Cache embeddings for recent thoughts to improve performance

[sourcery-ai]

Description

In the current implementation, embeddings for recent thoughts are recomputed each time the _analyze_patterns method is called. This can lead to unnecessary performance overhead, especially when the same thoughts are analyzed multiple times.

Suggested Improvement

To enhance performance, it is suggested to cache the embeddings for recent thoughts. This can be achieved by storing the embeddings in a thought_history attribute, which will prevent the need to recompute them repeatedly.

Proposed Solution

Introduce a caching mechanism within the _analyze_patterns method:

    def _analyze_patterns(self) -> float:
        if not hasattr(self, '_thought_embeddings'):
            self._thought_embeddings = {}

This change will ensure that embeddings are computed only once and reused in subsequent calls, thus improving the efficiency of the method.

Action Items

• Implement the caching mechanism as suggested.
• Test the implementation to ensure that it correctly caches and retrieves embeddings.
• Measure performance improvements to validate the effectiveness of the caching strategy.

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I created this issue for @leonvanbokhorst from #68 (comment).

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