lollms-webui/endpoints/docs/lollms_client_js/DOC.md

LollmsClient Quick Start

• constructor(host_address, model_name, ctx_size, personality, n_predict, temperature, top_k, top_p, repeat_penalty, repeat_last_n, seed, n_threads, service_key, default_generation_mode): Initializes a new LollmsClient instance.
• generateText(prompt, options): Generates text from the LoLLMs server.
• tokenize(prompt): Tokenizes the given prompt.
• detokenize(tokensList): Detokenizes the given list of tokens.
• generate(prompt, options): Generates text using the specified generation mode.
• generate_with_images(prompt, images, options): Generates text with images.
• lollms_generate(prompt, host_address, model_name, personality, n_predict, stream, temperature, top_k, top_p, repeat_penalty, repeat_last_n, seed, n_threads, service_key, streamingCallback): Generates text using the LoLLMs generation mode.
• lollms_generate_with_images(prompt, images, host_address, model_name, personality, n_predict, stream, temperature, top_k, top_p, repeat_penalty, repeat_last_n, seed, n_threads, service_key, streamingCallback): Generates text with images using the LoLLMs generation mode.
• openai_generate(prompt, host_address, model_name, personality, n_predict, stream, temperature, top_k, top_p, repeat_penalty, repeat_last_n, seed, n_threads, ELF_COMPLETION_FORMAT, service_key, streamingCallback): Generates text using the OpenAI generation mode.
• listMountedPersonalities(host_address): Lists mounted personalities.
• listModels(host_address): Lists available models.
• updateSettings(settings): Updates multiple settings of the LollmsClient instance at once.
  • Format: An object containing key-value pairs of settings to update.
  • Important elements:
    • host_address (string): The URL of the LoLLMs server (e.g., 'http://localhost:9600').
    • ctx_size (number): The context size for the AI model, typically a power of 2 (e.g., 2048, 4096).
    • n_predict (number): The number of tokens to predict, usually matching or smaller than the context size.
  • Example usage:

    lollmsClient.updateSettings({
      host_address: 'http://localhost:9600',
      ctx_size: 4096,
      n_predict: 2048,
      personality: 1,
      temperature: 0.7
    });
    

1. Initialize:

   const client = new LollmsClient('http://localhost:9600', <(optional) model name>);
   

2. Generate Text:

   const response = await client.generateText("Write a short story.");
   console.log(response);
   

3. Tokenize/Detokenize:

   const tokens = await client.tokenize("Hello, world!");
   // the tokens are a list of a list, the first entry is the token text and the second is the token id
   // Extract only the token IDs from the tokenized result
   const tokenIds = tokens.map(token => token[1]);
   // Use the token IDs for detokenization
   const text = await client.detokenize(tokenIds);
   

4. List Resources:

   const personalities = await client.listMountedPersonalities();
   const models = await client.listModels();