feat: Enhance configuration management and embedding capabilities

- Added JSON-based settings management in Config class for embedding and LLM configurations.
- Introduced methods to save and load settings from a JSON file.
- Updated BaseEmbedder and its subclasses to include max_tokens property for better token management.
- Enhanced chunking strategy to support recursive splitting of large symbols with improved overlap handling.
- Implemented comprehensive tests for recursive splitting and chunking behavior.
- Added CLI tools configuration management for better integration with external tools.
- Introduced a new command for compacting session memory into structured text for recovery.
This commit is contained in:
catlog22
2025-12-24 16:32:27 +08:00
parent b00113d212
commit e671b45948
25 changed files with 2889 additions and 153 deletions

View File

@@ -1166,10 +1166,12 @@ async function deleteModel(profile) {
* Initialize CodexLens index with bottom floating progress bar
* @param {string} indexType - 'vector' (with embeddings), 'normal' (FTS only), or 'full' (FTS + Vector)
* @param {string} embeddingModel - Model profile: 'code', 'fast'
* @param {string} embeddingBackend - Backend: 'fastembed' (local) or 'litellm' (API)
*/
async function initCodexLensIndex(indexType, embeddingModel) {
async function initCodexLensIndex(indexType, embeddingModel, embeddingBackend) {
indexType = indexType || 'vector';
embeddingModel = embeddingModel || 'code';
embeddingBackend = embeddingBackend || 'fastembed';
// For vector or full index, check if semantic dependencies are available
if (indexType === 'vector' || indexType === 'full') {
@@ -1235,7 +1237,8 @@ async function initCodexLensIndex(indexType, embeddingModel) {
var modelLabel = '';
if (indexType !== 'normal') {
var modelNames = { code: 'Code', fast: 'Fast' };
modelLabel = ' [' + (modelNames[embeddingModel] || embeddingModel) + ']';
var backendLabel = embeddingBackend === 'litellm' ? 'API: ' : '';
modelLabel = ' [' + backendLabel + (modelNames[embeddingModel] || embeddingModel) + ']';
}
progressBar.innerHTML =
@@ -1272,17 +1275,19 @@ async function initCodexLensIndex(indexType, embeddingModel) {
var apiIndexType = (indexType === 'full') ? 'vector' : indexType;
// Start indexing with specified type and model
startCodexLensIndexing(apiIndexType, embeddingModel);
startCodexLensIndexing(apiIndexType, embeddingModel, embeddingBackend);
}
/**
* Start the indexing process
* @param {string} indexType - 'vector' or 'normal'
* @param {string} embeddingModel - Model profile: 'code', 'fast'
* @param {string} embeddingBackend - Backend: 'fastembed' (local) or 'litellm' (API)
*/
async function startCodexLensIndexing(indexType, embeddingModel) {
async function startCodexLensIndexing(indexType, embeddingModel, embeddingBackend) {
indexType = indexType || 'vector';
embeddingModel = embeddingModel || 'code';
embeddingBackend = embeddingBackend || 'fastembed';
var statusText = document.getElementById('codexlensIndexStatus');
var progressBar = document.getElementById('codexlensIndexProgressBar');
var percentText = document.getElementById('codexlensIndexPercent');
@@ -1314,11 +1319,11 @@ async function startCodexLensIndexing(indexType, embeddingModel) {
}
try {
console.log('[CodexLens] Starting index for:', projectPath, 'type:', indexType, 'model:', embeddingModel);
console.log('[CodexLens] Starting index for:', projectPath, 'type:', indexType, 'model:', embeddingModel, 'backend:', embeddingBackend);
var response = await fetch('/api/codexlens/init', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ path: projectPath, indexType: indexType, embeddingModel: embeddingModel })
body: JSON.stringify({ path: projectPath, indexType: indexType, embeddingModel: embeddingModel, embeddingBackend: embeddingBackend })
});
var result = await response.json();
@@ -1883,6 +1888,16 @@ async function renderCodexLensManager() {
await loadCodexLensStatus();
}
// Load LiteLLM API config for embedding backend options
try {
var litellmResponse = await fetch('/api/litellm-api/config');
if (litellmResponse.ok) {
window.litellmApiConfig = await litellmResponse.json();
}
} catch (e) {
console.warn('[CodexLens] Could not load LiteLLM config:', e);
}
var response = await fetch('/api/codexlens/config');
var config = await response.json();
@@ -1946,6 +1961,15 @@ function buildCodexLensManagerPage(config) {
'<div class="bg-card border border-border rounded-lg p-5">' +
'<h4 class="text-lg font-semibold mb-4 flex items-center gap-2"><i data-lucide="layers" class="w-5 h-5 text-primary"></i> ' + t('codexlens.createIndex') + '</h4>' +
'<div class="space-y-4">' +
// Backend selector (fastembed local or litellm API)
'<div class="mb-4">' +
'<label class="block text-sm font-medium mb-1.5">' + (t('codexlens.embeddingBackend') || 'Embedding Backend') + '</label>' +
'<select id="pageBackendSelect" class="w-full px-3 py-2 border border-border rounded-lg bg-background text-sm" onchange="onEmbeddingBackendChange()">' +
'<option value="fastembed">' + (t('codexlens.localFastembed') || 'Local (FastEmbed)') + '</option>' +
'<option value="litellm">' + (t('codexlens.apiLitellm') || 'API (LiteLLM)') + '</option>' +
'</select>' +
'<p class="text-xs text-muted-foreground mt-1">' + (t('codexlens.backendHint') || 'Select local model or remote API endpoint') + '</p>' +
'</div>' +
// Model selector
'<div>' +
'<label class="block text-sm font-medium mb-1.5">' + t('codexlens.embeddingModel') + '</label>' +
@@ -2150,18 +2174,68 @@ function buildModelSelectOptionsForPage() {
return options;
}
/**
* Handle embedding backend change
*/
function onEmbeddingBackendChange() {
var backendSelect = document.getElementById('pageBackendSelect');
var modelSelect = document.getElementById('pageModelSelect');
if (!backendSelect || !modelSelect) return;
var backend = backendSelect.value;
if (backend === 'litellm') {
// Load LiteLLM embedding models
modelSelect.innerHTML = buildLiteLLMModelOptions();
} else {
// Load local fastembed models
modelSelect.innerHTML = buildModelSelectOptionsForPage();
}
}
/**
* Build LiteLLM model options from config
*/
function buildLiteLLMModelOptions() {
var litellmConfig = window.litellmApiConfig || {};
var providers = litellmConfig.providers || [];
var options = '';
providers.forEach(function(provider) {
if (!provider.enabled) return;
var models = provider.models || [];
models.forEach(function(model) {
if (model.type !== 'embedding' || !model.enabled) return;
var label = model.name || model.id;
var selected = options === '' ? ' selected' : '';
options += '<option value="' + model.id + '"' + selected + '>' + label + '</option>';
});
});
if (options === '') {
options = '<option value="" disabled selected>' + (t('codexlens.noApiModels') || 'No API embedding models configured') + '</option>';
}
return options;
}
// Make functions globally accessible
window.onEmbeddingBackendChange = onEmbeddingBackendChange;
/**
* Initialize index from page with selected model
*/
function initCodexLensIndexFromPage(indexType) {
var backendSelect = document.getElementById('pageBackendSelect');
var modelSelect = document.getElementById('pageModelSelect');
var selectedBackend = backendSelect ? backendSelect.value : 'fastembed';
var selectedModel = modelSelect ? modelSelect.value : 'code';
// For FTS-only index, model is not needed
if (indexType === 'normal') {
initCodexLensIndex(indexType);
} else {
initCodexLensIndex(indexType, selectedModel);
initCodexLensIndex(indexType, selectedModel, selectedBackend);
}
}