semantic
Semantic DataFrames for humans and agents.
fenic turns AI-assisted exploration of structured and unstructured data into reusable, inspectable DataFrame pipelines.
It's a DataFrame query engine for semantic data processing, with AI operators — extract, classify, summarize, embed, semantic join, and more — built into the query model. Use it to turn documents, transcripts, logs, eval traces, tickets, tables, and APIs into typed rows and repeatable workflows.
Semantic understanding on top of Git. Diff, blame, impact, log. Functions, not lines.
Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 26 languages via tree-sitter. Built for coding agents.
Your entire codebase as Claude's context.
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.
Serena is a powerful coding agent toolkit capable of turning an LLM into a fully-featured agent that works directly on your codebase. Unlike most other tools, it is not tied to an LLM, framework or an interface, making it easy to use it in a variety of ways.
Serena provides essential semantic code retrieval and editing tools that are akin to an IDE’s capabilities, extracting code entities at the symbol level and exploiting relational structure. When combined with an existing coding agent, these tools greatly enhance (token) efficiency.
Serena is free & open-source, enhancing the capabilities of LLMs you already have access to free of charge.
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Intelligent Query Result Caching for PostgreSQL
Leverage vector embeddings to cache and retrieve query results based on semantic similarity.
LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.
It adopts a modular architecture that combines multimodal preprocessing, semantic vector indexing, intelligent retrieval, and large language model inference. At its core, WeKnora follows the RAG (Retrieval-Augmented Generation) paradigm, enabling high-quality, context-aware answers by combining relevant document chunks with model reasoning.
Semantic search for agents.
A calm, CLI-native way to semantically grep everything, like code, images, pdfs and more.
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The SQLite of Semantic Search . Revolutionary 3D Spatial Linguistic Database.
Discover hidden connections in language through geometric intelligence
A modern open source language for analyzing, transforming, and modeling data.
Malloy is a modern open source language for describing data relationships and transformations. It is both a semantic modeling language and a query language that uses an existing SQL engine to execute queries. Malloy currently can connect to BigQuery, Snowflake, PostgreSQL, MySQL, Trino, or Presto, and natively supports DuckDB. We've built a Visual Studio Code extension to facilitate building Malloy data models, querying and transforming data, and creating simple visualizations and dashboards.
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Semantic Data Processing. Build data processing and data analysis pipelines that leverage the power of LLMs 🧠
Semlib is a Python library for building data processing and data analysis pipelines that leverage the power of large language models (LLMs). Semlib provides, as building blocks, familiar functional programming primitives like map, reduce, sort, and filter, but with a twist: Semlib's implementation of these operations are programmed with natural language descriptions rather than code. Under the hood, Semlib handles complexities such as prompting, parsing, concurrency control, caching, and cost tracking.
A powerful coding agent toolkit providing semantic retrieval and editing capabilities (MCP server & other integrations).
🚀 Serena is a powerful coding agent toolkit capable of turning an LLM into a fully-featured agent that works directly on your codebase. Unlike most other tools, it is not tied to an LLM, framework or an interface, making it easy to use it in a variety of ways.
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Semantic grep tool for use by AI and humans!
ck (seek) finds code by meaning, not just keywords. It's a drop-in replacement for grep that understands what you're looking for — search for "error handling" and find try/catch blocks, error returns, and exception handling code even when those exact words aren't present.
Video-Based AI Memory 🧠📹.
Video-based AI memory library. Store millions of text chunks in MP4 files with lightning-fast semantic search. No database needed.
Memvid revolutionizes AI memory management by encoding text data into videos, enabling lightning-fast semantic search across millions of text chunks with sub-second retrieval times. Unlike traditional vector databases that consume massive amounts of RAM and storage, Memvid compresses your knowledge base into compact video files while maintaining instant access to any piece of information.
Semantic unit testing is a testing approach that evaluates whether a function's implementation aligns with its documented behavior. The code is analyzed using LLMs to assess whether the implementation matches the expected behavior described in the docstring.
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batteries included search engine. Nixiesearch is a hybrid search engine that fine-tunes to your data.
📊 Cube — The Semantic Layer for Building Data Applications. The Universal Semantic Layer.
Build trust with a semantic layer. Connect siloed data, define consistent metrics, and power AI and analytics with context.
Cube is the semantic layer for building data applications. It helps data engineers and application developers access data from modern data stores, organize it into consistent definitions, and deliver it to every application.
Cube was designed to work with all SQL-enabled data sources, including cloud data warehouses like Snowflake or Google BigQuery, query engines like Presto or Amazon Athena, and application databases like Postgres. Cube has a built-in relational caching engine to provide sub-second latency and high concurrency for API requests.
txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
A minimalist stylesheet for HTML elements
No class names, no frameworks, just semantic HTML and you're done.
Minimal CSS Framework for semantic HTML. Elegant styles for all natives HTML elements without .classes and dark mode automatically enabled.