| <div align="center"> |
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| <img src="https://raw.githubusercontent.com/flatseek/flatseek/main/logo.svg" alt="Flatseek" width="72"> |
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| # Flatseek |
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| ### Open Knowledge Infrastructure for AI |
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| **Search. Retrieve. Run. Train.** |
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| Open-source infrastructure for building search systems, AI applications, and language models from your own knowledge. |
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| </div> |
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| --- |
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| ## About |
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| Flatseek is an open-source ecosystem for modern AI infrastructure. |
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| Instead of treating search, retrieval, model training, inference, and model storage as isolated problems, the ecosystem provides modular projects that work independently or together as a complete AI pipeline. |
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| Index your knowledge once, then reuse it across search, semantic retrieval, Retrieval-Augmented Generation (RAG), model training, inference, analytics, and deployment. |
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|
| ```text |
| Knowledge |
| │ |
| ┌───────────────────┴───────────────────┐ |
| │ │ |
| ▼ ▼ |
| |
| Flatseek Flatvec |
| Keyword Search Semantic Search |
| |
| │ │ |
| └───────────────────┬───────────────────┘ |
| │ |
| ▼ |
| |
| Flatask |
| RAG Runtime |
| |
| │ |
| ┌───────────────────┴───────────────────┐ |
| │ │ |
| ▼ ▼ |
| |
| Flattune Flatbuild |
| Dataset Generation Train Models |
| & Fine-tuning From Scratch |
| |
| │ │ |
| └───────────────────┬───────────────────┘ |
| │ |
| ▼ |
| |
| Flatweight |
| Model Storage Layer |
| |
| │ |
| ▼ |
| |
| Flatrun |
| Streaming Inference |
| |
| │ |
| ▼ |
| |
| Flatlens |
| Analytics & Exploration |
| ``` |
|
|
| --- |
| ## Projects |
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| | Project | Description | |
| |---------|-------------| |
| | **[Flatseek](https://github.com/flatseek/flatseek)** | Disk-first full-text search engine for portable datasets and production-scale search. An alternative to Elasticsearch, OpenSearch, and Meilisearch. | |
| | **[Flatvec](https://github.com/flatseek/flatvec)** | Disk-first vector search engine for semantic retrieval and RAG. An alternative to FAISS, Milvus, Pinecone, Qdrant, and Chroma. | |
| | **[Flatask](https://github.com/flatseek/flatask)** | Retrieval-Augmented Generation (RAG) runtime that connects keyword search, semantic search, and language models into a unified retrieval pipeline. | |
| | **[Flattune](https://github.com/flatseek/flattune)** | Dataset generation and fine-tuning pipeline for creating high-quality training corpora from existing knowledge. | |
| | **[Flatbuild](https://github.com/flatseek/flatbuild)** | Framework for training transformer language models from scratch, including tokenizer training, chat templates, checkpoint export, and GGUF conversion. | |
| | **[Flatweight](https://github.com/flatseek/flatweight)** | Storage-native model format and tooling for organizing, converting, and managing model weights for efficient deployment and streaming inference. | |
| | **[Flatrun](https://github.com/flatseek/flatrun)** | Streaming inference runtime that executes GGUF, SafeTensors, and MLX models directly from storage with minimal memory usage. | |
| | **[Flatlens](https://github.com/flatseek/flatlens)** | Analytics and visualization interface for exploring search indexes, datasets, retrieval pipelines, and AI workflows. | |
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| --- |
|
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| # Design Principles |
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| The Flat ecosystem is built around a few simple ideas: |
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| - Build knowledge once and reuse it everywhere. |
| - Keep data portable and storage-native. |
| - Prefer open formats over proprietary services. |
| - Make every project useful on its own. |
| - Compose projects into larger AI workflows when needed. |
| - Train, deploy, and share models with reproducible pipelines. |
| - Run efficiently on consumer hardware whenever possible. |
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| --- |
|
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| # License |
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| Unless otherwise noted, projects and published artifacts are released under the Apache License 2.0. |
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| --- |
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| <div align="center"> |
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| ### Build once. Search anywhere. Train from scratch. Run everywhere. |
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| </div> |
