Mirascope/mirascope

Health v2 · maintenance only

Adoption not part of the score

1522 stars · 125 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Mirascope is a Python (and TypeScript) library providing a unified, provider-agnostic interface for calling frontier LLMs like OpenAI, Anthropic, and Google models. It offers decorators for LLM calls, structured outputs via Pydantic, tool-based agent loops, and built-in tracing, versioning, and cost tracking.

Use cases

• call any LLM provider with one unified interface
• get structured output from LLM responses with pydantic models
• build agents that use tools and multi-turn loops
• add tracing and cost tracking to LLM calls
• stream LLM responses and handle async calls
• switch between OpenAI, Anthropic, and Google without rewriting code

When to choose

• you want a lightweight, decorator-based LLM abstraction without heavy framework lock-in
• you need structured outputs and tool-calling agents across multiple providers
• you want built-in observability like tracing, versioning, and cost tracking

When to avoid

• you need a full agent framework with orchestration, memory, and RAG pipelines out of the box
• you work primarily outside Python or TypeScript
• you prefer direct provider SDKs with no abstraction layer

Facets

library · maturity active

llm-inference agent-framework prompt-engineering sdk tracing middleware large-language-models developer-tools artificial-intelligence python cross-platform llm unified-interface structured-output llm-tools provider-agnostic observability anti-framework ai-agents retrieval-augmented-generation

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