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Showing 391 open source projects for "dynamicreports-examples"
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Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
...Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. Spring AI Alibaba Examples also supports experimentation through playground modules and encourages contributions to expand real-world AI use cases and improve development practices. -
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NVIDIA Generative AI Examples
Generative AI reference workflows
...The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. The repository includes examples covering topics such as retrieval-augmented generation pipelines, agent-based workflows, and multimodal AI applications that combine text, vision, and data processing. Many of the examples show how to deploy AI services using containerized environments, GPU acceleration, and microservices that can scale across modern infrastructure. ... -
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python-small-examples
Focus on creating classic Python small examples and cases
...The repository includes examples covering topics such as file processing, JSON manipulation, data visualization, and library usage. The examples are intentionally short and easy to read, making them useful for beginners who want to understand Python syntax and programming logic step by step. The repository is organized as a large collection of small scripts and notes that can be browsed individually without needing to study a full project. -
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Deep-Live-Cam
Real time face swap and one-click video deepfake
Real time face swap and one-click video deepfake with only a single image. Choose a face (image with the desired face) and the target image/video (image/video in which you want to replace the face) and click on Start. Open File Explorer and navigate to the directory you select your output to be in. You will find a directory named <video_title> where you can see the frames being swapped in real time. Once the processing is done, it will create the output file. -
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python-telegram-bot
A Python wrapper you can't refuse
...These make bot development much easier and straightforward. python-telegram-bot is free and open source, fun to use, and fast and easy to install. Visit https://github.com/python-telegram-bot/python-telegram-bot/blob/master/examples/README.md to see official examples or the project’s wiki on https://github.com/python-telegram-bot/python-telegram-bot/wiki/Examples to see other community-built bots. -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
...The project emphasizes practical experimentation, allowing beginners to modify and extend the example programs to explore new ideas. Many of the examples are accompanied by video explanations that guide learners through the code and demonstrate how the programs work in practice. -
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FramePack
Lets make video diffusion practical
...It’s useful for diffusion and generative models that learn from sequential image datasets, as well as classical pipelines that batch many related frames. With a simple API and examples, it invites experimentation on tradeoffs between compression, fidelity, and speed. -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools such as large language models, autonomous agents, and external APIs. ... -
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machine_learning_examples
A collection of machine learning examples and tutorials
...Many of the examples are accompanied by tutorials and educational materials that explain how the algorithms work and how they can be applied in real-world projects. The code is organized into small independent experiments so that learners can explore specific algorithms or techniques without needing to understand the entire codebase. -
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PaddleNLP
Easy-to-use and powerful NLP library with Awesome model zoo
PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities Taskflow And process-wide text area API: Support for the loading of rich Chinese data sets Dataset API, can flexibly and efficiently complete data pretreatment Data API, Preset 60 + pre-training word vector Embedding API, Providing 100 + pre-training model Transformer API Wait, the efficiency of NLP task modeling can be greatly improved. -
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Amazing-Python-Scripts
Curated collection of Amazing Python scripts
...The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning exercises. The repository encourages community contributions, allowing developers to add their own scripts and improve existing ones through pull requests. Examples include scripts for sentiment analysis, data scraping, web automation, log analysis, and interactive applications such as games or voice-controlled tools. ... -
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SHAP
A game theoretic approach to explain the output of ml models
...Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark tree models. To understand how a single feature effects the output of the model we can plot the SHAP value of that feature vs. the value of the feature for all the examples in a dataset. Since SHAP values represent a feature's responsibility for a change in the model output, the plot below represents the change in predicted house price as RM (the average number of rooms per house in an area) changes. -
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pyttsx3
Offline Text To Speech synthesis for python
...It supports both a high-level speak convenience function and a lower-level engine object with event hooks, queuing, and saving output to audio files. The repository includes examples and documentation that show how to adjust properties dynamically, persist synthesized output, and integrate pyttsx3 into GUIs or background services. -
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Python Code Tutorials
The Python Code Tutorials
...The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and applications step by step. Many tutorials focus on practical implementations such as building network scanners, web scraping tools, object detection systems, and automation utilities using Python libraries. The repository is organized into thematic directories that group tutorials by topic, allowing learners to navigate easily between areas such as ethical hacking, multimedia processing, or machine learning. -
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SetFit
Efficient few-shot learning with Sentence Transformers
SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples. -
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Agent Control
Centralized agent control plane for governing runtime agent behavior
...It is designed for production environments where organizations need observability, enforcement, and governance around autonomous or semi-autonomous AI systems. The repository includes SDKs, a server, telemetry components, examples, and integrations for common agent frameworks. It is especially useful for teams building customer-facing, internal, or enterprise agents that need scalable runtime guardrails. -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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TensorFlow Datasets
TFDS is a collection of datasets ready to use with TensorFlow,
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data. Datasets , enabling easy-to-use and high-performance input pipelines. To get started see the guide and our list of datasets. -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using... -
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Free LLM API resources
A list of free LLM inference resources accessible via API
...It collects a wide range of resources including hosted free-tier LLM APIs, documentation links, public model endpoints, open datasets useful for training or evaluation, tooling integrations, and examples showing how to interact with these services in real applications. This list helps developers, hobbyists, and researchers quickly find models they can use for prototyping, experimentation, or production proofs-of-concept without needing paid subscriptions, reducing friction for innovation. The repository typically categorizes offerings by provider, type of service (text, embeddings, vision), availability conditions (open without key, free tier with key), and usage examples to make discovery and adoption easier. -
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Claude Skills
Public repository for Agent Skills
Claude Skills is a public repository that showcases and serves as a collection of skills — modular, reusable packages of instructions, scripts, and resources that Claude and other compatible agents can dynamically discover and load to extend their capabilities on specialized tasks. Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document... -
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Scientific Agent Skills
A set of ready to use Agent Skills for research, science, engineering
...The repository includes 135 skills across scientific domains such as genomics, cheminformatics, clinical research, medical imaging, machine learning, physics, materials science, geospatial analysis, and scientific writing. Each skill provides curated documentation, examples, best practices, and integration guidance so agents can execute complex workflows more reliably. It is especially useful for researchers who need AI assistance with databases, Python libraries, literature review, data analysis, and scientific communication. The project also emphasizes extensibility, security review, and practical installation through npx or GitHub CLI. -
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Academic Research Skills for Claude Code
Academic Research Skills for Claude Code
...The project is designed as a self-guided resource, helping learners understand how to evaluate sources, synthesize information, and develop strong arguments. It likely integrates examples, templates, and conceptual explanations to bridge the gap between theory and practical research execution. The repository emphasizes skill-building rather than automation, making it especially useful for students and early-career researchers. Its overall goal is to enhance research literacy and reproducibility in academic workflows. -
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stable-diffusion-videos
Create videos with Stable Diffusion
Create videos with Stable Diffusion by exploring the latent space and morphing between text prompts. Try it yourself in Colab. -
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Agentic RAG for Dummies
A modular Agentic RAG built with LangGraph
...Instead of relying on static retrieval pipelines, the system shows how agents can orchestrate retrieval, reasoning, and tool usage in a more flexible decision loop. The repository provides practical examples and tutorials that guide developers through building agentic RAG systems using modern AI frameworks. These examples illustrate how agents can access knowledge bases, retrieve documents, analyze them, and refine their queries during multi-step reasoning processes. The repository focuses on simplifying complex architectural concepts so that beginners can understand how agentic retrieval systems are constructed.