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A local, offline-first AI agent built with DSPy, LangGraph, and Phi-3.5. Combines RAG and SQL to answer retail business questions. | Language: Python
Course notes for the DeepLearning.ai course DSPy: Build and Optimize Agentic Apps | Language: Jupyter Notebook
DSPy: Build and Optimize Agentic Apps | Language: Jupyter Notebook
Language: Jupyter Notebook
Language: Jupyter Notebook | License: MIT License
Enterprise AI Context Engineering with GEPA-DSPy - Comprehensive platform for AI context optimization with Supabase and Vercel deployment | Language:...
DSPy Hub: Share and discover optimized DSPy programs | Language: Python
DSPy artifacts for training on private data, signatures, modules, adapters, tools. By SmallCloud | Language: Python
Production-ready defense against indirect prompt injection attacks for DSPy applications | Language: Python
This application demonstrates a Retrieval-Augmented Generation (RAG) pipeline built with DSPy & inference pipeine using LitServe. It combines keyword...
AI-powered resume builder using the DSPy ReAct agent framework. It turns raw profiles into ATS-ready resumes by parsing job descriptions, extracting...
minimal example to reproduce issue with optionals in dspy | Language: Jupyter Notebook | License: MIT License