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Local-first AI Workflows with embedded devtools
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Python library for the instruction and reliable validation of structured outputs (JSON) of Large Language Models (LLMs) with Ollama and Pydantic. -> Deterministic work with LLMs.
Extract structured data from any unstructured web page
Pydantic + Instructor for Rust: extract structured, validated data from LLMs (OpenAI GPT, Anthropic Claude, Gemini, Grok/xAI) into native Rust structs & enums. Derive macros auto-generate JSON Schema, parse responses, and retry on validation errors. Type-safe structured outputs & function calling.
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Delphi FMX component for a better way for new feature introduction and step-by-step users guide in your program.
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Structured Generation Evals
Custom comfyui https://github.com/comfyanonymous/ComfyUI Nodes for interacting with Ollama https://ollama.com/ using the Instructor https://github.com/jxnl/instructor Library to provide structured output from your LLM
Type-safe structured data extraction from text using LLMs.
create pydantic models dynamically
Image Knowledge base / Idea / Problem Solve / Analysis
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A university management system is a Java-based software that streamlines administrative processes, improves data accuracy and security, and provides insights for universities to improve outcomes for students, faculty, and staff.
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JakIja is a cross-vendor online learning ecosystem built with Python Django, HTMX, and Tailwind CSS, providing secure self-paced learning with interactive content, assessments, and progress tracking in a modular and scalable architecture
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AI / ML Embeddings applied to the Steam Store.
An AI-powered chatbot built with Streamlit and Google Gemini that answers questions about food spots around Saveetha University campus — prices, locations, and student-recommended favorites.
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Personal research knowledge base with an AI-scientist loop — deep-read papers into grounded bilingual analyses, incubate divergent questions, cross-analyze your library, connect your own experiments, iterate with round-memory advice.
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Agentic Firewall sits between an AI agent or MCP client and an MCP server. It can enforce runtime policies and automatically test the server's tool-use attack surface with 17 OWASP ASI scenarios. It runs locally and sends no telemetry.
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