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Building AI Agents with Gemini & DSPy
This project was created for a live coding session where we explored building AI bots and agents using Google’s Gemini 2.5 Flash-Lite and DSPy. In...
This AI Framework Just BROKE The Internet: 50% Better Than ChatGPT Prompts!
The AI Revolution You HAVEN'T Heard About Yet... What if I told you that while everyone's obsessing over prompt engineering, ... | Channel: NotebookLM
Vector & Graph (Hybrid) RAG with Tool Calling in DSPy
Combining Vector Search and Graph Retrieval with Kuzu In this episode, we delve deeper into the integration of vector search ... | Channel: Kùzu
evalops/orbit-agent
A brutally honest "high‑orbit" startup advisor you can text or run from the CLI. Built with DSPy, it provides opinionated, YC-style advice and...
dleerdefi/llm-security-auditor
Universal LLM security auditor with automated jailbreak testing, DSPy optimization, and OWASP 2025-aligned attack patterns | Language: Python |...
mitkox/oda-r
oda-r is a professional-grade compiler for Declarative Self-improving Python (DSPy), featuring comprehensive error handling, logging, and...
milenegubetti/agent-auto-documentation
https://dspy.ai/ | Language: Jupyter Notebook
justSteve/RAGinDSPy
DSPy framework recipes for building RAG applications - extracted from weaviate/recipes | Language: Jupyter Notebook
Image extraction with DSPY | Python | Gemini
How to extract any information from images using DSPY and Gemini models. | Channel: kevin herbas
evalops/bandit_dspy
A DSPy library for security-aware LLM development using Bandit. | Language: Python | License: MIT License
tomek1911/GEPAR3D
[MICCAI 2025] Official repository for the 2025 MICCAI Paper "GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation" | Language: Jupyter...
gepa-ai/gepa-artifact
Language: Jupyter Notebook | License: MIT License
sachink1729/Healthcare-AI-Assistant-Medical-Data-Qdrant-Dspy-Groq
Building Private Healthcare AI Assistant for Clinics Using Qdrant Hybrid Cloud, DSPy and Groq - Llama3 | Language: Jupyter Notebook | License: Apache...
Automated Prompt Engineering with DSPy | Prompt Optimization for Financial News Semantic Analysis
Learn to use DSPy to automatically optimize your prompts, turning a mediocre baseline into a high-performing pipeline. | Channel: Venelin Valkov