exception-handling
Exception Handling & Recovery
Exception Handling ensures that an agentic system degrades gracefully rather than crashing. In the nondeterministic world of LLMs, failures are common: models hallucinate, APIs time out, and outputs are malformed. This pattern wraps critical operations in "try/catch" blocks that trigger recovery agents or fallback strategies.
When to Use
- Production Systems: Essential for any user-facing application.
- Unreliable Tools: When using 3rd-party APIs that might be down or rate-limited.
- Structured Output: When the model occasionally fails to output valid JSON.
- Safety: When a tool might return dangerous or unexpected data.
Use Cases
- API Fallback: "Primary model API failed? Switch to backup model API." or "Tool A failed? Try Tool B."
- Refusal Handling: If the model refuses to answer (due to safety filters), catch the refusal and rephrase the prompt or explain why it can't answer.
- Validation Repair: If JSON validation fails, pass the error back to the model to fix the syntax.
Implementation Pattern
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A hybrid pattern where the system pauses execution to request human approval, input, or disambiguation before proceeding with critical actions. Use when user asks to "add human approval", "require human review", "human-in-the-loop", or mentions approval workflows, human oversight, or escalation.
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