Recommendation System with Conversation Memory
The recommendation engine has been upgraded to maintain persistent conversation history between recommendation requests, creating more efficient and consistent content discovery.
New Features
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Persistent Context: Recommendation system now preserves conversation history across multiple requests
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Contextual Request Handling: Each "Get Recommendations" action builds upon previous interactions instead of reinitializing
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Intelligent Memory Management: Separate context tracking for TV and movie recommendations
Technical Enhancements
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Token Usage Reduction: Subsequent recommendation requests require approximately 90% fewer tokens
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Modified Context Management: Updates to OpenAIService.js enable state preservation between API calls
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Optimized Initialization: Conversation reset logic now only triggers when necessary, not on every request
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Streamlined Prompt Design: Subsequent requests use condensed prompts that reference existing conversation history
This update significantly improves both performance and recommendation relevance by maintaining user preference data and content history across multiple recommendations requests.