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https://github.com/ItzCrazyKns/Perplexica.git
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feat(providers): implement custom classes
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149
src/lib/models/providers/ollama/ollamaLLM.ts
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149
src/lib/models/providers/ollama/ollamaLLM.ts
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import z from 'zod';
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import BaseLLM from '../../base/llm';
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import {
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GenerateObjectInput,
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GenerateOptions,
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GenerateTextInput,
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GenerateTextOutput,
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StreamTextOutput,
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} from '../../types';
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import { Ollama } from 'ollama';
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import { parse } from 'partial-json';
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type OllamaConfig = {
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baseURL: string;
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model: string;
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options?: GenerateOptions;
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};
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class OllamaLLM extends BaseLLM<OllamaConfig> {
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ollamaClient: Ollama;
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constructor(protected config: OllamaConfig) {
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super(config);
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this.ollamaClient = new Ollama({
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host: this.config.baseURL || 'http://localhost:11434',
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});
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}
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withOptions(options: GenerateOptions) {
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this.config.options = {
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...this.config.options,
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...options,
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};
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return this;
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}
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async generateText(input: GenerateTextInput): Promise<GenerateTextOutput> {
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this.withOptions(input.options || {});
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const res = await this.ollamaClient.chat({
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model: this.config.model,
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messages: input.messages,
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options: {
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top_p: this.config.options?.topP,
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temperature: this.config.options?.temperature,
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num_predict: this.config.options?.maxTokens,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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stop: this.config.options?.stopSequences,
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},
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});
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return {
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content: res.message.content,
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additionalInfo: {
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reasoning: res.message.thinking,
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},
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};
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}
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async *streamText(
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input: GenerateTextInput,
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): AsyncGenerator<StreamTextOutput> {
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this.withOptions(input.options || {});
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const stream = await this.ollamaClient.chat({
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model: this.config.model,
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messages: input.messages,
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stream: true,
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options: {
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top_p: this.config.options?.topP,
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temperature: this.config.options?.temperature,
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num_predict: this.config.options?.maxTokens,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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stop: this.config.options?.stopSequences,
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},
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});
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for await (const chunk of stream) {
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yield {
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contentChunk: chunk.message.content,
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done: chunk.done,
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additionalInfo: {
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reasoning: chunk.message.thinking,
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},
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};
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}
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}
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async generateObject<T>(input: GenerateObjectInput): Promise<T> {
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this.withOptions(input.options || {});
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const response = await this.ollamaClient.chat({
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model: this.config.model,
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messages: input.messages,
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format: z.toJSONSchema(input.schema),
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options: {
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top_p: this.config.options?.topP,
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temperature: this.config.options?.temperature,
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num_predict: this.config.options?.maxTokens,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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stop: this.config.options?.stopSequences,
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},
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});
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try {
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return input.schema.parse(JSON.parse(response.message.content)) as T;
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} catch (err) {
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throw new Error(`Error parsing response from Ollama: ${err}`);
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}
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}
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async *streamObject<T>(input: GenerateObjectInput): AsyncGenerator<T> {
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let recievedObj: string = '';
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this.withOptions(input.options || {});
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const stream = await this.ollamaClient.chat({
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model: this.config.model,
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messages: input.messages,
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format: z.toJSONSchema(input.schema),
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stream: true,
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options: {
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top_p: this.config.options?.topP,
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temperature: this.config.options?.temperature,
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num_predict: this.config.options?.maxTokens,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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stop: this.config.options?.stopSequences,
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},
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});
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for await (const chunk of stream) {
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recievedObj += chunk.message.content;
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try {
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yield parse(recievedObj) as T;
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} catch (err) {
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console.log('Error parsing partial object from Ollama:', err);
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yield {} as T;
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}
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}
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}
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}
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export default OllamaLLM;
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