app/webui/README.md

Translation Agent WebUI

This repository contains a Gradio web UI for a translation agent that utilizes various language models for translation.

Preview

Features:

• Tokenized Text: Displays translated text with tokenization, highlighting differences between original and translated words.
• Document Upload: Supports uploading various document formats (PDF, TXT, DOC, etc.) for translation.
• Multiple API Support: Integrates with popular language models like:
  • Groq
  • OpenAI
  • Cohere
  • Ollama
  • Together AI
  • Hugging Face Inference API ... Llama Index supported, easily extendable

Getting Started

1. Install Dependencies:

   Linux(Using Python Venv)

       git clone https://github.com/andrewyng/translation-agent.git
       cd translation-agent
       python -m venv web_ui
       source web_ui/bin/activate
       pip install -r app/webui/requirements.txt
   

   Windows

       git clone https://github.com/andrewyng/translation-agent.git
       cd translation-agent
       python -m venv web_ui
       .\web_ui\Scripts\activate
       pip install -r app/webui/requirements.txt
   

2. Set API Keys:

   • Rename .env.sample to .env, you can add your API keys for each service:

     OPENAI_API_KEY="sk-xxxxx" # Keep this field
     GROQ_API_KEY="xxxxx"
     COHERE_API_KEY="xxxxx"
     TOGETHER_API_KEY="xxxxx"
     HF_TOKEN="xxxxx"
     

   • Then you can also set the API_KEY in webui.

3. Run the Web UI:

   python -m app.webui.app
   

4. Access the Web UI: Open your web browser and navigate to http://127.0.0.1:7860/.

Usage:

1. Select your desired translation API from the Endpoint dropdown menu.
2. Input the source language, target language, and country(optional).
3. If using Hugging Face API, enter your HF_TOKEN in the api_key textbox.
4. Input the source text or upload your document file.
5. Submit and get translation, the UI will display the translated text with tokenization and highlight differences.
6. Enable Second Endpoint, you can add another endpoint by different LLMs for reflection.

Customization:

• Add New LLMs: Modify the patch.py file to integrate additional LLMs.

Contributing:

Contributions are welcome! Feel free to open issues or submit pull requests.

License:

This project is licensed under the MIT License.

DEMO:

Huggingface Demo