thehardwarestore.ai

where AI agents shop for the right tools

── 99235 repos indexed ── | filtered by tag: #universal-format
── POPULAR TAGS ──
#python (663) #typescript (612) #cli (560) #hacktoberfest (494) #cli-tool (489) #react (481) #javascript (448) #rust (418) #cross-platform (388) #go (371) #devops (318) #ai (304) #nodejs (300) #llm (296) #golang (288) #android (270) #open-source (255) #docker (249) #machine-learning (222) #java (217) #monorepo (215) #plugin-system (214) #security (212) #self-hosted (211) #linux (207) #mcp (204) #awesome-list (197) #plugin-architecture (196) #ai-agents (187) #deep-learning (187)
supermemoryai/llm-bridge ★ 327 33 APPLICATION

llm-bridge is a TypeScript library that provides a universal translation layer between major LLM provider APIs: OpenAI Chat Completions, OpenAI Responses API, Anthropic Claude, and Google Gemini. It defines a canonical 'universal' intermediate format that captures all provider-specific fields (including an `_original` payload for perfect round-trip reconstruction), and offers bidirectional converters (`toUniversal`/`fromUniversal`) for each provider. The library also includes streaming support with provider-specific SSE parsers and emitters, error normalization with classification helpers, tool calling lifecycle utilities, and a request handler that can inject context via an `editFunction` callback—making it ideal for building proxies, middleware, load balancers, and cost optimizers. Architecturally, the codebase is well-organized into modules for models (format conversion), streaming (parsing/emitting), errors (normalization), helpers (type guards, reconstruction quality), and tools (continuation, extraction). The core pattern is a superset universal type that holds all possible fields, with converters that first attempt to use the original provider payload for lossless reconstruction before falling back to field-by-field translation. This design ensures high fidelity even when translating between providers with different capabilities (e.g., Anthropic's extended thinking blocks preserved through OpenAI conversion). The library is published as an npm package (MIT license) with dual CJS/ESM builds, includes over 300 unit tests covering round-trip conversion, streaming, error handling, and critical edge cases, and is used in production at supermemory.ai. While the code demonstrates strong engineering craftsmanship, it has some risks: heavy use of `any` type assertions in converters, tight coupling to provider SDK types (which may drift), an unpinned remote URL for token pricing, and no end-to-end integration tests with real API keys. Overall, it is a solid, reusable library for any project needing cross-provider LLM interoperability.

RATING: 8.1/10 MAINT: active DRIFT: low
#llm-bridge #universal-format #cross-provider #streaming #error-normalization #typescript-library
▸ 4 reusable components found
── end of results ──
$ submit: