npm install @reaatech/media-pipeline-mcp-ollama
# or
pnpm add @reaatech/media-pipeline-mcp-ollama

import { OllamaProvider } from "@reaatech/media-pipeline-mcp-ollama";
 
const provider = new OllamaProvider({
  baseUrl: "http://localhost:11434",
  defaultModel: "llama3.2",
});
 
// Text completion
const textResult = await provider.execute({
  operation: "text.complete",
  params: {
    prompt: "Write a haiku about cherry blossoms",
    temperature: 0.7,
    max_tokens: 100,
  },
  config: {},
});
 
console.log(textResult.data.toString()); // The generated haiku
console.log(textResult.metadata.model); // "llama3.2"
 
// Embedding generation
const embedResult = await provider.execute({
  operation: "embedding.generate",
  params: {
    input: "What is the meaning of life?",
    model: "nomic-embed-text",
  },
  config: {},
});
 
const embedding = JSON.parse(embedResult.data.toString());
console.log(embedResult.metadata.dimensions); // e.g. 768
 
// Image description (requires multimodal model)
const descResult = await provider.execute({
  operation: "image.describe",
  params: {
    artifact_data: imageBuffer,
    model: "llama3.2-vision",
    prompt: "Describe this image in detail.",
  },
  config: {},
});
 
console.log(descResult.data.toString()); // Image description

const provider = new OllamaProvider({
  baseUrl: "http://localhost:11434",
  autoPull: true,     // Pull models automatically if not present
  defaultModel: "llama3.2",
});

interface OllamaConfig {
  baseUrl?: string;        // Default: "http://localhost:11434"
  defaultModel?: string;   // Default: "llama3.2"
  timeoutMs?: number;      // Default: 120000 (2 min)
  headers?: Record<string, string>;  // Custom HTTP headers
  autoPull?: boolean;      // Default: false — auto-pull missing models
}