feat: integrate custom features for smart context management

- Added a new integration script to manage custom features related to smart context.
- Implemented handlers for smart context operations (get, update, clear, stats) in ipc.
- Created a SmartContextStore class to manage context snippets and summaries.
- Developed hooks for React to interact with smart context (useSmartContext, useUpdateSmartContext, useClearSmartContext, useSmartContextStats).
- Included backup and restore functionality in the integration script.
- Validated integration by checking for custom modifications and file existence.

backups/backup-20251218-094212/testing/fake-llm-server/README.md

@@ -0,0 +1,116 @@
+# Fake LLM Server
+
+A simple server that mimics the OpenAI streaming chat completions API for testing purposes.
+
+## Features
+
+- Implements a basic version of the OpenAI chat completions API
+- Supports both streaming and non-streaming responses
+- Always responds with "hello world" message
+- Simulates a 429 rate limit error when the last message is "[429]"
+- Configurable through environment variables
+
+## Installation
+
+```bash
+npm install
+```
+
+## Usage
+
+Start the server:
+
+```bash
+# Development mode
+npm run dev
+
+# Production mode
+npm run build
+npm start
+```
+
+### Example usage
+
+```
+curl -X POST http://localhost:3500/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"Say something"}],"model":"any-model","stream":true}'
+```
+
+The server will be available at http://localhost:3500 by default.
+
+## API Endpoints
+
+### POST /v1/chat/completions
+
+This endpoint mimics OpenAI's chat completions API.
+
+#### Request Format
+
+```json
+{
+  "messages": [{ "role": "user", "content": "Your prompt here" }],
+  "model": "any-model",
+  "stream": true
+}
+```
+
+- Set `stream: true` to receive a streaming response
+- Set `stream: false` or omit it for a regular JSON response
+
+#### Response
+
+For non-streaming requests, you'll get a standard JSON response:
+
+```json
+{
+  "id": "chatcmpl-123456789",
+  "object": "chat.completion",
+  "created": 1699000000,
+  "model": "fake-model",
+  "choices": [
+    {
+      "index": 0,
+      "message": {
+        "role": "assistant",
+        "content": "hello world"
+      },
+      "finish_reason": "stop"
+    }
+  ]
+}
+```
+
+For streaming requests, you'll receive a series of server-sent events (SSE), each containing a chunk of the response.
+
+### Simulating Rate Limit Errors
+
+To test how your application handles rate limiting, send a message with content exactly equal to `[429]`:
+
+```json
+{
+  "messages": [{ "role": "user", "content": "[429]" }],
+  "model": "any-model"
+}
+```
+
+This will return a 429 status code with the following response:
+
+```json
+{
+  "error": {
+    "message": "Too many requests. Please try again later.",
+    "type": "rate_limit_error",
+    "param": null,
+    "code": "rate_limit_exceeded"
+  }
+}
+```
+
+## Configuration
+
+You can configure the server by modifying the `PORT` variable in the code.
+
+## Use Case
+
+This server is primarily intended for testing applications that integrate with OpenAI's API, allowing you to develop and test without making actual API calls to OpenAI.