ollama

Documentation

Overview

ollama implements an API client for ollama https://github.com/ollama/ollama/blob/main/docs/api.md

Index

• func WithInsecure() llm.Opt
• func WithKeepAlive(v time.Duration) llm.Opt
• func WithOption(key string, value any) llm.Opt
• func WithPullStatus(fn func(*PullStatus)) llm.Opt
• func WithTruncate(v bool) llm.Opt
• type Client
  • func New(endPoint string, opts ...client.ClientOpt) (*Client, error)
  • func (ollama *Client) Chat(ctx context.Context, prompt llm.Context, opts ...llm.Opt) (*Response, error)
  • func (ollama *Client) CopyModel(ctx context.Context, source, destination string) error
  • func (ollama *Client) DeleteModel(ctx context.Context, name string) error
  • func (ollama *Client) GenerateEmbedding(ctx context.Context, name string, prompt []string, opts ...llm.Opt) (*EmbeddingMeta, error)
  • func (ollama *Client) GetModel(ctx context.Context, name string) (llm.Model, error)
  • func (ollama *Client) ListModels(ctx context.Context) ([]llm.Model, error)
  • func (ollama *Client) ListRunningModels(ctx context.Context) ([]llm.Model, error)
  • func (ollama *Client) Models(ctx context.Context) ([]llm.Model, error)
  • func (*Client) Name() string
  • func (ollama *Client) PullModel(ctx context.Context, name string, opts ...llm.Opt) (llm.Model, error)
• type Data
• type EmbeddingMeta
  • func (m EmbeddingMeta) String() string
• type MessageMeta
• type Metrics
• type ModelDetails
• type ModelInfo
• type ModelMeta
• type PullStatus
  • func (m PullStatus) String() string
• type Response
  • func (response Response) Role() string
  • func (r Response) String() string
  • func (response Response) Text() string
  • func (response Response) ToolCalls() []llm.ToolCall
• type ToolCall
• type ToolCallFunction
• type ToolFunction

Functions

func WithInsecure

func WithInsecure() llm.Opt

Pull Model: Allow insecure connections for pulling models.

func WithKeepAlive

func WithKeepAlive(v time.Duration) llm.Opt

Embeddings & Chat: Controls how long the model will stay loaded into memory following the request.

func WithOption

func WithOption(key string, value any) llm.Opt

Embeddings & Chat: model-specific options.

func WithPullStatus

func WithPullStatus(fn func(*PullStatus)) llm.Opt

Pull Model: Stream the response as it is received.

func WithTruncate

func WithTruncate(v bool) llm.Opt

Embeddings: Does not truncate the end of each input to fit within context length. Returns error if context length is exceeded.

Types

type Client

type Client struct {
	*client.Client
}

func New

func New(endPoint string, opts ...client.ClientOpt) (*Client, error)

Create a new client, with an ollama endpoint, which should be something like "http://localhost:11434/api"

func (*Client) Chat

func (ollama *Client) Chat(ctx context.Context, prompt llm.Context, opts ...llm.Opt) (*Response, error)

func (*Client) CopyModel

func (ollama *Client) CopyModel(ctx context.Context, source, destination string) error

Copy a local model by name

func (*Client) DeleteModel

func (ollama *Client) DeleteModel(ctx context.Context, name string) error

Delete a local model by name

func (*Client) GenerateEmbedding

func (ollama *Client) GenerateEmbedding(ctx context.Context, name string, prompt []string, opts ...llm.Opt) (*EmbeddingMeta, error)

func (*Client) GetModel

func (ollama *Client) GetModel(ctx context.Context, name string) (llm.Model, error)

Get model details

func (*Client) ListModels

func (ollama *Client) ListModels(ctx context.Context) ([]llm.Model, error)

List models

func (*Client) ListRunningModels

func (ollama *Client) ListRunningModels(ctx context.Context) ([]llm.Model, error)

List running models

func (*Client) Models

func (ollama *Client) Models(ctx context.Context) ([]llm.Model, error)

Agent interface

func (*Client) Name

func (*Client) Name() string

Return the name of the agent

func (*Client) PullModel

func (ollama *Client) PullModel(ctx context.Context, name string, opts ...llm.Opt) (llm.Model, error)

Pull a remote model locally

type Data

type Data []byte

Data represents the raw binary data of an image file.

type EmbeddingMeta

type EmbeddingMeta struct {
	Model      string      `json:"model"`
	Embeddings [][]float64 `json:"embeddings"`
	Metrics
}

EmbeddingMeta is the metadata for a generated embedding vector

func (EmbeddingMeta) String

func (m EmbeddingMeta) String() string

type MessageMeta

type MessageMeta struct {
	Role         string     `json:"role"`
	Content      string     `json:"content,omitempty"`
	FunctionName string     `json:"name,omitempty"`       // Function name for a tool result
	Images       []Data     `json:"images,omitempty"`     // Image attachments
	ToolCalls    []ToolCall `json:"tool_calls,omitempty"` // Tool calls from the assistant
}

Chat Message

type Metrics

type Metrics struct {
	TotalDuration      time.Duration `json:"total_duration,omitempty"`
	LoadDuration       time.Duration `json:"load_duration,omitempty"`
	PromptEvalCount    int           `json:"prompt_eval_count,omitempty"`
	PromptEvalDuration time.Duration `json:"prompt_eval_duration,omitempty"`
	EvalCount          int           `json:"eval_count,omitempty"`
	EvalDuration       time.Duration `json:"eval_duration,omitempty"`
}

Metrics

type ModelDetails

type ModelDetails struct {
	ParentModel       string   `json:"parent_model,omitempty"`
	Format            string   `json:"format"`
	Family            string   `json:"family"`
	Families          []string `json:"families"`
	ParameterSize     string   `json:"parameter_size"`
	QuantizationLevel string   `json:"quantization_level"`
}

ModelDetails are the details of the model

type ModelInfo

type ModelInfo map[string]any

ModelInfo provides additional model parameters

type ModelMeta

type ModelMeta struct {
	Name       string       `json:"name"`
	Model      string       `json:"model,omitempty"`
	ModifiedAt time.Time    `json:"modified_at"`
	Size       int64        `json:"size,omitempty"`
	Digest     string       `json:"digest,omitempty"`
	Details    ModelDetails `json:"details"`
	File       string       `json:"modelfile,omitempty"`
	Parameters string       `json:"parameters,omitempty"`
	Template   string       `json:"template,omitempty"`
	Info       ModelInfo    `json:"model_info,omitempty"`
}

ModelMeta is the metadata for an ollama model

type PullStatus

type PullStatus struct {
	Status         string `json:"status"`
	DigestName     string `json:"digest,omitempty"`
	TotalBytes     int64  `json:"total,omitempty"`
	CompletedBytes int64  `json:"completed,omitempty"`
}

PullStatus provides the status of a pull operation in a callback function

func (PullStatus) String

func (m PullStatus) String() string

type Response

type Response struct {
	Model     string      `json:"model"`
	CreatedAt time.Time   `json:"created_at"`
	Message   MessageMeta `json:"message"`
	Done      bool        `json:"done"`
	Reason    string      `json:"done_reason,omitempty"`
	Metrics
}

Chat Response

func (Response) Role

func (response Response) Role() string

func (Response) String

func (r Response) String() string

func (Response) Text

func (response Response) Text() string

func (Response) ToolCalls

func (response Response) ToolCalls() []llm.ToolCall

type ToolCall

type ToolCall struct {
	Function ToolCallFunction `json:"function"`
}

type ToolCallFunction

type ToolCallFunction struct {
	Index     int            `json:"index,omitempty"`
	Name      string         `json:"name"`
	Arguments map[string]any `json:"arguments"`
}

type ToolFunction

type ToolFunction struct {
	Type     string   `json:"type"` // function
	Function llm.Tool `json:"function"`
}

ToolFunction