The llm_model package is a ROS package that provides a conversational interface using the OpenAI API. The package includes a node called ChatGPTNode which interacts with the ChatGPT service to implement conversational interactions.
This file contains the implementation of the ChatGPTNode node, which is responsible for providing a conversational interface using the OpenAI API. The node implements the ChatGPT service callback function llm_callback, which is called whenever a client sends a request to the ChatGPT service.
The ChatGPTNode node also includes a client function function_call_client and a publisher output_publisher. The function_call_client function is used to call other functions using ROS Service, while the output_publisher publishes messages to a topic.
The chatgpt.py file also includes a function called add_message_to_history to update chat history records. The file writes chat history records to a JSON file using Python's JSON library.
Overall, the chatgpt.py file provides a ROS-based conversational interface with the OpenAI API, allowing users to interact with a chatbot.
To test the turtle_robot.py file with robot node, use the following ROS command-line to publish a speed command that makes the turtlesim rotate:
ros2 service call /ChatGPT_service llm_interfaces/srv/ChatGPT '{request_text: "Let the turtlesim rotate counterclockwise at a great angular velocity of 50 rad/s and move forward at a certain linear velocity"}'Reset the turtlesim
ros2 service call /ChatGPT_service llm_interfaces/srv/ChatGPT '{request_text: "I want the little turtle to go back to where it started."}'