252 lines
7.5 KiB
TypeScript
252 lines
7.5 KiB
TypeScript
import * as plugins from './plugins.js';
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import * as paths from './paths.js';
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import { MultiModalModel } from './abstract.classes.multimodal.js';
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import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
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export interface IOllamaProviderOptions {
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baseUrl?: string;
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model?: string;
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visionModel?: string; // Model to use for vision tasks (e.g. 'llava')
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}
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export class OllamaProvider extends MultiModalModel {
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private options: IOllamaProviderOptions;
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private baseUrl: string;
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private model: string;
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private visionModel: string;
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constructor(optionsArg: IOllamaProviderOptions = {}) {
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super();
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this.options = optionsArg;
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this.baseUrl = optionsArg.baseUrl || 'http://localhost:11434';
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this.model = optionsArg.model || 'llama2';
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this.visionModel = optionsArg.visionModel || 'llava';
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}
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async start() {
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// Verify Ollama is running
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try {
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const response = await fetch(`${this.baseUrl}/api/tags`);
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if (!response.ok) {
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throw new Error('Failed to connect to Ollama server');
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}
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} catch (error) {
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throw new Error(`Failed to connect to Ollama server at ${this.baseUrl}: ${error.message}`);
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}
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}
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async stop() {}
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public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
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// Create a TextDecoder to handle incoming chunks
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const decoder = new TextDecoder();
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let buffer = '';
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let currentMessage: { role: string; content: string; } | null = null;
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// Create a TransformStream to process the input
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const transform = new TransformStream<Uint8Array, string>({
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async transform(chunk, controller) {
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buffer += decoder.decode(chunk, { stream: true });
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// Try to parse complete JSON messages from the buffer
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while (true) {
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const newlineIndex = buffer.indexOf('\n');
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if (newlineIndex === -1) break;
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const line = buffer.slice(0, newlineIndex);
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buffer = buffer.slice(newlineIndex + 1);
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if (line.trim()) {
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try {
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const message = JSON.parse(line);
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currentMessage = {
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role: message.role || 'user',
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content: message.content || '',
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};
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} catch (e) {
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console.error('Failed to parse message:', e);
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}
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}
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}
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// If we have a complete message, send it to Ollama
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if (currentMessage) {
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const response = await fetch(`${this.baseUrl}/api/chat`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: this.model,
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messages: [{ role: currentMessage.role, content: currentMessage.content }],
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stream: true,
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}),
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});
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// Process each chunk from Ollama
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const reader = response.body?.getReader();
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if (reader) {
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try {
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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const chunk = new TextDecoder().decode(value);
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const lines = chunk.split('\n');
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for (const line of lines) {
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if (line.trim()) {
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try {
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const parsed = JSON.parse(line);
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const content = parsed.message?.content;
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if (content) {
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controller.enqueue(content);
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}
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} catch (e) {
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console.error('Failed to parse Ollama response:', e);
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}
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}
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}
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}
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} finally {
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reader.releaseLock();
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}
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}
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currentMessage = null;
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}
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},
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flush(controller) {
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if (buffer) {
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try {
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const message = JSON.parse(buffer);
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controller.enqueue(message.content || '');
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} catch (e) {
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console.error('Failed to parse remaining buffer:', e);
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}
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}
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}
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});
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// Connect the input to our transform stream
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return input.pipeThrough(transform);
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}
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// Implementing the synchronous chat interaction
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public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
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// Format messages for Ollama
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const messages = [
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{ role: 'system', content: optionsArg.systemMessage },
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...optionsArg.messageHistory,
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{ role: 'user', content: optionsArg.userMessage }
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];
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// Make API call to Ollama
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const response = await fetch(`${this.baseUrl}/api/chat`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: this.model,
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messages: messages,
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stream: false
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}),
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});
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if (!response.ok) {
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throw new Error(`Ollama API error: ${response.statusText}`);
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}
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const result = await response.json();
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return {
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role: 'assistant' as const,
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message: result.message.content,
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};
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}
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public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
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throw new Error('Audio generation is not supported by Ollama.');
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}
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public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
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const base64Image = optionsArg.image.toString('base64');
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const response = await fetch(`${this.baseUrl}/api/chat`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: this.visionModel,
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messages: [{
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role: 'user',
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content: optionsArg.prompt,
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images: [base64Image]
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}],
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stream: false
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}),
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});
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if (!response.ok) {
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throw new Error(`Ollama API error: ${response.statusText}`);
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}
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const result = await response.json();
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return result.message.content;
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}
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public async document(optionsArg: {
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systemMessage: string;
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userMessage: string;
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pdfDocuments: Uint8Array[];
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messageHistory: ChatMessage[];
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}): Promise<{ message: any }> {
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// Convert PDF documents to images using SmartPDF
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const smartpdfInstance = new plugins.smartpdf.SmartPdf();
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let documentImageBytesArray: Uint8Array[] = [];
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for (const pdfDocument of optionsArg.pdfDocuments) {
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const documentImageArray = await smartpdfInstance.convertPDFToPngBytes(pdfDocument);
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documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
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}
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// Convert images to base64
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const base64Images = documentImageBytesArray.map(bytes => Buffer.from(bytes).toString('base64'));
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// Send request to Ollama with images
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const response = await fetch(`${this.baseUrl}/api/chat`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: this.visionModel,
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messages: [
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{ role: 'system', content: optionsArg.systemMessage },
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...optionsArg.messageHistory,
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{
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role: 'user',
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content: optionsArg.userMessage,
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images: base64Images
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}
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],
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stream: false
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}),
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});
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if (!response.ok) {
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throw new Error(`Ollama API error: ${response.statusText}`);
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}
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const result = await response.json();
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return {
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message: {
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role: 'assistant',
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content: result.message.content
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}
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};
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}
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} |