Search Results for "raw"
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48 projects for "raw" with 2 filters applied:
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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.
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Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Humanizer Skill
Claude Code skill that removes signs of AI-generated writing from text
...It provides a suite of algorithms that convert timestamps, identifiers, file sizes, code tokens, and structured data into phrases that resemble typical human phrasing rather than compact machine output. For example, date and time values can be expressed as relative terms (“two hours ago”), and file sizes can be shown in intuitive units instead of raw bytes. It also includes functions for transforming camelCase, snake_case, or PascalCase identifiers into spaced and capitalized representations suitable for user interfaces, reports, or documentation. Beyond text formatting, the library can handle pluralization, enumeration formatting (“A, B, and C”), and token expansion so that program-generated content feels more conversational. -
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EverMemOS
Long-term memory OS for AI with structured recall and context awarenes
...EverMemOS goes beyond simple retrieval by actively applying stored knowledge to current tasks, improving personalization and consistency. EverMemOS uses a multi-stage memory lifecycle to convert raw dialogue into structured semantic data, supporting long-horizon reasoning and adaptive behavior across sessions. -
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OpenHealth
AI health assistant for private, local data-driven insights mgmt
...A strong emphasis is placed on privacy, as the platform can run entirely locally, ensuring that sensitive medical data does not need to leave the user’s environment. OpenHealth also includes a data parsing layer that transforms raw medical inputs into structured datasets, making them usable for analysis and AI-driven insights. OpenHealth separates data ingestion, processing, and AI interaction, enabling flexibility in integrating different models and data sources. -
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graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
...The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, graphify serves as a bridge between raw data and visual insight. -
Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
...The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. By producing Markdown rather than raw text, the tool makes it easier to integrate documents into knowledge bases, documentation systems, or language model pipelines that rely on structured input. The software is particularly useful for developers working with technical documents, academic papers, or reports that need to be indexed, summarized, or processed by downstream AI systems. -
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AsmJit
Low-latency machine code generation
AsmJit is a low-level code generation library designed for dynamically creating machine code at runtime, enabling just-in-time (JIT) compilation for performance-critical applications. It provides a high-level API that abstracts away the complexity of writing raw assembly while still allowing fine-grained control over instruction generation. The library supports multiple architectures, including x86 and x64, making it versatile for cross-platform development. It is commonly used in applications such as emulators, compilers, and high-performance computing systems where runtime optimization is essential. asmjit emphasizes low latency and efficiency, ensuring that generated code executes quickly without significant overhead. ... -
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PasteGuard
Masks sensitive data and secrets before they reach AI
...It sits between an application and the LLM provider, automatically replacing names, emails, tokens, and other personally identifiable information (PII) with placeholders so that external services never see raw sensitive values, and then optionally unmasking them in the returned output. PasteGuard supports two primary modes: mask mode, which anonymizes data and still uses external APIs; and route mode, which forwards sensitive requests to a local LLM inference engine while sending the rest to the cloud. It can be self-hosted via Docker, works with a wide range of SDKs and tools, and includes a browser extension for automatic protection in everyday AI chats. -
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rep+
Burp-style HTTP Repeater for Chrome DevTools with built‑in AI
...It includes AI-assisted insights, where contextual explanations and attack vector suggestions help interpret request outcomes or propose modifications. Additional productivity features like exporting/importing requests, various representation modes (pretty/raw/hex), and bulk replay mechanisms make it suitable for debugging, performance checking, or security probing. -
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FISSURE
The RF and reverse engineering framework for everyone
...The project brings together tools for capturing, inspecting, decoding, replaying, and analyzing RF signals across a wide range of wireless technologies. It is designed as a practical environment for researchers and operators who need to move from raw spectrum observation to structured investigation without stitching together too many separate utilities by hand. The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. Its architecture is oriented toward extensibility, so users can integrate additional hardware, signal-processing components, and protocol-specific modules depending on their needs. -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
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Rill
Fast SQL-based BI tool for real-time dashboards and analytics
Rill is an operational BI tool that turns raw datasets into fast, interactive dashboards using SQL and a code-first approach. It helps data teams move from data lake to insight quickly, without the complexity of traditional BI systems. With an embedded in-memory database powered by DuckDB or ClickHouse, queries run in milliseconds, enabling real-time exploration and analysis. -
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LLM Scraper
Extract structured data from webpages using LLM-powered scraping
...LLM Scraper integrates browser automation through Playwright, allowing it to load webpages and process their content before sending it to a language model for interpretation. Multiple content processing modes are supported, including raw HTML, cleaned HTML, Markdown, extracted text, screenshots, and custom inputs, making it adaptable to a wide range of scraping scenarios. LLM Scraper also provides streaming output and code generation capabilities that help developers build reusable scraping workflows. -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
...The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework. -
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Wiseflow
Enhance any agent's browser use skill
...The platform continuously monitors specified sources such as websites, social platforms, and other digital channels to identify relevant data according to user-defined interests or topics. By combining web crawling, content parsing, and large language model analysis, the system extracts concise insights from raw information streams and converts them into structured data that can be stored or analyzed. This automated workflow helps reduce the noise associated with large information ecosystems and highlights the most important insights for users. Wiseflow can automatically categorize extracted content, assign tags, and upload processed results into databases or knowledge systems for further use. -
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verl
Volcano Engine Reinforcement Learning for LLMs
VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy. It ships with reference implementations of popular alignment algorithms and clear examples that make it straightforward to reproduce baselines before customizing. ... -
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Hindsight
Hindsight: Agent Memory That Learns
...Instead of relying solely on vector similarity or basic retrieval techniques, Hindsight organizes information into distinct categories such as facts, experiences, beliefs, and observations, allowing agents to differentiate between raw data and inferred knowledge. The system operates through three core mechanisms—retain, recall, and reflect—which respectively handle storing information, retrieving relevant context, and generating new insights based on accumulated experience. -
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DeepSeek-OCR
Contexts Optical Compression
...It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. It supports local deployment, enabling organizations concerned about privacy or latency to run the pipeline on-premises rather than send sensitive documents to third-party cloud services. ... -
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Auto-Deep-Research
Your Fully-Automated Personal AI Assistant
...It also embeds validation loops, where intermediate drafts are self-checked for consistency, coverage, and alignment with sound reasoning practices, reducing reliance on raw generation alone. -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. -
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kg-gen
Knowledge Graph Generation from Any Text
...Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing higher-quality graph structures from raw text. The framework addresses common problems in automatic knowledge graph construction, particularly sparsity and duplication of entities, by applying a clustering and entity-resolution process that merges semantically similar nodes. This allows the generated graphs to be denser, more coherent, and easier to use for downstream tasks such as retrieval-augmented generation, semantic search, and reasoning systems. -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
...Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. It includes an “Ask” feature that lets users query the generated wiki using RAG-style retrieval, enabling interactive question-answering and exploration. -
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Engram
A New Axis of Sparsity for Large Language Models
...Engineered with speed and memory efficiency in mind, Engram supports batched indexing, incremental updates, and custom distance metrics so developers can tailor search behaviors to their domain’s needs. In addition to raw similarity search, the project includes tools for clustering, ranking, and filtering results, enabling richer user experiences like “related content”, semantic auto-completion, and contextual filtering. -
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MuseGAN
An AI for Music Generation
...The system focuses specifically on generating multi-track polyphonic music, meaning that it can simultaneously produce multiple instrument parts such as drums, bass, piano, guitar, and strings. Instead of generating raw audio, the model operates on piano-roll representations of music, which encode notes as time-pitch matrices for each instrument track. This representation allows the neural network to capture rhythmic patterns, harmonic relationships, and structural dependencies across instruments. The architecture is based on convolutional GAN models that learn temporal musical structure and inter-track relationships from training data. ... -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
...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 runtime context — to generate SQL queries that are both technically correct and semantically meaningful. The system then executes those queries against a database and interprets the results, returning human-friendly insights not just raw rows, while learning from errors and successes to reduce repeated mistakes. -
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically from large image–text or weakly supervised corpora. It includes utilities to build concept vocabularies, map supervision signals to those vocabularies, and measure zero-shot or few-shot generalization. ...
