update files search methods && semantic search mehtod

src/core/llm/manager.ts

@@ -17,7 +17,7 @@ import { GroqProvider } from './groq'
 import { InfioProvider } from './infio'
 import { OllamaProvider } from './ollama'
 import { OpenAIAuthenticatedProvider } from './openai'
-import { OpenAICompatibleProvider } from './openai-compatible-provider'
+import { OpenAICompatibleProvider } from './openai-compatible'
 
 
 export type LLMManagerInterface = {

src/core/rag/embedding.ts

@@ -1,3 +1,6 @@
+import https from 'https'
+import { URL } from 'url'
+
 import { GoogleGenerativeAI } from '@google/generative-ai'
 import { OpenAI } from 'openai'
 
@@ -176,6 +179,42 @@ export const getEmbeddingModel = (
 				},
 			}
 		}
+		case ApiProvider.OpenAICompatible: {
+			const openai = new OpenAI({
+				apiKey: settings.openaicompatibleProvider.apiKey,
+				baseURL: settings.openaicompatibleProvider.baseUrl,
+				dangerouslyAllowBrowser: true,
+			});
+			return {
+				id: settings.embeddingModelId,
+				dimension: 0,
+				getEmbedding: async (text: string) => {
+					try {
+						if (!openai.apiKey) {
+							throw new LLMAPIKeyNotSetException(
+								'OpenAI Compatible API key is missing. Please set it in settings menu.',
+							)
+						}
+						const embedding = await openai.embeddings.create({
+							model: settings.embeddingModelId,
+							input: text,
+							encoding_format: "float",
+						})
+						return embedding.data[0].embedding
+					} catch (error) {
+						if (
+							error.status === 429 &&
+							error.message.toLowerCase().includes('rate limit')
+						) {
+							throw new LLMRateLimitExceededException(
+								'OpenAI Compatible API rate limit exceeded. Please try again later.',
+							)
+						}
+						throw error
+					}
+				},
+			}
+		}
 		default:
 			throw new Error('Invalid embedding model')
 	}

src/core/rag/rag-engine.ts

@@ -34,7 +34,8 @@ export class RAGEngine {
 	}
 
 	async initializeDimension(): Promise<void> {
-		if (this.embeddingModel.dimension === 0 && this.settings.embeddingModelProvider === ApiProvider.Ollama) {
+		if (this.embeddingModel.dimension === 0 &&
+			(this.settings.embeddingModelProvider === ApiProvider.Ollama || this.settings.embeddingModelProvider === ApiProvider.OpenAICompatible)) {
 			this.embeddingModel.dimension = (await this.embeddingModel.getEmbedding("hello world")).length
 		}
 	}

src/core/ripgrep/index.ts

@@ -30,8 +30,8 @@ export function truncateLine(line: string, maxLength: number = MAX_LINE_LENGTH):
 	return line.length > maxLength ? line.substring(0, maxLength) + " [truncated...]" : line
 }
 
-async function getBinPath(): Promise<string | undefined> {
-	const binPath = path.join("/opt/homebrew/bin/", binName)
+async function getBinPath(ripgrepPath: string): Promise<string | undefined> {
+	const binPath = path.join(ripgrepPath, binName)
 	return (await pathExists(binPath)) ? binPath : undefined
 }
 
@@ -86,20 +86,21 @@ async function execRipgrep(bin: string, args: string[]): Promise<string> {
 export async function regexSearchFiles(
 	directoryPath: string,
 	regex: string,
+	ripgrepPath: string,
 ): Promise<string> {
-	const rgPath = await getBinPath()
+	const rgPath = await getBinPath(ripgrepPath)
 
 	if (!rgPath) {
 		throw new Error("Could not find ripgrep binary")
 	}
 
-	// 使用--glob参数排除.obsidian目录
+	// use --glob param to exclude .obsidian directory
 	const args = [
 		"--json", 
 		"-e", 
 		regex, 
 		"--glob", 
-		"!.obsidian/**", // 排除.obsidian目录及其所有子目录
+		"!.obsidian/**", // exclude .obsidian directory and all its subdirectories
 		"--glob",
 		"!.git/**",
 		"--context",