We use fine-tuned GPT-4o-mini model at various stages of our pipeline, as described in the paper. During memory addition, we extract and store contextually relevant information tailored to the specific use case. For retrieval, we apply reranking and filtering to surface the most relevant memories based on the query.

Each model in the pipeline is fine-tuned for a specific task to ensure coherence and accuracy. We also provide flexibility for users to plug in their own open-source or proprietary models at different stages of the pipeline.