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@ -1,69 +1,21 @@
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const { app, BrowserWindow, ipcMain, dialog } = require("electron"); |
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const pdfParse = require("pdf-parse"); |
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const mammoth = require("mammoth"); |
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const fs = require("fs"); |
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const path = require("path"); |
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const os = require("os"); |
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const { queryOpenAI } = require("./chatgpt.js"); |
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const axios = require("axios"); |
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const fsExtra = require("fs-extra"); |
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const OpenAI = require("openai"); |
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const Ollama = require("ollama"); |
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const Anthropic = require("@anthropic-ai/sdk"); |
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let fetch, allModels; |
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let fetch; |
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import("node-fetch").then((module) => { |
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fetch = module.default; |
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}); |
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const unzipper = require("unzipper"); |
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let win; |
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function promptUserForApiKey() { |
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// Create a new window to prompt the user for the API key
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const promptWindow = new BrowserWindow({ |
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// Window configuration for the prompt
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width: 500, |
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height: 200, |
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webPreferences: { |
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nodeIntegration: true, |
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contextIsolation: false, // Consider security implications
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}, |
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}); |
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// Handle the API key submission from the prompt window
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ipcMain.on("submit-api-key", (event, apiKey) => { |
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if (apiKey) { |
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saveApiKey(apiKey); |
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promptWindow.close(); |
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createWindow(); // Proceed to create the main window
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} else { |
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// Handle invalid input or user cancellation
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promptWindow.close(); |
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} |
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}); |
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} |
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function loadApiKey() { |
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const configPath = path.join(os.homedir(), ".config", "fabric", ".env"); |
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if (fs.existsSync(configPath)) { |
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const envContents = fs.readFileSync(configPath, { encoding: "utf8" }); |
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const matches = envContents.match(/^OPENAI_API_KEY=(.*)$/m); |
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if (matches && matches[1]) { |
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return matches[1]; |
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} |
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} |
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return null; |
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} |
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function saveApiKey(apiKey) { |
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const configPath = path.join(os.homedir(), ".config", "fabric"); |
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const envFilePath = path.join(configPath, ".env"); |
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if (!fs.existsSync(configPath)) { |
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fs.mkdirSync(configPath, { recursive: true }); |
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} |
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fs.writeFileSync(envFilePath, `OPENAI_API_KEY=${apiKey}`); |
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process.env.OPENAI_API_KEY = apiKey; // Set for current session
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} |
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let openai; |
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let ollama; |
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function ensureFabricFoldersExist() { |
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return new Promise(async (resolve, reject) => { |
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@ -87,8 +39,9 @@ function ensureFabricFoldersExist() {
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}); |
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} |
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async function downloadAndUpdatePatterns(patternsPath) { |
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async function downloadAndUpdatePatterns() { |
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try { |
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// Download the zip file
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const response = await axios({ |
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method: "get", |
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url: "https://github.com/danielmiessler/fabric/archive/refs/heads/main.zip", |
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@ -99,16 +52,15 @@ async function downloadAndUpdatePatterns(patternsPath) {
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fs.writeFileSync(zipPath, response.data); |
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console.log("Zip file written to:", zipPath); |
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// Prepare for extraction
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const tempExtractPath = path.join(os.tmpdir(), "fabric_extracted"); |
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fsExtra.emptyDirSync(tempExtractPath); |
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await fsExtra.remove(patternsPath); // Delete the existing patterns directory
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await fsExtra.emptyDir(tempExtractPath); |
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// Extract the zip file
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await fs |
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.createReadStream(zipPath) |
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.pipe(unzipper.Extract({ path: tempExtractPath })) |
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.promise(); |
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console.log("Extraction complete"); |
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const extractedPatternsPath = path.join( |
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@ -117,21 +69,40 @@ async function downloadAndUpdatePatterns(patternsPath) {
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"patterns" |
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); |
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await fsExtra.copy(extractedPatternsPath, patternsPath); |
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// Compare and move folders
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const existingPatternsPath = path.join( |
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os.homedir(), |
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".config", |
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"fabric", |
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"patterns" |
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); |
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if (fs.existsSync(existingPatternsPath)) { |
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const existingFolders = await fsExtra.readdir(existingPatternsPath); |
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for (const folder of existingFolders) { |
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if (!fs.existsSync(path.join(extractedPatternsPath, folder))) { |
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await fsExtra.move( |
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path.join(existingPatternsPath, folder), |
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path.join(extractedPatternsPath, folder) |
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); |
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console.log( |
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`Moved missing folder ${folder} to the extracted patterns directory.` |
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); |
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} |
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} |
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} |
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// Overwrite the existing patterns directory with the updated extracted directory
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await fsExtra.copy(extractedPatternsPath, existingPatternsPath, { |
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overwrite: true, |
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}); |
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console.log("Patterns successfully updated"); |
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// Inform the renderer process that the patterns have been updated
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win.webContents.send("patterns-updated"); |
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// win.webContents.send("patterns-updated");
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} catch (error) { |
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console.error("Error downloading or updating patterns:", error); |
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} |
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} |
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function checkApiKeyExists() { |
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const configPath = path.join(os.homedir(), ".config", "fabric", ".env"); |
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return fs.existsSync(configPath); |
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} |
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function getPatternFolders() { |
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const patternsPath = path.join(os.homedir(), ".config", "fabric", "patterns"); |
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return fs |
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@ -140,6 +111,114 @@ function getPatternFolders() {
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.map((dirent) => dirent.name); |
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} |
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function checkApiKeyExists() { |
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const configPath = path.join(os.homedir(), ".config", "fabric", ".env"); |
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return fs.existsSync(configPath); |
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} |
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function loadApiKeys() { |
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const configPath = path.join(os.homedir(), ".config", "fabric", ".env"); |
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let keys = { openAIKey: null, claudeKey: null }; |
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if (fs.existsSync(configPath)) { |
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const envContents = fs.readFileSync(configPath, { encoding: "utf8" }); |
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const openAIMatch = envContents.match(/^OPENAI_API_KEY=(.*)$/m); |
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const claudeMatch = envContents.match(/^CLAUDE_API_KEY=(.*)$/m); |
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if (openAIMatch && openAIMatch[1]) { |
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keys.openAIKey = openAIMatch[1]; |
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openai = new OpenAI({ apiKey: keys.openAIKey }); |
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} |
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if (claudeMatch && claudeMatch[1]) { |
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keys.claudeKey = claudeMatch[1]; |
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claude = new Anthropic({ apiKey: keys.claudeKey }); |
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} |
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} |
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return keys; |
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} |
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function saveApiKeys(openAIKey, claudeKey) { |
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const configPath = path.join(os.homedir(), ".config", "fabric"); |
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const envFilePath = path.join(configPath, ".env"); |
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if (!fs.existsSync(configPath)) { |
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fs.mkdirSync(configPath, { recursive: true }); |
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} |
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let envContent = ""; |
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if (openAIKey) { |
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envContent += `OPENAI_API_KEY=${openAIKey}\n`; |
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process.env.OPENAI_API_KEY = openAIKey; // Set for current session
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openai = new OpenAI({ apiKey: openAIKey }); |
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} |
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if (claudeKey) { |
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envContent += `CLAUDE_API_KEY=${claudeKey}\n`; |
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process.env.CLAUDE_API_KEY = claudeKey; // Set for current session
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claude = new Anthropic({ apiKey: claudeKey }); |
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} |
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fs.writeFileSync(envFilePath, envContent.trim()); |
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} |
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async function getOllamaModels() { |
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ollama = new Ollama.Ollama(); |
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const _models = await ollama.list(); |
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return _models.models.map((x) => x.name); |
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} |
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async function getModels() { |
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ollama = new Ollama.Ollama(); |
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allModels = { |
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gptModels: [], |
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claudeModels: [], |
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ollamaModels: [], |
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}; |
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let keys = loadApiKeys(); // Assuming loadApiKeys() is updated to return both keys
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if (keys.claudeKey) { |
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// Assuming claudeModels do not require an asynchronous call to be fetched
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claudeModels = [ |
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"claude-3-opus-20240229", |
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"claude-3-sonnet-20240229", |
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"claude-3-haiku-20240307", |
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"claude-2.1", |
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]; |
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allModels.claudeModels = claudeModels; |
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} |
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if (keys.openAIKey) { |
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openai = new OpenAI({ apiKey: keys.openAIKey }); |
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// Wrap asynchronous call with a Promise to handle it in parallel
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gptModelsPromise = openai.models.list(); |
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} |
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// Check if ollama exists and has a list method
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if ( |
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typeof ollama !== "undefined" && |
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ollama.list && |
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typeof ollama.list === "function" |
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) { |
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// Assuming ollama.list() returns a Promise
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ollamaModelsPromise = getOllamaModels(); |
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} else { |
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console.log("ollama is not available or does not support listing models."); |
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} |
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// Wait for all asynchronous operations to complete
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try { |
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const results = await Promise.all( |
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[gptModelsPromise, ollamaModelsPromise].filter(Boolean) |
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); // Filter out undefined promises
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allModels.gptModels = results[0]?.data || []; // Assuming the first promise is always GPT models if it exists
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allModels.ollamaModels = results[1] || []; // Assuming the second promise is always Ollama models if it exists
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} catch (error) { |
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console.error("Error fetching models from OpenAI or Ollama:", error); |
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} |
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return allModels; // Return the aggregated results
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} |
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function getPatternContent(patternName) { |
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const patternPath = path.join( |
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os.homedir(), |
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@ -157,6 +236,76 @@ function getPatternContent(patternName) {
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} |
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} |
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async function ollamaMessage(system, user, model, event) { |
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ollama = new Ollama.Ollama(); |
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const userMessage = { |
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role: "user", |
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content: user, |
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}; |
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const systemMessage = { role: "system", content: system }; |
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const response = await ollama.chat({ |
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model: model, |
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messages: [systemMessage, userMessage], |
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stream: true, |
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}); |
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let responseMessage = ""; |
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for await (const chunk of response) { |
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const content = chunk.message.content; |
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if (content) { |
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responseMessage += content; |
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event.reply("model-response", content); |
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} |
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event.reply("model-response-end", responseMessage); |
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} |
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} |
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async function openaiMessage(system, user, model, event) { |
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const userMessage = { role: "user", content: user }; |
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const systemMessage = { role: "system", content: system }; |
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const stream = await openai.chat.completions.create( |
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{ |
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model: model, |
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messages: [systemMessage, userMessage], |
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stream: true, |
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}, |
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{ responseType: "stream" } |
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); |
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let responseMessage = ""; |
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for await (const chunk of stream) { |
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const content = chunk.choices[0].delta.content; |
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if (content) { |
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responseMessage += content; |
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event.reply("model-response", content); |
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} |
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} |
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event.reply("model-response-end", responseMessage); |
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} |
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async function claudeMessage(system, user, model, event) { |
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const userMessage = { role: "user", content: user }; |
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const systemMessage = system; |
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const response = await claude.messages.create({ |
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model: model, |
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system: systemMessage, |
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max_tokens: 4096, |
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messages: [userMessage], |
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stream: true, |
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temperature: 0.0, |
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top_p: 1.0, |
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}); |
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let responseMessage = ""; |
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for await (const chunk of response) { |
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if (chunk.delta && chunk.delta.text) { |
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responseMessage += chunk.delta.text; |
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event.reply("model-response", chunk.delta.text); |
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} |
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} |
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event.reply("model-response-end", responseMessage); |
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} |
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function createWindow() { |
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win = new BrowserWindow({ |
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width: 800, |
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@ -174,50 +323,31 @@ function createWindow() {
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win = null; |
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}); |
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} |
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ipcMain.on("process-complex-file", (event, filePath) => { |
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const extension = path.extname(filePath).toLowerCase(); |
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let fileProcessPromise; |
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|
if (extension === ".pdf") { |
|
|
|
|
const dataBuffer = fs.readFileSync(filePath); |
|
|
|
|
fileProcessPromise = pdfParse(dataBuffer).then((data) => data.text); |
|
|
|
|
} else if (extension === ".docx") { |
|
|
|
|
fileProcessPromise = mammoth |
|
|
|
|
.extractRawText({ path: filePath }) |
|
|
|
|
.then((result) => result.value) |
|
|
|
|
.catch((err) => { |
|
|
|
|
console.error("Error processing DOCX file:", err); |
|
|
|
|
throw new Error("Error processing DOCX file."); |
|
|
|
|
}); |
|
|
|
|
} else { |
|
|
|
|
event.reply("file-response", "Error: Unsupported file type"); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
fileProcessPromise |
|
|
|
|
.then((extractedText) => { |
|
|
|
|
// Sending the extracted text back to the frontend.
|
|
|
|
|
event.reply("file-response", extractedText); |
|
|
|
|
}) |
|
|
|
|
.catch((error) => { |
|
|
|
|
// Handling any errors during file processing and sending them back to the frontend.
|
|
|
|
|
event.reply("file-response", `Error processing file: ${error.message}`); |
|
|
|
|
}); |
|
|
|
|
}); |
|
|
|
|
|
|
|
|
|
ipcMain.on("start-query-openai", async (event, system, user) => { |
|
|
|
|
if (system == null || user == null) { |
|
|
|
|
console.error("Received null for system or user message"); |
|
|
|
|
event.reply("openai-response", "Error: System or user message is null."); |
|
|
|
|
ipcMain.on("start-query", async (event, system, user, model) => { |
|
|
|
|
if (system == null || user == null || model == null) { |
|
|
|
|
console.error("Received null for system, user message, or model"); |
|
|
|
|
event.reply( |
|
|
|
|
"model-response-error", |
|
|
|
|
"Error: System, user message, or model is null." |
|
|
|
|
); |
|
|
|
|
return; |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
try { |
|
|
|
|
await queryOpenAI(system, user, (message) => { |
|
|
|
|
event.reply("openai-response", message); |
|
|
|
|
}); |
|
|
|
|
const _gptModels = allModels.gptModels.map((model) => model.id); |
|
|
|
|
if (allModels.claudeModels.includes(model)) { |
|
|
|
|
await claudeMessage(system, user, model, event); |
|
|
|
|
} else if (_gptModels.includes(model)) { |
|
|
|
|
await openaiMessage(system, user, model, event); |
|
|
|
|
} else if (allModels.ollamaModels.includes(model)) { |
|
|
|
|
await ollamaMessage(system, user, model, event); |
|
|
|
|
} else { |
|
|
|
|
event.reply("model-response-error", "Unsupported model: " + model); |
|
|
|
|
} |
|
|
|
|
} catch (error) { |
|
|
|
|
console.error("Error querying OpenAI:", error); |
|
|
|
|
event.reply("no-api-key", "Error querying OpenAI."); |
|
|
|
|
console.error("Error querying model:", error); |
|
|
|
|
event.reply("model-response-error", "Error querying model."); |
|
|
|
|
} |
|
|
|
|
}); |
|
|
|
|
|
|
|
|
|
@ -245,31 +375,32 @@ ipcMain.handle("get-pattern-content", async (event, patternName) => {
|
|
|
|
|
} |
|
|
|
|
}); |
|
|
|
|
|
|
|
|
|
ipcMain.handle("save-api-key", async (event, apiKey) => { |
|
|
|
|
ipcMain.handle("save-api-keys", async (event, { openAIKey, claudeKey }) => { |
|
|
|
|
try { |
|
|
|
|
const configPath = path.join(os.homedir(), ".config", "fabric"); |
|
|
|
|
if (!fs.existsSync(configPath)) { |
|
|
|
|
fs.mkdirSync(configPath, { recursive: true }); |
|
|
|
|
} |
|
|
|
|
|
|
|
|
|
const envFilePath = path.join(configPath, ".env"); |
|
|
|
|
fs.writeFileSync(envFilePath, `OPENAI_API_KEY=${apiKey}`); |
|
|
|
|
process.env.OPENAI_API_KEY = apiKey; |
|
|
|
|
saveApiKeys(openAIKey, claudeKey); |
|
|
|
|
return "API Keys saved successfully."; |
|
|
|
|
} catch (error) { |
|
|
|
|
console.error("Error saving API keys:", error); |
|
|
|
|
throw new Error("Failed to save API Keys."); |
|
|
|
|
} |
|
|
|
|
}); |
|
|
|
|
|
|
|
|
|
return "API Key saved successfully."; |
|
|
|
|
ipcMain.handle("get-models", async (event) => { |
|
|
|
|
try { |
|
|
|
|
const models = await getModels(); |
|
|
|
|
return models; |
|
|
|
|
} catch (error) { |
|
|
|
|
console.error("Error saving API key:", error); |
|
|
|
|
throw new Error("Failed to save API Key."); |
|
|
|
|
console.error("Failed to get models:", error); |
|
|
|
|
return { gptModels: [], claudeModels: [], ollamaModels: [] }; |
|
|
|
|
} |
|
|
|
|
}); |
|
|
|
|
|
|
|
|
|
app.whenReady().then(async () => { |
|
|
|
|
try { |
|
|
|
|
const apiKey = loadApiKey(); |
|
|
|
|
if (!apiKey) { |
|
|
|
|
const keys = loadApiKeys(); |
|
|
|
|
if (!keys.openAIKey && !keys.claudeKey) { |
|
|
|
|
promptUserForApiKey(); |
|
|
|
|
} else { |
|
|
|
|
process.env.OPENAI_API_KEY = apiKey; |
|
|
|
|
createWindow(); |
|
|
|
|
} |
|
|
|
|
await ensureFabricFoldersExist(); // Ensure fabric folders exist
|
|
|
|
|
@ -278,7 +409,6 @@ app.whenReady().then(async () => {
|
|
|
|
|
// After window creation, check if the API key exists
|
|
|
|
|
if (!checkApiKeyExists()) { |
|
|
|
|
console.log("API key is missing. Prompting user to input API key."); |
|
|
|
|
// Optionally, directly invoke a function here to show a prompt in the renderer process
|
|
|
|
|
win.webContents.send("request-api-key"); |
|
|
|
|
} |
|
|
|
|
} catch (error) { |
|
|
|
|
|
xssdoctor
8 months ago