@nomyx/assistant
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A powerful assistant library and cli for your AI projects. works with Vertex AI (Claude and Gemini)
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text/typescript
import { ChatMessage, ChatOptions, ProviderResponse } from '../../../types/chat';
import { ProviderCapabilities, EmbeddingProvider } from '../../../types/provider';
import { Tool, GenericToolSchema, StandardizedToolCall } from '../../../types/tool';
import { ILogger } from '../../../types/common';
import { BaseProvider } from '../BaseProvider';
import { VertexProviderConfig, VertexModel } from './types';
import { VertexConfig } from './config';
import { VertexCache } from './cache';
import { chat } from './chat';
import { streamChat } from './streaming';
import { embed, embedBatch } from './embedding';
import { convertToolSchema, convertToolCall } from './tools';
import { handleVertexError, VertexProviderError } from './errors';
export class VertexProvider extends BaseProvider implements EmbeddingProvider {
private config: VertexConfig;
private cache: VertexCache;
constructor(config: VertexProviderConfig, logger: ILogger) {
super(logger);
this.config = new VertexConfig(config, logger);
this.cache = new VertexCache();
}
async chat(messages: ChatMessage[], options: ChatOptions, tools?: Tool[]): Promise<ProviderResponse> {
try {
const cacheKey = { messages, options, tools };
if (this.cache.has(cacheKey)) {
this.logger.debug('Cache hit for chat request');
return this.cache.get(cacheKey)!;
}
const processedMessages = await this.applyMiddleware(messages);
const response = await chat(this.config, processedMessages, options, tools);
const processedResponse = await this.applyMiddlewareToResponse(response);
if (processedResponse.toolCalls) {
processedResponse.toolCalls = await this.applyMiddlewareToToolCalls(processedResponse.toolCalls);
}
this.cache.set(cacheKey, processedResponse);
return processedResponse;
} catch (error: unknown) {
this.logger.error('Error in VertexProvider chat', { error: error instanceof Error ? error.message : String(error) });
throw handleVertexError(error);
}
}
async *streamChat(messages: ChatMessage[], options: ChatOptions, tools?: Tool[]): AsyncIterableIterator<ProviderResponse> {
try {
const processedMessages = await this.applyMiddleware(messages);
for await (const response of streamChat(this.config, processedMessages, options, tools)) {
const processedResponse = await this.applyMiddlewareToResponse(response);
if (processedResponse.toolCalls) {
processedResponse.toolCalls = await this.applyMiddlewareToToolCalls(processedResponse.toolCalls);
}
yield processedResponse;
}
} catch (error: unknown) {
this.logger.error('Error in VertexProvider streamChat', { error: error instanceof Error ? error.message : String(error) });
throw handleVertexError(error);
}
}
getCapabilities(): ProviderCapabilities {
return {
maxTokens: 2048, // This may vary depending on the specific model
supportsFunctionCalling: true,
supportsStreaming: true,
supportedModels: Object.values(VertexModel),
maxSimultaneousCalls: 1,
supportsSemanticCaching: false,
};
}
async embed(text: string): Promise<number[]> {
try {
return await embed(this.config, text);
} catch (error: unknown) {
this.logger.error('Error in VertexProvider embed', { error: error instanceof Error ? error.message : String(error) });
throw handleVertexError(error);
}
}
async embedBatch(texts: string[]): Promise<number[][]> {
try {
return await embedBatch(this.config, texts);
} catch (error: unknown) {
this.logger.error('Error in VertexProvider embedBatch', { error: error instanceof Error ? error.message : String(error) });
throw handleVertexError(error);
}
}
convertToolSchema(schema: GenericToolSchema): any {
return convertToolSchema(schema, this.config.getModelType());
}
convertToolCall(call: any): StandardizedToolCall {
return convertToolCall(call, this.config.getModelType());
}
clearCache(): void {
this.cache.clear();
this.logger.debug('VertexProvider cache cleared');
}
}
export * from './types';
export { VertexProviderError } from './errors';