Node ↔ Python bridge for DSPy. Spawns a uv-pinned Python sub-process that hosts compiled DSPy programs and answers JSON-line RPC. Substrate pick #1 of the AI tech modernization proposal §6.
OpenAI ChatGPT integration for TS-DSPy - enables type-safe LLM interactions with GPT-3.5, GPT-4, and other OpenAI models for TypeScript
Gemini API integration for TS-DSPy - enables type-safe LLM interactions with Gemini models for TypeScript
Production-ready examples for @ruvector/agentic-synth - DSPy training, multi-model benchmarking, and advanced synthetic data generation patterns
Effect-native DSPy — programming, not prompting, language models
AI-guided LLM optimization. Install → Tell Claude 'Read .claude/agents/iris.md' → Claude becomes your optimization guide. DSPy prompts, Ax hyperparameters, local LLMs, federated learning. You talk, Iris handles the rest.
AI agent orchestration framework for TypeScript/Node.js - 29 adapters (LangChain, AutoGen, CrewAI, OpenAI Assistants, LlamaIndex, Semantic Kernel, Haystack, DSPy, Agno, MCP, OpenClaw, A2A, Codex, MiniMax, NemoClaw, APS, Copilot, LangGraph, Anthropic Compu
Core library for building type-safe LLM applications with structured input/output signatures, automatic validation, and reasoning patterns within TypeScript
A 1:1 TypeScript alternative to DSPy — Declarative Self-improving Language Programs
DSPy.ts 2.0 - Advanced declarative AI framework with multi-agent orchestration, self-learning capabilities, and state-of-the-art optimizers. Powered by AgentDB, ReasoningBank, and Swarm architecture.
Hal9: Create and Share Generative Apps
SDK for LLM pipelines with OpenCode, Codex, and Zod
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Close the eval-to-improvement loop for promptfoo. Automatically evaluate, identify low-scoring prompts, rewrite with any LLM, and re-evaluate.
OpenTelemetry SpanProcessor for atrib. Reads OpenInference-shaped spans and emits signed atrib records on a parallel pipeline. One integration reaches every framework with OpenInference instrumentation.
CLI tool to scan codebases for LLM SDK usage, AI frameworks, and exposed API tokens
Pi package inspired by Hermes Agent Self-Evolution for reflective improvement of skills, prompts, and instruction files.
Shared TypeScript types for Cogitator
CLI for promptc.
Cognitive-driven multi-agent orchestration for society.db, prompt-vault, and agent-kernel
TypeScript implementation of GEPA (Gradient-free Evolution of Prompts and Agents) - Complete port with 100% feature parity
AI agent with an internal ecology of strategies that compete and evolve based on real task performance
Compile and optimize LLM prompts in JavaScript using type-safe schemas and examples.
A DSPy rewrite(not port) to Rust.
Derive macros for DSRs (DSPy Rust)
High-performance, zero-copy library for optimizing language model prompts and programs
BitPolar: near-optimal vector quantization with zero training overhead — 3-bit precision, provably unbiased inner products (ICLR 2026)
Declarative Agents in Rust
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
Multi-prompt Instruction Proposal Optimizer — automated prompt optimization
The Ruby framework for programming with large language models. DSPy.rb brings structured LLM programming to Ruby developers. Instead of wrestling with prompt strings and parsing responses, you define typed signatures using idiomatic Ruby to compose and decompose AI Worklows and AI Agents.
Provides DSPy::TypeSystem::SorbetJsonSchema without requiring the full DSPy stack, enabling reuse in sibling gems and downstream projects.
Provides the OpenAI plus the Ollama and OpenRouter adapters so OpenAI-compatible providers can be added to DSPy.rb projects independently of the core gem.
Provides a unified adapter using RubyLLM to access OpenAI, Anthropic, Gemini, Bedrock, Ollama, and more through a single interface in DSPy.rb projects.
Provides the GeminiAdapter so Gemini-compatible providers can be added to DSPy.rb projects independently of the core gem.
Provides the AnthropicAdapter so Claude-compatible providers can be added to DSPy.rb projects independently of the core gem.
Optional optimizer bundle for DSPy.rb that ships the MIPROv2 teleprompter, Gaussian Process backend, and supporting dependencies for Bayesian optimization.
Provides DSPy::Observability, AsyncSpanProcessor, and ObservationType so instrumentation can be enabled independently from the main DSPy gem.
Ships DSPy::Teleprompt::GEPA plus reflective adapters, experiment tracking, and telemetry hooks built on top of the GEPA optimizer core gem.
DSPy datasets provide prebuilt loaders, caching, and schema metadata for benchmark corpora used in DSPy examples and teleprompters.
Provides the DSPy::Evals runtime, concurrency, callbacks, and export helpers for benchmarking Ruby DSPy programs.
CodeAct provides Think-Code-Observe agents that synthesize and execute Ruby code dynamically. Ship DSPy.rb workflows that write custom Ruby code while tracking execution history, observations, and safety signals.