Mechanical bot
Mechanical Bot is a chatbot specifically designed to assist users with mechanical engineering-related inquiries.
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Description
Mechanical-bot
Mechanical Bot is a chatbot specifically designed to assist users with mechanical engineering-related inquiries. By integrating data about various mechanical systems, designs, and processes into a large language model (LLM), this chatbot provides insightful information and advice on topics such as machinery, mechanical design, materials, and maintenance.
Features Interactive chatbot interface for mechanical engineering-related questions. Extensive database of information on machinery, mechanical systems, and design principles. Personalized advice and recommendations based on user queries. Access to industry trends and updates in mechanical engineering.
Installation To get started with Mechanical Bot, follow these steps:
Clone the repository: git clone https://github.com/your-username/mechanical-bot.git cd MechanicalBot
Install the Gaia Node by running the following command: curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/install.sh' | bash
Run the following command to update your config.json to run with a small language model: --config https://raw.githubusercontent.com/harishkotra/Gaia-8G/refs/heads/main/config_8g.json
Start the node: gaianet start
How to Use Open your web browser and navigate to the generated link. Start interacting with the chatbot by typing your mechanical engineering-related questions (e.g., mechanical design principles, material properties, machinery maintenance).
License This project is licensed under the MIT License. See the LICENSE file for details.
Progress During Hackathon
During the hackathon, we developed Mechanical Bot, a chatbot designed to provide real-time assistance and insights on mechanical engineering topics. The bot leverages a large language model (LLM) trained on a vast database covering machinery, mechanical design, material properties, and maintenance practices. Challenges included structuring complex engineering data for optimal LLM performance and ensuring the bot could cater to a wide range of mechanical engineering topics. The result is a functional, interactive tool for engineers, students, and enthusiasts alike.