agent

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

type AgentConfig struct {
	ToolsFile      string // Path to the YAML configuration file defining available tools
	UserPrompt     string // Initial user prompt to send to the LLM
	Once           bool   // Whether to run in one-shot mode (exit after first response)
	Version        string // Version information for the agent
	MCPShellBinary string // Path to mcpshell binary (for spawning MCP server subprocess)
	ModelConfig           // Embedded model configuration (Model, APIKey, APIURL, Prompts)

	// RAG configuration
	RAGSources []string                   // Names of RAG sources to use (from config file)
	RAGConfig  map[string]RAGSourceConfig // RAG source definitions (from config file)
}

type AgentConfigFile struct {
	Models []ModelConfig `yaml:"models"` // Legacy: flat list of models

	// Role-based configuration for multi-agent system
	Orchestrator *ModelConfig `yaml:"orchestrator,omitempty"` // Root agent that plans and orchestrates
	ToolRunner   *ModelConfig `yaml:"tool-runner,omitempty"`  // Sub-agent that executes tools

	// RAG configuration
	RAG map[string]RAGSourceConfig `yaml:"rag,omitempty"` // Named RAG knowledge sources
}

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

type Config struct {
	Agent AgentConfigFile `yaml:"agent"`

	// Runtime fields (not from YAML)
	ToolsFile      string   // Path to tools configuration file
	RAGSources     []string // Names of RAG sources to use
	MCPShellBinary string   // Path to mcpshell binary (for spawning MCP server subprocess)
}

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

type ModelConfig struct {
	Model   string               `yaml:"model"`
	Class   string               `yaml:"class,omitempty"`   // Class of the model, e.g., "ollama", "openai", etc.
	Name    string               `yaml:"name,omitempty"`    // Name of the model, optional
	Default bool                 `yaml:"default,omitempty"` // Whether this is the default model
	APIKey  string               `yaml:"api-key,omitempty"` // API key, optional
	APIURL  string               `yaml:"api-url,omitempty"` // API URL, optional
	Prompts common.PromptsConfig `yaml:"prompts,omitempty"` // Prompts configuration, optional
}

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

type ModelProvider interface {
	// InitializeClient creates and configures the client for this model provider
	InitializeClient(config ModelConfig, logger *common.Logger) (*openai.Client, error)

	// ValidateConfig validates the configuration for this model provider
	ValidateConfig(config ModelConfig, logger *common.Logger) error

	// GetProviderName returns the human-readable name of the provider
	GetProviderName() string
}

type OllamaProvider struct{}

type OpenAIProvider struct{}

type RAGChunkingConfig struct {
	Size                  int  `yaml:"size,omitempty"`
	Overlap               int  `yaml:"overlap,omitempty"`
	RespectWordBoundaries bool `yaml:"respect_word_boundaries,omitempty"`
}

type RAGFusionConfig struct {
	Strategy string             `yaml:"strategy,omitempty"` // Fusion strategy: "rrf", "weighted", "max"
	K        int                `yaml:"k,omitempty"`        // RRF parameter k (default: 60)
	Weights  map[string]float64 `yaml:"weights,omitempty"`  // Strategy weights for weighted fusion
}

type RAGResultsConfig struct {
	Limit             int              `yaml:"limit,omitempty"`               // Maximum number of results to return
	Fusion            *RAGFusionConfig `yaml:"fusion,omitempty"`              // How to combine results from multiple strategies
	Deduplicate       bool             `yaml:"deduplicate,omitempty"`         // Remove duplicate documents
	IncludeScore      bool             `yaml:"include_score,omitempty"`       // Include relevance scores
	ReturnFullContent bool             `yaml:"return_full_content,omitempty"` // Return full document content
}

type RAGSourceConfig struct {
	Description string              `yaml:"description"`
	Docs        []string            `yaml:"docs,omitempty"`       // Shared documents across all strategies
	Strategies  []RAGStrategyConfig `yaml:"strategies,omitempty"` // Array of strategy configurations
	Results     *RAGResultsConfig   `yaml:"results,omitempty"`
}

type RAGStrategyConfig struct {
	Type     string            `yaml:"type"`               // Strategy type: "chunked-embeddings", "bm25"
	Docs     []string          `yaml:"docs,omitempty"`     // Strategy-specific documents
	Database string            `yaml:"database,omitempty"` // Database path for this strategy
	Chunking RAGChunkingConfig `yaml:"chunking,omitempty"` // Chunking configuration
	Limit    int               `yaml:"limit,omitempty"`    // Max results from this strategy

	// Strategy-specific parameters (e.g., model, threshold, vector_dimensions for chunked-embeddings)
	Model            string  `yaml:"model,omitempty"`
	Threshold        float64 `yaml:"threshold,omitempty"`
	VectorDimensions int     `yaml:"vector_dimensions,omitempty"`
	SimilarityMetric string  `yaml:"similarity_metric,omitempty"`
	K1               float64 `yaml:"k1,omitempty"` // BM25 parameter
	B                float64 `yaml:"b,omitempty"`  // BM25 parameter
}