Production focused Self-harnessed LM runtime (RLM) that allows the LM to call its sub-lm with DSPy signatures. Define your inputs, outputs, and tools — the model handles its own control flow. Get fully interpretable trajectories and performance that scales directly with model improvements. Without context rot.
A multi-agent LLM system for detecting and resolving cognitive dissonance.
Multi-Faceted AI Agent and Workflow Autotuning. Automatically optimizes LangChain, LangGraph, DSPy programs for better quality, lower execution latency, and lower execution cost. Also has a simple agent/workflow framework
Automated generation of comprehensive Agents.md for LLMs, driven by the DSPy Recursive language model implementation.
Strwythura: construct an entity-resolved knowledge graph from structured data sources and unstructured content sources, implementing an ontology pipeline, plus context engineering for optimizing AI application outcomes within a specific domain. This produces a Streamlit app, with MLOps instrumentation.
A comprehensive 0-to-1 guide for building self-improving LLM applications with DSPy framework
WIP - Allows you to create DSPy pipelines using ComfyUI
dspy-cli is a tool for creating, developing, testing, and deploying DSPy programs as HTTP APIs.
Extract structured data from any content using LLMs.
Collection of Claude Skills for DSPy framework - program language models, optimize prompts, and build RAG pipelines systematically
Transform an Obsidian vault into PARA + Zettelkasten structure using DSPy and RLM
Adaptive Agentic AI Reasoning using Microsoft Agent Framework -- Join the Discord for suggestion or support ! https://discord.gg/ebgy7gtZHK
Claude Code for DSPy: Comprehensive CLI to Optimize Your DSPy Code. our AI-Powered DSPy Development Assistant
AI-powered platform for OSINT intelligence analysis. Features archive discovery with hypothesis-driven investigation, GLiNER entity extraction, Mapbox geospatial visualization, network analysis, and document processing. Built with FastAPI, Next.js, Weaviate, and DSPy.
Turn feature specs into merged PRs with a self-supervising swarm of coding agents — parallel execution, isolated sandboxes, DAG dependencies. Open-source, self-hostable, model-agnostic (Claude / Gemini / Codex).
prompt engineering experiments with DSPy GEPA and TextGrad
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