fhlmi

What it is and what it does

fhlmi is a Python library that abstracts away the differences between multiple large language model providers, letting you write code once and swap providers without changing your application logic. It wraps providers under a common async interface, exposing methods like `call_single()` and `call()` that accept text or structured messages.

The library handles several operational concerns automatically: it tracks token usage and cost per request, enforces rate limits (tokens per minute and requests per minute) with in-memory or Redis-backed storage, retries failed requests, and supports tool calling and structured output schemas. You configure providers and limits through a config dictionary, then call the LLM through the unified interface—no need to learn each provider's API separately.

Use it for:

• Build a multi-provider LLM application where you can switch between providers by changing config without rewriting code.
• Enforce rate limits across concurrent requests to avoid hitting provider quotas or incurring unexpected costs.
• Track token usage and cost per LLM call to monitor spending and optimize prompt efficiency.
• Implement tool calling against multiple LLM providers using a single abstraction.
• Embed LLM capabilities in async Python services that need retries, timeouts, and cross-process rate limiting.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

fhlmi provides a unified async Python interface to multiple large language models, handling authentication, rate limiting, cost tracking, and tool calling across different LLM providers.

Yes, if you need a unified interface to multiple LLM providers with built-in rate limiting and cost tracking. The library is actively maintained, has low install friction, and is permissively licensed. However, verify that all runtime dependencies fit your environment before committing; the dependency footprint is substantial.

Install

fhlmi on PyPI

pip install fhlmi

uv add fhlmi

poetry add fhlmi

Installing fhlmi

Before you install

Low friction install with a pure Python wheel. Active maintenance (last commit 2026-08-12, 10 days since release) and 139 repository stars suggest ongoing development. Requires Python 3.11 or later.

License in practice

Apache License 2.0 is permissive: you can use, modify, and distribute fhlmi freely in commercial and private projects, provided you include a copy of the license and document any changes you make.

Quickstart

pip install fhlmi

from fhlmi import LiteLLMModel

llm = LiteLLMModel()
result = await llm.call_single("What is the meaning of life?")

Requires Python 3.11 or later; async/await context required; LLM provider credentials must be set in environment.

Verify before relying

• Whether all 10 runtime dependencies are required for basic usage or if some are optional.
• Whether fhaviary is a public package or an internal dependency that may affect installation.
• Cost estimation accuracy and which LLM providers' pricing models are supported.
• Whether Redis is required for rate limiting or if in-memory storage is sufficient for typical workloads.

Package facts

Evidence: fhlmi-1.0.5-py3-none-any.whl

Tags

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