chatmodel

Documentation

Index

• type Anthropic
  • func NewAnthropic(apiKey string, optFns ...func(o *AnthropicOptions)) (*Anthropic, error)
  • func (cm *Anthropic) Callbacks() []schema.Callback
  • func (cm *Anthropic) Generate(ctx context.Context, messages schema.ChatMessages, ...) (*schema.ModelResult, error)
  • func (cm *Anthropic) InvocationParams() map[string]any
  • func (cm *Anthropic) Type() string
  • func (cm *Anthropic) Verbose() bool
• type AnthropicOptions
• type AzureOpenAIOptions
• type Fake
  • func NewFake(response string) *Fake
  • func (cm *Fake) Callbacks() []schema.Callback
  • func (cm *Fake) Generate(ctx context.Context, messages schema.ChatMessages, ...) (*schema.ModelResult, error)
  • func (cm *Fake) InvocationParams() map[string]any
  • func (cm *Fake) Type() string
  • func (cm *Fake) Verbose() bool
• type OpenAI
  • func NewAzureOpenAI(apiKey, baseURL string, optFns ...func(o *AzureOpenAIOptions)) (*OpenAI, error)
  • func NewOpenAI(apiKey string, optFns ...func(o *OpenAIOptions)) (*OpenAI, error)
  • func (cm *OpenAI) Callbacks() []schema.Callback
  • func (cm *OpenAI) Generate(ctx context.Context, messages schema.ChatMessages, ...) (*schema.ModelResult, error)
  • func (cm *OpenAI) InvocationParams() map[string]any
  • func (cm *OpenAI) Type() string
  • func (cm *OpenAI) Verbose() bool
• type OpenAIOptions

Types

type Anthropic

type Anthropic struct {
	schema.Tokenizer
	// contains filtered or unexported fields
}

func NewAnthropic

func NewAnthropic(apiKey string, optFns ...func(o *AnthropicOptions)) (*Anthropic, error)

func (*Anthropic) Callbacks

func (cm *Anthropic) Callbacks() []schema.Callback

func (*Anthropic) Generate

func (cm *Anthropic) Generate(ctx context.Context, messages schema.ChatMessages, optFns ...func(o *schema.GenerateOptions)) (*schema.ModelResult, error)

func (*Anthropic) InvocationParams

func (cm *Anthropic) InvocationParams() map[string]any

func (*Anthropic) Type

func (cm *Anthropic) Type() string

func (*Anthropic) Verbose

func (cm *Anthropic) Verbose() bool

type AnthropicOptions

type AnthropicOptions struct {
	*schema.CallbackOptions
	Tokenizer schema.Tokenizer
	// Model name to use.
	ModelName string
	// Denotes the number of tokens to predict per generation.
	MaxTokens int
}

type AzureOpenAIOptions

type AzureOpenAIOptions struct {
	OpenAIOptions
	Deployment string
}

type Fake

type Fake struct {
	schema.Tokenizer
	// contains filtered or unexported fields
}

func NewFake

func NewFake(response string) *Fake

func (*Fake) Callbacks

func (cm *Fake) Callbacks() []schema.Callback

func (*Fake) Generate

func (cm *Fake) Generate(ctx context.Context, messages schema.ChatMessages, optFns ...func(o *schema.GenerateOptions)) (*schema.ModelResult, error)

func (*Fake) InvocationParams

func (cm *Fake) InvocationParams() map[string]any

func (*Fake) Type

func (cm *Fake) Type() string

func (*Fake) Verbose

func (cm *Fake) Verbose() bool

type OpenAI

type OpenAI struct {
	schema.Tokenizer
	// contains filtered or unexported fields
}

func NewAzureOpenAI

func NewAzureOpenAI(apiKey, baseURL string, optFns ...func(o *AzureOpenAIOptions)) (*OpenAI, error)

func NewOpenAI

func NewOpenAI(apiKey string, optFns ...func(o *OpenAIOptions)) (*OpenAI, error)

func (*OpenAI) Callbacks

func (cm *OpenAI) Callbacks() []schema.Callback

func (*OpenAI) Generate

func (cm *OpenAI) Generate(ctx context.Context, messages schema.ChatMessages, optFns ...func(o *schema.GenerateOptions)) (*schema.ModelResult, error)

func (*OpenAI) InvocationParams

func (cm *OpenAI) InvocationParams() map[string]any

func (*OpenAI) Type

func (cm *OpenAI) Type() string

func (*OpenAI) Verbose

func (cm *OpenAI) Verbose() bool

type OpenAIOptions

type OpenAIOptions struct {
	*schema.CallbackOptions
	schema.Tokenizer
	// Model name to use.
	ModelName string
	// Sampling temperature to use.
	Temperatur float32
	// The maximum number of tokens to generate in the completion.
	// -1 returns as many tokens as possible given the prompt and
	//the models maximal context size.
	MaxTokens int
	// Total probability mass of tokens to consider at each step.
	TopP float32
	// Penalizes repeated tokens.
	PresencePenalty float32
	// Penalizes repeated tokens according to frequency.
	FrequencyPenalty float32
	// How many completions to generate for each prompt.
	N int
	// Batch size to use when passing multiple documents to generate.
	BatchSize int
}