This project is a Streamlit web application that provides AI-powered translation of uploaded CSV or text files. Users can select source and target languages, upload files, and download the translated text. The application uses a custom module, Translator, which interfaces with an AI language model to perform translations.

• File Upload: Supports CSV, TXT, and Markdown file uploads.
• Language Detection and Translation: Automatically detects or allows the user to select the source language. Users can choose the target language.
• Progress Feedback: Displays a progress bar and status while translating.
• Translation Download: Allows users to download the translated text as a file.
• Streamlit Interface: Provides a simple web-based UI to interact with the translator.

1. Clone the repository:

   git clone https://github.com/birdhouses/Translator.git
   cd Translator

2. Install the required Python packages:

   pip install -r requirements.txt

3. Set up environment variables:

   • Create a .env file in the root directory with the following content:

     OPENAI_API_KEY=your_openai_api_key
     OPENAI_ASSISTANT_ID=your_assistant_id
     

4. Run the application:

   streamlit run app.py

1. Open the Streamlit application in your browser.
2. Upload a CSV or text file that you want to translate.
3. Select the source language (or choose "Detect Language").
4. Select the target language for translation.
5. Enter a model name if you want to use a custom model (default is "gpt-4o-mini").
6. Click the Translate button.
7. Download the translated file or view the translated text in the text area.

The main entry point for the Streamlit app. It handles:

• File uploads.
• Language selection.
• Calling the Translator module for translation.
• Displaying progress and results to the user.

Contains the Translator class, which handles the text translation using an AI model:

• Splits the input text into manageable chunks for translation.
• Interacts with the Assistant class to obtain translated results.
• Provides progress feedback during translation.

Implements the Assistant class, which interacts with the OpenAI API:

• Handles the conversation with the assistant.
• Retrieves the translated text.
• Manages tool calls and progress updates.

• streamlit: Used for creating the web UI.
• pandas: For handling CSV files.
• tiktoken: To tokenize text for input to the AI model.
• openai: To communicate with the OpenAI API.
• python-dotenv: For loading environment variables from a .env file.

This project is licensed under the MIT License. See the LICENSE file for more details.

• This project uses OpenAI's language models for translations.
• Streamlit is used to create the user interface for easy interaction.

Feel free to fork the repository and submit pull requests. Any contributions to improve this project are welcome!