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separate llama.cpp server api into a different source file

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master
Alessandro Mauri 11 months ago
parent 0a493294cf
commit 960b2190bf
6 changed files with 350 additions and 165 deletions
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  1. 2
      TODO.md
  2. 17
      package.json
  3. 58
      src/common.ts
  4. 127
      src/extension.ts
  5. 189
      src/llamacpp-api.ts
  6. 116
      src/openai-api.ts

2
TODO.md
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@ -1,4 +1,4 @@
[x] - in extensions.json add suffix for languages that require it such as css where comments are: /* stuff */ [x] - in extensions.json add suffix for languages that require it such as css where comments are: /_ stuff _/
[] - test cancel token [] - test cancel token
[] - add fill in middle [] - add fill in middle
[x] - add config option to disable the extension [x] - add config option to disable the extension

17
package.json
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@ -223,6 +223,16 @@
"dumbpilot.llamaSystemPrompt": { "dumbpilot.llamaSystemPrompt": {
"type": "string", "type": "string",
"description": "The system prompt that the model considers at the beginning of every request, used by instruct models" "description": "The system prompt that the model considers at the beginning of every request, used by instruct models"
},
"dumbpilot.llamaUseOpenAIAPI": {
"type": "boolean",
"default": true,
"description": "Use the OpenAI API to make requests to the server instead of the llama.cpp server API"
},
"dumbpilot.llamaModelName": {
"type": "string",
"default": "deepseek-coder-6.7B-base.gguf",
"description": "Name of the model to use, only works in OpenAI API mode"
} }
} }
} }
@ -246,5 +256,12 @@
"mocha": "^10.2.0", "mocha": "^10.2.0",
"typescript": "^5.2.2", "typescript": "^5.2.2",
"@vscode/test-electron": "^2.3.6" "@vscode/test-electron": "^2.3.6"
},
"prettier": {
"tabWidth": 4,
"printWidth": 100,
"useTabs": true,
"singleQuote": true,
"trailingComma": "es5"
} }
} }

58
src/common.ts
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@ -0,0 +1,58 @@
import * as vscode from 'vscode';
// common data structures and functions
export type FetchErrorCause = {
errno: number;
code: string;
syscall: string;
address: string;
port: number;
};
// a summary of the received data
export type ResponseData = {
content: string;
tokens: number;
time: number;
};
// Show a message notification with a set timeout
export async function showMessageWithTimeout(message: string, timeout: number): Promise<void> {
void vscode.window.withProgress(
{
location: vscode.ProgressLocation.Notification,
title: message,
cancellable: false,
},
(progress, token) => {
token.onCancellationRequested(() => {});
// This is magic I don't understand
const p = new Promise<void>((resolve) => {
setTimeout(resolve, timeout);
});
return p;
}
);
}
// show a message on the status bar until the promise is resolved
export async function showPendingStatusBar(
message: string,
operation: Promise<any>
): Promise<void> {
void vscode.window
.withProgress(
{
location: vscode.ProgressLocation.Window,
title: message,
},
() => operation
)
.then(
(aok) => {},
(err) => {}
);
// we already resolve the operation elsewhere
}

127
src/extension.ts
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@ -1,17 +1,19 @@
import { ok } from 'assert'; import { ok } from 'assert';
import * as vscode from 'vscode'; import * as vscode from 'vscode';
import commentPrefix from './comments.json'; import commentPrefix from './comments.json';
import {createLlamacppRequest, llamaData, llamaRequest, llamacppRequestEndpoint} from './llamacpp-api'; import {
LlamaData,
LlamaRequest,
type fetchErrorCause = { createLlamacppRequest,
errno: number, llamacppRequestEndpoint,
code: string, llamacppMakeRequest,
syscall: string, } from './llamacpp-api';
address: string, import {
port: number FetchErrorCause,
}; ResponseData,
showMessageWithTimeout,
showPendingStatusBar,
} from './common';
// clean up the document // clean up the document
function clean_text(txt: string): string { function clean_text(txt: string): string {
@ -24,56 +26,26 @@ function clean_text(txt: string): string {
return txt; return txt;
} }
// Show a message notification with a set timeout
async function showMessageWithTimeout(message: string, timeout: number): Promise<void> {
void vscode.window.withProgress(
{
location: vscode.ProgressLocation.Notification,
title: message,
cancellable: false,
}, (progress, token) => {
token.onCancellationRequested(() => {});
// This is magic I don't understand
const p = new Promise<void>((resolve) => {
setTimeout(resolve, timeout);
});
return p;
});
};
// show a message on the status bar until the promise is resolved
async function showPendingStatusBar(message: string, operation: Promise<any>): Promise<void> {
void vscode.window.withProgress(
{
location: vscode.ProgressLocation.Window,
title: message,
}, () => operation ).then((aok) => {}, (err) => {});
// we already resolve the operation elsewhere
}
export function activate(context: vscode.ExtensionContext) { export function activate(context: vscode.ExtensionContext) {
console.log('dumbpilot is now active'); console.log('dumbpilot is now active');
let config = vscode.workspace.getConfiguration("dumbpilot"); let config = vscode.workspace.getConfiguration('dumbpilot');
// handle completion changes // handle completion changes
context.subscriptions.push(vscode.workspace.onDidChangeConfiguration(e => { context.subscriptions.push(
config = vscode.workspace.getConfiguration("dumbpilot"); vscode.workspace.onDidChangeConfiguration((e) => {
})); config = vscode.workspace.getConfiguration('dumbpilot');
})
);
// TODO: work with local configurations // TODO: work with local configurations
let disposable = vscode.commands.registerCommand("dumbpilot.enableCompletion", () => { let disposable = vscode.commands.registerCommand('dumbpilot.enableCompletion', () => {
config.update("completionEnabled", true); config.update('completionEnabled', true);
}); });
context.subscriptions.push(disposable); context.subscriptions.push(disposable);
disposable = vscode.commands.registerCommand("dumbpilot.disableCompletion", () => { disposable = vscode.commands.registerCommand('dumbpilot.disableCompletion', () => {
config.update("completionEnabled", false); config.update('completionEnabled', false);
}); });
// Register a new provider of inline completions, this does not decide how it is invoked // Register a new provider of inline completions, this does not decide how it is invoked
@ -81,9 +53,8 @@ export function activate(context: vscode.ExtensionContext) {
// https://github.com/microsoft/vscode-extension-samples/blob/main/inline-completions/src/extension.ts // https://github.com/microsoft/vscode-extension-samples/blob/main/inline-completions/src/extension.ts
const provider: vscode.InlineCompletionItemProvider = { const provider: vscode.InlineCompletionItemProvider = {
async provideInlineCompletionItems(document, position, context, token) { async provideInlineCompletionItems(document, position, context, token) {
// disable if predictive completion is disabled // disable if predictive completion is disabled
if (config.get("completionEnabled") as boolean === false) { if ((config.get('completionEnabled') as boolean) === false) {
return null; return null;
} }
@ -95,14 +66,14 @@ export function activate(context: vscode.ExtensionContext) {
// FIXME: I don't know if this works // FIXME: I don't know if this works
token.onCancellationRequested(() => { token.onCancellationRequested(() => {
console.log("dumbpilot: operation cancelled, may still be running on the server"); console.log('dumbpilot: operation cancelled, may still be running on the server');
return null; return null;
}); });
//console.log('dumbpilot: completion invoked at position: line=' + position.line + ' char=' + position.character); //console.log('dumbpilot: completion invoked at position: line=' + position.line + ' char=' + position.character);
const result: vscode.InlineCompletionList = { const result: vscode.InlineCompletionList = {
items: [] items: [],
}; };
// Get the document's text and position to send to the model // Get the document's text and position to send to the model
@ -127,45 +98,15 @@ export function activate(context: vscode.ExtensionContext) {
// FIXME: is there a more efficient way? // FIXME: is there a more efficient way?
doc_before = pfx + ' ' + fname + sfx + '\n' + doc_before; doc_before = pfx + ' ' + fname + sfx + '\n' + doc_before;
const request: llamaRequest = createLlamacppRequest(config, doc_before, doc_after); // actially make the request
console.log(JSON.stringify(request)); const request: LlamaRequest = createLlamacppRequest(config, doc_before, doc_after);
const endpoint: string = llamacppRequestEndpoint(config);
let data: llamaData; let data: ResponseData = await llamacppMakeRequest(request, endpoint);
// try to send the request to the running server
try {
const response_promise = fetch(
llamacppRequestEndpoint(config),
{
method: 'POST',
headers: {
'content-type': 'application/json; charset=UTF-8'
},
body: JSON.stringify(request)
}
);
showPendingStatusBar("dumbpilot waiting", response_promise); result.items.push({
const response = await response_promise; insertText: data.content,
if (response.ok === false) { range: new vscode.Range(position, position),
throw new Error("llama server request is not ok??"); });
}
data = await response.json() as llamaData;
const gen_tokens = data.timings.predicted_n;
const gen_time = (data.timings.predicted_ms / 1000).toFixed(2);
showMessageWithTimeout(`predicted ${gen_tokens} tokens in ${gen_time} seconds`, 1500);
} catch (e: any) {
const err = e as TypeError;
const cause: fetchErrorCause = err.cause as fetchErrorCause;
const estr: string = err.message + ' ' + cause.code + ' at ' + cause.address + ':' + cause.port;
// let the user know something went wrong
// TODO: maybe add a retry action or something
showMessageWithTimeout('dumbpilot error: ' + estr, 3000);
return null;
};
result.items.push({insertText: data.content, range: new vscode.Range(position, position)});
return result; return result;
}, },
}; };

189
src/llamacpp-api.ts
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@ -1,83 +1,91 @@
import * as vscode from 'vscode'; import * as vscode from 'vscode';
import './common';
import {
FetchErrorCause,
ResponseData,
showMessageWithTimeout,
showPendingStatusBar,
} from './common';
// llama.cpp server response format // llama.cpp server response format
export type llamaData = { export type LlamaData = {
content: string, content: string;
generation_settings: JSON, generation_settings: JSON;
model: string, model: string;
prompt: string, prompt: string;
stopped_eos: boolean, stopped_eos: boolean;
stopped_limit: boolean, stopped_limit: boolean;
stopped_word: boolean, stopped_word: boolean;
stopping_word: string, stopping_word: string;
timings: { timings: {
predicted_ms: number, predicted_ms: number;
predicted_n: number, predicted_n: number;
predicted_per_second: number, predicted_per_second: number;
predicted_per_token_ms: number, predicted_per_token_ms: number;
prompt_ms: number, prompt_ms: number;
prompt_n: number, prompt_n: number;
prompt_per_second: number, prompt_per_second: number;
prompt_per_token_ms: number prompt_per_token_ms: number;
},
tokens_cached: number,
tokens_evaluated: number,
tokens_predicted: number,
truncated: boolean
}; };
tokens_cached: number;
export type llamaRequest = { tokens_evaluated: number;
n_predict: number, tokens_predicted: number;
mirostat: number, truncated: boolean;
repeat_penalty: number,
frequency_penalty: number,
presence_penalty: number,
repeat_last_n: number,
temperature: number,
top_p: number,
top_k: number,
typical_p: number,
tfs_z: number,
seed: number,
stream: boolean,
cache_prompt: boolean,
prompt?: string,
input_prefix?: string,
input_suffix?: string
}; };
export type LlamaRequest = {
n_predict: number;
mirostat: number;
repeat_penalty: number;
frequency_penalty: number;
presence_penalty: number;
repeat_last_n: number;
temperature: number;
top_p: number;
top_k: number;
typical_p: number;
tfs_z: number;
seed: number;
stream: boolean;
cache_prompt: boolean;
prompt?: string;
input_prefix?: string;
input_suffix?: string;
};
export function createLlamacppRequest(config: vscode.WorkspaceConfiguration, doc_before: string, doc_after: string): llamaRequest export function createLlamacppRequest(
{ config: vscode.WorkspaceConfiguration,
let request: llamaRequest = { doc_before: string,
n_predict: config.get("llamaMaxtokens") as number, doc_after: string
mirostat: config.get("llamaMirostat") as number, ): LlamaRequest {
repeat_penalty: config.get("llamaRepeatPenalty") as number, let request: LlamaRequest = {
frequency_penalty: config.get("llamaFrequencyPenalty,") as number, n_predict: config.get('llamaMaxtokens') as number,
presence_penalty: config.get("llamaPresencePenalty,") as number, mirostat: config.get('llamaMirostat') as number,
repeat_last_n: config.get("llamaRepeatCtx,") as number, repeat_penalty: config.get('llamaRepeatPenalty') as number,
temperature: config.get("llamaTemperature") as number, frequency_penalty: config.get('llamaFrequencyPenalty,') as number,
top_p: config.get("llamaTop_p") as number, presence_penalty: config.get('llamaPresencePenalty,') as number,
top_k: config.get("llamaTop_k") as number, repeat_last_n: config.get('llamaRepeatCtx,') as number,
typical_p: config.get("llamaTypical_p") as number, temperature: config.get('llamaTemperature') as number,
tfs_z: config.get("llamaTailfree_z,") as number, top_p: config.get('llamaTop_p') as number,
seed: config.get("llamaSeed") as number, top_k: config.get('llamaTop_k') as number,
typical_p: config.get('llamaTypical_p') as number,
tfs_z: config.get('llamaTailfree_z,') as number,
seed: config.get('llamaSeed') as number,
stream: false, stream: false,
cache_prompt: config.get("llamaCachePrompt") as boolean cache_prompt: config.get('llamaCachePrompt') as boolean,
}; };
const fim = config.get("fimEnabled") as boolean; const fim = config.get('fimEnabled') as boolean;
const fimRequest = config.get("useFillInMiddleRequest") as boolean; const fimRequest = config.get('useFillInMiddleRequest') as boolean;
if (fim === true) { if (fim === true) {
if (fimRequest === true) { if (fimRequest === true) {
request.input_prefix = doc_before; request.input_prefix = doc_before;
request.input_suffix = doc_after; request.input_suffix = doc_after;
} else { } else {
const fim_beg = config.get("fimBeginString") as string; const fim_beg = config.get('fimBeginString') as string;
const fim_hole = config.get("fimHoleString") as string; const fim_hole = config.get('fimHoleString') as string;
const fim_end = config.get("fimEndString") as string; const fim_end = config.get('fimEndString') as string;
request.prompt = fim_beg + doc_before + fim_hole + doc_after + fim_end; request.prompt = fim_beg + doc_before + fim_hole + doc_after + fim_end;
} }
} else { } else {
@ -87,11 +95,10 @@ export function createLlamacppRequest(config: vscode.WorkspaceConfiguration, doc
return request; return request;
} }
export function llamacppRequestEndpoint(config: vscode.WorkspaceConfiguration): string export function llamacppRequestEndpoint(config: vscode.WorkspaceConfiguration): string {
{ const fim = config.get('fimEnabled') as boolean;
const fim = config.get("fimEnabled") as boolean; const fimRequest = config.get('useFillInMiddleRequest') as boolean;
const fimRequest = config.get("useFillInMiddleRequest") as boolean; let req_str: string = config.get('llamaHost') as string;
let req_str: string = config.get("llamaHost") as string;
if (fim === true && fimRequest === true) { if (fim === true && fimRequest === true) {
req_str += '/infill'; req_str += '/infill';
@ -101,3 +108,49 @@ export function llamacppRequestEndpoint(config: vscode.WorkspaceConfiguration):
return req_str; return req_str;
} }
export async function llamacppMakeRequest(
request: LlamaRequest,
endpoint: string
): Promise<ResponseData> {
let ret: ResponseData = {
content: '',
tokens: 0,
time: 0,
};
let data: LlamaData;
// try to send the request to the running server
try {
const response_promise = fetch(endpoint, {
method: 'POST',
headers: {
'content-type': 'application/json; charset=UTF-8',
},
body: JSON.stringify(request),
});
showPendingStatusBar('dumbpilot waiting', response_promise);
const response = await response_promise;
if (response.ok === false) {
throw new Error('llama server request is not ok??');
}
data = (await response.json()) as LlamaData;
const gen_tokens = data.timings.predicted_n;
const gen_time = (data.timings.predicted_ms / 1000).toFixed(2);
showMessageWithTimeout(`predicted ${gen_tokens} tokens in ${gen_time} seconds`, 1500);
ret.content = data.content;
ret.tokens = data.tokens_predicted;
ret.time = data.timings.predicted_ms / 1000;
} catch (e: any) {
const err = e as TypeError;
const cause: FetchErrorCause = err.cause as FetchErrorCause;
const estr: string =
err.message + ' ' + cause.code + ' at ' + cause.address + ':' + cause.port;
// let the user know something went wrong
// TODO: maybe add a retry action or something
showMessageWithTimeout('dumbpilot error: ' + estr, 3000);
}
return ret;
}

116
src/openai-api.ts
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@ -0,0 +1,116 @@
import * as vscode from 'vscode';
// oogabooga/text-generation-webui OpenAI compatible API
// https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API
type OpenAICompletionRequest = {
model?: string; // automatic
prompt: string;
best_of?: number; // 1
echo?: boolean; // false
frequency_penalty?: number; // null
logit_bias?: object; // null
logprobs?: number; // 0
max_tokens?: number; // 16
n?: number; // 1
presence_penalty?: number; // 0
stop?: string;
stream?: boolean; // false
suffix?: string;
temperature?: number; // 1
top_p?: number; // 1
user?: string;
preset?: string;
min_p?: number; // 1
top_k?: number; // 1
repetition_penalty?: number; // 1
repetition_penalty_range?: number; // 1024
typical_p?: number; // 1
tfs?: number; // 1
top_a?: number; // 0
epsilon_cutoff?: number; // 0
eta_cutoff?: number; // 0
guidance_scale?: number; // 1
negative_prompt?: string; // ""
penalty_alpha?: number; // 0
mirostat_mode?: number; // 0
mirostat_tau?: number; // 5
mirostat_eta?: number; // 0.1
temperature_last?: boolean; // false
do_sample?: boolean; // true
seed?: number; // -1
encoder_repetition_penalty?: number; // 1
no_repeat_ngram_size?: number; // 0
min_length?: number; // 0
num_beams?: number; // 1
length_penalty?: number; // 1
early_stopping?: boolean; // false
truncation_length?: number; // 0
max_tokens_second?: number; // 0
custom_token_bans?: string; // ""
auto_max_new_tokens?: boolean; // false
ban_eos_token?: boolean; // false
add_bos_token?: boolean; // true
skip_special_tokens?: boolean; // true
grammar_string?: string; // ''
};
type OpenAICompletionSuccessResponse = {
id: string;
choices: object[];
created?: number;
model: string;
object?: string;
usage: object;
};
type OpenAICompletionFailureResponse = {
detail: {
loc: (string | number)[];
msg: string;
type: string;
}[];
};
type OpenAICompletionResponse = OpenAICompletionSuccessResponse | OpenAICompletionFailureResponse;
export function createOpenAIAPIRequest(
config: vscode.WorkspaceConfiguration,
doc_before: string,
doc_after: string
): OpenAICompletionRequest {
let request: OpenAICompletionRequest = {
prompt: '',
max_tokens: config.get('llamaMaxtokens') as number,
mirostat_mode: config.get('llamaMirostat') as number,
repetition_penalty: config.get('llamaRepeatPenalty') as number,
frequency_penalty: config.get('llamaFrequencyPenalty,') as number,
presence_penalty: config.get('llamaPresencePenalty,') as number,
repetition_penalty_range: config.get('llamaRepeatCtx,') as number,
temperature: config.get('llamaTemperature') as number,
top_p: config.get('llamaTop_p') as number,
top_k: config.get('llamaTop_k') as number,
typical_p: config.get('llamaTypical_p') as number,
tfs: config.get('llamaTailfree_z,') as number,
seed: config.get('llamaSeed') as number,
stream: false,
};
const fim = config.get('fimEnabled') as boolean;
if (fim === true) {
const fim_beg = config.get('fimBeginString') as string;
const fim_hole = config.get('fimHoleString') as string;
const fim_end = config.get('fimEndString') as string;
request.prompt = fim_beg + doc_before + fim_hole + doc_after + fim_end;
} else {
request.prompt = doc_before;
}
return request;
}
// for now only completions is implemented
export function OpenAIAPIRequestEndpoint(config: vscode.WorkspaceConfiguration): string {
return '/v1/completions';
}
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