SynapseKit

SynapseKit is an async-first Python framework designed for building production-grade LLM applications. It offers a comprehensive set of tools and components to streamline the development of RAG pipelines, AI agents, and graph workflows, all while maintaining a focus on performance and ease of use.

Core Value Proposition

SynapseKit empowers engineers to build robust LLM applications with full control and minimal boilerplate. Its async-native architecture ensures efficient resource utilization, while its streaming-first approach delivers a responsive user experience. With only two hard dependencies, SynapseKit promotes a lean and modular development environment.

Key Features

• Async-Native: Every API is designed with async/await first, ensuring optimal performance for asynchronous operations. Sync wrappers are also available for scripts and notebooks.
• Streaming-First: Token-level streaming is a core feature, providing real-time feedback and a seamless user experience across all supported LLM providers.
• Minimal Dependencies: With only numpy and rank-bm25 as hard dependencies, SynapseKit keeps your project lightweight and manageable. Additional capabilities are available through optional extras.
• Unified Interface: Interact with 27 LLM providers and 5 vector stores using a consistent API, allowing you to switch providers without extensive code modifications.
• Cost Intelligence: Integrated cost tracking and budget management tools provide full visibility and control over LLM costs, eliminating the need for external SaaS solutions.
• One-Command Deployment: Easily deploy RAG pipelines, agents, or graphs as production-ready FastAPI applications with a single command.
• Composable Architecture: RAG pipelines, agents, and graph nodes are fully interchangeable, enabling you to create complex and customized workflows.
• Transparent Design: SynapseKit avoids hidden chains, callbacks, and global state, offering clear and understandable Python code that you can easily read and customize.

Use Cases

• RAG Pipelines: Build retrieval-augmented generation pipelines with features like streaming, BM25 reranking, conversation memory, and token tracing.
• AI Agents: Implement ReAct loops for various LLMs, with native function calling support for OpenAI, Anthropic, Gemini, and Mistral. Access 41 built-in tools and extend functionality with custom tools.
• Graph Workflows: Create DAG-based asynchronous pipelines with parallel execution, conditional routing, typed state, fan-out/fan-in, SSE streaming, event callbacks, and human-in-the-loop integration.

Supported Providers & Integrations

SynapseKit supports a wide range of LLM providers, including OpenAI, Anthropic, Ollama, Gemini, Cohere, Mistral, Bedrock, Azure, Groq, DeepSeek, OpenRouter, Together, Fireworks, SambaNova, and more. It also integrates with popular vector stores like InMemory, ChromaDB, FAISS, Qdrant, and Pinecone, providing a unified interface for all backends.