Search Results for "json-py"
Sort By:
Showing 83 open source projects for "json-py"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
1
Lingua-Py
The most accurate natural language detection library for Python
Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing... -
2
notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
notebooklm-py is an unofficial Python API and agent-ready integration layer for Google NotebookLM that exposes NotebookLM functionality through code, the command line, and AI agent workflows. Its goal is to provide programmatic access not just to standard notebook operations, but also to many capabilities that are either limited or unavailable in the web interface, making it especially useful for automation and custom pipelines. -
3
supabase-py
Python Client for Supabase. Query Postgres from Flask, Django
Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue. -
4
JSON_REPAIR
A python module to repair invalid JSON from LLMs
json_repair is an open-source Python library designed to automatically fix malformed JSON data and convert it into valid, parseable structures. The tool is particularly useful in scenarios where JSON output is generated by large language models or external services that may produce syntactically invalid responses. Instead of failing when encountering errors such as missing quotes, trailing commas, or incomplete objects, the library analyzes the malformed data and reconstructs it into valid JSON. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
5
MinerU
A high-quality tool for convert PDF to Markdown and JSON
MinerU is an open-source, high-quality document extraction toolkit focused on converting PDFs (and other document formats) into structured Markdown and JSON. It leverages OCR and layout analysis to preserve semantic structure and metadata, ideal for research and data science workflows. -
6
Nexa SDK
Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML
...It supports text generation, image generation, vision-language models (VLM), and speech-to-text (ASR), and text-to-speech (TTS) capabilities. Additionally, it offers an OpenAI-compatible API server with JSON schema mode for function calling and streaming support, and a user-friendly Streamlit UI. Users can run Nexa SDK in any device with Python environment, and GPU acceleration is supported, including CUDA, Metal, and ROCm. An executable version is also available. -
7
DocArray
The data structure for multimodal data
...Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases. -
8
AlphaFold 3
AlphaFold 3 inference pipeline
...The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources. -
9
Agent Development Kit (ADK)
Open-source, code-first Python toolkit for building, evaluating, etc.
...This is especially important in high-security applications where verifying that a device is genuine and uncompromised is critical. ADK Python helps developers verify hardware-backed keys, work with JSON Web Tokens (JWT), and integrate with Android’s Key Attestation infrastructure. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
10
ShortGPT
AI framework for automated short video creation and editing tools
...It can automatically assemble videos by combining generated scripts, sourced media assets, captions, and synthesized voice narration. A modular editing system based on structured markup and JSON allows editing steps to be broken into manageable components that can be interpreted by language models. -
11
CLI-Anything
Making ALL Software Agent-Native
...It integrates with multiple AI platforms such as Claude Code, OpenClaw, Codex, and GitHub Copilot CLI, enabling cross-platform compatibility and flexibility. CLI-Anything emphasizes structured outputs such as JSON to reduce parsing complexity and improve reliability in automation scenarios. -
12
stt
Voice Recognition to Text Tool
stt is a standalone speech recognition tool that locally converts spoken content in audio or video files into textual formats without requiring internet access, giving users control over their data and reducing reliance on external APIs. It leverages open-source speech models such as Faster-Whisper to recognize and transcribe human speech into plain text, structured JSON objects, or subtitle files with time codes, making it suitable for both personal and professional transcription tasks. The project is designed to be easy to deploy: you can run a local Python server that exposes an HTTP API for uploading audio/video files and retrieving transcriptions in different formats. It supports GPU acceleration if available, enabling faster processing on compatible hardware but still offers reliable performance on CPUs alone. -
13
Chandra
OCR model for complex documents with layout-aware structured outputs
...It focuses on preserving full document layout, meaning that extracted text is accompanied by positional metadata like bounding boxes for each element. Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. It is capable of handling over 40 languages and is optimized to read difficult inputs such as messy handwriting and multi-column layouts. Chandra can be run locally using transformer-based inference or deployed with a high-performance server setup for large-scale processing. ... -
14
Qwen-2.5-VL
Qwen2.5-VL is the multimodal large language model series
...Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation (exceeding 8,000 tokens), and structured data comprehension, such as tables and JSON formats. They support context lengths up to 128,000 tokens and offer multilingual capabilities in over 29 languages, including Chinese, English, French, Spanish, and more. The models are open-source under the Apache 2.0 license, with resources and documentation available on platforms like Hugging Face and ModelScope. -
15
Outlines
Structured Outputs
...Instead of repairing malformed responses afterward, it constrains generation to match a requested type or format. Developers can require predefined choices, primitive Python types, Pydantic models, JSON schemas, regular expressions, function signatures, or custom grammars. The same interface works with local models, inference servers, and hosted APIs from several providers. Supported integrations include Transformers, llama.cpp, vLLM, Ollama, OpenAI, and Gemini. It also provides reusable prompt templates and application abstractions for packaging prompts with output constraints. ... -
16
iFixAi
Independent Auditing of AI Agents
...The same engine can test hosted providers or a real agent endpoint and can use self-grading, an independent judge, or a multi-judge ensemble. Results are delivered as JSON, Markdown, and terminal scorecards for review or automation. Saved configuration supports repeatable local runs, onboarding, and CI workflows. -
17
Hiring Agent
AI agent to evaluate and score resumes
...It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access. -
18
ScrapeGraphAI
Python scraper based on AI
Extracting content from websites and local documents using LLM. ScrapeGraphAI is a web scraping python library that uses LLM and direct graph logic to create scraping pipelines for websites and local documents (XML, HTML, JSON, Markdown, etc.). Just say which information you want to extract and the library will do it for you. -
19
Unstract
No-code LLM Platform to launch APIs and ETL Pipelines
Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to refine prompts and extraction logic before deploying at scale. Unstract supports deploying structured extraction as REST API endpoints or embedding it into data engineering ETL pipelines, which allows it to plug directly into data warehouses, cloud storage, or downstream analytics systems. ... -
20
ARC-AGI-1 Task Generator
Generates original ARC-AGI-1-style tasks distribution-matched
...The project is intended to complement public benchmark scores by testing whether reasoning abilities transfer to newly generated examples. Generated tasks use the standard ARC train-and-test JSON structure. This makes the output compatible with existing ARC evaluation harnesses and analysis pipelines. The repository also includes scripts for labeling, describing, visualizing, and generating tasks, including stratified generation. It was developed alongside research on BDH-CQ and recurrent latent reasoning. -
21
Ideogram 4
Open image model at the forefront of design
...It is built for users who need more than generic image generation, especially when layout, typography, composition, color, and language understanding matter. The project introduces a structured JSON prompting workflow that gives creators more explicit control over scene details and visual constraints. It can also accept plain-text prompts, making it accessible to users who prefer a simpler generation style. Ideogram 4 is especially useful for design-heavy outputs such as posters, ads, mockups, branded graphics, and images that include readable text. ... -
22
segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the segment-anything-eo repository, and credit for its original version goes to Aliaksandr Hancharenka. -
23
Sparrow
Structured data extraction and instruction calling with ML, LLM
Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to identify and extract meaningful data fields from heterogeneous document layouts. The architecture is modular, allowing developers to build customizable processing pipelines that integrate with external tools and data extraction frameworks. ... -
24
labelme Image Polygonal Annotation
Image polygonal annotation with Python
Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Image annotation for polygon, rectangle, circle, line and point. Image flag annotation for classification and cleaning. Video annotation. (video annotation). GUI customization (predefined labels / flags, auto-saving, label validation, etc). Exporting VOC-format dataset for semantic/instance segmentation. (semantic segmentation, instance segmentation). Exporting COCO-format dataset... -
25
Guardrails
Adding guardrails to large language models
Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid,...
