feat: implement fuzzy search and replace functionality with Levenshtein distance

- Added `applySearchReplace` function to handle search and replace operations with fuzzy matching capabilities.
- Introduced tests for various scenarios including fuzzy matching with typos, exact matches, and handling whitespace differences.
- Created a parser for search/replace blocks to facilitate the new functionality.
- Updated prompts for search-replace operations to clarify usage and examples.
- Added utility functions for text normalization and language detection based on file extensions.
- Implemented a minimal stdio MCP server for local testing with tools for adding numbers and printing environment variables.

e2e-tests/azure_send_message.spec.ts

@@ -0,0 +1,25 @@
+import { testWithConfigSkipIfWindows } from "./helpers/test_helper";
+
+// Set environment variables before the test runs to enable Azure testing
+
+const testAzure = testWithConfigSkipIfWindows({
+  preLaunchHook: async () => {
+    process.env.TEST_AZURE_BASE_URL = "http://localhost:3500/azure";
+    process.env.AZURE_API_KEY = "fake-azure-key-for-testing";
+    process.env.AZURE_RESOURCE_NAME = "fake-resource-for-testing";
+  },
+});
+
+testAzure("send message through Azure OpenAI", async ({ po }) => {
+  // Set up Azure without test provider
+  await po.setUpAzure();
+
+  // Select Azure model
+  await po.selectTestAzureModel();
+
+  // Send a test prompt that returns a normal conversational response
+  await po.sendPrompt("tc=basic");
+
+  // Verify we get a response (this means Azure integration is working)
+  await po.snapshotMessages();
+});