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Merge branch 'neo-server' into parser-v2

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This commit is contained in:
LenAnderson
2024-04-19 09:07:42 -04:00
parent b7b57421e6 dee8f45986
commit 1de09bf71d
20 changed files with 284 additions and 62 deletions
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3
post-install.js
View File

@@ -60,7 +60,8 @@ function convertConfig() {
try {
console.log(color.blue('Converting config.conf to config.yaml. Your old config.conf will be renamed to config.conf.bak'));
const config = require(path.join(process.cwd(), './config.conf'));
fs.renameSync('./config.conf', './config.conf.bak');
fs.copyFileSync('./config.conf', './config.conf.bak');
fs.rmSync('./config.conf');
fs.writeFileSync('./config.yaml', yaml.stringify(config));
console.log(color.green('Conversion successful. Please check your config.yaml and fix it if necessary.'));
} catch (error) {

2
public/scripts/PromptManager.js
View File

@@ -841,7 +841,7 @@ class PromptManager {
const promptReferences = this.getPromptOrderForCharacter(this.activeCharacter);
for (let i = promptReferences.length - 1; i >= 0; i--) {
const reference = promptReferences[i];
if (-1 === this.serviceSettings.prompts.findIndex(prompt => prompt.identifier === reference.identifier)) {
if (reference && -1 === this.serviceSettings.prompts.findIndex(prompt => prompt.identifier === reference.identifier)) {
promptReferences.splice(i, 1);
this.log('Removed unused reference: ' + reference.identifier);
}

2
public/scripts/extensions/stable-diffusion/comfyWorkflowEditor.html
View File

@@ -19,6 +19,8 @@
<li data-placeholder="scale" class="sd_comfy_workflow_editor_not_found">"%scale%"</li>
<li data-placeholder="width" class="sd_comfy_workflow_editor_not_found">"%width%"</li>
<li data-placeholder="height" class="sd_comfy_workflow_editor_not_found">"%height%"</li>
<li data-placeholder="user_avatar" class="sd_comfy_workflow_editor_not_found">"%user_avatar%"</li>
<li data-placeholder="char_avatar" class="sd_comfy_workflow_editor_not_found">"%char_avatar%"</li>
<li><hr></li>
<li data-placeholder="seed" class="sd_comfy_workflow_editor_not_found">
"%seed%"

52
public/scripts/extensions/stable-diffusion/index.js
View File

@@ -2111,21 +2111,11 @@ async function generateMultimodalPrompt(generationType, quietPrompt) {
let avatarUrl;
if (generationType == generationMode.USER_MULTIMODAL) {
avatarUrl = getUserAvatar(user_avatar);
avatarUrl = getUserAvatarUrl();
}
if (generationType == generationMode.CHARACTER_MULTIMODAL || generationType === generationMode.FACE_MULTIMODAL) {
const context = getContext();
if (context.groupId) {
const groupMembers = context.groups.find(x => x.id === context.groupId)?.members;
const lastMessageAvatar = context.chat?.filter(x => !x.is_system && !x.is_user)?.slice(-1)[0]?.original_avatar;
const randomMemberAvatar = Array.isArray(groupMembers) ? groupMembers[Math.floor(Math.random() * groupMembers.length)]?.avatar : null;
const avatarToUse = lastMessageAvatar || randomMemberAvatar;
avatarUrl = formatCharacterAvatar(avatarToUse);
} else {
avatarUrl = getCharacterAvatar(context.characterId);
}
avatarUrl = getCharacterAvatarUrl();
}
try {
@@ -2152,6 +2142,24 @@ async function generateMultimodalPrompt(generationType, quietPrompt) {
}
}
function getCharacterAvatarUrl() {
const context = getContext();
if (context.groupId) {
const groupMembers = context.groups.find(x => x.id === context.groupId)?.members;
const lastMessageAvatar = context.chat?.filter(x => !x.is_system && !x.is_user)?.slice(-1)[0]?.original_avatar;
const randomMemberAvatar = Array.isArray(groupMembers) ? groupMembers[Math.floor(Math.random() * groupMembers.length)]?.avatar : null;
const avatarToUse = lastMessageAvatar || randomMemberAvatar;
return formatCharacterAvatar(avatarToUse);
} else {
return getCharacterAvatar(context.characterId);
}
}
function getUserAvatarUrl() {
return getUserAvatar(user_avatar);
}
/**
* Generates a prompt using the main LLM API.
* @param {string} quietPrompt - The prompt to use for the image generation.
@@ -2636,6 +2644,22 @@ async function generateComfyImage(prompt, negativePrompt) {
(extension_settings.sd.comfy_placeholders ?? []).forEach(ph => {
workflow = workflow.replace(`"%${ph.find}%"`, JSON.stringify(substituteParams(ph.replace)));
});
if (/%user_avatar%/gi.test(workflow)) {
const response = await fetch(getUserAvatarUrl());
if (response.ok) {
const avatarBlob = await response.blob();
const avatarBase64 = await getBase64Async(avatarBlob);
workflow = workflow.replace('"%user_avatar%"', JSON.stringify(avatarBase64));
}
}
if (/%char_avatar%/gi.test(workflow)) {
const response = await fetch(getCharacterAvatarUrl());
if (response.ok) {
const avatarBlob = await response.blob();
const avatarBase64 = await getBase64Async(avatarBlob);
workflow = workflow.replace('"%char_avatar%"', JSON.stringify(avatarBase64));
}
}
console.log(`{
"prompt": ${workflow}
}`);
@@ -2649,6 +2673,10 @@ async function generateComfyImage(prompt, negativePrompt) {
}`,
}),
});
if (!promptResult.ok) {
const text = await promptResult.text();
throw new Error(text);
}
return { format: 'png', data: await promptResult.text() };
}

77
public/scripts/extensions/vectors/index.js
View File

@@ -35,6 +35,7 @@ const settings = {
include_wi: false,
togetherai_model: 'togethercomputer/m2-bert-80M-32k-retrieval',
openai_model: 'text-embedding-ada-002',
cohere_model: 'embed-english-v3.0',
summarize: false,
summarize_sent: false,
summary_source: 'main',
@@ -68,6 +69,15 @@ const settings = {
const moduleWorker = new ModuleWorkerWrapper(synchronizeChat);
/**
* Gets the Collection ID for a file embedded in the chat.
* @param {string} fileUrl URL of the file
* @returns {string} Collection ID
*/
function getFileCollectionId(fileUrl) {
return `file_${getStringHash(fileUrl)}`;
}
async function onVectorizeAllClick() {
try {
if (!settings.enabled_chats) {
@@ -308,7 +318,7 @@ async function processFiles(chat) {
const dataBankCollectionIds = [];
for (const file of dataBank) {
const collectionId = `file_${getStringHash(file.url)}`;
const collectionId = getFileCollectionId(file.url);
const hashesInCollection = await getSavedHashes(collectionId);
dataBankCollectionIds.push(collectionId);
@@ -354,7 +364,7 @@ async function processFiles(chat) {
const fileName = message.extra.file.name;
const fileUrl = message.extra.file.url;
const collectionId = `file_${getStringHash(fileUrl)}`;
const collectionId = getFileCollectionId(fileUrl);
const hashesInCollection = await getSavedHashes(collectionId);
// File is already in the collection
@@ -598,6 +608,9 @@ function getVectorHeaders() {
case 'openai':
addOpenAiHeaders(headers);
break;
case 'cohere':
addCohereHeaders(headers);
break;
default:
break;
}
@@ -636,6 +649,16 @@ function addOpenAiHeaders(headers) {
});
}
/**
* Add headers for the Cohere API source.
* @param {object} headers Header object
*/
function addCohereHeaders(headers) {
Object.assign(headers, {
'X-Cohere-Model': extension_settings.vectors.cohere_model,
});
}
/**
* Inserts vector items into a collection
* @param {string} collectionId - The collection to insert into
@@ -647,7 +670,8 @@ async function insertVectorItems(collectionId, items) {
settings.source === 'palm' && !secret_state[SECRET_KEYS.MAKERSUITE] ||
settings.source === 'mistral' && !secret_state[SECRET_KEYS.MISTRALAI] ||
settings.source === 'togetherai' && !secret_state[SECRET_KEYS.TOGETHERAI] ||
settings.source === 'nomicai' && !secret_state[SECRET_KEYS.NOMICAI]) {
settings.source === 'nomicai' && !secret_state[SECRET_KEYS.NOMICAI] ||
settings.source === 'cohere' && !secret_state[SECRET_KEYS.COHERE]) {
throw new Error('Vectors: API key missing', { cause: 'api_key_missing' });
}
@@ -760,7 +784,7 @@ async function purgeFileVectorIndex(fileUrl) {
}
console.log(`Vectors: Purging file vector index for ${fileUrl}`);
const collectionId = `file_${getStringHash(fileUrl)}`;
const collectionId = getFileCollectionId(fileUrl);
const response = await fetch('/api/vector/purge', {
method: 'POST',
@@ -816,6 +840,7 @@ function toggleSettings() {
$('#vectors_chats_settings').toggle(!!settings.enabled_chats);
$('#together_vectorsModel').toggle(settings.source === 'togetherai');
$('#openai_vectorsModel').toggle(settings.source === 'openai');
$('#cohere_vectorsModel').toggle(settings.source === 'cohere');
$('#nomicai_apiKey').toggle(settings.source === 'nomicai');
}
@@ -859,6 +884,42 @@ async function onViewStatsClick() {
}
async function onVectorizeAllFilesClick() {
try {
const dataBank = getDataBankAttachments();
const chatAttachments = getContext().chat.filter(x => x.extra?.file).map(x => x.extra.file);
const allFiles = [...dataBank, ...chatAttachments];
for (const file of allFiles) {
const text = await getFileAttachment(file.url);
const collectionId = getFileCollectionId(file.url);
await vectorizeFile(text, file.name, collectionId, settings.chunk_size);
}
toastr.success('All files vectorized', 'Vectorization successful');
} catch (error) {
console.error('Vectors: Failed to vectorize all files', error);
toastr.error('Failed to vectorize all files', 'Vectorization failed');
}
}
async function onPurgeFilesClick() {
try {
const dataBank = getDataBankAttachments();
const chatAttachments = getContext().chat.filter(x => x.extra?.file).map(x => x.extra.file);
const allFiles = [...dataBank, ...chatAttachments];
for (const file of allFiles) {
await purgeFileVectorIndex(file.url);
}
toastr.success('All files purged', 'Purge successful');
} catch (error) {
console.error('Vectors: Failed to purge all files', error);
toastr.error('Failed to purge all files', 'Purge failed');
}
}
jQuery(async () => {
if (!extension_settings.vectors) {
extension_settings.vectors = settings;
@@ -913,6 +974,12 @@ jQuery(async () => {
Object.assign(extension_settings.vectors, settings);
saveSettingsDebounced();
});
$('#vectors_cohere_model').val(settings.cohere_model).on('change', () => {
$('#vectors_modelWarning').show();
settings.cohere_model = String($('#vectors_cohere_model').val());
Object.assign(extension_settings.vectors, settings);
saveSettingsDebounced();
});
$('#vectors_template').val(settings.template).on('input', () => {
settings.template = String($('#vectors_template').val());
Object.assign(extension_settings.vectors, settings);
@@ -947,6 +1014,8 @@ jQuery(async () => {
$('#vectors_vectorize_all').on('click', onVectorizeAllClick);
$('#vectors_purge').on('click', onPurgeClick);
$('#vectors_view_stats').on('click', onViewStatsClick);
$('#vectors_files_vectorize_all').on('click', onVectorizeAllFilesClick);
$('#vectors_files_purge').on('click', onPurgeFilesClick);
$('#vectors_size_threshold').val(settings.size_threshold).on('input', () => {
settings.size_threshold = Number($('#vectors_size_threshold').val());

29
public/scripts/extensions/vectors/settings.html
View File

@@ -10,13 +10,14 @@
Vectorization Source
</label>
<select id="vectors_source" class="text_pole">
<option value="transformers">Local (Transformers)</option>
<option value="cohere">Cohere</option>
<option value="extras">Extras</option>
<option value="openai">OpenAI</option>
<option value="palm">Google MakerSuite (PaLM)</option>
<option value="transformers">Local (Transformers)</option>
<option value="mistral">MistralAI</option>
<option value="togetherai">TogetherAI</option>
<option value="nomicai">NomicAI</option>
<option value="openai">OpenAI</option>
<option value="togetherai">TogetherAI</option>
</select>
</div>
<div class="flex-container flexFlowColumn" id="openai_vectorsModel">
@@ -29,6 +30,20 @@
<option value="text-embedding-3-large">text-embedding-3-large</option>
</select>
</div>
<div class="flex-container flexFlowColumn" id="cohere_vectorsModel">
<label for="vectors_cohere_model">
Vectorization Model
</label>
<select id="vectors_cohere_model" class="text_pole">
<option value="embed-english-v3.0">embed-english-v3.0</option>
<option value="embed-multilingual-v3.0">embed-multilingual-v3.0</option>
<option value="embed-english-light-v3.0">embed-english-light-v3.0</option>
<option value="embed-multilingual-light-v3.0">embed-multilingual-light-v3.0</option>
<option value="embed-english-v2.0">embed-english-v2.0</option>
<option value="embed-english-light-v2.0">embed-english-light-v2.0</option>
<option value="embed-multilingual-v2.0">embed-multilingual-v2.0</option>
</select>
</div>
<div class="flex-container flexFlowColumn" id="together_vectorsModel">
<label for="vectors_togetherai_model">
Vectorization Model
@@ -167,6 +182,14 @@
</label>
</div>
</div>
<div class="flex-container">
<div id="vectors_files_vectorize_all" class="menu_button menu_button_icon" title="Vectorize all files in the Data Bank and current chat.">
Vectorize All
</div>
<div id="vectors_files_purge" class="menu_button menu_button_icon" title="Purge all file vectors in the Data Bank and current chat.">
Purge Vectors
</div>
</div>
</div>
<hr>

4
public/scripts/instruct-mode.js
View File

@@ -354,7 +354,9 @@ export function formatInstructModeSystemPrompt(systemPrompt) {
const separator = power_user.instruct.wrap ? '\n' : '';
if (power_user.instruct.system_sequence_prefix) {
systemPrompt = power_user.instruct.system_sequence_prefix + separator + systemPrompt;
// TODO: Replace with a proper 'System' prompt entity name input
const prefix = power_user.instruct.system_sequence_prefix.replace(/{{name}}/gi, 'System');
systemPrompt = prefix + separator + systemPrompt;
}
if (power_user.instruct.system_sequence_suffix) {

4
public/scripts/popup.js
View File

@@ -119,6 +119,9 @@ export class Popup {
const keyListener = (evt) => {
switch (evt.key) {
case 'Escape': {
// does it really matter where we check?
const topModal = document.elementFromPoint(window.innerWidth / 2, window.innerHeight / 2)?.closest('.shadow_popup');
if (topModal == this.dom) {
evt.preventDefault();
evt.stopPropagation();
this.completeCancelled();
@@ -126,6 +129,7 @@ export class Popup {
break;
}
}
}
};
const keyListenerBound = keyListener.bind(this);
window.addEventListener('keydown', keyListenerBound);

3
src/endpoints/assets.js
View File

@@ -227,7 +227,8 @@ router.post('/download', jsonParser, async (request, response) => {
// Move into asset place
console.debug('Download finished, moving file from', temp_path, 'to', file_path);
fs.renameSync(temp_path, file_path);
fs.copyFileSync(temp_path, file_path);
fs.rmSync(temp_path);
response.sendStatus(200);
}
catch (error) {

6
src/endpoints/backgrounds.js
View File

@@ -51,7 +51,8 @@ router.post('/rename', jsonParser, function (request, response) {
return response.sendStatus(400);
}
fs.renameSync(oldFileName, newFileName);
fs.copyFileSync(oldFileName, newFileName);
fs.rmSync(oldFileName);
invalidateThumbnail(request.user.directories, 'bg', request.body.old_bg);
return response.send('ok');
});
@@ -63,7 +64,8 @@ router.post('/upload', urlencodedParser, function (request, response) {
const filename = request.file.originalname;
try {
fs.renameSync(img_path, path.join(request.user.directories.backgrounds, filename));
fs.copyFileSync(img_path, path.join(request.user.directories.backgrounds, filename));
fs.rmSync(img_path);
invalidateThumbnail(request.user.directories, 'bg', filename);
response.send(filename);
} catch (err) {

3
src/endpoints/characters.js
View File

@@ -680,7 +680,8 @@ router.post('/rename', jsonParser, async function (request, response) {
// Rename chats folder
if (fs.existsSync(oldChatsPath) && !fs.existsSync(newChatsPath)) {
fs.renameSync(oldChatsPath, newChatsPath);
fs.cpSync(oldChatsPath, newChatsPath, { recursive: true });
fs.rmSync(oldChatsPath, { recursive: true, force: true });
}
// Remove the old character file

3
src/endpoints/chats.js
View File

@@ -213,8 +213,9 @@ router.post('/rename', jsonParser, async function (request, response) {
return response.status(400).send({ error: true });
}
fs.copyFileSync(pathToOriginalFile, pathToRenamedFile);
fs.rmSync(pathToOriginalFile);
console.log('Successfully renamed.');
fs.renameSync(pathToOriginalFile, pathToRenamedFile);
return response.send({ ok: true });
});

47
src/endpoints/vectors.js
View File

@@ -12,23 +12,26 @@ const SOURCES = ['transformers', 'mistral', 'openai', 'extras', 'palm', 'togethe
* @param {string} source - The source of the vector
* @param {Object} sourceSettings - Settings for the source, if it needs any
* @param {string} text - The text to get the vector for
* @param {boolean} isQuery - If the text is a query for embedding search
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[]>} - The vector for the text
*/
async function getVector(source, sourceSettings, text, directories) {
async function getVector(source, sourceSettings, text, isQuery, directories) {
switch (source) {
case 'nomicai':
return require('../nomicai-vectors').getNomicAIVector(text, source, directories);
return require('../vectors/nomicai-vectors').getNomicAIVector(text, source, directories);
case 'togetherai':
case 'mistral':
case 'openai':
return require('../openai-vectors').getOpenAIVector(text, source, directories, sourceSettings.model);
return require('../vectors/openai-vectors').getOpenAIVector(text, source, directories, sourceSettings.model);
case 'transformers':
return require('../embedding').getTransformersVector(text);
return require('../vectors/embedding').getTransformersVector(text);
case 'extras':
return require('../extras-vectors').getExtrasVector(text, sourceSettings.extrasUrl, sourceSettings.extrasKey);
return require('../vectors/extras-vectors').getExtrasVector(text, sourceSettings.extrasUrl, sourceSettings.extrasKey);
case 'palm':
return require('../makersuite-vectors').getMakerSuiteVector(text, directories);
return require('../vectors/makersuite-vectors').getMakerSuiteVector(text, directories);
case 'cohere':
return require('../vectors/cohere-vectors').getCohereVector(text, isQuery, directories, sourceSettings.model);
}
throw new Error(`Unknown vector source ${source}`);
@@ -39,10 +42,11 @@ async function getVector(source, sourceSettings, text, directories) {
* @param {string} source - The source of the vector
* @param {Object} sourceSettings - Settings for the source, if it needs any
* @param {string[]} texts - The array of texts to get the vector for
* @param {boolean} isQuery - If the text is a query for embedding search
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[][]>} - The array of vectors for the texts
*/
async function getBatchVector(source, sourceSettings, texts, directories) {
async function getBatchVector(source, sourceSettings, texts, isQuery, directories) {
const batchSize = 10;
const batches = Array(Math.ceil(texts.length / batchSize)).fill(undefined).map((_, i) => texts.slice(i * batchSize, i * batchSize + batchSize));
@@ -50,21 +54,24 @@ async function getBatchVector(source, sourceSettings, texts, directories) {
for (let batch of batches) {
switch (source) {
case 'nomicai':
results.push(...await require('../nomicai-vectors').getNomicAIBatchVector(batch, source, directories));
results.push(...await require('../vectors/nomicai-vectors').getNomicAIBatchVector(batch, source, directories));
break;
case 'togetherai':
case 'mistral':
case 'openai':
results.push(...await require('../openai-vectors').getOpenAIBatchVector(batch, source, directories, sourceSettings.model));
results.push(...await require('../vectors/openai-vectors').getOpenAIBatchVector(batch, source, directories, sourceSettings.model));
break;
case 'transformers':
results.push(...await require('../embedding').getTransformersBatchVector(batch));
results.push(...await require('../vectors/embedding').getTransformersBatchVector(batch));
break;
case 'extras':
results.push(...await require('../extras-vectors').getExtrasBatchVector(batch, sourceSettings.extrasUrl, sourceSettings.extrasKey));
results.push(...await require('../vectors/extras-vectors').getExtrasBatchVector(batch, sourceSettings.extrasUrl, sourceSettings.extrasKey));
break;
case 'palm':
results.push(...await require('../makersuite-vectors').getMakerSuiteBatchVector(batch, directories));
results.push(...await require('../vectors/makersuite-vectors').getMakerSuiteBatchVector(batch, directories));
break;
case 'cohere':
results.push(...await require('../vectors/cohere-vectors').getCohereBatchVector(batch, isQuery, directories, sourceSettings.model));
break;
default:
throw new Error(`Unknown vector source ${source}`);
@@ -106,7 +113,7 @@ async function insertVectorItems(directories, collectionId, source, sourceSettin
await store.beginUpdate();
const vectors = await getBatchVector(source, sourceSettings, items.map(x => x.text), directories);
const vectors = await getBatchVector(source, sourceSettings, items.map(x => x.text), false, directories);
for (let i = 0; i < items.length; i++) {
const item = items[i];
@@ -165,7 +172,7 @@ async function deleteVectorItems(directories, collectionId, source, hashes) {
*/
async function queryCollection(directories, collectionId, source, sourceSettings, searchText, topK) {
const store = await getIndex(directories, collectionId, source);
const vector = await getVector(source, sourceSettings, searchText, directories);
const vector = await getVector(source, sourceSettings, searchText, true, directories);
const result = await store.queryItems(vector, topK);
const metadata = result.map(x => x.item.metadata);
@@ -184,7 +191,7 @@ async function queryCollection(directories, collectionId, source, sourceSettings
* @returns {Promise<Record<string, { hashes: number[], metadata: object[] }>>} - The top K results from each collection
*/
async function multiQueryCollection(directories, collectionIds, source, sourceSettings, searchText, topK) {
const vector = await getVector(source, sourceSettings, searchText, directories);
const vector = await getVector(source, sourceSettings, searchText, true, directories);
const results = [];
for (const collectionId of collectionIds) {
@@ -223,13 +230,19 @@ async function multiQueryCollection(directories, collectionIds, source, sourceSe
*/
function getSourceSettings(source, request) {
if (source === 'togetherai') {
let model = String(request.headers['x-togetherai-model']);
const model = String(request.headers['x-togetherai-model']);
return {
model: model,
};
} else if (source === 'openai') {
let model = String(request.headers['x-openai-model']);
const model = String(request.headers['x-openai-model']);
return {
model: model,
};
} else if (source === 'cohere') {
const model = String(request.headers['x-cohere-model']);
return {
model: model,

14
src/users.js
View File

@@ -286,12 +286,22 @@ async function migrateUserData() {
// Copy the file to the new location
fs.cpSync(migration.old, migration.new, { force: true });
// Move the file to the backup location
fs.renameSync(migration.old, path.join(backupDirectory, path.basename(migration.old)));
fs.cpSync(
migration.old,
path.join(backupDirectory, path.basename(migration.old)),
{ recursive: true, force: true }
);
fs.rmSync(migration.old, { recursive: true, force: true });
} else {
// Copy the directory to the new location
fs.cpSync(migration.old, migration.new, { recursive: true, force: true });
// Move the directory to the backup location
fs.renameSync(migration.old, path.join(backupDirectory, path.basename(migration.old)));
fs.cpSync(
migration.old,
path.join(backupDirectory, path.basename(migration.old)),
{ recursive: true, force: true }
);
fs.rmSync(migration.old, { recursive: true, force: true });
}
} catch (error) {
console.error(color.red(`Error migrating ${migration.old} to ${migration.new}:`), error.message);

65
src/vectors/cohere-vectors.js Normal file
View File

@@ -0,0 +1,65 @@
const fetch = require('node-fetch').default;
const { SECRET_KEYS, readSecret } = require('../endpoints/secrets');
/**
* Gets the vector for the given text batch from an OpenAI compatible endpoint.
* @param {string[]} texts - The array of texts to get the vector for
* @param {boolean} isQuery - If the text is a query for embedding search
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @param {string} model - The model to use for the embedding
* @returns {Promise<number[][]>} - The array of vectors for the texts
*/
async function getCohereBatchVector(texts, isQuery, directories, model) {
const key = readSecret(directories, SECRET_KEYS.COHERE);
if (!key) {
console.log('No API key found');
throw new Error('No API key found');
}
const response = await fetch('https://api.cohere.ai/v1/embed', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${key}`,
},
body: JSON.stringify({
texts: texts,
model: model,
input_type: isQuery ? 'search_query' : 'search_document',
truncate: 'END',
}),
});
if (!response.ok) {
const text = await response.text();
console.log('API request failed', response.statusText, text);
throw new Error('API request failed');
}
const data = await response.json();
if (!Array.isArray(data?.embeddings)) {
console.log('API response was not an array');
throw new Error('API response was not an array');
}
return data.embeddings;
}
/**
* Gets the vector for the given text from an OpenAI compatible endpoint.
* @param {string} text - The text to get the vector for
* @param {boolean} isQuery - If the text is a query for embedding search
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @param {string} model - The model to use for the embedding
* @returns {Promise<number[]>} - The vector for the text
*/
async function getCohereVector(text, isQuery, directories, model) {
const vectors = await getCohereBatchVector([text], isQuery, directories, model);
return vectors[0];
}
module.exports = {
getCohereBatchVector,
getCohereVector,
};

2
src/embedding.js → src/vectors/embedding.js
View File

@@ -6,7 +6,7 @@ const TASK = 'feature-extraction';
* @returns {Promise<number[]>} - The vectorized text in form of an array of numbers
*/
async function getTransformersVector(text) {
const module = await import('./transformers.mjs');
const module = await import('../transformers.mjs');
const pipe = await module.default.getPipeline(TASK);
const result = await pipe(text, { pooling: 'mean', normalize: true });
const vector = Array.from(result.data);

0
src/extras-vectors.js → src/vectors/extras-vectors.js
View File

6
src/makersuite-vectors.js → src/vectors/makersuite-vectors.js
View File

@@ -1,10 +1,10 @@
const fetch = require('node-fetch').default;
const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
const { SECRET_KEYS, readSecret } = require('../endpoints/secrets');
/**
* Gets the vector for the given text from gecko model
* @param {string[]} texts - The array of texts to get the vector for
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[][]>} - The array of vectors for the texts
*/
async function getMakerSuiteBatchVector(texts, directories) {
@@ -16,7 +16,7 @@ async function getMakerSuiteBatchVector(texts, directories) {
/**
* Gets the vector for the given text from PaLM gecko model
* @param {string} text - The text to get the vector for
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[]>} - The vector for the text
*/
async function getMakerSuiteVector(text, directories) {

6
src/nomicai-vectors.js → src/vectors/nomicai-vectors.js
View File

@@ -1,5 +1,5 @@
const fetch = require('node-fetch').default;
const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
const { SECRET_KEYS, readSecret } = require('../endpoints/secrets');
const SOURCES = {
'nomicai': {
@@ -13,7 +13,7 @@ const SOURCES = {
* Gets the vector for the given text batch from an OpenAI compatible endpoint.
* @param {string[]} texts - The array of texts to get the vector for
* @param {string} source - The source of the vector
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[][]>} - The array of vectors for the texts
*/
async function getNomicAIBatchVector(texts, source, directories) {
@@ -64,7 +64,7 @@ async function getNomicAIBatchVector(texts, source, directories) {
* Gets the vector for the given text from an OpenAI compatible endpoint.
* @param {string} text - The text to get the vector for
* @param {string} source - The source of the vector
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @returns {Promise<number[]>} - The vector for the text
*/
async function getNomicAIVector(text, source, directories) {

6
src/openai-vectors.js → src/vectors/openai-vectors.js
View File

@@ -1,5 +1,5 @@
const fetch = require('node-fetch').default;
const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
const { SECRET_KEYS, readSecret } = require('../endpoints/secrets');
const SOURCES = {
'togetherai': {
@@ -23,7 +23,7 @@ const SOURCES = {
* Gets the vector for the given text batch from an OpenAI compatible endpoint.
* @param {string[]} texts - The array of texts to get the vector for
* @param {string} source - The source of the vector
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @param {string} model - The model to use for the embedding
* @returns {Promise<number[][]>} - The array of vectors for the texts
*/
@@ -79,7 +79,7 @@ async function getOpenAIBatchVector(texts, source, directories, model = '') {
* Gets the vector for the given text from an OpenAI compatible endpoint.
* @param {string} text - The text to get the vector for
* @param {string} source - The source of the vector
* @param {import('./users').UserDirectoryList} directories - The directories object for the user
* @param {import('../users').UserDirectoryList} directories - The directories object for the user
* @param {string} model - The model to use for the embedding
* @returns {Promise<number[]>} - The vector for the text
*/