ClickUi: Your Cross-Platform AI Assistant for Local and Cloud Models

Introduction

ClickUi is an innovative, open-source AI assistant built entirely in Python, designed to bring the power of artificial intelligence directly to your desktop. It empowers users to interact with various AI models, supporting both local solutions like Ollama and paid API services such as OpenAI, Claude, and Google. With its intuitive interface, accessible via a simple Ctrl+k hotkey, ClickUi offers a seamless experience for voice and text interactions, file attachments, and integrated web searches. It aims to be the most widely used computer-based AI assistant, providing a versatile and customizable tool for enhanced productivity.

Installation

Getting started with ClickUi involves a few straightforward steps, primarily leveraging Conda for environment management. For Windows users, an Install.bat script is available for a simplified setup.

Manual Installation Steps:

Install Anaconda/Conda: Download and install Anaconda or Conda from https://www.anaconda.com/download/success.
Clone the Repository: Obtain the ClickUi source code by cloning its GitHub repository.
Create and Activate Conda Environment: Navigate to the cloned directory in your terminal and run:
```
conda create --name click_ui --file conda_packages.txt
conda activate click_ui
```
Install Python Dependencies: Install the required Python packages:
```
pip install -r requirements.txt
```
Configure API Keys: Edit the .voiceconfig file in the root directory to set up your API keys and preferred engine/model.
Start the Program: Run python clickui.py from your activated Conda environment. Once you see "Ready!...", press Ctrl+k to launch the interface.

Examples

ClickUi integrates several powerful functionalities to provide a comprehensive AI experience.

Voice Interaction:
Leverage Whisper for automatic speech recognition and Kokoro for text-to-speech, enabling natural voice conversations with your AI assistant.

import whisper as openai_whisper

whisper_model = openai_whisper.load_model("base", device='cuda')

def transcribe_audio(audio_data, samplerate):
    # ... (simplified for brevity) ...
    result = whisper_model.transcribe(temp_wav_name, fp16=False)
    return result["text"]

Text Chat:
Engage with AI models through a familiar text-based chat interface, supporting direct queries and responses.

class ChatDialog(QWidget):
    # ...
    def handle_reply_send(self):
        text = self.reply_line.text().strip()
        if text:
            self.add_message(text, role="user")
            self.reply_line.clear()
            # ... AI processing ...

File Attachments:
Easily attach text-based files (e.g., .txt, .csv, .xlsx) via drag-and-drop, allowing the AI to process and respond based on their content.

class FileDropLineEdit(QLineEdit):
    file_attached = Signal(list)

    def dropEvent(self, event):
        if event.mimeData().hasUrls():
            attachments = []
            for url in event.mimeData().urls():
                file_path = url.toLocalFile()
                ext = os.path.splitext(file_path)[1].lower()
                if ext in ['.txt', '.csv', '.xlsx', '.xls']:
                    # ... read file content ...
                    attachments.append({'filename': file_name, 'content': content})
            if attachments:
                self.attachments = attachments
                self.file_attached.emit(attachments)
            event.acceptProposedAction()
        else:
            super().dropEvent(event)

Google Search Integration:
Perform real-time Google searches directly from the assistant to fetch up-to-date information and enhance AI responses.

def google_search(query: str) -> str:
    # ...
    url = f"https://www.google.com/search?q={encoded_query}"
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True, args=["--disable-blink-features=AutomationControlled"])
        page = context.new_page()
        page.goto(url)
        page.wait_for_load_state("networkidle")
        html = page.content()
        browser.close()
    soup = BeautifulSoup(html, 'html.parser')
    text = soup.get_text()
    cleaned_text = ' '.join(text.split())[0:5000]
    return cleaned_text

AI Models Integration:
ClickUi supports a wide range of AI models, including OpenAI, Google, Ollama, Claude, Groq, and OpenRouter, allowing users to switch between them based on their needs.

def call_openai(prompt: str, model_name: str, reasoning_effort: str) -> str:
    import openai
    # ...
    openai.api_key = OPENAI_API_KEY
    # ... API call logic ...
    try:
        response = openai.chat.completions.create(**api_params)
    except Exception as e:
        print(f"Error connecting to OpenAI: {e}")
        return ""
    # ... response handling ...

Why Use It

ClickUi stands out as a versatile and powerful AI assistant for several reasons:

Unparalleled Versatility: Seamlessly switch between various local and cloud-based AI models, offering flexibility to choose the best tool for any task.
Comprehensive Feature Set: From natural voice interactions and text chat to intelligent web scraping for property lookups and Google searches, ClickUi provides a rich suite of tools.
Open-Source Empowerment: Being open-source, ClickUi encourages community contributions and allows for deep customization, ensuring it evolves with user needs.
Cross-Platform Accessibility: Built purely in Python, it's designed to run efficiently across Windows, macOS, and Linux, making advanced AI accessible to everyone.
Enhanced Productivity: With quick access via a global hotkey and integrated functionalities, ClickUi streamlines workflows and boosts efficiency for daily tasks.

ClickUi: Your Cross-Platform AI Assistant for Local and Cloud Models

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