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https://github.com/ItzCrazyKns/Perplexica.git
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feat(providers): implement custom classes
This commit is contained in:
163
src/lib/models/providers/openai/openaiLLM.ts
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163
src/lib/models/providers/openai/openaiLLM.ts
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import OpenAI from 'openai';
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import BaseLLM from '../../base/llm';
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import { zodTextFormat, zodResponseFormat } from 'openai/helpers/zod';
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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 { parse } from 'partial-json';
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type OpenAIConfig = {
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apiKey: string;
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model: string;
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baseURL?: string;
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options?: GenerateOptions;
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};
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class OpenAILLM extends BaseLLM<OpenAIConfig> {
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openAIClient: OpenAI;
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constructor(protected config: OpenAIConfig) {
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super(config);
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this.openAIClient = new OpenAI({
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apiKey: this.config.apiKey,
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baseURL: this.config.baseURL || 'https://api.openai.com/v1',
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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 response = await this.openAIClient.chat.completions.create({
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model: this.config.model,
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messages: input.messages,
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temperature: this.config.options?.temperature || 1.0,
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top_p: this.config.options?.topP,
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max_completion_tokens: this.config.options?.maxTokens,
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stop: this.config.options?.stopSequences,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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});
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if (response.choices && response.choices.length > 0) {
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return {
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content: response.choices[0].message.content!,
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additionalInfo: {
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finishReason: response.choices[0].finish_reason,
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},
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};
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}
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throw new Error('No response from OpenAI');
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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.openAIClient.chat.completions.create({
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model: this.config.model,
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messages: input.messages,
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temperature: this.config.options?.temperature || 1.0,
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top_p: this.config.options?.topP,
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max_completion_tokens: this.config.options?.maxTokens,
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stop: this.config.options?.stopSequences,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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stream: true,
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});
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for await (const chunk of stream) {
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if (chunk.choices && chunk.choices.length > 0) {
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yield {
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contentChunk: chunk.choices[0].delta.content || '',
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done: chunk.choices[0].finish_reason !== null,
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additionalInfo: {
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finishReason: chunk.choices[0].finish_reason,
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},
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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.openAIClient.chat.completions.parse({
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messages: input.messages,
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model: this.config.model,
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temperature: this.config.options?.temperature || 1.0,
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top_p: this.config.options?.topP,
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max_completion_tokens: this.config.options?.maxTokens,
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stop: this.config.options?.stopSequences,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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response_format: zodResponseFormat(input.schema, 'object'),
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});
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if (response.choices && response.choices.length > 0) {
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try {
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return input.schema.parse(response.choices[0].message.parsed) as T;
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} catch (err) {
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throw new Error(`Error parsing response from OpenAI: ${err}`);
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}
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}
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throw new Error('No response from OpenAI');
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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 = this.openAIClient.responses.stream({
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model: this.config.model,
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input: input.messages,
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temperature: this.config.options?.temperature || 1.0,
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top_p: this.config.options?.topP,
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max_completion_tokens: this.config.options?.maxTokens,
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stop: this.config.options?.stopSequences,
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frequency_penalty: this.config.options?.frequencyPenalty,
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presence_penalty: this.config.options?.presencePenalty,
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text: {
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format: zodTextFormat(input.schema, 'object'),
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},
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});
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for await (const chunk of stream) {
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if (chunk.type === 'response.output_text.delta' && chunk.delta) {
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recievedObj += chunk.delta;
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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 OpenAI:', err);
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yield {} as T;
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}
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} else if (chunk.type === 'response.output_text.done' && chunk.text) {
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try {
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yield parse(chunk.text) as T;
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} catch (err) {
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throw new Error(`Error parsing response from OpenAI: ${err}`);
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}
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}
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}
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}
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}
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export default OpenAILLM;
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