7 posts tagged with "LLM Frameworks"

30 notebooks. 25 benchmarks. SynapseKit 14 wins (8.39/10), LangChain 7 wins (6.83/10), LlamaIndex 4 wins (6.40/10). Here is where each framework wins, where it loses, and which one you should actually use.

LangChain 1.x removed its evaluation module. Most teams never noticed. Notebook #24 of the LLM Showdown tests which frameworks give you faithfulness, relevancy, and regression tracking out of the box - and which ones leave you to build it from scratch.

A linear chain handles most tasks. Research, generate, done. But production workflows branch. If the query is complex, run a deeper research step. If it is simple, take the fast path. If quality is insufficient, loop back. This requires a graph, not a chain. Notebook #23 of the LLM Showdown tests which frameworks ship graph primitives - and which force you to build infrastructure from scratch.

Every framework says await. Every framework says "production-ready". At one concurrent request, the difference is invisible. At 50 concurrent requests, LangChain's LCEL middleware costs 19.2% of theoretical throughput while SynapseKit loses only 3.2%. Notebook #22 of the LLM Showdown isolates the framework tax on async IO - and the gap is 7x in overhead milliseconds.

Six benchmarks. SynapseKit wins 4 on ergonomics. LangChain wins the one you'll hit in production: per-tool error recovery. LlamaIndex scores 7/18 - not a maturity gap, an architectural one. It's a retrieval framework that added agents.

LangChain wins on both dimensions - fewest lines (5) and most built-in error features (6/7). But its ToolException converts failures into LLM observations, making the model your error handler. SynapseKit's CircuitBreaker stops broken services from being hammered. LlamaIndex ships 1/7 features and expects you to bring the rest.

SynapseKit is an async-first Python framework for building LLM applications - chains, agents, RAG pipelines, tool calling, and multi-agent orchestration. Two base dependencies. 48 built-in tools. 31 LLM providers. Designed for engineers who need production-grade tooling without production-grade complexity.