Llmswap – Python package to reduce LLM API costs by 50-90% with caching
I built llmswap to solve a problem I kept hitting in hackathons - burning through API credits while testing the same prompts repeatedly during development. It's a simple Python package that provides a unified interface for OpenAI, Anthropic, Google Gemini, and local models (Ollama), with built-in response caching that can cut API costs by 50-90%. Key features: - Intelligent caching with TTL and memory limits - Context-aware caching for multi-user apps - Auto-fallback between providers when one fails - Zero configuration - works with environment variables from llmswap import LLMClient client…
In plain words
Llmswap is a Python package that reduces API costs for large language models by caching responses across OpenAI, Anthropic, Google Gemini, and local Ollama models. It provides a unified interface with intelligent caching featuring TTL controls, memory limits, and context awareness for multi-user applications. The package includes automatic fallback between providers and requires zero configuration, working directly with environment variables. Caching is disabled by default for security but can be enabled for significant cost reductions.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I built llmswap to solve a problem I kept hitting in hackathons - burning through API credits while testing the same prompts repeatedly during development. It's a simple Python package that provides a unified interface for OpenAI, Anthropic, Google Gemini, and local models (Ollama), with built-in response caching that can cut API costs by 50-90%. Key features: - Intelligent caching with TTL and memory limits - Context-aware caching for multi-user apps - Auto-fallback between providers when one fails - Zero configuration - works with environment variables from llmswap import LLMClient client = LLMClient(cache_enabled=True) response = client.query("Explain quantum computing") # Second identical query returns from cache instantly (free) The caching is disabled by default for security. When enabled, it's thread-safe and includes context isolation for multi-user applications. Built this from components of a hackathon project. Already at 2.2k downloads on PyPI. Hope it helps others save on API costs during development. GitHub: https://github.com/sreenathmmenon/llmswap PyPI: https://pypi.org/project/llmswap/
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