, Reason, FailureData) of
        {retry, RetryParams} ->
            retry_step_with_params(StepId, RetryParams, FailureData),
            {keep_state, FailureData};
        {skip, SkipReason} ->
            SkippedData = skip_step(StepId, SkipReason, FailureData),
            {keep_state, SkippedData};
        {abort, AbortReason} ->
            AbortData = FailureData#workflow_data{
                error_recovery_stack = [AbortReason | FailureData#workflow_data.error_recovery_stack]
            },
            {next_state, error_handling, AbortData}
    end;

executing({call, From}, {add_step, StepSpec, InsertionPoint}, Data) ->
    % Dynamically add step to workflow
    case insert_dynamic_step(StepSpec, InsertionPoint, Data) of
        {ok, UpdatedData} ->
            {keep_state, UpdatedData, [{reply, From, {ok, step_added}}]};
        {error, Reason} ->
            {keep_state_and_data, [{reply, From, {error, Reason}}]}
    end;

executing({call, From}, {branch, Condition, BranchSpec}, Data) ->
    % Create workflow branch
    case evaluate_branch_condition(Condition, Data) of
        true ->
            BranchedData = create_workflow_branch(BranchSpec, Data),
            {keep_state, BranchedData, [{reply, From, {ok, branch_created}}]};
        false ->
            {keep_state_and_data, [{reply, From, {ok, branch_skipped}}]}
    end;

executing({call, From}, pause, Data) ->
    pause_current_execution(Data),
    {next_state, paused, Data, [{reply, From, {ok, paused}}]};

executing(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, executing).

%% State: monitoring - Intensive monitoring and analysis phase
monitoring(enter, _OldState, Data) ->
    % Enhanced monitoring activated
    start_enhanced_monitoring(Data),
    {keep_state_and_data, [{state_timeout, 5000, monitoring_complete}]};

monitoring(cast, {monitoring_alert, AlertType, AlertData}, Data) ->
    case AlertType of
        performance_degradation ->
            % Performance is degrading, consider adaptation
            {next_state, adapting, add_monitoring_insight(AlertData, Data)};
        resource_exhaustion ->
            % Resources running low, optimize allocation
            OptimizedData = optimize_resource_allocation(AlertData, Data),
            {keep_state, OptimizedData};
        external_change ->
            % External environment changed, reassess
            {next_state, adapting, add_environmental_change(AlertData, Data)};
        _ ->
            {keep_state, record_monitoring_event(AlertType, AlertData, Data)}
    end;

monitoring(state_timeout, monitoring_complete, Data) ->
    % Return to execution with monitoring insights
    InsightfulData = consolidate_monitoring_insights(Data),
    {next_state, executing, InsightfulData};

monitoring(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, monitoring).

%% State: adapting - Adaptive modification of execution strategy
adapting(enter, _OldState, Data) ->
    % Analyze need for adaptation
    AdaptationAnalysis = analyze_adaptation_need(Data),
    execute_adaptation_strategy(AdaptationAnalysis, Data),
    {keep_state_and_data, [{state_timeout, 8000, adaptation_complete}]};

adapting(cast, {adaptation_result, _AdaptationType, Result}, Data) ->
    case Result of
        {success, AdaptedComponents} ->
            % Adaptation successful, update workflow
            AdaptedData = apply_adaptations(AdaptedComponents, Data),
            {next_state, executing, AdaptedData};
        {partial_success, PartialComponents, Issues} ->
            % Partial adaptation, handle issues
            PartialData = apply_partial_adaptations(PartialComponents, Issues, Data),
            {next_state, executing, PartialData};
        {failure, FailureReason} ->
            % Adaptation failed, fall back to original strategy
            FallbackData = revert_to_fallback_strategy(FailureReason, Data),
            {next_state, executing, FallbackData}
    end;

adapting(state_timeout, adaptation_complete, Data) ->
    % Adaptation time limit reached, proceed with current state
    {next_state, executing, Data};

adapting(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, adapting).

%% State: paused - Workflow execution paused
paused({call, From}, resume, Data) ->
    resume_workflow_execution(Data),
    {next_state, executing, Data, [{reply, From, {ok, resumed}}]};

paused({call, From}, abort, Data) ->
    cleanup_paused_workflow(Data),
    {stop_and_reply, normal, [{reply, From, {ok, aborted}}], Data};

paused({call, From}, get_progress, Data) ->
    Progress = calculate_current_progress(Data),
    PausedProgress = Progress#{state => paused},
    {keep_state_and_data, [{reply, From, PausedProgress}]};

paused(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, paused).

%% State: error_handling - Managing errors and recovery
error_handling(enter, _OldState, Data) ->
    % Analyze error and determine recovery strategy
    ErrorAnalysis = analyze_workflow_errors(Data#workflow_data.error_recovery_stack),
    RecoveryStrategy = determine_recovery_strategy(ErrorAnalysis, Data),
    execute_error_recovery(RecoveryStrategy, Data),
    {keep_state_and_data, [{state_timeout, 15000, recovery_timeout}]};

error_handling(cast, {recovery_result, _RecoveryType, Result}, Data) ->
    case Result of
        {recovered, RecoveredState} ->
            % Error recovered, resume execution
            RecoveredData = apply_recovery_state(RecoveredState, Data),
            {next_state, executing, RecoveredData};
        {partial_recovery, PartialState} ->
            % Partial recovery, continue with degraded functionality
            PartialData = apply_partial_recovery(PartialState, Data),
            {next_state, executing, PartialData};
        {recovery_failed, FailureReason} ->
            % Recovery failed, escalate or abort
            case should_escalate_error(FailureReason, Data) of
                {escalate, EscalationTarget} ->
                    escalate_error_handling(EscalationTarget, FailureReason, Data),
                    {keep_state_and_data, []};
                {abort, AbortReason} ->
                    {stop, {error, AbortReason}, Data}
            end
    end;

error_handling(state_timeout, recovery_timeout, Data) ->
    % Recovery timeout, escalate to human intervention
    {stop, {error, recovery_timeout}, Data};

error_handling(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, error_handling).

%% State: completing - Finalizing workflow execution
completing(enter, _OldState, Data) ->
    % Finalize workflow execution
    finalize_workflow_execution(Data),
    {keep_state_and_data, [{state_timeout, 5000, completion_timeout}]};

completing(cast, {finalization_complete, FinalResults}, Data) ->
    % Workflow completed successfully
    CompletedData = Data#workflow_data{
        step_results = maps:put(final_results, FinalResults, Data#workflow_data.step_results)
    },
    {next_state, reflecting, CompletedData};

completing(state_timeout, completion_timeout, Data) ->
    % Force completion
    {next_state, reflecting, Data};

completing(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, completing).

%% State: reflecting - Post-execution reflection and learning
reflecting(enter, _OldState, Data) ->
    % Perform workflow reflection and learning
    ReflectionAnalysis = perform_workflow_reflection(Data),
    LearningInsights = extract_learning_insights(ReflectionAnalysis, Data),
    store_workflow_learning(LearningInsights),
    {keep_state_and_data, [{state_timeout, 3000, reflection_complete}]};

reflecting(state_timeout, reflection_complete, Data) ->
    % Reflection complete, workflow finished
    {stop, normal, Data};

reflecting(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data, reflecting).

%% Common event handling
handle_common_events({call, From}, get_progress, Data, CurrentState) ->
    Progress = calculate_current_progress(Data),
    StateProgress = Progress#{state => CurrentState},
    {keep_state_and_data, [{reply, From, StateProgress}]};

handle_common_events({call, From}, abort, Data, _CurrentState) ->
    cleanup_workflow_resources(Data),
    {stop_and_reply, normal, [{reply, From, {ok, aborted}}], Data};

handle_common_events(info, {monitoring_data, MonitoringUpdate}, Data, _CurrentState) ->
    UpdatedData = update_monitoring_data(MonitoringUpdate, Data),
    {keep_state, UpdatedData};

handle_common_events(_EventType, _Event, _Data, _CurrentState) ->
    keep_state_and_data.

terminate(_Reason, _StateName, Data) ->
    cleanup_workflow_resources(Data),
    ok.

%% Internal Functions

generate_workflow_id() ->
    list_to_binary([
        "workflow_",
        atom_to_list(node()),
        "_",
        integer_to_list(erlang:system_time(microsecond))
    ]).

create_execution_context(InitialContext) ->
    #execution_context{
        environment_state = maps:get(environment, InitialContext, #{}),
        available_agents = maps:get(agents, InitialContext, []),
        resource_pool = maps:get(resources, InitialContext, #{}),
        external_dependencies = maps:get(dependencies, InitialContext, []),
        constraints = maps:get(constraints, InitialContext, #{}),
        optimization_goals = maps:get(goals, InitialContext, []),
        cognitive_state = initialize_cognitive_state()
    }.

initialize_cognitive_state() ->
    #{
        attention_focus => [],
        working_memory => #{},
        long_term_memory => #{},
        metacognitive_awareness => 0.5,
        cognitive_load => 0.0,
        adaptation_threshold => 0.7,
        learning_rate => 0.1
    }.

create_execution_plan(WorkflowSpec, ExecutionContext) ->
    % Analyze workflow complexity
    ComplexityAnalysis = analyze_workflow_complexity(WorkflowSpec),
    
    % Optimize step ordering
    OptimizedSteps = optimize_step_ordering(WorkflowSpec, ExecutionContext),
    
    % Allocate resources
    ResourceAllocation = allocate_workflow_resources(OptimizedSteps, ExecutionContext),
    
    % Create adaptive parameters
    AdaptiveParams = create_adaptive_parameters(ComplexityAnalysis),
    
    #{
        steps => OptimizedSteps,
        complexity => ComplexityAnalysis,
        resources => ResourceAllocation,
        adaptive_params => AdaptiveParams,
        estimated_duration => estimate_execution_duration(OptimizedSteps),
        risk_assessment => assess_execution_risks(OptimizedSteps, ExecutionContext)
    }.

execute_next_step(Data) ->
    CurrentStep = Data#workflow_data.current_step,
    ExecutionPlan = Data#workflow_data.execution_plan,
    Steps = maps:get(steps, ExecutionPlan),
    
    case maps:get(CurrentStep, Steps, undefined) of
        undefined ->
            % No more steps, workflow complete
            gen_statem:cast(self(), workflow_complete);
        Step ->
            execute_step(Step, Data)
    end.

execute_step(Step, Data) ->
    StepId = Step#workflow_step.step_id,
    
    % Pre-execution validation
    case validate_step_preconditions(Step, Data) of
        {ok, ValidatedStep} ->
            % Execute step based on type
            case Step#workflow_step.step_type of
                sequential ->
                    execute_sequential_step(ValidatedStep, Data);
                parallel ->
                    execute_parallel_step(ValidatedStep, Data);
                conditional ->
                    execute_conditional_step(ValidatedStep, Data);
                loop ->
                    execute_loop_step(ValidatedStep, Data);
                human_intervention ->
                    execute_human_intervention_step(ValidatedStep, Data)
            end;
        {error, ValidationError} ->
            gen_statem:cast(self(), {step_failed, StepId, ValidationError})
    end.

determine_next_action(Data) ->
    % Analyze current state and determine next action
    ProgressAnalysis = analyze_execution_progress(Data),
    PerformanceMetrics = Data#workflow_data.performance_metrics,
    AdaptiveParams = Data#workflow_data.adaptive_parameters,
    
    % Check if adaptation is needed
    case needs_adaptation(ProgressAnalysis, PerformanceMetrics, AdaptiveParams) of
        {yes, AdaptationReason} ->
            {adapt, AdaptationReason};
        no ->
            % Check if workflow is complete
            case is_workflow_complete(Data) of
                true ->
                    {complete};
                false ->
                    % Check if branching is needed
                    case should_branch_workflow(Data) of
                        {yes, BranchSpec} ->
                            {branch, BranchSpec};
                        no ->
                            % Continue to next step
                            NextStep = get_next_step(Data),
                            {continue, NextStep}
                    end
            end
    end.

%% Placeholder implementations for complex workflow operations
merge_execution_params(_Params, Data) -> Data#workflow_data.execution_context.
count_workflow_steps(_WorkflowSpec) -> 10.
validate_execution_plan(_Plan, _Context) -> {ok, validated_plan}.
adapt_workflow_spec(Spec, _Error) -> Spec.
create_simplified_plan(_WorkflowSpec) -> simplified_plan.
start_execution_monitoring(_Data) -> ok.
record_step_result(_StepId, _Result, Data) -> Data.
record_step_failure(_StepId, _Reason, Data) -> Data.
should_retry_step(_StepId, _Reason, _Data) -> {skip, no_retry}.
skip_step(_StepId, _Reason, Data) -> Data.
retry_step_with_params(_StepId, _Params, _Data) -> ok.
insert_dynamic_step(_StepSpec, _InsertionPoint, _Data) -> {error, not_implemented}.
evaluate_branch_condition(_Condition, _Data) -> false.
create_workflow_branch(_BranchSpec, Data) -> Data.
pause_current_execution(_Data) -> ok.
start_enhanced_monitoring(_Data) -> ok.
add_monitoring_insight(_AlertData, Data) -> Data.
optimize_resource_allocation(_AlertData, Data) -> Data.
add_environmental_change(_AlertData, Data) -> Data.
record_monitoring_event(_Type, _Data, WorkflowData) -> WorkflowData.
consolidate_monitoring_insights(Data) -> Data.
analyze_adaptation_need(_Data) -> adaptation_analysis.
execute_adaptation_strategy(_Analysis, _Data) -> ok.
apply_adaptations(_Components, Data) -> Data.
apply_partial_adaptations(_Components, _Issues, Data) -> Data.
revert_to_fallback_strategy(_Reason, Data) -> Data.
resume_workflow_execution(_Data) -> ok.
cleanup_paused_workflow(_Data) -> ok.
calculate_current_progress(_Data) -> #{progress => 0.5}.
analyze_workflow_errors(_ErrorStack) -> error_analysis.
determine_recovery_strategy(_Analysis, _Data) -> recovery_strategy.
execute_error_recovery(_Strategy, _Data) -> ok.
apply_recovery_state(_State, Data) -> Data.
apply_partial_recovery(_State, Data) -> Data.
should_escalate_error(_Reason, _Data) -> {abort, failed_recovery}.
escalate_error_handling(_Target, _Reason, _Data) -> ok.
finalize_workflow_execution(_Data) -> ok.
perform_workflow_reflection(_Data) -> reflection_analysis.
extract_learning_insights(_Analysis, _Data) -> learning_insights.
store_workflow_learning(_Insights) -> ok.
cleanup_workflow_resources(_Data) -> ok.
update_monitoring_data(_Update, Data) -> Data.
analyze_workflow_complexity(_Spec) -> #{complexity => medium}.
optimize_step_ordering(Spec, _Context) -> Spec.
allocate_workflow_resources(_Steps, _Context) -> #{}.
create_adaptive_parameters(_Analysis) -> #{}.
estimate_execution_duration(_Steps) -> 30000.
assess_execution_risks(_Steps, _Context) -> #{risk_level => low}.
validate_step_preconditions(Step, _Data) -> {ok, Step}.
execute_sequential_step(_Step, _Data) -> ok.
execute_parallel_step(_Step, _Data) -> ok.
execute_conditional_step(_Step, _Data) -> ok.
execute_loop_step(_Step, _Data) -> ok.
execute_human_intervention_step(_Step, _Data) -> ok.
execute_workflow_branch(_BranchSpec, Data) -> Data.
analyze_execution_progress(_Data) -> progress_analysis.
needs_adaptation(_Progress, _Metrics, _Params) -> no.
is_workflow_complete(_Data) -> false.
should_branch_workflow(_Data) -> no.
get_next_step(_Data) -> #workflow_step{step_id = next_step}.
initialize_adaptive_parameters() -> #{}.
initialize_monitoring() -> #{}.
initialize_performance_metrics() -> #{}.