II.
LibraryProcess overview
Reference · livelib-process:ai-agents-conversational--cost-optimization-llm
cost-optimization-llm overview
Cost Optimization for LLM Applications - Process for reducing LLM operational costs through prompt compression, intelligent caching, model selection strategies, and usage optimization.
Attributes
displayName
cost-optimization-llm
description
Cost Optimization for LLM Applications - Process for reducing LLM operational costs through
prompt compression, intelligent caching, model selection strategies, and usage optimization.
libraryPath
library/specializations/ai-agents-conversational/cost-optimization-llm.js
specialization
ai-agents-conversational
references
- - LLMLingua: https://github.com/microsoft/LLMLingua - GPTCache: https://gptcache.io/ - Semantic Router: https://github.com/aurelio-labs/semantic-router
example
const result = await orchestrate('specializations/ai-agents-conversational/cost-optimization-llm', {
systemName: 'production-chatbot',
currentCosts: { monthlySpend: 10000, avgTokensPerRequest: 2000 },
optimizationGoals: ['reduce-costs-30', 'maintain-quality']
});
usesAgents
- cost-optimizer
- compression-developer
- caching-developer
- routing-developer
- usage-optimizer
- savings-analyst
Outgoing edges
lib_applies_to_domain1
- domain:software-engineering·DomainSoftware Engineering
lib_belongs_to_specialization1
- specialization:ai-agents-conversational·Specialization
lib_implements_workflow1
- workflow:financial-planning·WorkflowFinancial Planning
lib_involves_role1
- role:devops-engineer·Role
uses_agent1
- lib-agent:ai-agents-conversational--cost-optimizer·LibraryAgentcost-optimizer
Incoming edges
None.