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README.md

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-# SwarmChat: Unified Audio, Text, and Simulation Environment for Human-Swarm Interaction
-
-SwarmChat is an innovative project that enables intuitive communication with swarm robotics through natural language. This system integrates advanced audio transcription, text processing, and safety mechanisms with a live simulation environment that visualizes a swarm of agents executing behavior trees.
-
-## Features
-
-- **Audio Input Processing**:
-
-  - Record commands via a microphone.
-  - Translate speech into English using the `facebook/seamless-m4t-v2-large` model.
-  - Perform a safety check on the translated text before execution.
-
-- **Text Input Processing**:
-
-  - Enter text commands for swarm control.
-  - Translate text using EuroLLM (EuroLLM-9B-Instruct-Q4_K_M.gguf).
-  - Detect unsafe or inappropriate content with an integrated safety module.
-
-- **Safety Module**:
-
-  - Utilizes a fine-tuned LLaMA-based model (llama-guard-3-8b-q4_k_m.gguf) for safety classification.
-  - Identifies unsafe content across predefined categories (e.g., violent crimes, privacy violations, hate speech).
-  - Ensures commands comply with safety standards.
-
-- **Swarm Simulation**:
-
-  - Visualize a swarm of agents in a live simulation powered by Violet simulator and Pygame.
-  - Agents are controlled by behavior trees defined in an XML file (`tree.xml`), using the `py_trees` framework.
-  - Real-time simulation updates streamed via a Gradio web interface.
-
-- **Behavior Tree Generator**:
-
-  - DeepSeek leverages a Llama-based model to dynamically generate behavior trees in XML format.
-  - Automatically extracts available behaviors from the SwarmAgent class and constructs a detailed prompt using a predefined XML template.
-  - Generates and saves new behavior tree configurations (updating tree.xml) based on user-specified tasks.
-
-- **Integrated Interface**:
-  - A unified Gradio web interface for both audio and text inputs.
-  - Live streaming of the simulation environment.
-  - Seamless switching between different input modalities.
-
-## Technology Stack
-
-- **Backend**:
-
-  - Python
-  - [Transformers](https://huggingface.co/transformers/) (Hugging Face)
-  - PyTorch
-  - Pygame
-  - Threading and Queue modules for simulation management
-
-- **Frontend**:
-
-  - [Gradio](https://gradio.app/) for an interactive web-based interface.
-
-- **AI Models**:
-
-  - **Speech Processing**: `facebook/seamless-m4t-v2-large` for audio transcription and translation.
-  - **Text Processing**: EuroLLM (EuroLLM-9B-Instruct-Q4_K_M.gguf) for text translation.
-  - **Safety Classification**: LLaMA Guard (llama-guard-3-8b-q4_k_m.gguf) for content safety assessment.
-  - **Behavior Tree Generation**: DeepSeek (using a Llama-based model DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf) for creating and updating behavior tree configurations.
-
-- **Behavior Trees**:
-  - Agents utilize behavior trees—parsed from XML and built with `py_trees`—to dictate their actions within the simulation.
-
-## Installation
-
-1. **Clone the repository**:
-
-   ```bash
-   git clone https://github.com/Inventors-Hub/SwarmChat.git
-   cd SwarmChat
-   ```
-
-2. **Install dependencies**:
-   ```bash
-   pip install -r requirements.txt
-   ```
-3. **Setup AI Models**:
-
-- Place the EuroLLM model file (`EuroLLM-9B-Instruct-Q4_K_M.gguf`) at the specified path in `text_processing.py`.
-- Place the LLaMA Guard model file (`llama-guard-3-8b-q4_k_m.gguf`) at the specified path in `safety_module.py`.
-- Place the DeepSeek model file (`DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf`) at the specified path in `bt_generator.py`.
-
-4. **Run the Application**:
-   ```bash
-   python app.py
-   ```
-5. **Access the Interface**:
-
-   Open your browser and navigate to http://127.0.0.1:7860 to start using SwarmChat.
-
-## Overview of Modules
-
-- **app.py**  
-  The main application integrates audio/text processing, behavior tree generation, and the live simulation. It sets up the Gradio interface, handles simulation streaming, and routes user inputs to the appropriate processing modules.
-
-- **speech_processing.py**  
-  Implements audio transcription and translation using the `facebook/seamless-m4t-v2-large` model.
-
-- **text_processing.py**  
-  Translates text commands using EuroLLM (EuroLLM-9B-Instruct-Q4_K_M.gguf).
-
-- **safety_module.py**  
-  Utilizes LLaMA Guard to assess the safety of incoming commands, ensuring compliance with safety policies.
-
-- **bt_generator.py**  
-  Dynamically generates behavior trees in XML format by extracting behaviors from the SwarmAgent class, constructing a prompt, and querying a Llama-based model. The generated XML is saved to `tree.xml` for simulation use.
-
-- **simulator_env.py**  
-  Powers the simulation environment, manages agent behaviors using XML-defined behavior trees, and handles real-time simulation updates.
+title: SwarmChat v2
+emoji: 🤖
+colorFrom: blue
+colorTo: indigo
+sdk: docker
+app_file: Dockerfile
+app_port: 7860
+pinned: false