reasoning

type DynamicPlanner struct {
	// contains filtered or unexported fields
}

type DynamicPlannerConfig struct {
	MaxBacktracks       int           // Maximum backtrack attempts
	MaxPlanDepth        int           // Maximum plan depth
	ConfidenceThreshold float64       // Minimum confidence to proceed
	Timeout             time.Duration // Overall timeout
	EnableParallel      bool          // Enable parallel path exploration
	MaxParallelPaths    int           // Maximum parallel paths to explore
	Model               string        // LLM model to use for reasoning steps
}

type ExecutionPlan struct {
	Goal           string          `json:"goal"`
	Steps          []ExecutionStep `json:"steps"`
	CurrentStep    int             `json:"current_step"`
	CompletedSteps []string        `json:"completed_steps"`
	Status         string          `json:"status"` // planning, executing, replanning, completed, failed
}

type ExecutionStep struct {
	ID          string `json:"id"`
	Description string `json:"description"`
	Tool        string `json:"tool,omitempty"`
	Arguments   string `json:"arguments,omitempty"`
	Status      string `json:"status"` // pending, running, completed, failed, skipped
	Result      string `json:"result,omitempty"`
	Error       string `json:"error,omitempty"`
}

type IterativeDeepening struct {
	// contains filtered or unexported fields
}

type IterativeDeepeningConfig struct {
	Breadth         int           // Number of parallel search queries per level
	MaxDepth        int           // Maximum recursion depth for exploration
	ResultsPerQuery int           // Maximum results to analyze per query
	MinConfidence   float64       // Minimum confidence to continue deepening (0-1)
	Timeout         time.Duration // Overall timeout for the entire research process
	ParallelSearch  bool          // Whether to execute searches in parallel
	SynthesisModel  string        // Model to use for final synthesis (empty = default)
}

type MemoryEntry struct {
	Task       string      `json:"task"`
	Reflection *Reflection `json:"reflection"`
}

type NodeStatus string

type PatternRegistry struct {
	// contains filtered or unexported fields
}

type PlanAndExecute struct {
	// contains filtered or unexported fields
}

type PlanExecuteConfig struct {
	MaxPlanSteps      int           // Maximum steps in initial plan
	MaxReplanAttempts int           // Maximum replanning attempts on failure
	Timeout           time.Duration // Overall timeout
	AdaptivePlanning  bool          // Allow plan modification during execution
	Model             string        // LLM model to use for reasoning steps
}

type PlanNode struct {
	ID           string      `json:"id"`
	ParentID     string      `json:"parent_id,omitempty"`
	Action       string      `json:"action"`
	Description  string      `json:"description"`
	Status       NodeStatus  `json:"status"`
	Result       string      `json:"result,omitempty"`
	Error        string      `json:"error,omitempty"`
	Confidence   float64     `json:"confidence"`
	Children     []*PlanNode `json:"children,omitempty"`
	Alternatives []*PlanNode `json:"alternatives,omitempty"` // Alternative paths if this fails
	CreatedAt    time.Time   `json:"created_at"`
	CompletedAt  *time.Time  `json:"completed_at,omitempty"`
}

type PlanStep struct {
	ID           string   `json:"id"`           // e.g., #E1, #E2
	Tool         string   `json:"tool"`         // Tool name to call
	Arguments    string   `json:"arguments"`    // Arguments (may reference previous steps like #E1)
	Dependencies []string `json:"dependencies"` // IDs of steps this depends on
	Reasoning    string   `json:"reasoning"`    // Why this step is needed
}

type ReWOO struct {
	// contains filtered or unexported fields
}

type ReWOOConfig struct {
	MaxPlanSteps    int           // Maximum steps in the plan
	Timeout         time.Duration // Overall timeout
	ParallelWorkers int           // Number of parallel workers for independent steps
	Model           string        // LLM model to use for reasoning steps
}

type ReasoningPattern interface {
	// 执行运行推理模式并返回最终结果.
	Execute(ctx context.Context, task string) (*ReasoningResult, error)
	// 名称返回图案名称 。
	Name() string
}

type ReasoningResult struct {
	Pattern      string          `json:"pattern"`
	Task         string          `json:"task"`
	FinalAnswer  string          `json:"final_answer"`
	Confidence   float64         `json:"confidence,omitempty"`
	Steps        []ReasoningStep `json:"steps"`
	TotalTokens  int             `json:"total_tokens"`
	TotalLatency time.Duration   `json:"total_latency"`
	Metadata     map[string]any  `json:"metadata,omitempty"`
}

type ReasoningStep struct {
	StepID     string          `json:"step_id"`
	Type       string          `json:"type"` // thought, action, observation, evaluation, backtrack
	Content    string          `json:"content"`
	Score      float64         `json:"score,omitempty"`
	Children   []ReasoningStep `json:"children,omitempty"`
	Duration   time.Duration   `json:"duration"`
	TokensUsed int             `json:"tokens_used,omitempty"`
}

type Reflection struct {
	Analysis     string   `json:"analysis"`
	Mistakes     []string `json:"mistakes"`
	NextStrategy string   `json:"next_strategy"`
}

type ReflexionConfig struct {
	MaxTrials        int           `json:"max_trials"`
	SuccessThreshold float64       `json:"success_threshold"`
	Timeout          time.Duration `json:"timeout"`
	EnableMemory     bool          `json:"enable_memory"`
	Model            string        `json:"model,omitempty"`
}

type ReflexionExecutor struct {
	// contains filtered or unexported fields
}

type ReflexionMemory struct {
	// contains filtered or unexported fields
}

type TrajectoryCollector struct {
	// contains filtered or unexported fields
}

type TrajectoryEvaluator interface {
	Evaluate(ctx context.Context, record *TrajectoryRecord) (float64, error)
}

type TrajectoryRecord struct {
	ID          string           `json:"id"`
	AgentID     string           `json:"agent_id"`
	Pattern     string           `json:"pattern"`
	Task        string           `json:"task"`
	Steps       []TrajectoryStep `json:"steps"`
	FinalAnswer string           `json:"final_answer"`
	Quality     float64          `json:"quality,omitempty"`
	TotalTokens int              `json:"total_tokens"`
	Duration    time.Duration    `json:"duration"`
	CreatedAt   time.Time        `json:"created_at"`
	Metadata    map[string]any   `json:"metadata,omitempty"`
}

type TrajectoryStep struct {
	Index      int            `json:"index"`
	Type       string         `json:"type"` // thought, action, observation, reflection, tool_call
	Content    string         `json:"content"`
	ToolName   string         `json:"tool_name,omitempty"`
	ToolArgs   map[string]any `json:"tool_args,omitempty"`
	ToolResult string         `json:"tool_result,omitempty"`
	TokensUsed int            `json:"tokens_used,omitempty"`
	Duration   time.Duration  `json:"duration"`
	Timestamp  time.Time      `json:"timestamp"`
}

type TrajectoryStepOption func(*TrajectoryStep)

type TrajectoryStore interface {
	Save(ctx context.Context, record *TrajectoryRecord) error
	Load(ctx context.Context, id string) (*TrajectoryRecord, error)
	ListByAgent(ctx context.Context, agentID string, limit int) ([]*TrajectoryRecord, error)
}

type TreeOfThought struct {
	// contains filtered or unexported fields
}

type TreeOfThoughtConfig struct {
	BranchingFactor int           // Number of thoughts to generate at each step
	MaxDepth        int           // Maximum depth of the thought tree
	BeamWidth       int           // Number of best paths to keep (beam search)
	EvaluationMode  string        // "self" (LLM self-eval) or "vote" (majority voting)
	PruneThreshold  float64       // Minimum score to keep a branch (0-1)
	Timeout         time.Duration // Overall timeout
	ParallelEval    bool          // Evaluate branches in parallel
	Model           string        // LLM model for thought generation
	EvalModel       string        // LLM model for evaluation (can be cheaper)
}

type Trial struct {
	Number     int         `json:"number"`
	Action     string      `json:"action"`
	Result     string      `json:"result"`
	Score      float64     `json:"score"`
	Reflection *Reflection `json:"reflection,omitempty"`
}