This project demonstrates how to create an interactive communication assistant using the LangChain library. The assistant maintains session histories, manages message sizes, and provides responses based on past interactions.
- Environment Setup: Loads and sets up environment variables.
- Model Initialization: Initializes the GPT-4 model via ChatOpenAI.
- Session History: Manages message histories for different sessions.
- Message Trimming: Limits the number of tokens in the message history.
- Prompt Template: Creates a structured prompt template.
- Runnable Chain: Sets up a processing chain that includes history management and message trimming.
- Response Streaming: Streams responses from the model and prints them.
- Trimming and Invocation: Trims a set of messages and invokes the model to get a response.
This script is designed to facilitate interactive communication with an AI model, maintaining session histories, and managing message sizes to ensure efficient processing. The primary use case is for creating a helpful assistant that can remember past interactions and respond accordingly.
- Python 3.7+
- LangChain
- OpenAI API Key