schema

package
v0.0.13 Latest Latest
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 Go to latest Published: Jun 19, 2023 License: MIT Imports: 3 Imported by: 6

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Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func ChatMessageToMap added in v0.0.12 

func ChatMessageToMap(cm ChatMessage) map[string]string

Types

type AIChatMessage 

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

func NewAIChatMessage 

func NewAIChatMessage(text string) *AIChatMessage

func (AIChatMessage) Text 

func (m AIChatMessage) Text() string

func (AIChatMessage) Type 

func (m AIChatMessage) Type() ChatMessageType

type Agent 

type Agent interface {
	Plan(ctx context.Context, intermediateSteps []AgentStep, inputs map[string]string) ([]AgentAction, *AgentFinish, error)
	InputKeys() []string
	OutputKeys() []string
}

type AgentAction 

type AgentAction struct {
	Tool      string
	ToolInput string
	Log       string
}

AgentAction is the agent's action to take.

type AgentFinish 

type AgentFinish struct {
	ReturnValues map[string]any
	Log          string
}

AgentFinish is the agent's return value.

type AgentStep 

type AgentStep struct {
	Action      AgentAction
	Observation string
}

AgentStep is a step of the agent.

type Callback 

type Callback interface {
	AlwaysVerbose() bool
	RaiseError() bool
	OnLLMStart(llmName string, prompts []string) error
	OnLLMNewToken(token string) error
	OnLLMEnd(result *LLMResult) error
	OnLLMError(llmError error) error
	OnChainStart(chainName string, inputs *ChainValues) error
	OnChainEnd(outputs *ChainValues) error
	OnChainError(chainError error) error
}

type CallbackOptions added in v0.0.13 

type CallbackOptions struct {
	Callbacks []Callback
	Verbose   bool
}

type Chain 

type Chain interface {
	Call(ctx context.Context, inputs ChainValues) (ChainValues, error)
	Type() string
	Verbose() bool
	Callbacks() []Callback
	Memory() Memory
	InputKeys() []string
	OutputKeys() []string
}

type ChainValues 

type ChainValues map[string]any

type ChatMessage 

type ChatMessage interface {
	Text() string
	Type() ChatMessageType
}

func MapToChatMessage added in v0.0.12 

func MapToChatMessage(m map[string]string) (ChatMessage, error)

type ChatMessageHistory 

type ChatMessageHistory interface {
	// Messages returns the messages stored in the store.
	Messages(ctx context.Context) (ChatMessages, error)
	// Add a user message to the store.
	AddUserMessage(ctx context.Context, text string) error
	// Add an AI message to the store.
	AddAIMessage(ctx context.Context, text string) error
	// Add a self-created message to the store.
	AddMessage(ctx context.Context, message ChatMessage) error
	// Remove all messages from the store.
	Clear(ctx context.Context) error
}

type ChatMessageType 

type ChatMessageType string
const (
	ChatMessageTypeHuman   ChatMessageType = "human"
	ChatMessageTypeAI      ChatMessageType = "ai"
	ChatMessageTypeSystem  ChatMessageType = "system"
	ChatMessageTypeGeneric ChatMessageType = "generic"
)

type ChatMessages added in v0.0.9 

type ChatMessages []ChatMessage

func (ChatMessages) Format added in v0.0.9 

func (cm ChatMessages) Format(optFns ...func(o *StringifyChatMessagesOptions)) (string, error)

type ChatModel added in v0.0.13 

type ChatModel interface {
	Model
	Generate(ctx context.Context, messages ChatMessages) (*LLMResult, error)
}

type Document 

type Document struct {
	PageContent string
	Metadata    map[string]any
}

type DocumentLoader 

type DocumentLoader interface {
	Load(ctx context.Context) ([]Document, error)
	LoadAndSplit(ctx context.Context, splitter TextSplitter)
}

type Embedder 

type Embedder interface {
	// EmbedDocuments returns a vector for each text.
	EmbedDocuments(ctx context.Context, texts []string) ([][]float64, error)
	// EmbedQuery embeds a single text.
	EmbedQuery(ctx context.Context, text string) ([]float64, error)
}

Embedder is the interface for creating vector embeddings from texts.

type GenerateOptions 

type GenerateOptions struct {
	Stop      []string
	Callbacks []Callback
}

type Generation 

type Generation struct {
	Text    string
	Message ChatMessage
	Info    map[string]any
}

type GenericChatMessage 

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

func NewGenericChatMessage 

func NewGenericChatMessage(text, role string) *GenericChatMessage

func (GenericChatMessage) Role 

func (m GenericChatMessage) Role() string

func (GenericChatMessage) Text 

func (m GenericChatMessage) Text() string

func (GenericChatMessage) Type 

func (m GenericChatMessage) Type() ChatMessageType

type HumanChatMessage 

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

func NewHumanChatMessage 

func NewHumanChatMessage(text string) *HumanChatMessage

func (HumanChatMessage) Text 

func (m HumanChatMessage) Text() string

func (HumanChatMessage) Type 

func (m HumanChatMessage) Type() ChatMessageType

type LLM 

type LLM interface {
	Model
	Generate(ctx context.Context, prompts []string, stop []string) (*LLMResult, error)
}

type LLMResult 

type LLMResult struct {
	Generations [][]*Generation
	LLMOutput   map[string]any
}

type Memory 

type Memory interface {
	// Input keys this memory class will load dynamically.
	MemoryVariables() []string
	// Return key-value pairs given the text input to the chain.
	// If None, return all memories
	LoadMemoryVariables(ctx context.Context, inputs map[string]any) (map[string]any, error)
	// Save the context of this model run to memory.
	SaveContext(ctx context.Context, inputs map[string]any, outputs map[string]any) error
	// Clear memory contents.
	Clear(ctx context.Context) error
}

type Model added in v0.0.13 

type Model interface {
	Tokenizer
	Type() string
	Verbose() bool
	Callbacks() []Callback
}

type OutputParser 

type OutputParser[T any] interface {
	// Parse parses the output of an LLM call.
	Parse(text string) (T, error)
	// ParseWithPrompt parses the output of an LLM call with the prompt used.
	ParseWithPrompt(text string, prompt PromptValue) (T, error)
	// GetFormatInstructions returns a string describing the format of the output.
	GetFormatInstructions() (string, error)
	// Type returns the string type key uniquely identifying this class of parser
	Type() string
}

OutputParser is an interface for parsing the output of an LLM call.

type PromptValue 

type PromptValue interface {
	String() string
	Messages() ChatMessages
}

type Retriever 

type Retriever interface {
	GetRelevantDocuments(ctx context.Context, query string) ([]Document, error)
}

type StringifyChatMessagesOptions 

type StringifyChatMessagesOptions struct {
	HumanPrefix  string
	AIPrefix     string
	SystemPrefix string
}

type SystemChatMessage 

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

func NewSystemChatMessage 

func NewSystemChatMessage(text string) *SystemChatMessage

func (SystemChatMessage) Text 

func (m SystemChatMessage) Text() string

func (SystemChatMessage) Type 

func (m SystemChatMessage) Type() ChatMessageType

type TextSplitter 

type TextSplitter interface {
	SplitDocuments(docs []Document) ([]Document, error)
}

type Tokenizer 

type Tokenizer interface {
	GetTokenIDs(text string) ([]int, error)
	GetNumTokens(text string) (int, error)
	GetNumTokensFromMessage(messages ChatMessages) (int, error)
}

type Tool 

type Tool interface {
	Name() string
	Description() string
	Run(ctx context.Context, query string) (string, error)
}

type VectorStore added in v0.0.10 

type VectorStore interface {
	AddDocuments(ctx context.Context, docs []Document) error
	SimilaritySearch(ctx context.Context, query string) ([]Document, error)
}

Source Files

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