Quick Start Guide

from runlog import runlog

# Just add the decorator - that's it!
@runlog(service="my-agent", env="development")
def handle_user_query(user_input: str):
    # Your existing agent code stays exactly the same
    context = search_knowledge_base(user_input)
    response = llm.generate(prompt=user_input, context=context)
    
    if response.confidence < 0.8:
        return escalate_to_human(user_input)
    
    return response.text

# RunLog now automatically tracks every step

import { runlog } from "@runlog/sdk";

// Just add the decorator - that's it!
@runlog({ service: "my-agent", env: "development" })
async function processUserQuery(input: string): Promise<string> {
  // Your existing agent code stays exactly the same
  const context = await searchKnowledgeBase(input);
  const response = await llm.generate({
    prompt: input,
    context: context
  });
  
  return response;
}

// Full observability with zero code changes

# Create a policy file: policies.yaml
policies:
  - id: cost_limit
    when: { cost: { gt: 0.50 } }
    action: deny
    
  - id: sensitive_operations  
    when: { input: { contains: "transfer" } }
    action: require_approval

# Your decorated functions automatically follow these policies!
@runlog(service="banking", policies="./policies.yaml")
def handle_banking_request(user_input: str):
    # No policy code needed - it's automatic
    return process_request(user_input)