ollamaclient

Go package and example utilities for using Ollama / LLMs

APACHE-2.0 License

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ollamaclient

A Go package for using Ollama and large language models (LLMs).

Example use

package main

import (
    "fmt"

    "github.com/xyproto/ollamaclient/v2"
    "github.com/xyproto/usermodel"
)

func main() {
    oc := ollamaclient.New(usermodel.GetTextGenerationModel())
    oc.Verbose = true
    if err := oc.PullIfNeeded(); err != nil {
        fmt.Println("Error:", err)
        return
    }
    prompt := "Write a haiku about the color of cows."
    output, err := oc.GetOutput(prompt)
    if err != nil {
        fmt.Println("Error:", err)
        return
    }
    fmt.Printf("\n%s\n", output)
}

Example output (with verbosity set to true):

Sending request to http://localhost:11434/api/tags
Sending request to http://localhost:11434/api/generate: {"model":"gemma2:2b","prompt":"Write a haiku about the color of cows.","options":{"seed":256,"tempera}

Brown hides, gentle eyes,
Mooing low in grassy fields,
Milk flows, life's sweet hue.

Make sure to install and run Ollama first, or set OLLAMA_HOST to a valid host.

Using images in the prompt, with the llava model

A simple way to describe images:

package main

import (
    "fmt"
    "log"

    "github.com/xyproto/ollamaclient/v2"
    "github.com/xyproto/usermodel"
)

func main() {
    model := usermodel.GetVisionModel()
    oc := ollamaclient.New(model)
    oc.SetReproducible()
    if err := oc.PullIfNeeded(true); err != nil {
        log.Fatalln(err)
    }
    imageFilenames := []string{"carrot1.png", "carrot2.png"}
    const desiredWordCount = 7
    description, err := oc.DescribeImages(imageFilenames, desiredWordCount)
    if err != nil {
        log.Fatalln(err)
    }
    fmt.Println(description)
}

See v2/cmd/describeimage for an example that uses a custom prompt.

Embeddings

  • The .Embeddings method can be used to pass in a prompt and return a []float64.

Environment variables

These environment variables are supported:

  • OLLAMA_HOST (http://localhost:11434 by default)
  • OLLAMA_MODEL (uses the model defined by llm-manager by default)
  • OLLAMA_VERBOSE (false by default)

The summarize utility

Getting started:

  1. Install ollama and start it as a service.
  2. Install the summarize utility: go install github.com/xyproto/ollamaclient/cmd/summarize@latest
  3. Summarize a README.md file and a source code file: summarize README.md ollamaclient.go. This will also download the model if it's the first run.
  4. Write a poem about one or more files: summarize --prompt "Write a poem about the following files:" README.md

Usage:

./summarize [flags] <filename1> [<filename2> ...]

Flags:

  • -m, --model: Specify an Ollama model.
  • -o, --output: Define an output file to store the summary.
  • -p, --prompt: Specify a custom prompt header for summary. The default is Write a short summary of a project that contains the following files:
  • -w, --wrap: Set the word wrap width. Use -1 to detect the terminal width.
  • -v, --version: Display the current version.
  • -V, --verbose: Enable verbose logging.

Generate a summary with a custom prompt:

./summarize -w -1 -p "Summarize these files:" README.md CONFIG.md

Generate a summary, saving the output to a file:

./summarize -o output.txt README.md CONFIG.md

Generate a summary with custom word wrap width:

./summarize -w 100 README.md

Testing

go test depends on a local Ollama server being up and running, and will attempt to download and use various models.

General info

  • Version: 2.7.0
  • License: Apache 2