mirror of
https://github.com/ggerganov/llama.cpp.git
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Expose generation timings from server & update completions.js (#2116)
* use javascript generators as much cleaner API Also add ways to access completion as promise and EventSource * export llama_timings as struct and expose them in server * update readme, update baked includes * llama : uniform variable names + struct init --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Tobias Lütke
GitHub
parent
983b555e9d
commit
31cfbb1013
@ -26,20 +26,17 @@ Command line options:
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## Build
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Build llama.cpp with server from repository root with either make or CMake.
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server is build alongside everything else from the root of the project
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- Using `make`:
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```bash
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LLAMA_BUILD_SERVER=1 make
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make
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```
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- Using `CMake`:
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```bash
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mkdir build-server
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cd build-server
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cmake -DLLAMA_BUILD_SERVER=ON ..
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cmake --build . --config Release
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```
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@ -208,24 +205,30 @@ openai.api_base = "http://<Your api-server IP>:port"
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Then you can utilize llama.cpp as an OpenAI's **chat.completion** or **text_completion** API
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### Extending the Web Front End
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### Extending or building alternative Web Front End
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The default location for the static files is `examples/server/public`. You can extend the front end by running the server binary with `--path` set to `./your-directory` and importing `/completion.js` to get access to the llamaComplete() method. A simple example is below:
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The default location for the static files is `examples/server/public`. You can extend the front end by running the server binary with `--path` set to `./your-directory` and importing `/completion.js` to get access to the llamaComplete() method.
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```
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Read the documentation in `/completion.js` to see convenient ways to access llama.
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A simple example is below:
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```html
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<html>
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<body>
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<pre>
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<script type="module">
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import { llamaComplete } from '/completion.js'
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import { llama } from '/completion.js'
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llamaComplete({
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prompt: "### Instruction:\nWrite dad jokes, each one paragraph. You can use html formatting if needed.\n\n### Response:",
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n_predict: 1024,
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},
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null,
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(chunk) => document.write(chunk.data.content)
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)
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const prompt = `### Instruction:
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Write dad jokes, each one paragraph.
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You can use html formatting if needed.
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### Response:`
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for await (const chunk of llama(prompt)) {
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document.write(chunk.data.content)
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}
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</script>
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</pre>
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</body>
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@ -7,187 +7,369 @@ unsigned char completion_js[] = {
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0x66, 0x20, 0x6c, 0x6c, 0x61, 0x6d, 0x61, 0x28, 0x70, 0x61, 0x72, 0x61,
|
||||
0x6d, 0x73, 0x2e, 0x70, 0x72, 0x6f, 0x6d, 0x70, 0x74, 0x2c, 0x20, 0x70,
|
||||
0x61, 0x72, 0x61, 0x6d, 0x73, 0x2c, 0x20, 0x7b, 0x20, 0x63, 0x6f, 0x6e,
|
||||
0x74, 0x72, 0x6f, 0x6c, 0x6c, 0x65, 0x72, 0x20, 0x7d, 0x29, 0x29, 0x20,
|
||||
0x7b, 0x0a, 0x20, 0x20, 0x20, 0x20, 0x63, 0x61, 0x6c, 0x6c, 0x62, 0x61,
|
||||
0x63, 0x6b, 0x28, 0x63, 0x68, 0x75, 0x6e, 0x6b, 0x29, 0x3b, 0x0a, 0x20,
|
||||
0x20, 0x7d, 0x0a, 0x7d, 0x0a, 0x0a, 0x2f, 0x2f, 0x20, 0x47, 0x65, 0x74,
|
||||
0x20, 0x74, 0x68, 0x65, 0x20, 0x6d, 0x6f, 0x64, 0x65, 0x6c, 0x20, 0x69,
|
||||
0x6e, 0x66, 0x6f, 0x20, 0x66, 0x72, 0x6f, 0x6d, 0x20, 0x74, 0x68, 0x65,
|
||||
0x20, 0x73, 0x65, 0x72, 0x76, 0x65, 0x72, 0x2e, 0x20, 0x54, 0x68, 0x69,
|
||||
0x73, 0x20, 0x69, 0x73, 0x20, 0x75, 0x73, 0x65, 0x66, 0x75, 0x6c, 0x20,
|
||||
0x66, 0x6f, 0x72, 0x20, 0x67, 0x65, 0x74, 0x74, 0x69, 0x6e, 0x67, 0x20,
|
||||
0x74, 0x68, 0x65, 0x20, 0x63, 0x6f, 0x6e, 0x74, 0x65, 0x78, 0x74, 0x20,
|
||||
0x77, 0x69, 0x6e, 0x64, 0x6f, 0x77, 0x20, 0x61, 0x6e, 0x64, 0x20, 0x73,
|
||||
0x6f, 0x20, 0x6f, 0x6e, 0x2e, 0x0a, 0x65, 0x78, 0x70, 0x6f, 0x72, 0x74,
|
||||
0x20, 0x63, 0x6f, 0x6e, 0x73, 0x74, 0x20, 0x6c, 0x6c, 0x61, 0x6d, 0x61,
|
||||
0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x49, 0x6e, 0x66, 0x6f, 0x20, 0x3d, 0x20,
|
||||
0x61, 0x73, 0x79, 0x6e, 0x63, 0x20, 0x28, 0x29, 0x20, 0x3d, 0x3e, 0x20,
|
||||
0x7b, 0x0a, 0x20, 0x20, 0x69, 0x66, 0x20, 0x28, 0x21, 0x67, 0x65, 0x6e,
|
||||
0x65, 0x72, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x5f, 0x73, 0x65, 0x74, 0x74,
|
||||
0x69, 0x6e, 0x67, 0x73, 0x29, 0x20, 0x7b, 0x0a, 0x20, 0x20, 0x20, 0x20,
|
||||
0x67, 0x65, 0x6e, 0x65, 0x72, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x5f, 0x73,
|
||||
0x65, 0x74, 0x74, 0x69, 0x6e, 0x67, 0x73, 0x20, 0x3d, 0x20, 0x61, 0x77,
|
||||
0x61, 0x69, 0x74, 0x20, 0x66, 0x65, 0x74, 0x63, 0x68, 0x28, 0x22, 0x2f,
|
||||
0x6d, 0x6f, 0x64, 0x65, 0x6c, 0x2e, 0x6a, 0x73, 0x6f, 0x6e, 0x22, 0x29,
|
||||
0x2e, 0x74, 0x68, 0x65, 0x6e, 0x28, 0x72, 0x20, 0x3d, 0x3e, 0x20, 0x72,
|
||||
0x2e, 0x6a, 0x73, 0x6f, 0x6e, 0x28, 0x29, 0x29, 0x3b, 0x0a, 0x20, 0x20,
|
||||
0x7d, 0x0a, 0x20, 0x20, 0x72, 0x65, 0x74, 0x75, 0x72, 0x6e, 0x20, 0x67,
|
||||
0x65, 0x6e, 0x65, 0x72, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x5f, 0x73, 0x65,
|
||||
0x74, 0x74, 0x69, 0x6e, 0x67, 0x73, 0x3b, 0x0a, 0x7d, 0x0a
|
||||
};
|
||||
unsigned int completion_js_len = 2275;
|
||||
unsigned int completion_js_len = 4462;
|
||||
|
||||
@ -4,10 +4,6 @@
|
||||
# get the directory of this script file
|
||||
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
|
||||
PUBLIC=$DIR/public
|
||||
OUTPUT=$DIR/templats.hpp
|
||||
|
||||
echo "// Generated file, do not edit" > $OUTPUT
|
||||
echo "" > $OUTPUT
|
||||
|
||||
echo "download js bundle files"
|
||||
curl https://npm.reversehttp.com/@preact/signals-core,@preact/signals,htm/preact,preact,preact/hooks > $PUBLIC/index.js
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -5,20 +5,29 @@ const paramDefaults = {
|
||||
stop: ["</s>"]
|
||||
};
|
||||
|
||||
/**
|
||||
* This function completes the input text using a llama dictionary.
|
||||
* @param {object} params - The parameters for the completion request.
|
||||
* @param {object} controller - an instance of AbortController if you need one, or null.
|
||||
* @param {function} callback - The callback function to call when the completion is done.
|
||||
* @returns {string} the completed text as a string. Ideally ignored, and you get at it via the callback.
|
||||
*/
|
||||
export const llamaComplete = async (params, controller, callback) => {
|
||||
let generation_settings = null;
|
||||
|
||||
|
||||
// Completes the prompt as a generator. Recommended for most use cases.
|
||||
//
|
||||
// Example:
|
||||
//
|
||||
// import { llama } from '/completion.js'
|
||||
//
|
||||
// const request = llama("Tell me a joke", {n_predict: 800})
|
||||
// for await (const chunk of request) {
|
||||
// document.write(chunk.data.content)
|
||||
// }
|
||||
//
|
||||
export async function* llama(prompt, params = {}, config = {}) {
|
||||
let controller = config.controller;
|
||||
|
||||
if (!controller) {
|
||||
controller = new AbortController();
|
||||
}
|
||||
const completionParams = { ...paramDefaults, ...params };
|
||||
|
||||
// we use fetch directly here becasue the built in fetchEventSource does not support POST
|
||||
const completionParams = { ...paramDefaults, ...params, prompt };
|
||||
|
||||
const response = await fetch("/completion", {
|
||||
method: 'POST',
|
||||
body: JSON.stringify(completionParams),
|
||||
@ -36,7 +45,6 @@ export const llamaComplete = async (params, controller, callback) => {
|
||||
let content = "";
|
||||
|
||||
try {
|
||||
|
||||
let cont = true;
|
||||
|
||||
while (cont) {
|
||||
@ -59,18 +67,21 @@ export const llamaComplete = async (params, controller, callback) => {
|
||||
result.data = JSON.parse(result.data);
|
||||
content += result.data.content;
|
||||
|
||||
// callack
|
||||
if (callback) {
|
||||
cont = callback(result) != false;
|
||||
}
|
||||
// yield
|
||||
yield result;
|
||||
|
||||
// if we got a stop token from server, we will break here
|
||||
if (result.data.stop) {
|
||||
if (result.data.generation_settings) {
|
||||
generation_settings = result.data.generation_settings;
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
if (e.name !== 'AbortError') {
|
||||
console.error("llama error: ", e);
|
||||
}
|
||||
throw e;
|
||||
}
|
||||
finally {
|
||||
@ -79,3 +90,79 @@ export const llamaComplete = async (params, controller, callback) => {
|
||||
|
||||
return content;
|
||||
}
|
||||
|
||||
// Call llama, return an event target that you can subcribe to
|
||||
//
|
||||
// Example:
|
||||
//
|
||||
// import { llamaEventTarget } from '/completion.js'
|
||||
//
|
||||
// const conn = llamaEventTarget(prompt)
|
||||
// conn.addEventListener("message", (chunk) => {
|
||||
// document.write(chunk.detail.content)
|
||||
// })
|
||||
//
|
||||
export const llamaEventTarget = (prompt, params = {}, config = {}) => {
|
||||
const eventTarget = new EventTarget();
|
||||
(async () => {
|
||||
let content = "";
|
||||
for await (const chunk of llama(prompt, params, config)) {
|
||||
if (chunk.data) {
|
||||
content += chunk.data.content;
|
||||
eventTarget.dispatchEvent(new CustomEvent("message", { detail: chunk.data }));
|
||||
}
|
||||
if (chunk.data.generation_settings) {
|
||||
eventTarget.dispatchEvent(new CustomEvent("generation_settings", { detail: chunk.data.generation_settings }));
|
||||
}
|
||||
if (chunk.data.timings) {
|
||||
eventTarget.dispatchEvent(new CustomEvent("timings", { detail: chunk.data.timings }));
|
||||
}
|
||||
}
|
||||
eventTarget.dispatchEvent(new CustomEvent("done", { detail: { content } }));
|
||||
})();
|
||||
return eventTarget;
|
||||
}
|
||||
|
||||
// Call llama, return a promise that resolves to the completed text. This does not support streaming
|
||||
//
|
||||
// Example:
|
||||
//
|
||||
// llamaPromise(prompt).then((content) => {
|
||||
// document.write(content)
|
||||
// })
|
||||
//
|
||||
// or
|
||||
//
|
||||
// const content = await llamaPromise(prompt)
|
||||
// document.write(content)
|
||||
//
|
||||
export const llamaPromise = (prompt, params = {}, config = {}) => {
|
||||
return new Promise(async (resolve, reject) => {
|
||||
let content = "";
|
||||
try {
|
||||
for await (const chunk of llama(prompt, params, config)) {
|
||||
content += chunk.data.content;
|
||||
}
|
||||
resolve(content);
|
||||
} catch (error) {
|
||||
reject(error);
|
||||
}
|
||||
});
|
||||
};
|
||||
|
||||
/**
|
||||
* (deprecated)
|
||||
*/
|
||||
export const llamaComplete = async (params, controller, callback) => {
|
||||
for await (const chunk of llama(params.prompt, params, { controller })) {
|
||||
callback(chunk);
|
||||
}
|
||||
}
|
||||
|
||||
// Get the model info from the server. This is useful for getting the context window and so on.
|
||||
export const llamaModelInfo = async () => {
|
||||
if (!generation_settings) {
|
||||
generation_settings = await fetch("/model.json").then(r => r.json());
|
||||
}
|
||||
return generation_settings;
|
||||
}
|
||||
|
||||
@ -6,7 +6,6 @@
|
||||
<title>llama.cpp - chat</title>
|
||||
|
||||
<style>
|
||||
|
||||
body {
|
||||
background-color: #fff;
|
||||
color: #000;
|
||||
@ -22,10 +21,6 @@
|
||||
height: 100%;
|
||||
}
|
||||
|
||||
header, footer {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
main {
|
||||
margin: 3px;
|
||||
display: flex;
|
||||
@ -99,6 +94,15 @@
|
||||
margin: 0.5em 0;
|
||||
display: block;
|
||||
}
|
||||
|
||||
header, footer {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
footer {
|
||||
font-size: 80%;
|
||||
color: #888;
|
||||
}
|
||||
</style>
|
||||
|
||||
<script type="module">
|
||||
@ -106,10 +110,10 @@
|
||||
html, h, signal, effect, computed, render, useSignal, useEffect, useRef
|
||||
} from '/index.js';
|
||||
|
||||
import { llamaComplete } from '/completion.js';
|
||||
import { llama } from '/completion.js';
|
||||
|
||||
const session = signal({
|
||||
prompt: "This is a conversation between user and llama, a friendly chatbot. respond in markdown.",
|
||||
prompt: "This is a conversation between user and llama, a friendly chatbot. respond in simple markdown.",
|
||||
template: "{{prompt}}\n\n{{history}}\n{{char}}:",
|
||||
historyTemplate: "{{name}}: {{message}}",
|
||||
transcript: [],
|
||||
@ -118,15 +122,6 @@
|
||||
user: "User",
|
||||
})
|
||||
|
||||
const transcriptUpdate = (transcript) => {
|
||||
session.value = {
|
||||
...session.value,
|
||||
transcript
|
||||
}
|
||||
}
|
||||
|
||||
const chatStarted = computed(() => session.value.transcript.length > 0)
|
||||
|
||||
const params = signal({
|
||||
n_predict: 400,
|
||||
temperature: 0.7,
|
||||
@ -136,8 +131,18 @@
|
||||
top_p: 0.5,
|
||||
})
|
||||
|
||||
const llamaStats = signal(null)
|
||||
const controller = signal(null)
|
||||
|
||||
const generating = computed(() => controller.value == null )
|
||||
const chatStarted = computed(() => session.value.transcript.length > 0)
|
||||
|
||||
const transcriptUpdate = (transcript) => {
|
||||
session.value = {
|
||||
...session.value,
|
||||
transcript
|
||||
}
|
||||
}
|
||||
|
||||
// simple template replace
|
||||
const template = (str, extraSettings) => {
|
||||
@ -158,7 +163,7 @@
|
||||
|
||||
transcriptUpdate([...session.value.transcript, ["{{user}}", msg]])
|
||||
|
||||
const payload = template(session.value.template, {
|
||||
const prompt = template(session.value.template, {
|
||||
message: msg,
|
||||
history: session.value.transcript.flatMap(([name, message]) => template(session.value.historyTemplate, {name, message})).join("\n"),
|
||||
});
|
||||
@ -168,22 +173,26 @@
|
||||
|
||||
const llamaParams = {
|
||||
...params.value,
|
||||
prompt: payload,
|
||||
stop: ["</s>", template("{{char}}:"), template("{{user}}:")],
|
||||
}
|
||||
|
||||
await llamaComplete(llamaParams, controller.value, (message) => {
|
||||
const data = message.data;
|
||||
for await (const chunk of llama(prompt, llamaParams, { controller: controller.value })) {
|
||||
const data = chunk.data;
|
||||
currentMessage += data.content;
|
||||
|
||||
// remove leading whitespace
|
||||
currentMessage = currentMessage.replace(/^\s+/, "")
|
||||
|
||||
transcriptUpdate([...history, ["{{char}}", currentMessage]])
|
||||
|
||||
if (data.stop) {
|
||||
console.log("-->", data, ' response was:', currentMessage, 'transcript state:', session.value.transcript);
|
||||
console.log("Completion finished: '", currentMessage, "', summary: ", data);
|
||||
}
|
||||
|
||||
if (data.timings) {
|
||||
llamaStats.value = data.timings;
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
controller.value = null;
|
||||
}
|
||||
@ -220,7 +229,6 @@
|
||||
<form onsubmit=${submit}>
|
||||
<div>
|
||||
<textarea type="text" rows=2 onkeypress=${enterSubmits} value="${message}" oninput=${(e) => message.value = e.target.value} placeholder="Say something..."/>
|
||||
|
||||
</div>
|
||||
<div class="right">
|
||||
<button type="submit" disabled=${!generating.value} >Send</button>
|
||||
@ -243,7 +251,7 @@
|
||||
}, [messages])
|
||||
|
||||
const chatLine = ([user, msg]) => {
|
||||
return html`<p key=${msg}><strong>${template(user)}:</strong> <${Markdown} text=${template(msg)} /></p>`
|
||||
return html`<p key=${msg}><strong>${template(user)}:</strong> <${Markdownish} text=${template(msg)} /></p>`
|
||||
};
|
||||
|
||||
return html`
|
||||
@ -313,7 +321,8 @@
|
||||
</form>
|
||||
`
|
||||
}
|
||||
const Markdown = (params) => {
|
||||
// poor mans markdown replacement
|
||||
const Markdownish = (params) => {
|
||||
const md = params.text
|
||||
.replace(/^#{1,6} (.*)$/gim, '<h3>$1</h3>')
|
||||
.replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>')
|
||||
@ -324,7 +333,18 @@ const Markdown = (params) => {
|
||||
.replace(/`(.*?)`/g, '<code>$1</code>')
|
||||
.replace(/\n/gim, '<br />');
|
||||
return html`<span dangerouslySetInnerHTML=${{ __html: md }} />`;
|
||||
};
|
||||
};
|
||||
|
||||
const ModelGenerationInfo = (params) => {
|
||||
if (!llamaStats.value) {
|
||||
return html`<span/>`
|
||||
}
|
||||
return html`
|
||||
<span>
|
||||
${llamaStats.value.predicted_per_token_ms.toFixed()}ms per token, ${llamaStats.value.predicted_per_second.toFixed(2)} tokens per second
|
||||
</span>
|
||||
`
|
||||
}
|
||||
|
||||
function App(props) {
|
||||
|
||||
@ -338,12 +358,13 @@ const Markdown = (params) => {
|
||||
<${chatStarted.value ? ChatLog : ConfigForm} />
|
||||
</main>
|
||||
|
||||
<footer id="write">
|
||||
<section id="write">
|
||||
<${MessageInput} />
|
||||
</footer>
|
||||
</section>
|
||||
|
||||
<footer>
|
||||
<p>Powered by <a href="https://github.com/ggerganov/llama.cpp">llama.cpp</a> and <a href="https://ggml.ai">ggml.ai</a></p>
|
||||
<p><${ModelGenerationInfo} /></p>
|
||||
<p>Powered by <a href="https://github.com/ggerganov/llama.cpp">llama.cpp</a> and <a href="https://ggml.ai">ggml.ai</a>.</p>
|
||||
</footer>
|
||||
</div>
|
||||
`;
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
32
llama.cpp
32
llama.cpp
@ -3480,23 +3480,35 @@ llama_token llama_token_nl() {
|
||||
return 13;
|
||||
}
|
||||
|
||||
struct llama_timings llama_get_timings(struct llama_context * ctx) {
|
||||
struct llama_timings result = {
|
||||
/*.t_start_ms =*/ 1e-3 * ctx->t_start_us,
|
||||
/*.t_end_ms =*/ 1.00 * ggml_time_ms(),
|
||||
/*.t_load_ms =*/ 1e-3 * ctx->t_load_us,
|
||||
/*.t_sample_ms =*/ 1e-3 * ctx->t_sample_us,
|
||||
/*.t_p_eval_ms =*/ 1e-3 * ctx->t_p_eval_us,
|
||||
/*.t_eval_ms =*/ 1e-3 * ctx->t_eval_us,
|
||||
|
||||
/*.n_sample =*/ std::max(1, ctx->n_sample),
|
||||
/*.n_p_eval =*/ std::max(1, ctx->n_p_eval),
|
||||
/*.n_eval =*/ std::max(1, ctx->n_eval),
|
||||
};
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
void llama_print_timings(struct llama_context * ctx) {
|
||||
const int64_t t_end_us = ggml_time_us();
|
||||
|
||||
const int32_t n_sample = std::max(1, ctx->n_sample);
|
||||
const int32_t n_eval = std::max(1, ctx->n_eval);
|
||||
const int32_t n_p_eval = std::max(1, ctx->n_p_eval);
|
||||
const llama_timings timings = llama_get_timings(ctx);
|
||||
|
||||
fprintf(stderr, "\n");
|
||||
fprintf(stderr, "%s: load time = %8.2f ms\n", __func__, ctx->t_load_us / 1000.0);
|
||||
fprintf(stderr, "%s: load time = %8.2f ms\n", __func__, timings.t_load_ms);
|
||||
fprintf(stderr, "%s: sample time = %8.2f ms / %5d runs (%8.2f ms per token, %8.2f tokens per second)\n",
|
||||
__func__, 1e-3 * ctx->t_sample_us, n_sample, 1e-3 * ctx->t_sample_us / n_sample, 1e6 / ctx->t_sample_us * n_sample);
|
||||
__func__, timings.t_sample_ms, timings.n_sample, timings.t_sample_ms / timings.n_sample, 1e3 / timings.t_sample_ms * timings.n_sample);
|
||||
fprintf(stderr, "%s: prompt eval time = %8.2f ms / %5d tokens (%8.2f ms per token, %8.2f tokens per second)\n",
|
||||
__func__, 1e-3 * ctx->t_p_eval_us, n_p_eval, 1e-3 * ctx->t_p_eval_us / n_p_eval, 1e6 / ctx->t_p_eval_us * n_p_eval);
|
||||
__func__, timings.t_p_eval_ms, timings.n_p_eval, timings.t_p_eval_ms / timings.n_p_eval, 1e3 / timings.t_p_eval_ms * timings.n_p_eval);
|
||||
fprintf(stderr, "%s: eval time = %8.2f ms / %5d runs (%8.2f ms per token, %8.2f tokens per second)\n",
|
||||
__func__, 1e-3 * ctx->t_eval_us, n_eval, 1e-3 * ctx->t_eval_us / n_eval, 1e6 / ctx->t_eval_us * n_eval);
|
||||
fprintf(stderr, "%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0);
|
||||
__func__, timings.t_eval_ms, timings.n_eval, timings.t_eval_ms / timings.n_eval, 1e3 / timings.t_eval_ms * timings.n_eval);
|
||||
fprintf(stderr, "%s: total time = %8.2f ms\n", __func__, (timings.t_end_ms - timings.t_start_ms));
|
||||
}
|
||||
|
||||
void llama_reset_timings(struct llama_context * ctx) {
|
||||
|
||||
15
llama.h
15
llama.h
@ -134,6 +134,20 @@ extern "C" {
|
||||
bool quantize_output_tensor; // quantize output.weight
|
||||
} llama_model_quantize_params;
|
||||
|
||||
// performance timing information
|
||||
struct llama_timings {
|
||||
double t_start_ms;
|
||||
double t_end_ms;
|
||||
double t_load_ms;
|
||||
double t_sample_ms;
|
||||
double t_p_eval_ms;
|
||||
double t_eval_ms;
|
||||
|
||||
int32_t n_sample;
|
||||
int32_t n_p_eval;
|
||||
int32_t n_eval;
|
||||
};
|
||||
|
||||
LLAMA_API struct llama_context_params llama_context_default_params();
|
||||
LLAMA_API struct llama_model_quantize_params llama_model_quantize_default_params();
|
||||
|
||||
@ -331,6 +345,7 @@ extern "C" {
|
||||
LLAMA_API llama_token llama_sample_token(struct llama_context * ctx, llama_token_data_array * candidates);
|
||||
|
||||
// Performance information
|
||||
LLAMA_API struct llama_timings llama_get_timings(struct llama_context * ctx);
|
||||
LLAMA_API void llama_print_timings(struct llama_context * ctx);
|
||||
LLAMA_API void llama_reset_timings(struct llama_context * ctx);
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user