dev: finishing fetch data types and also readme update

Author: anisiosts

README.md

@@ -1,27 +1,149 @@
-# <img src="./images/logo.png" width=20> RevEng.AI Binary Ninja Plugin
+# <img src="./images/banner.png"> 
 
-A Binary Ninja plugin for integrating with the RevEng.AI platform.
+# Official Binary Ninja Plugin for RevEng.AI
 
-## Installation
+### Features Supported
 
-1. Ensure you have Python 3.9 or later installed
-2. Install the required dependencies:
-   ```bash
-   pip install -r requirements.txt
-   ```
-3. Copy the `revengai_bn` directory to your Binary Ninja plugins directory:
-   - Linux: `~/.binaryninja/plugins/`
-   - Windows: `%APPDATA%\Binary Ninja\plugins\`
-   - macOS: `~/Library/Application Support/Binary Ninja/plugins/`
+This plugin brings the power of RevEng.AI directly into Binary Ninja. Here are the main features currently supported:
 
+- **Configuration Panel**: Easily configure your API credentials and platform settings.
+- **Choose a Source**: Select the uploaded binary whose analysis will be used for other features such as matching and renaming.
+- **Process Binary**: Upload the currently loaded binary in Binary Ninja to RevEng.AI for analysis.
+- **Auto-Unstrip**: Automatically restore stripped symbols in your binary using our AI engine.
+- **Function Matching**: Compare and match functions from your current binary with those in your existing collections.
 
-## Requirements
+---
 
-- Binary Ninja 5.0 or later
-- Python 3.9 or later
-- Internet connection for API access
-- RevEng.AI API key
+## Installation & Running 🚀
+
+### Step 1: Locate Binary Ninja Plugins Folder
+
+Locate your Binary Ninja user plugin directory:
+
+- **Tools > Plugins > Open Plugin Folder** from the Binary Ninja menu
+
+> 💡 **Tip**: This opens the correct path regardless of OS or install type.
+
+Expected output locations:
+ - Linux: `~/.binaryninja/plugins/`
+ - Windows: `%APPDATA%\Binary Ninja\plugins\`
+ - macOS: `~/Library/Application Support/Binary Ninja/plugins/`
+
+
+### Step 2: Download & Install the Plugin
+
+1. Visit the releases page: https://github.com/RevEngAI/reai-ida/releases
+2. Download the latest release (look for the most recent version).
+3. Extract the contents into the opened plugin folder.
+4. Ensure the folder structure looks like this:
+
+```
+~/.binaryninja/plugins/
+   └── revengai/
+      └── [plugin files...]
+```
+
+> 🖼️ *Insert screenshot of the correct plugin folder structure*
+
+### Step 3: Install Dependencies
+
+In your system terminal (not inside Binary Ninja), install required dependencies using:
+
+```bash
+pip install -r ~/.binaryninja/plugins/revengai/requirements.txt
+```
+
+Or directly from within Binary Ninja’s built-in Python terminal:
+
+```python
+import subprocess
+subprocess.check_call(['pip', 'install', '-r', '/path/to/revengai/requirements.txt'])
+```
+
+---
+
+## Using the Plugin ⚙️
+
+Once installed, you’ll find `RevEng.AI` in the Binary Ninja toolbar menu.
+
+> 🖼️ *Insert screenshot of the RevEng.AI menu in Binary Ninja*
+
+### 1. Configure the Plugin
+
+Select `Configuration` from the menu to set up your API key and host.
+
+> 🖼️ *Insert screenshot of configuration window*
+
+Clicking "Continue" will validate your API key and auto-populate available models.
+
+---
+
+### 2. Choose Source Analysis
+
+If you’ve already uploaded and processed a binary in the platform, you can select it as your working source.
+
+> 🖼️ *Insert screenshot of the choose-source UI*
+
+This is required before using some features like function matching or auto-unstrip.
+
+---
+
+### 3. Process a Binary
+
+Upload the currently loaded binary to RevEng.AI:
+
+- Open your binary in Binary Ninja
+- Select `RevEng.AI > Process Binary`
+
+> 🖼️ *Insert screenshot of binary processing prompt*
+
+The plugin will handle the upload and initiate the analysis. Once completed, an internal analysis ID is assigned.
+
+---
+
+### 4. Auto-Unstrip
+
+Bring back stripped symbol names automatically:
+
+- Select `RevEng.AI > Auto-Unstrip`
+
+> 🖼️ *Insert screenshot of auto-unstrip in action*
+
+Functions will be renamed with the most likely matching names from your configured collections.
+
+---
+
+### 5. Match Functions
+
+Use function matching to identify similar functions in other binaries or collections:
+
+- Open any function
+- Click `RevEng.AI > Match Functions`
+
+> 🖼️ *Insert screenshot of match functions result*
+
+Matched functions are displayed with similarity and metadata. You can navigate or rename based on the results.
+
+---
+
+## Troubleshooting
+
+- Only Binary Ninja 3.0+ is supported
+- Python 3.9 or later is required
+- Ensure your API key is valid and your analysis contains function-level information
+
+## Software Requirements
+
+This plugin relies on:
+
+- [reait](https://github.com/RevEngAI/reait)
+- requests
+- PySide6
 
 ## License
 
 This plugin is released under the GPL-2.0 license. 
+
+## Disclaimer
+
+Binary Ninja is a trademark of Vector 35. This project is not affiliated with or endorsed by Vector 35.

features/match_functions/tab_result.py

@@ -1,7 +1,7 @@
 from binaryninja import PluginCommand, log_info, BinaryView
 from .auto_unstrip import AutoUnstrip
 from .auto_unstrip_dialog import AutoUnstripDialog
-from revengai_bn.utils import BaseAuthFeature
+from revengai.utils import BaseAuthFeature
 
 class AutoUnstripFeature(BaseAuthFeature):
     def __init__(self, config=None):

images/banner.png

@@ -7,7 +7,7 @@
 from PySide6.QtGui import QPixmap, QIcon
 from PySide6.QtCore import QCoreApplication
 from PySide6.QtWidgets import QMessageBox
-from revengai_bn.utils import create_progress_dialog
+from revengai.utils import create_progress_dialog
 from .auto_unstrip_thread import AutoUnstripThread
 import os
 

__init__.py revengai/__init__.py__init__.py renamed to revengai/__init__.py

@@ -1,7 +1,7 @@
 from binaryninja import PluginCommand, log_info, BinaryView
 from .choose_source import ChooseSource
 from .choose_source_dialog import ChooseSourceDialog
-from revengai_bn.utils import BaseAuthFeature
+from revengai.utils import BaseAuthFeature
 
 class ChooseSourceFeature(BaseAuthFeature):
     def __init__(self, config=None):