Search Results for "data access layer"
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Showing 358 open source projects for "data access layer"
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live... -
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OPAL
Policy and data administration, distribution, and real-time updates
OPAL is an open-source administration layer for keeping authorization policies and authorization data synchronized in real time. It works with policy engines such as OPA and Cedar so applications can make decisions using current policy and data without constantly rebuilding custom sync logic. The project aggregates policy and data from external sources, watches for changes, and distributes updates to connected policy agents. -
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OCRmyPDF
OCRmyPDF adds an OCR text layer to scanned PDF files
OCRmyPDF adds an optical character recognition (OCR) text layer to scanned PDF files, allowing them to be searched. PDF is the best format for storing and exchanging scanned documents. Unfortunately, PDFs can be difficult to modify. OCRmyPDF makes it easy to apply image processing and OCR (recognized, searchable text) to existing PDFs. -
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Feast
Feature Store for Machine Learning
...Avoid data leakage by generating point-in-time correct feature sets so data scientists can focus on feature engineering rather than debugging error-prone dataset joining logic. This ensure that future feature values do not leak to models during training. Decouple ML from data infrastructure by providing a single data access layer that abstracts feature storage from feature retrieval, ensuring models remain portable as you move from training models to serving models, from batch model -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. -
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Docling
Get your documents ready for gen AI
...Its modular architecture allows developers to extend functionality and integrate specialized models for tasks such as OCR and audio transcription. Overall, Docling serves as a comprehensive preprocessing layer for AI applications that require reliable, structured access to complex document data. -
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Bracket
Selfhosted tournament system
Bracket is an open-source tool that tracks and manages data access across your PostgreSQL database. It provides visibility into which parts of your codebase are accessing which tables and columns, enabling data governance, security auditing, and architectural insights. Bracket is particularly helpful for growing teams needing better observability in complex applications. -
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E2M
E2M converts various file types (doc, docx, epub, html, htm, url
...By acting as a transformation layer, the software can support workflows such as converting data formats, integrating services, or bridging incompatible systems. The mirror hosted on SourceForge ensures that developers can continue accessing the project even if the primary repository becomes unavailable. -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
...Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. Because the storage layer (3FS) is optimized for random access and high throughput, smallpond can shuffle data, repartition, and manage intermediate results across nodes. -
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Copulas
A library to model multivariate data using copulas
Access & manipulate learned parameters. With complete access to the internals of the model, set or tune parameters to your choosing. -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
PipesHub AI is an open-source, enterprise-grade workplace AI platform designed to unify search, knowledge management, and workflow automation across distributed organizational systems. It connects to a wide range of enterprise tools such as Google Workspace, Slack, Jira, and Confluence, aggregating data into a centralized knowledge layer that can be queried using natural language. The platform uses knowledge graphs and ranking algorithms to provide context-rich answers along with traceable sources, improving transparency and trust in AI-generated insights. PipesHub also enables the creation of custom AI agents and applications through a no-code interface, allowing teams to automate workflows and build intelligent tools without deep technical expertise. ... -
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Legion MCP
A server that helps people access and query data in databases
The Legion MCP Server is designed to help users access and query data in databases using the Legion Query Runner, integrated with the Model Context Protocol (MCP) Python SDK. It facilitates efficient data retrieval and analysis through standardized interfaces. -
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DictDataBase
A python NoSQL dictionary database, with concurrent access and ACID
DictDataBase (DictDB) is a lightweight, Python-based in-memory database that uses dictionaries as its primary data structure. It provides a simple and efficient way to store, retrieve, and manipulate data without requiring an external database server. DictDB is useful for applications needing fast lookups, temporary storage, or embedded database functionalities. -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
...Overall, the repository acts as a modular capability layer that transforms general AI agents into domain-aware computational scientists. -
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OpenDataMCP
Connect any Open Data to any LLM with Model Context Protocol
An initiative aimed at connecting open datasets to Large Language Models (LLMs) using the Model Context Protocol, facilitating seamless access and integration of public data into AI applications. -
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Seeker
Accurately Locate Smartphones using Social Engineering
Seeker is an open source project that demonstrates how to obtain precise location information from devices using social engineering and web-based techniques. The tool sets up a phishing page that asks for location permissions, allowing GPS and other device data to be shared if the user consents. It can capture latitude, longitude, accuracy, altitude, direction, and even speed, with results displayed in a terminal. The project supports both manual deployment and tunneling services like Ngrok for external access. While primarily intended as an educational resource on security awareness, it highlights the risks of exposing geolocation data online. ... -
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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. -
18
geowifi
OSINT tool for locating WiFi networks using BSSID or SSID data
geowifi is an open source OSINT tool designed to search and retrieve geolocation information about WiFi networks using their BSSID or SSID identifiers. It queries several public WiFi geolocation databases and aggregates the results to help identify the approximate location of a wireless access point. By combining multiple data sources such as Wigle, Apple, Google, WifiDB, Mylnikov, and Combain, the tool can provide location data that may include coordinates and additional network metadata. Users can run searches through a command-line interface by specifying either the BSSID (MAC address) or the SSID of a network. The results can be displayed in different formats, including a structured JSON output or an interactive HTML map showing the discovered locations. geowifi also supports API-based integrations with certain services, which allows geowifi to retrieve more accurate or detailed geolocation data when valid API credentials are configured. -
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Fantasy PL MCP
Fantasy Premier League MCP Server
Fantasy Premier League MCP Server is a Model Context Protocol (MCP) server that provides access to Fantasy Premier League (FPL) data and tools. It allows interaction with FPL data in MCP-compatible clients, enabling users to manage their fantasy teams effectively. -
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Coomer Downloader App
Coomer downloader
...The application typically supports features such as authentication, rate limiting, and retry mechanisms to ensure reliable downloads even when dealing with unstable connections or restricted endpoints. It is often used for personal archiving, data collection, or offline access to content that may otherwise be difficult to manage manually. The tool operates through a command-line interface, making it suitable for scripting and integration into automated workflows. -
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glom
Python's nested data operator
glom is a Python library and command-line tool for accessing, restructuring, and transforming nested data. It is designed for real-world data structures where dictionaries, objects, and lists are deeply nested and difficult to handle cleanly. Developers can use path-based access to retrieve values without writing long chains of fragile indexing code. The library also provides readable error messages, which makes debugging broken paths much easier. -
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kagglehub
Python library to access Kaggle resources
...The library is designed to work both inside and outside Kaggle Notebooks, with native behavior that can adapt when it runs in Kaggle’s hosted notebook environment. It is useful for machine learning workflows where data, models, and notebook artifacts need to be pulled into scripts, experiments, or pipelines. kagglehub also supports authentication so users can access private or restricted resources when their account has permission. Its main value is making Kaggle assets easier to consume programmatically in Python-first data science and AI development workflows. -
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DouK-Downloader
TikTok releases/likes/compilations/live streams/videos/atlases/music
...The software goes beyond simple downloading by offering comprehensive data collection features, including comments, user statistics, and trending data such as hot boards and search results. It supports automated workflows like incremental downloads, duplicate detection, and persistent storage of collected data in formats like CSV, XLSX, and SQLite, making it useful for both content archiving and analytics. -
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OpenDAN
OpenDAN is an open source Personal AI OS
OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers,... -
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LlamaIndex
Central interface to connect your LLM's with external data
LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. LlamaIndex is a simple, flexible interface between your external data and LLMs. It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when...
