Search Results for "build" - Page 20
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Showing 1079 open source projects for "build"
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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.
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Shinkai: Local AI Agents
Shinkai allows you to create advanced AI (local) agents effortlessly
...These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized payments and transactions - Flexible AI Models - Choose from cloud models (GPT-4, Claude) or run locally - Universal Compatibility - Works with Model Context Protocol (MCP) for cross-platform integration - Local Security - Crypto keys and computations stay on your device Shinkai transforms AI from single-task tools into collaborative, autonomous systems that can operate in decentralized networks while maintaining privacy and security. -
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SAVA
A Signal Acquisition, Visualization & Analysis software
A Signal Acquisition, Visualization & Analysis software application: * Signals, as in analog sensor data * Acquisition, as in data sampling/capturing/recording * Visualization, as in plotting raw/processed data * Analysis, as in live/post data processing Capabilities: The software has build in support for National Instruments Daq equipment (NI-DAQ) or it can load external source scripts (python), for customizable data sources. Supports data exporting/importing to multiple file formats (H5, CSV, Matlab, txt) Raw and analyzed data can be visualized and inspected in real-time or via playback. Most traditional signal processing methods are available, such as trending (Mean, Peak, Min/Max, RMS, Variance, Kurtosis, Skew, MAD) and frequency domain analysis (FFT, FRF, Order Spectrum). ... -
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AutoTrader
A Python-based development platform for automated trading systems
...The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. Capable of simulating multiple order types, stop-losse,s and take-profits, cross-exchange arbitrage and portfolio strategies, AutoTrader has more than enough to build a profitable trading system. -
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JesseAi
Advanced AI-Powered Python Crypto Trading Bot 2026 - Free Backtesting
Jesse Bot: Advanced AI-Powered Python Best Crypto Trading Bot & Framework (2026) Jesse Bot — free open-source Python crypto trading bot & robust framework for cryptocurrency markets. Build, backtest, AI-optimize, and execute precise automated strategies with zero look-ahead bias. Use JesseGPT — built-in AI assistant — to write, debug, and refine strategies effortlessly, even as a beginner. Secure live trading on Binance, Bybit & major exchanges, full risk management, leverage/futures support, and pro analytics. One of the best open-source alternatives to Freqtrade with genuine AI edge: privacy-first self-hosting (no shared API keys), multi-timeframe/symbol backtesting, custom indicators, ML-enhanced signals. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Canopy
Retrieval Augmented Generation (RAG) framework
...It is designed to handle many of the complex components required for a RAG workflow, including document chunking, embedding generation, prompt construction, and chat history management. Developers can use Canopy to quickly build chat systems that answer questions using their own data instead of relying solely on the pretrained knowledge of the language model. The framework includes a built-in server and command-line interface that allow users to experiment with RAG pipelines and compare outputs between retrieval-augmented responses and standard LLM responses. -
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local-llm
Run LLMs locally on Cloud Workstations
...This approach improves data privacy and control, as all inference can be performed locally without sending sensitive information to external APIs. It also integrates seamlessly with Google Cloud services, allowing developers to build and test AI-powered applications within the broader cloud ecosystem. -
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PyCAPGE
PyCAPGE - Python Classic Adventure Point and Click Game Engine
...It implements intelligent Pathfinding to navigate complex environments automatically. The engine natively supports Multi-Character gameplay, allowing dynamic switching between protagonists. Developers can build rich narratives using the branching Dialogue System and a Cutscene Manager for scripted events. The architecture is data-driven: texts and definitions are separated into YAML files for easy localization. Includes a JSON Save/Load system and debug console. -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
AIConfig is an open-source framework designed to simplify the development and management of generative AI applications by separating AI logic from application code. The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. This approach improves collaboration between developers, prompt engineers, and machine learning practitioners by turning... -
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snorkel
A system for quickly generating training data with weak supervision
...Given this premise, we set out to explore the radical idea that you could bring mathematical and systems structure to the messy and often entirely manual process of training data creation and management, starting by empowering users to programmatically label, build, and manage training data. Snorkel Flow, an end-to-end machine learning platform for developing and deploying AI applications. Snorkel Flow incorporates many of the concepts of the Snorkel project with a range of newer techniques around weak supervision modeling, data augmentation, multi-task learning, data slicing and structuring. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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snntorch
Deep and online learning with spiking neural networks in Python
snntorch is a deep learning library that enables researchers and developers to build and train spiking neural networks using the PyTorch framework. Spiking neural networks are biologically inspired models that communicate through discrete spike events rather than continuous activation values, making them closer to how neurons operate in the brain. The library extends PyTorch’s tensor computation capabilities to support gradient-based learning for networks composed of spiking neurons. ... -
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dude uncomplicated data extraction
dude uncomplicated data extraction: A simple framework
Dude is a very simple framework for writing web scrapers using Python decorators. The design, inspired by Flask, was to easily build a web scraper in just a few lines of code. Dude has an easy-to-learn syntax. Dude is currently in Pre-Alpha. Please expect breaking changes. You can run your scraper from terminal/shell/command-line by supplying URLs, the output filename of your choice and the paths to your python scripts to dude scrape command. -
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GitGot
Semi-automated tool for discovering exposed secrets in GitHub data
...GitGot leverages the GitHub Search API to perform queries across repositories, files, and gists, allowing security researchers and penetration testers to discover sensitive information that may have been unintentionally exposed in public code. During a search session, users review results and provide feedback that allows GitGot to filter out irrelevant or repetitive findings. This feedback is used to build blacklists that eliminate results based on repository names, file names, user names, or fuzzy matches of file content. The approach helps reduce noise while guiding the search process toward more relevant results. -
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Plugins Quickstart
Get a ChatGPT plugin up and running in under 5 minutes
plugins-quickstart is a starter project created by OpenAI to help developers build and deploy ChatGPT plugins quickly. It provides a minimal but complete example of how to structure a plugin, implement an API, and define the necessary configuration files. The repository demonstrates how a plugin can be served, authenticated, and integrated with ChatGPT for real-world use. By including both the backend code and plugin manifest, it guides developers through the end-to-end development workflow. ... -
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autollm
Ship RAG based LLM web apps in seconds
autollm is an open-source Python framework designed to make it much faster to build retrieval-augmented generation applications and expose them as usable services with minimal setup. The project focuses on simplifying the usual stack of model selection, document ingestion, vector storage, querying, and API deployment into a more unified developer experience. Its core idea is that a developer can create a query engine from a document set in just a few lines and then turn that same engine into a FastAPI application almost instantly. ... -
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Sonnet
TensorFlow-based neural network library
...Users are also encouraged to build their own modules. Sonnet is designed to be extremely unopinionated about your use of modules. It is simple to understand, and offers clear and focused code. -
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Digital Forensics Guide
Learn all about Digital Forensics and Computer Forensics
...It organizes foundational topics such as evidence acquisition, disk and memory analysis, file system structures, network forensics, artifact extraction, timeline generation, and reporting into digestible modules that help build core competency. Alongside conceptual explanations, the guide includes practical examples with widely used tools (like Autopsy, Volatility, Sleuth Kit, and network analysis suites), illustrating how investigations proceed from initial data capture to final analysis. The goal is to provide both a learning path and a quick reference for real-world casework, bridging the gap between academic theory and operational practice. -
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MMDeploy
OpenMMLab Model Deployment Framework
...All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy. -
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Errbot
Chatbot daemon that connects to your favorite chat services
...Extending Errbot and adding your own commands can be done by creating a plugin, which is simply a class derived from BotPlugin. The docstrings will be automatically reused by the !help command. We aim to give you all the tools you need to build a customized bot safely, without having to worry about basic functionality. As such, Errbot comes with a wealth of features out of the box. One of the main goals of Errbot is to make it easy to share your plugin with others as well. -
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InternLM
Official release of InternLM series
...The repository highlights multiple model sizes intended to serve different needs, from efficient research and prototyping to more capable deployments for complex scenarios. Beyond model weights, the project emphasizes an ecosystem view, pointing developers to compatible tools and projects across training and inference so teams can build end-to-end workflows. InternLM’s direction includes strong general-purpose capabilities and ongoing iterations that target improved reasoning, coding, and tool-use behaviors. The broader InternLM ecosystem also includes training tooling and guidance aimed at making fine-tuning and adaptation more accessible across hardware setups, including smaller single-GPU environments and larger multi-node configurations. -
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Oblivion-Inverse
Open source e-mail tracker made with Flask, setup & run in 10 minutes
Oblivion-Inverse is a simple, free & open source e-mail tracking solution which based on the usage of web beacons or tracking pixels. Build with Flask and setup under 10 minutes on your own production environment. Designed to provide information about the email read status, time, IP address of the recipient's device or proxy, as well as request headers such as the user-agent, which can reveal details about the recipient's browser, operating system, and device. Generate tracking links for your emails and drag the tracking pixel to the end of the message body. ... -
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CLIP-as-service
Embed images and sentences into fixed-length vectors
...Async client support. Easily switch between gRPC, HTTP, WebSocket protocols with TLS and compression. Smooth integration with neural search ecosystem including Jina and DocArray. Build cross-modal and multi-modal solutions in no time. -
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RAGs
Build ChatGPT over your data, all with natural language
...Built with Streamlit and powered by the LlamaIndex ecosystem, the tool allows users to construct AI assistants that answer questions using their own data sources. Instead of requiring extensive programming knowledge, the application allows users to configure and build a RAG system using natural language instructions. The system automatically generates pipeline configurations that control how documents are retrieved, processed, and summarized before being used by a language model to generate responses. Users can also inspect and adjust parameters such as the number of retrieved documents, summarization strategies, and query settings through a configuration interface. ... -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. ... -
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Example Streamlit
Example Streamlit app that you can fork to test out share.streamlit.io
streamlit-example is an open source sample app created by the Streamlit team to demonstrate how to quickly build and deploy applications with Streamlit. The repository contains a minimal Python app (streamlit_app.py) that can be customized by editing the source file. It is designed for use with share.streamlit.io, allowing developers to fork the repo and instantly deploy their own interactive app. The project includes basic dependencies defined in requirements.txt and supports containerized development via .devcontainer. ... -
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EvaDB
Database system for building simpler and faster AI-powered application
Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents...
