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Expose generation timings from server & update completions.js (#2116)

Browse Source 
* 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 2023-07-05 16:51:13 -04:00 committed by GitHub
parent 983b555e9d
commit 31cfbb1013
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9 changed files with 1921 additions and 1363 deletions
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35
examples/server/README.md
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@ -26,20 +26,17 @@ Command line options:
## Build ## Build
Build llama.cpp with server from repository root with either make or CMake. server is build alongside everything else from the root of the project
- Using `make`: - Using `make`:
```bash ```bash
LLAMA_BUILD_SERVER=1 make make
``` ```
- Using `CMake`: - Using `CMake`:
```bash ```bash
mkdir build-server
cd build-server
cmake -DLLAMA_BUILD_SERVER=ON ..
cmake --build . --config Release cmake --build . --config Release
``` ```
@ -208,24 +205,30 @@ openai.api_base = "http://<Your api-server IP>:port"
Then you can utilize llama.cpp as an OpenAI's **chat.completion** or **text_completion** API Then you can utilize llama.cpp as an OpenAI's **chat.completion** or **text_completion** API
### Extending the Web Front End ### Extending or building alternative Web Front End
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: 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.
``` Read the documentation in `/completion.js` to see convenient ways to access llama.
A simple example is below:
```html
<html> <html>
<body> <body>
<pre> <pre>
<script type="module"> <script type="module">
import { llamaComplete } from '/completion.js' import { llama } from '/completion.js'
llamaComplete({ const prompt = `### Instruction:
prompt: "### Instruction:\nWrite dad jokes, each one paragraph. You can use html formatting if needed.\n\n### Response:", Write dad jokes, each one paragraph.
n_predict: 1024, You can use html formatting if needed.
},
null, ### Response:`
(chunk) => document.write(chunk.data.content)
) for await (const chunk of llama(prompt)) {
document.write(chunk.data.content)
}
</script> </script>
</pre> </pre>
</body> </body>

548
examples/server/completion.js.hpp
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@ -7,187 +7,369 @@ unsigned char completion_js[] = {
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}; };
unsigned int completion_js_len = 2275; unsigned int completion_js_len = 4462;

4
examples/server/deps.sh
View File

@ -4,10 +4,6 @@
# get the directory of this script file # get the directory of this script file
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
PUBLIC=$DIR/public PUBLIC=$DIR/public
OUTPUT=$DIR/templats.hpp
echo "// Generated file, do not edit" > $OUTPUT
echo "" > $OUTPUT
echo "download js bundle files" echo "download js bundle files"
curl https://npm.reversehttp.com/@preact/signals-core,@preact/signals,htm/preact,preact,preact/hooks > $PUBLIC/index.js curl https://npm.reversehttp.com/@preact/signals-core,@preact/signals,htm/preact,preact,preact/hooks > $PUBLIC/index.js

1581
examples/server/index.html.hpp
View File

File diff suppressed because it is too large Load Diff

119
examples/server/public/completion.js
View File

@ -5,20 +5,29 @@ const paramDefaults = {
stop: ["</s>"] stop: ["</s>"]
}; };
/** let generation_settings = null;
* 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. // Completes the prompt as a generator. Recommended for most use cases.
* @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. // Example:
*/ //
export const llamaComplete = async (params, controller, callback) => { // 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) { if (!controller) {
controller = new AbortController(); 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", { const response = await fetch("/completion", {
method: 'POST', method: 'POST',
body: JSON.stringify(completionParams), body: JSON.stringify(completionParams),
@ -36,7 +45,6 @@ export const llamaComplete = async (params, controller, callback) => {
let content = ""; let content = "";
try { try {
let cont = true; let cont = true;
while (cont) { while (cont) {
@ -59,18 +67,21 @@ export const llamaComplete = async (params, controller, callback) => {
result.data = JSON.parse(result.data); result.data = JSON.parse(result.data);
content += result.data.content; content += result.data.content;
// callack // yield
if (callback) { yield result;
cont = callback(result) != false;
}
// if we got a stop token from server, we will break here // if we got a stop token from server, we will break here
if (result.data.stop) { if (result.data.stop) {
if (result.data.generation_settings) {
generation_settings = result.data.generation_settings;
}
break; break;
} }
} }
} catch (e) { } catch (e) {
console.error("llama error: ", e); if (e.name !== 'AbortError') {
console.error("llama error: ", e);
}
throw e; throw e;
} }
finally { finally {
@ -79,3 +90,79 @@ export const llamaComplete = async (params, controller, callback) => {
return content; 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;
}

129
examples/server/public/index.html
View File

@ -6,7 +6,6 @@
<title>llama.cpp - chat</title> <title>llama.cpp - chat</title>
<style> <style>
body { body {
background-color: #fff; background-color: #fff;
color: #000; color: #000;
@ -22,10 +21,6 @@
height: 100%; height: 100%;
} }
header, footer {
text-align: center;
}
main { main {
margin: 3px; margin: 3px;
display: flex; display: flex;
@ -99,6 +94,15 @@
margin: 0.5em 0; margin: 0.5em 0;
display: block; display: block;
} }
header, footer {
text-align: center;
}
footer {
font-size: 80%;
color: #888;
}
</style> </style>
<script type="module"> <script type="module">
@ -106,10 +110,10 @@
html, h, signal, effect, computed, render, useSignal, useEffect, useRef html, h, signal, effect, computed, render, useSignal, useEffect, useRef
} from '/index.js'; } from '/index.js';
import { llamaComplete } from '/completion.js'; import { llama } from '/completion.js';
const session = signal({ 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}}:", template: "{{prompt}}\n\n{{history}}\n{{char}}:",
historyTemplate: "{{name}}: {{message}}", historyTemplate: "{{name}}: {{message}}",
transcript: [], transcript: [],
@ -118,15 +122,6 @@
user: "User", user: "User",
}) })
const transcriptUpdate = (transcript) => {
session.value = {
...session.value,
transcript
}
}
const chatStarted = computed(() => session.value.transcript.length > 0)
const params = signal({ const params = signal({
n_predict: 400, n_predict: 400,
temperature: 0.7, temperature: 0.7,
@ -136,8 +131,18 @@
top_p: 0.5, top_p: 0.5,
}) })
const llamaStats = signal(null)
const controller = signal(null) const controller = signal(null)
const generating = computed(() => controller.value == 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 // simple template replace
const template = (str, extraSettings) => { const template = (str, extraSettings) => {
@ -158,7 +163,7 @@
transcriptUpdate([...session.value.transcript, ["{{user}}", msg]]) transcriptUpdate([...session.value.transcript, ["{{user}}", msg]])
const payload = template(session.value.template, { const prompt = template(session.value.template, {
message: msg, message: msg,
history: session.value.transcript.flatMap(([name, message]) => template(session.value.historyTemplate, {name, message})).join("\n"), history: session.value.transcript.flatMap(([name, message]) => template(session.value.historyTemplate, {name, message})).join("\n"),
}); });
@ -168,22 +173,26 @@
const llamaParams = { const llamaParams = {
...params.value, ...params.value,
prompt: payload,
stop: ["</s>", template("{{char}}:"), template("{{user}}:")], stop: ["</s>", template("{{char}}:"), template("{{user}}:")],
} }
await llamaComplete(llamaParams, controller.value, (message) => { for await (const chunk of llama(prompt, llamaParams, { controller: controller.value })) {
const data = message.data; const data = chunk.data;
currentMessage += data.content; currentMessage += data.content;
// remove leading whitespace // remove leading whitespace
currentMessage = currentMessage.replace(/^\s+/, "") currentMessage = currentMessage.replace(/^\s+/, "")
transcriptUpdate([...history, ["{{char}}", currentMessage]]) transcriptUpdate([...history, ["{{char}}", currentMessage]])
if (data.stop) { 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; controller.value = null;
} }
@ -219,13 +228,12 @@
return html` return html`
<form onsubmit=${submit}> <form onsubmit=${submit}>
<div> <div>
<textarea type="text" rows=2 onkeypress=${enterSubmits} value="${message}" oninput=${(e) => message.value = e.target.value} placeholder="Say something..."/> <textarea type="text" rows=2 onkeypress=${enterSubmits} value="${message}" oninput=${(e) => message.value = e.target.value} placeholder="Say something..."/>
</div> </div>
<div class="right"> <div class="right">
<button type="submit" disabled=${!generating.value} >Send</button> <button type="submit" disabled=${!generating.value} >Send</button>
<button onclick=${stop} disabled=${generating}>Stop</button> <button onclick=${stop} disabled=${generating}>Stop</button>
<button onclick=${reset}>Reset</button> <button onclick=${reset}>Reset</button>
</div> </div>
</form> </form>
` `
@ -243,7 +251,7 @@
}, [messages]) }, [messages])
const chatLine = ([user, msg]) => { 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` return html`
@ -313,39 +321,52 @@
</form> </form>
` `
} }
const Markdown = (params) => { // poor mans markdown replacement
const md = params.text const Markdownish = (params) => {
.replace(/^#{1,6} (.*)$/gim, '<h3>$1</h3>') const md = params.text
.replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>') .replace(/^#{1,6} (.*)$/gim, '<h3>$1</h3>')
.replace(/__(.*?)__/g, '<strong>$1</strong>') .replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>')
.replace(/\*(.*?)\*/g, '<em>$1</em>') .replace(/__(.*?)__/g, '<strong>$1</strong>')
.replace(/_(.*?)_/g, '<em>$1</em>') .replace(/\*(.*?)\*/g, '<em>$1</em>')
.replace(/```.*?\n([\s\S]*?)```/g, '<pre><code>$1</code></pre>') .replace(/_(.*?)_/g, '<em>$1</em>')
.replace(/`(.*?)`/g, '<code>$1</code>') .replace(/```.*?\n([\s\S]*?)```/g, '<pre><code>$1</code></pre>')
.replace(/\n/gim, '<br />'); .replace(/`(.*?)`/g, '<code>$1</code>')
return html`<span dangerouslySetInnerHTML=${{ __html: md }} />`; .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, ${llamaStats.value.predicted_per_second.toFixed(2)} tokens per second
</span>
`
}
function App(props) { function App(props) {
return html` return html`
<div id="container"> <div id="container">
<header> <header>
<h1>llama.cpp</h1> <h1>llama.cpp</h1>
</header> </header>
<main id="content"> <main id="content">
<${chatStarted.value ? ChatLog : ConfigForm} /> <${chatStarted.value ? ChatLog : ConfigForm} />
</main> </main>
<footer id="write"> <section id="write">
<${MessageInput} /> <${MessageInput} />
</footer> </section>
<footer> <footer>
<p>Powered by <a href="https://github.com/ggerganov/llama.cpp">llama.cpp</a> and <a href="https://ggml.ai">ggml.ai</a></p> <p><${ModelGenerationInfo} /></p>
</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>
</div> </footer>
</div>
`; `;
} }

821
examples/server/server.cpp
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File diff suppressed because it is too large Load Diff

32
llama.cpp
View File

@ -3480,23 +3480,35 @@ llama_token llama_token_nl() {
return 13; 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) { void llama_print_timings(struct llama_context * ctx) {
const int64_t t_end_us = ggml_time_us(); const llama_timings timings = llama_get_timings(ctx);
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);
fprintf(stderr, "\n"); 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", 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", 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", 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); __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__, (t_end_us - ctx->t_start_us)/1000.0); 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) { void llama_reset_timings(struct llama_context * ctx) {

15
llama.h
View File

@ -134,6 +134,20 @@ extern "C" {
bool quantize_output_tensor; // quantize output.weight bool quantize_output_tensor; // quantize output.weight
} llama_model_quantize_params; } 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_context_params llama_context_default_params();
LLAMA_API struct llama_model_quantize_params llama_model_quantize_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); LLAMA_API llama_token llama_sample_token(struct llama_context * ctx, llama_token_data_array * candidates);
// Performance information // 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_print_timings(struct llama_context * ctx);
LLAMA_API void llama_reset_timings(struct llama_context * ctx); LLAMA_API void llama_reset_timings(struct llama_context * ctx);