@agentic-kit/ollama

A JavaScript/TypeScript client for the Ollama LLM server, supporting model listing, text generation, streaming responses, embeddings, and model management.

Installation

npm install @agentic-kit/ollama

Usage

import OllamaClient, { GenerateInput } from '@agentic-kit/ollama';

// Create a client (default port 11434)
const client = new OllamaClient('http://localhost:11434');

// List available models
const models = await client.listModels();
console.log('Available models:', models);

// Non-streaming text generation
const output = await client.generate({ model: 'mistral', prompt: 'Hello, Ollama!' });
console.log(output);

// Streaming generation
await client.generate(
  { model: 'mistral', prompt: 'Hello, streaming!', stream: true },
  (chunk) => {
    console.log('Received chunk:', chunk);
  }
);

// Pull a model to local cache
await client.pullModel('mistral');

// Generate embeddings
const embedding = await client.generateEmbedding('Compute embeddings');
console.log('Embedding vector length:', embedding.length);

// Generate a conversational response with context
const response = await client.generateResponse(
  'What is the capital of France?',
  'Geography trivia'
);
console.log(response);

// Delete a pulled model when done
await client.deleteModel('mistral');

API Reference

• new OllamaClient(baseUrl?: string) – defaults to http://localhost:11434
• .listModels(): Promise<string[]>
• .generate(input: GenerateInput, onChunk?: (chunk: string) => void): Promise<string | void>
• .generateStreamingResponse(prompt: string, onChunk: (chunk: string) => void, context?: string): Promise<void>
• .generateEmbedding(text: string): Promise<number[]>
• .generateResponse(prompt: string, context?: string): Promise<string>
• .pullModel(model: string): Promise<void>
• .deleteModel(model: string): Promise<void>

GenerateInput type

interface GenerateInput {
  model: string;
  prompt: string;
  stream?: boolean;
}

Contributing

Please open issues or pull requests on GitHub.

Related Constructive Tooling

🤖 AI & Agent Development

• agentic-kit: 🧰 Provider-agnostic LLM adapter with streaming and multi-turn support. Swap between Anthropic, OpenAI, Ollama, and any OpenAI-compatible endpoint.

📦 Package Management

• pgpm: 🖥️ PostgreSQL Package Manager for modular Postgres development. Works with database workspaces, scaffolding, migrations, seeding, and installing database packages.

🧪 Testing

• pgsql-test: 📊 Isolated testing environments with per-test transaction rollbacks—ideal for integration tests, complex migrations, and RLS simulation.
• pgsql-seed: 🌱 PostgreSQL seeding utilities for CSV, JSON, SQL data loading, and pgpm deployment.
• supabase-test: 🧪 Supabase-native test harness preconfigured for the local Supabase stack—per-test rollbacks, JWT/role context helpers, and CI/GitHub Actions ready.

🧠 Parsing & AST

• pgsql-parser: 🔄 SQL conversion engine that interprets and converts PostgreSQL syntax.
• libpg-query-node: 🌉 Node.js bindings for libpg_query, converting SQL into parse trees.
• @pgsql/types: 📝 Type definitions for PostgreSQL AST nodes in TypeScript.
• @pgsql/utils: 🛠️ AST utilities for constructing and transforming PostgreSQL syntax trees.

Credits

🛠 Built by the Constructive team — creators of modular Postgres tooling for secure, composable backends. If you like our work, contribute on GitHub.

Disclaimer

AS DESCRIBED IN THE LICENSES, THE SOFTWARE IS PROVIDED "AS IS", AT YOUR OWN RISK, AND WITHOUT WARRANTIES OF ANY KIND.

No developer or entity involved in creating this software will be liable for any claims or damages whatsoever associated with your use, inability to use, or your interaction with other users of the code, including any direct, indirect, incidental, special, exemplary, punitive or consequential damages, or loss of profits, cryptocurrencies, tokens, or anything else of value.