Search Results for "org..json" - Page 6
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Showing 321 open source projects for "org..json"
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent... -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation... -
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TTRL
Test-Time Reinforcement Learning
TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. This makes the... -
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Changelog CI
Changelog CI is a GitHub Action that enables a project
...Finally, It writes the generated changelog at the beginning of the CHANGELOG.md/CHANGELOG.rst (or user-provided filename) file. In addition to that, if a user provides a configuration file (JSON/YAML), Changelog CI parses the user-provided configuration file and renders the changelog according to user's configuration. -
Outbound sales softwareAdversus is an outbound dialing solution that helps you streamline your call strategies, automate manual processes, and provide valuable insights to improve your outbound workflows and efficiency.
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pre-commit-hooks
Some out-of-the-box hooks for pre-commit
Some out-of-the-box hooks for pre-commit. Using pre-commit-hooks with pre-commit. Instead of loading the files, simply parse them for syntax. A syntax-only check enables extensions and unsafe constructs which would otherwise be forbidden. Using this option removes all guarantees of portability to other yaml implementations. Detect symlinks which are changed to regular files with a content of a path that that symlink was pointing to. This usually happens on Windows when a user clones a... -
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Lambda Builders
Python library to compile, build & package AWS Lambda functions
...AWS Lambda Builders also supports Custom workflow through a Makefile. Lambda Builders is the brains behind the sam build command from AWS SAM CLI. Lambda Builders is a Python library. It additionally exposes a JSON-RPC 2.0 interface to use in other languages. Build Actions could be implemented in any programming language. Preferably in the language that they are building. Some build actions simply execute a binary (like Golang) without writing a Go script. We provide a generic Python runner to implement such build actions. A build action is a module that knows how to build for a particular programming language & framework (ex: Python+PIP). ... -
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OuteTTS
Interface for OuteTTS models
...The project supports multiple backends including llama.cpp (Python bindings and server), Hugging Face Transformers, ExLlamaV2, VLLM and a JavaScript interface via Transformers.js, allowing it to run on CPUs, NVIDIA CUDA GPUs, AMD ROCm, Vulkan-capable GPUs, and Apple Metal. It also includes a notion of speaker profiles: you can create a speaker from a short audio sample, save it as JSON, and reuse it for consistent voice identity across generations and sessions. For best quality, the model is designed to work with a reference speaker clip and will inherit emotion, style, and accent from that reference. -
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AWS Data Wrangler
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
...Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). Built on top of other open-source projects like Pandas, Apache Arrow and Boto3, it offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses, and Databases. Convert the column name to be compatible with Amazon Athena and the AWS Glue Catalog. Run a query against AWS CloudWatchLogs Insights and convert the results to Pandas DataFrame. ... -
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Live Agent Studio
Open source AI Agents hosted on the oTTomator Live Agent Studio
Live Agent Studio is a curated repository of open-source AI agents associated with the oTTomator Live Agent Studio platform, showcasing a variety of agent implementations that illustrate how autonomous and semi-autonomous tools can be constructed using modern AI frameworks. Each agent in the collection is designed for a specific use case — such as content summarization, task automation, travel planning, or RAG workflows — and is provided with the code or configuration needed to explore and... -
Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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Prompt Declaration Language
Prompt Declaration Language is a declarative prompt programming lang
LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming... -
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requests-cache
Persistent HTTP cache for python requests
...When they expire, you still save time with conditional requests. Works with several storage backends including SQLite, Redis, MongoDB, and DynamoDB; or save responses as plain JSON files, YAML, and more. Use Cache-Control and other standard HTTP headers, define your own expiration schedule, and keep your cache clutter-free with backends that natively support TTL or any combination of strategies. Works out of the box with zero config, but with a robust set of features for configuring and extending the library to suit your needs. -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a... -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling... -
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node-gyp
Node.js native addon build tool
...If you have multiple Python versions installed, you can identify which Python version node-gyp should use. A binding.gyp file describes the configuration to build your module, in a JSON-like format. This file gets placed in the root of your package, alongside package.json. -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
...Benchmarks in the README highlight improvements in latency and token cost for scenarios involving multiple tools, showing that code execution often outperforms traditional JSON-based function calling. -
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mcp-use
A solution to build and deploy MCP agents and applications
mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate... -
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Protenix
A trainable PyTorch reproduction of AlphaFold 3
Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as... -
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dj-stripe
dj-stripe automatically syncs your Stripe Data to your local database
...For example, if you need to interact with a customer subscription, you can use dj-stripe’s Subscription Model, in your code, to get the subscription data for that customer as well as the related models’ data too (if need be and potentially in 1 database query!) instead of making multiple slower and unreliable consecutive network calls only to parse through 1 or more of Stripe’s JSON like objects! We make it simple for you to collect sensitive data such as credit card numbers and remain PCI compliant. This means the sensitive data is sent directly to Stripe instead of passing through your server. We support all Stripe supported wallets including but not limited to Apple Pay and Google Pay. -
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Swirl
Swirl queries any number of data sources with APIs
...Built on the Python/Django/RabbitMQ stack, SWIRL includes connectors to Apache Solr, ChatGPT, Elastic, OpenSearch | PostgreSQL, Google BigQuery plus generic HTTP/GET/JSON with configurations for premium services. -
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uvicorn-gunicorn-fastapi
Docker image with Uvicorn managed by Gunicorn
Docker image with Uvicorn managed by Gunicorn for high-performance FastAPI web applications in Python with performance auto-tuning. Optionally with Alpine Linux. -
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LangChain Extract
Did you say you like data?
...Built using FastAPI and the LangChain framework, the application exposes a REST API that can process documents and return structured outputs that match user-defined JSON schemas. Developers can create reusable “extractors” that define what type of information should be pulled from a document, along with example prompts that improve extraction quality through in-context learning. -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
...AIConfig supports multiple model providers and modalities, enabling developers to experiment with different models without rewriting application logic. The configuration format is JSON-serializable and integrates with tools such as Python and Node SDKs, allowing the same configuration file to be used across multiple environments. -
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EulerSharp
Euler Yet another proof Engine
...It performs controlled chaining and it supports Euler paths [3]. Via N3 [4] it is interoperable with Cwm [5]. [1] http://eulersharp.sourceforge.net/README [2] http://www.w3.org/DesignIssues/diagrams/sweb-stack/2006a [3] http://mathworld.wolfram.com/KoenigsbergBridgeProblem.html [4] http://www.w3.org/TeamSubmission/n3/ [5] http://www.w3.org/2000/10/swap/doc/cwm -
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nmon for Linux
Linux performance monitoring on-screen or to CSV file
nmon is short for Nigel's Performance Monitor It either shows you the stats on-screen updating once a second or saves the data to a CSV file for later analysis and graphing. For details see the homepage ==> http://nmon.sourceforge.net Please use the latest version. The new version "njmon" outputs JSON format that a lot of tools use these days. It integrates well with saving data directly to InfluxDB and graphing with Grafana. -
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NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
