core/apps/webapp/app/lib/model.server.ts
2025-09-26 17:16:33 +05:30

153 lines
3.8 KiB
TypeScript

import {
type CoreMessage,
type LanguageModelV1,
embed,
generateText,
streamText,
} from "ai";
import { openai } from "@ai-sdk/openai";
import { logger } from "~/services/logger.service";
import { createOllama, type OllamaProvider } from "ollama-ai-provider";
import { anthropic } from "@ai-sdk/anthropic";
import { google } from "@ai-sdk/google";
import { createAmazonBedrock } from "@ai-sdk/amazon-bedrock";
import { fromNodeProviderChain } from "@aws-sdk/credential-providers";
export async function makeModelCall(
stream: boolean,
messages: CoreMessage[],
onFinish: (text: string, model: string) => void,
options?: any,
) {
let modelInstance: LanguageModelV1 | undefined;
let model = process.env.MODEL as any;
const ollamaUrl = process.env.OLLAMA_URL;
let ollama: OllamaProvider | undefined;
if (ollamaUrl) {
ollama = createOllama({
baseURL: ollamaUrl,
});
}
const bedrock = createAmazonBedrock({
region: process.env.AWS_REGION || 'us-east-1',
credentialProvider: fromNodeProviderChain(),
});
const generateTextOptions: any = {}
model = 'us.amazon.nova-premier-v1:0'
switch (model) {
case "gpt-4.1-2025-04-14":
case "gpt-4.1-mini-2025-04-14":
case "gpt-5-mini-2025-08-07":
case "gpt-5-2025-08-07":
case "gpt-4.1-nano-2025-04-14":
modelInstance = openai(model, { ...options });
generateTextOptions.temperature = 1
break;
case "claude-3-7-sonnet-20250219":
case "claude-3-opus-20240229":
case "claude-3-5-haiku-20241022":
modelInstance = anthropic(model, { ...options });
break;
case "gemini-2.5-flash-preview-04-17":
case "gemini-2.5-pro-preview-03-25":
case "gemini-2.0-flash":
case "gemini-2.0-flash-lite":
modelInstance = google(model, { ...options });
break;
case "us.meta.llama3-3-70b-instruct-v1:0":
case "us.deepseek.r1-v1:0":
case "qwen.qwen3-32b-v1:0":
case "openai.gpt-oss-120b-1:0":
case "us.mistral.pixtral-large-2502-v1:0":
case "us.amazon.nova-premier-v1:0":
modelInstance = bedrock(`${model}`);
break;
default:
if (ollama) {
modelInstance = ollama(model);
}
logger.warn(`Unsupported model type: ${model}`);
break;
}
if (!modelInstance) {
throw new Error(`Unsupported model type: ${model}`);
}
if (stream) {
return streamText({
model: modelInstance,
messages,
...generateTextOptions,
onFinish: async ({ text }) => {
onFinish(text, model);
},
});
}
const { text, response } = await generateText({
model: modelInstance,
messages,
...generateTextOptions,
});
onFinish(text, model);
return text;
}
/**
* Determines if the current model is proprietary (OpenAI, Anthropic, Google, Grok)
* or open source (accessed via Bedrock, Ollama, etc.)
*/
export function isProprietaryModel(): boolean {
const model = process.env.MODEL;
if (!model) return false;
// Proprietary model patterns
const proprietaryPatterns = [
/^gpt-/, // OpenAI models
/^claude-/, // Anthropic models
/^gemini-/, // Google models
/^grok-/, // xAI models
];
return proprietaryPatterns.some(pattern => pattern.test(model));
}
export async function getEmbedding(text: string) {
const ollamaUrl = process.env.OLLAMA_URL;
// Default to using Ollama
const model = process.env.EMBEDDING_MODEL;
if (model === "text-embedding-3-small") {
// Use OpenAI embedding model when explicitly requested
const { embedding } = await embed({
model: openai.embedding("text-embedding-3-small"),
value: text,
});
return embedding;
}
const ollama = createOllama({
baseURL: ollamaUrl,
});
const { embedding } = await embed({
model: ollama.embedding(model as string),
value: text,
});
return embedding;
}