Feat/add.azure.and.other.providers (#607)
* fix: claude-4 not having the right max_tokens * feat: add bedrock support * chore: fix package-lock.json * fix: rename baseUrl to baseURL * feat: add azure support * fix: final touches of azure integration * feat: add google vertex provider * chore: fix tests and refactor task-manager.test.js * chore: move task 92 to 94
This commit is contained in:
Ralph Khreish
@@ -4,160 +4,39 @@
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*/
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import { createOllama } from 'ollama-ai-provider';
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import { log } from '../../scripts/modules/utils.js'; // Import logging utility
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import { generateObject, generateText, streamText } from 'ai';
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import { BaseAIProvider } from './base-provider.js';
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// Consider making model configurable via config-manager.js later
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const DEFAULT_MODEL = 'llama3'; // Or a suitable default for Ollama
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const DEFAULT_TEMPERATURE = 0.2;
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export class OllamaAIProvider extends BaseAIProvider {
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constructor() {
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super();
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this.name = 'Ollama';
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}
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function getClient(baseUrl) {
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// baseUrl is optional, defaults to http://localhost:11434
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return createOllama({
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baseUrl: baseUrl || undefined
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});
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}
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/**
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* Override auth validation - Ollama doesn't require API keys
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* @param {object} params - Parameters to validate
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*/
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validateAuth(_params) {
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// Ollama runs locally and doesn't require API keys
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// No authentication validation needed
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}
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/**
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* Generates text using an Ollama model.
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*
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* @param {object} params - Parameters for the generation.
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* @param {string} params.modelId - Specific model ID to use (overrides default).
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* @param {number} params.temperature - Generation temperature.
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* @param {Array<object>} params.messages - The conversation history (system/user prompts).
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* @param {number} [params.maxTokens] - Optional max tokens.
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* @param {string} [params.baseUrl] - Optional Ollama base URL.
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* @returns {Promise<string>} The generated text content.
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* @throws {Error} If API call fails.
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*/
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async function generateOllamaText({
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modelId = DEFAULT_MODEL,
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messages,
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maxTokens,
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temperature = DEFAULT_TEMPERATURE,
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baseUrl
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}) {
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log('info', `Generating text with Ollama model: ${modelId}`);
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/**
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* Creates and returns an Ollama client instance.
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* @param {object} params - Parameters for client initialization
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* @param {string} [params.baseURL] - Optional Ollama base URL (defaults to http://localhost:11434)
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* @returns {Function} Ollama client function
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* @throws {Error} If initialization fails
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*/
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getClient(params) {
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try {
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const { baseURL } = params;
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try {
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const client = getClient(baseUrl);
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const result = await generateText({
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model: client(modelId),
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messages,
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maxTokens,
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temperature
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});
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log('debug', `Ollama generated text: ${result.text}`);
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return {
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text: result.text,
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usage: {
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inputTokens: result.usage.promptTokens,
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outputTokens: result.usage.completionTokens
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}
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};
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} catch (error) {
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log(
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'error',
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`Error generating text with Ollama (${modelId}): ${error.message}`
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);
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throw error;
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return createOllama({
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...(baseURL && { baseURL })
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});
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} catch (error) {
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this.handleError('client initialization', error);
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}
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}
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}
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/**
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* Streams text using an Ollama model.
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*
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* @param {object} params - Parameters for the streaming.
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* @param {string} params.modelId - Specific model ID to use (overrides default).
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* @param {number} params.temperature - Generation temperature.
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* @param {Array<object>} params.messages - The conversation history.
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* @param {number} [params.maxTokens] - Optional max tokens.
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* @param {string} [params.baseUrl] - Optional Ollama base URL.
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* @returns {Promise<ReadableStream>} A readable stream of text deltas.
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* @throws {Error} If API call fails.
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*/
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async function streamOllamaText({
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modelId = DEFAULT_MODEL,
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temperature = DEFAULT_TEMPERATURE,
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messages,
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maxTokens,
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baseUrl
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}) {
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log('info', `Streaming text with Ollama model: ${modelId}`);
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try {
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const ollama = getClient(baseUrl);
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const stream = await streamText({
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model: modelId,
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messages,
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temperature,
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maxTokens
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});
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return stream;
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} catch (error) {
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log(
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'error',
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`Error streaming text with Ollama (${modelId}): ${error.message}`
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);
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throw error;
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}
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}
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/**
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* Generates a structured object using an Ollama model using the Vercel AI SDK's generateObject.
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*
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* @param {object} params - Parameters for the object generation.
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* @param {string} params.modelId - Specific model ID to use (overrides default).
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* @param {number} params.temperature - Generation temperature.
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* @param {Array<object>} params.messages - The conversation history.
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* @param {import('zod').ZodSchema} params.schema - Zod schema for the expected object.
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* @param {string} params.objectName - Name for the object generation context.
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* @param {number} [params.maxTokens] - Optional max tokens.
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* @param {number} [params.maxRetries] - Max retries for validation/generation.
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* @param {string} [params.baseUrl] - Optional Ollama base URL.
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* @returns {Promise<object>} The generated object matching the schema.
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* @throws {Error} If generation or validation fails.
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*/
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async function generateOllamaObject({
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modelId = DEFAULT_MODEL,
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temperature = DEFAULT_TEMPERATURE,
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messages,
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schema,
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objectName = 'generated_object',
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maxTokens,
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maxRetries = 3,
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baseUrl
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}) {
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log('info', `Generating object with Ollama model: ${modelId}`);
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try {
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const ollama = getClient(baseUrl);
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const result = await generateObject({
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model: ollama(modelId),
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mode: 'tool',
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schema: schema,
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messages: messages,
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tool: {
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name: objectName,
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description: `Generate a ${objectName} based on the prompt.`
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},
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maxOutputTokens: maxTokens,
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temperature: temperature,
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maxRetries: maxRetries
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});
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return {
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object: result.object,
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usage: {
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inputTokens: result.usage.promptTokens,
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outputTokens: result.usage.completionTokens
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}
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};
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} catch (error) {
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log(
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'error',
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`Ollama generateObject ('${objectName}') failed: ${error.message}`
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);
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throw error;
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}
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}
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export { generateOllamaText, streamOllamaText, generateOllamaObject };
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