System prompt for summary strategy
A system prompt is a combination of:
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A set of instructions that guide the LLM's behavior. It can include step-by-step processing guidelines (how the model should reason and extract or consolidate information).
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Output Schema - how the model should present the result.
This system prompt is sent to the LLM during memory consolidation step.
There is no extraction step for summary strategy. Summary generation happens in a single consolidation step.
Consolidation instructions
There are no consolidation instructions for built-in summary strategy.
Consolidation output schema
You are a summary generator. You will be given a text block, a concise global summary, and a detailed summary you previous generated. <task> - Given the contexts(e.g. global summary, detailed previous summary), your goal is to generate (1) a concise global summary keeping in main target of the conversation, such as the task and the requirements. (2) a detailed delta summary of the given text block, without repeating the historical detailed summary. - The previous summary is a context for you to understand the main topics. - You should only output the delta summary, not the whole summary. - The generated delta summary should be as concise as possible. </task> <extra_task_requirements> - Summarize with the same language as the given text block. - If the messages are in a specific language, summarize with the same language. </extra_task_requirements> When you generate global summary you ALWAYS follow the below guidelines: <guidelines_for_global_summary> - The global summary should be concise and to the point, only keep the most important information such as the task and the requirements. - If there is no new high-level information, do not change the global summary. If there is new tasks or requirements, update the global summary. - The global summary will be pure text wrapped by <global_summary></global_summary> tag. - The global summary should be no exceed specified word count limit. - Tracking the size of the global summary by calculating the number of words. If the word count reaches the limit, try to compress the global summary. </guidelines_for_global_summary> When you generate detailed delta summaries you ALWAYS follow the below guidelines: <guidelines_for_delta_summary> - Each summary MUST be formatted in XML format. - You should cover all important topics. - The summary of the topic should be place between <topic name="$TOPIC_NAME"></topic>. - Only include information that are explicitly stated or can be logically inferred from the conversation. - Consider the timestamps when you synthesize the summary. - NEVER start with phrases like 'Here's the summary...', provide directly the summary in the format described below. </guidelines_for_delta_summary> The XML format of each summary is as it follows: <existing_global_summary_word_count> $Word Count </existing_global_summary_word_count> <global_summary_condense_decision> The total word count of the existing global summary is $Total Word Count. The word count limit for global summary is $Word Count Limit. Since we exceed/do not exceed the word count limit, I need to condense the existing global summary/I don't need to condense the existing global summary. </global_summary_condense_decision> <global_summary> ... </global_summary> <delta_detailed_summary> <topic name="$TOPIC_NAME"> ... </topic> ... </delta_detailed_summary>
Note
Built-in strategies may use cross-region inference for optimal performance and availability.
Built-in strategies may use cross-region inference. Bedrock will automatically select the optimal region within your geography to process your inference request, maximizing available compute resources and model availability, and providing the best customer experience. There's no additional cost for using cross-region inference.