mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-10-31 23:28:51 +01:00
caa106d4e0
* server: format error to json * server: do not crash on grammar error * fix api key test case * revert limit max n_predict * small fix * correct coding style * update completion.js * launch_slot_with_task * update docs * update_slots * update webui * update readme
203 lines
5.7 KiB
JavaScript
203 lines
5.7 KiB
JavaScript
const paramDefaults = {
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stream: true,
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n_predict: 500,
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temperature: 0.2,
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stop: ["</s>"]
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};
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let generation_settings = null;
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// Completes the prompt as a generator. Recommended for most use cases.
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//
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// Example:
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//
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// import { llama } from '/completion.js'
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//
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// const request = llama("Tell me a joke", {n_predict: 800})
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// for await (const chunk of request) {
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// document.write(chunk.data.content)
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// }
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//
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export async function* llama(prompt, params = {}, config = {}) {
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let controller = config.controller;
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if (!controller) {
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controller = new AbortController();
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}
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const completionParams = { ...paramDefaults, ...params, prompt };
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const response = await fetch("/completion", {
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method: 'POST',
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body: JSON.stringify(completionParams),
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headers: {
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'Connection': 'keep-alive',
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'Content-Type': 'application/json',
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'Accept': 'text/event-stream',
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...(params.api_key ? {'Authorization': `Bearer ${params.api_key}`} : {})
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},
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signal: controller.signal,
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});
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const reader = response.body.getReader();
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const decoder = new TextDecoder();
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let content = "";
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let leftover = ""; // Buffer for partially read lines
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try {
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let cont = true;
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while (cont) {
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const result = await reader.read();
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if (result.done) {
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break;
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}
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// Add any leftover data to the current chunk of data
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const text = leftover + decoder.decode(result.value);
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// Check if the last character is a line break
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const endsWithLineBreak = text.endsWith('\n');
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// Split the text into lines
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let lines = text.split('\n');
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// If the text doesn't end with a line break, then the last line is incomplete
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// Store it in leftover to be added to the next chunk of data
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if (!endsWithLineBreak) {
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leftover = lines.pop();
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} else {
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leftover = ""; // Reset leftover if we have a line break at the end
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}
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// Parse all sse events and add them to result
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const regex = /^(\S+):\s(.*)$/gm;
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for (const line of lines) {
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const match = regex.exec(line);
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if (match) {
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result[match[1]] = match[2]
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// since we know this is llama.cpp, let's just decode the json in data
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if (result.data) {
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result.data = JSON.parse(result.data);
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content += result.data.content;
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// yield
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yield result;
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// if we got a stop token from server, we will break here
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if (result.data.stop) {
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if (result.data.generation_settings) {
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generation_settings = result.data.generation_settings;
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}
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cont = false;
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break;
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}
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}
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if (result.error) {
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try {
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result.error = JSON.parse(result.error);
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if (result.error.message.includes('slot unavailable')) {
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// Throw an error to be caught by upstream callers
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throw new Error('slot unavailable');
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} else {
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console.error(`llama.cpp error [${result.error.code} - ${result.error.type}]: ${result.error.message}`);
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}
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} catch(e) {
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console.error(`llama.cpp error ${result.error}`)
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}
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}
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}
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}
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}
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} catch (e) {
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if (e.name !== 'AbortError') {
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console.error("llama error: ", e);
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}
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throw e;
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}
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finally {
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controller.abort();
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}
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return content;
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}
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// Call llama, return an event target that you can subscribe to
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//
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// Example:
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//
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// import { llamaEventTarget } from '/completion.js'
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//
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// const conn = llamaEventTarget(prompt)
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// conn.addEventListener("message", (chunk) => {
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// document.write(chunk.detail.content)
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// })
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//
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export const llamaEventTarget = (prompt, params = {}, config = {}) => {
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const eventTarget = new EventTarget();
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(async () => {
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let content = "";
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for await (const chunk of llama(prompt, params, config)) {
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if (chunk.data) {
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content += chunk.data.content;
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eventTarget.dispatchEvent(new CustomEvent("message", { detail: chunk.data }));
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}
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if (chunk.data.generation_settings) {
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eventTarget.dispatchEvent(new CustomEvent("generation_settings", { detail: chunk.data.generation_settings }));
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}
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if (chunk.data.timings) {
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eventTarget.dispatchEvent(new CustomEvent("timings", { detail: chunk.data.timings }));
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}
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}
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eventTarget.dispatchEvent(new CustomEvent("done", { detail: { content } }));
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})();
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return eventTarget;
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}
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// Call llama, return a promise that resolves to the completed text. This does not support streaming
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//
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// Example:
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//
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// llamaPromise(prompt).then((content) => {
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// document.write(content)
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// })
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//
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// or
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//
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// const content = await llamaPromise(prompt)
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// document.write(content)
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//
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export const llamaPromise = (prompt, params = {}, config = {}) => {
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return new Promise(async (resolve, reject) => {
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let content = "";
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try {
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for await (const chunk of llama(prompt, params, config)) {
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content += chunk.data.content;
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}
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resolve(content);
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} catch (error) {
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reject(error);
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}
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});
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};
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/**
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* (deprecated)
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*/
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export const llamaComplete = async (params, controller, callback) => {
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for await (const chunk of llama(params.prompt, params, { controller })) {
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callback(chunk);
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}
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}
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// Get the model info from the server. This is useful for getting the context window and so on.
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export const llamaModelInfo = async () => {
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if (!generation_settings) {
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const props = await fetch("/props").then(r => r.json());
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generation_settings = props.default_generation_settings;
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}
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return generation_settings;
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}
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