LM Studio

Code

const chat = new quikchat('#chat', lmStudioCallback, {
  theme: 'quikchat-theme-light',
  titleArea: { title: 'Memory Chat', show: true, align: 'left' }
});

function lmStudioCallback(chatInstance, userInput) {
  let start = true, id;
  chatInstance.messageAddNew(userInput, 'user', 'right');

  fetch('http://localhost:1234/v1/chat/completions', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      model: 'lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF',
      messages: [
        { role: 'system', content: 'You are a skilled assistant.' },
        ...chatInstance.historyGet()
      ],
      stream: true
    })
  })
  .then(r => r.body.getReader())
  .then(reader => {
    // Parse SSE stream (OpenAI-compatible format)
    return reader.read().then(function process(result) {
      if (result.done) return;
      let line = new TextDecoder().decode(result.value).replace('data: ', '');
      try {
        const data = JSON.parse(line.trim());
        const content = data.choices[0]?.delta?.content;
        if (content) {
          if (start) {
            id = chatInstance.messageAddNew(content, 'bot', 'left');
            start = false;
          } else {
            chatInstance.messageAppendContent(id, content);
          }
        }
      } catch (e) { /* partial chunk */ }
      return reader.read().then(process);
    });
  });
}