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The LLM agent is the brain of OpenBunny. It analyzes conversation context and uses tools to create tasks, update existing ones, manage contacts, and detect duplicates.

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Agent loop

The agent runs a multi-turn tool-use loop with up to 10 iterations (configurable via AGENT_MAX_ITERATIONS). Each iteration:
  1. The agent receives the conversation context and available tools
  2. It decides whether to call a tool or finish processing
  3. Tool results are fed back for the next iteration
  4. The loop ends when the agent calls the done tool or hits the iteration limit

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Decision outcomes

The agent classifies each conversation into one of four outcomes:

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Available tools

The agent has access to these tools during processing:

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Task tools

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Contact tools

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Control tools

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Deduplication

The agent uses a dedupe_key system to prevent duplicate tasks. Each key follows the format:
For example: backend::fix::login-timeout or design::create::new-landing-page. Before creating a task, the agent searches for existing tasks with similar dedupe keys and descriptions using vector similarity. If a likely duplicate is found, the agent updates the existing task instead.

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Conversation context

The agent receives:
  • The channel name and type (Slack, WhatsApp, etc.)
  • Recent messages in the conversation with sender information
  • The linked contact profiles for known senders
  • A system prompt that defines the agent’s behavior and available tools