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Documentation Index

Fetch the complete documentation index at: https://hastekit.ai/docs/llms.txt

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Configure whether the agent maintains conversation history across interactions and how to manage long conversations.

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Configuration

Enable Conversation History - Toggle switch to enable or disable conversation history. When enabled, the agent will:
  • Store conversation messages
  • Use previous context in subsequent interactions
  • Maintain state across multiple conversation turns
When disabled, each interaction is treated as a new conversation without context from previous messages.

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Summarization

When conversation history is enabled, you can configure summarization to manage long conversations and reduce token usage.

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LLM-Based Summarization

Uses an LLM to intelligently summarize older conversation history while preserving important context. Configuration:
  • Summarizer Model - LLM provider and model for summarization
  • Summarizer Prompt - Instructions for how to summarize conversations
  • Token Threshold - Summarization triggers when total tokens exceed this value
  • Keep Recent Count - Number of recent conversation runs to keep unsummarized
How it works:
  • Monitors total token count in conversation history
  • When threshold is exceeded, keeps the most recent N runs intact
  • Summarizes older runs into a single system message
  • Preserves important context while reducing token usage

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Sliding Window Summarization

Keeps only the most recent N conversation runs and discards older ones. This is a simple, cost-effective approach that doesn’t require an LLM. Configuration:
  • Keep Count - Number of recent conversation runs to retain
How it works:
  • Messages are grouped by conversation run ID
  • Only the most recent N runs are kept
  • Older runs are discarded without summarization