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  • How to pass conversation history back to the API
    Instead, you can just run embeddings on several recent conversation turns The embeddings AI can understand conversational flow, and semantics will be drawn towards the conclusion and the next output It is a magnitude less expensive and faster
  • How to incorporate context chat history in OpenAI ChatBot . . .
    There is very simple solution that can remember the long conversation, more than 100+ messages history, and will answer the questions It's a mix of prompt engineering + database + logical flow I have created a detailed article on how to implement it
  • Managing Chat History and Context at scale in Generative AI . . .
    The solution involves three key components that work together to ensure chat history is stored, summarized, and queried efficiently: In-Memory Chat History Storage (Redis): Purpose: Provides immediate access to recent chat messages, reducing latency during live conversations
  • How to manage Conversation History with OpenAI API?
    Efficiently managing conversation history with OpenAI API is crucial for creating responsive and cost-effective applications By leveraging techniques like summarization, rolling windows, and vector databases, developers can maintain rich conversational experiences while minimizing overhead
  • How to add a history of past message in Azure OpenAI REST API
    To maintain historical context in repeat API calls with Azure OpenAI REST API, you can include a summary of previous interactions as context in your subsequent API calls Unfortunately, OpenAI’s GPT-3 API does not currently support sessions or maintaining state between API calls
  • How do you maintain historical context in repeat API calls?
    To maintain historical context in repeat API calls, you can include a summary of previous interactions as context in your subsequent API calls This can be done by concatenating all the previous outputs and using them as the “prompt” in your next API call
  • How to Make LLM Remember Conversation with Langchain
    The historical conversation can be compressed into summary with ConversationSummaryMemory The summary can be passed as history to the LLM





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