an ambient intelligence library
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Updated
Jun 7, 2025 - Python
an ambient intelligence library
OpenAI's Structured Outputs with Logprobs
Structured Data Extractor for AI Agents. Search your documents or the web for specific data and get it back in JSON or Markdown in a single tool call.
OpenAi.JsonSchema is a lightweight library for generating valid JSON Schema for OpenAI models' Structured Outputs feature. It supports a wide range of types, ensures compatibility with OpenAI's JSON Schema format, and leverages C# descriptions and attributes for schema generation.
Python command-line tool for interacting with AI models through the OpenRouter API/Cloudflare AI Gateway, or local self-hosted Ollama. Optionally support Microsoft LLMLingua prompt token compression
This project demonstrates how to get structured outputs from Deepseek R1 reasoning model and do tool calling using an OpenAI summarization step. It's made using Next.js serverless routes and uses shadcn/ui for the frontend.
Swift Macro for OpenAI API Structured Outputs.
Serialize your functions with tools-rs!
Experiment using JsonSchemaExporter in .NET 9 to improve developer experience with OpenAI's Structured Outputs
Iterate over scans of forms, and have gpt-4o pull data from them into a csv file
This repository covers all the code materials covered within Jose Portilla's Langchain with Python Bootcamp on Udemy.
Presentation at PyData Global: Building Knowledge Graph-Based Agents with Structured Text Generation and Open-Weights Models
Job posting parser with structured outputs
Presentación en la conferencia IADevs 2024: Potenciando la Generación Aumentada usando Recuperación con Grafos de Conocimiento
This repository demonstrates structured data extraction using various language models and frameworks. It includes examples of generating JSON outputs for name and age extraction from text prompts. The project leverages models like Qwen and frameworks such as LangChain, vLLM, and Outlines for Transformers models.
Prompt (cue) management and execution for tabular data.
An extension of the LLM-based spatial layout generation from image description from https://github.com/Attention-Refocusing/attention-refocusing using OpenAI and Ollama structured outputs
Metaschema for validating OpenAI Structured Outputs schemas
Demonstrates enforcing structured outputs from LLMs using LangChain (Google Gemini & HuggingFace) with Pydantic, TypedDict, and JSON Schema. Includes standalone examples for data validation and schema‑driven text generation. Quickly run each script to see how to produce reliably formatted AI responses.
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