Evandro Fonseca Junior
d5dd3a9f09
- Add currentConversationId prop to ChatContainer for loading selected conversations - Implement logic to load messages when conversation is selected and clear when deselected - Improve user message rendering with proper whitespace handling - Enhance MarkdownRenderer with content normalization and adjusted spacing for better readability - Add paragraph styling to markdown output for improved layout This enables users to switch between conversations seamlessly and provides cleaner message display.
105 lines
3.0 KiB
TypeScript
105 lines
3.0 KiB
TypeScript
import { Ollama } from "ollama";
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export const OLLAMA_HOST = process.env.OLLAMA_HOST || "http://localhost:11434";
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export async function listModelsViaSdk() {
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try {
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const client = new Ollama({ host: OLLAMA_HOST });
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const res = await client.list();
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return res?.models ?? [];
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} catch (e) {
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throw e;
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}
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}
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export async function listModelsViaHttp() {
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const url = `${OLLAMA_HOST}/api/tags`;
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const res = await fetch(url, { cache: "no-store" });
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if (!res.ok) throw new Error(`Ollama HTTP error ${res.status}`);
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const data = await res.json();
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return data?.models ?? [];
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}
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export async function chatWithStream(
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model: string,
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messages: Array<{ role: string; content: string }>,
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options?: Record<string, unknown>,
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system?: string
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) {
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const client = new Ollama({ host: OLLAMA_HOST });
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return client.chat({
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model,
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messages: system
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? [...messages, { role: "system", content: system }]
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: messages,
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stream: true,
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options,
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});
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}
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export async function pullModel(model: string) {
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const client = new Ollama({ host: OLLAMA_HOST });
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return client.pull({ model, stream: true });
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}
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export async function checkModelExists(modelName: string): Promise<boolean> {
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try {
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const models = await listModelsViaSdk();
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return models.some((model) => model.name === modelName);
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} catch (error) {
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console.error("Erro ao verificar modelos:", error);
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return false;
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}
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}
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export async function ensureModelExists(
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modelName: string,
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description?: string
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): Promise<void> {
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const exists = await checkModelExists(modelName);
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if (!exists) {
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console.log(`📥 Baixando modelo ${modelName}...`);
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if (description) {
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console.log(`ℹ️ ${description}`);
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}
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const stream = await pullModel(modelName);
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let downloadedBytes = 0;
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let totalBytes = 0;
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let progress = 0;
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// Processar stream para mostrar progresso
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for await (const chunk of stream) {
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if (chunk.status === "downloading" && chunk.completed && chunk.total) {
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downloadedBytes = chunk.completed;
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totalBytes = chunk.total;
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progress = Math.round((downloadedBytes / totalBytes) * 100);
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// Criar barra de progresso visual
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const barLength = 20;
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const filledLength = Math.round((progress / 100) * barLength);
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const bar =
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"█".repeat(filledLength) + "░".repeat(barLength - filledLength);
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// Mostrar progresso com informações
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const downloadedMB = (downloadedBytes / 1024 / 1024).toFixed(1);
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const totalMB = (totalBytes / 1024 / 1024).toFixed(1);
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process.stdout.write(
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`\r📥 ${modelName}: [${bar}] ${progress}% (${downloadedMB}MB/${totalMB}MB)`
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);
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} else if (chunk.status === "success") {
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console.log(`\n✅ Modelo ${modelName} baixado com sucesso!`);
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if (description) {
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console.log(
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`🎯 ${description.replace("será usado", "agora funciona")}`
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);
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}
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break;
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}
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}
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} else {
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console.log(`✅ Modelo ${modelName} já está disponível`);
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}
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}
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