Add files using upload-large-folder tool

README.md

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+---
+tags:
+  - vector-database
+  - embeddings
+  - parquet
+  - qdrant
+  - stackoverflow
+  - question-answering
+pretty_name: StackOverflow Vector Dataset - LUA
+license: cc-by-sa-4.0
+size_categories:
+  - 1M<n<10M
+---
+
+# LUA StackOverflow Vector Dataset
+
+## Summary
+
+This repository contains the LUA shard of the Stack2Graph vector retrieval dataset.
+Each Hugging Face dataset repository contains one programming-language shard and is intended to restore or rebuild the Qdrant collection `stackoverflow_lua_vector`.
+
+The dataset is the vector counterpart to the Stack2Graph RDF knowledge graph. It is designed for hybrid retrieval, graph entry-point finding, and retrieval-augmented generation experiments over Stack Overflow content.
+
+Stack2Graph source:
+[https://github.com/tha-atlas/Stack2Graph](https://github.com/tha-atlas/Stack2Graph)
+
+## Repository Layout
+
+```text
+README.md
+dataset_manifest.json
+qdrant_snapshots/
+  collections_manifest.json
+  stackoverflow_lua_vector.tar.zst
+  stackoverflow_lua_vector.snapshot.zst.part_000
+  ...
+question_metadata/
+  r0_00000.parquet
+chunk_records/
+  r0_00000.parquet
+question_records/
+  r0_00000.parquet
+```
+
+- `dataset_manifest.json`: language-scoped manifest listing the files in this shard.
+- `qdrant_snapshots/collections_manifest.json`: language-scoped Qdrant snapshot manifest.
+- `qdrant_snapshots/stackoverflow_lua_vector.*`: optional Qdrant restore artifact files for `stackoverflow_lua_vector`.
+- `question_metadata/*.parquet`: question-level metadata used by parent-child chunk retrieval.
+- `chunk_records/*.parquet`: chunk-level vector rows when parent-child indexing is enabled.
+- `question_records/*.parquet`: question-level vector rows when non-chunked export is used.
+
+The Hugging Face upload is one repository per language. During upload, the local leading language directory is removed, so local files such as `lua/chunk_records/r0_00000.parquet` appear in this repository as `chunk_records/r0_00000.parquet`.
+
+## Data Model
+
+Rows are derived from Stack Overflow questions tagged for LUA.
+
+The current Stack2Graph vector pipeline uses:
+
+- dense vectors from `Qwen/Qwen3-Embedding-8B`
+- 4096-dimensional dense embeddings with last-token pooling
+- instruction-aware query embedding for retrieval
+- sparse lexical vectors from `BAAI/bge-m3`
+- unified question text containing title, tags, cleaned problem text, and code
+- optional parent-child indexing where chunk hits collapse back to parent question IDs
+
+When Qdrant snapshots are included, they are the fastest restore path. The Parquet files remain the portable fallback for rebuilding the collection.
+
+## Coverage
+
+This repository contains only the LUA shard. A Stack Overflow question can appear in more than one language shard when it has multiple programming-language tags.
+
+The dataset is not a complete Stack Overflow mirror. Full question and answer graph context lives in the corresponding Stack2Graph knowledge graph artifacts; the vector dataset stores retrieval rows, vectors, sparse weights, and routing metadata.
+
+## Recommended Use
+
+Use this dataset for:
+
+- semantic and hybrid retrieval
+- Qdrant restore or ingestion tests
+- Stack2Graph RAG experiments
+- graph entry-point retrieval before QLever graph expansion
+- vector database benchmarking and diagnostics
+
+This dataset is not intended as a standalone supervised training dataset.
+
+## Restore With Stack2Graph
+
+You do not need to regenerate embeddings to use this dataset.
+
+Typical workflow:
+
+1. Clone Stack2Graph and configure `.env` with service paths and HF token.
+2. Start local services:
+
+```bash
+docker compose up -d
+```
+
+3. Download and restore vector artifacts:
+
+```bash
+python -m experiment.sources.hf --skip-kg
+```
+
+The loader restores Qdrant snapshots when present and falls back to Parquet ingestion when snapshots are unavailable.
+
+## Manual Use
+
+For manual use, inspect `dataset_manifest.json`, then either:
+
+- restore the Qdrant snapshot artifacts under `qdrant_snapshots/`, or
+- ingest the listed Parquet shards into a compatible vector database.
+
+The target Qdrant collection name is:
+
+```text
+stackoverflow_lua_vector
+```
+
+## Quality Notes
+
+- Embedding quality depends on the configured Stack2Graph export pipeline and model versions.
+- Sparse text can be generated from the same unified text as dense embeddings or from a lexical variant, depending on export configuration.
+- Community-generated Stack Overflow content may contain errors, outdated information, bias, or incomplete answers.
+- Rebuilding from Parquet may produce operational differences if Qdrant collection settings differ from the original export.
+
+## License And Attribution
+
+This dataset is derived from Stack Overflow content and is distributed under `CC-BY-SA-4.0`.
+Preserve required attribution and license notices when redistributing derived artifacts.
+
+## Citation
+
+If you use this dataset, cite the Stack2Graph project and preserve Stack Overflow attribution requirements:
+
+- Stack2Graph: A Structured Knowledge Representation of Stack Overflow Data for Retrieval-based Question Answering

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dataset_manifest.json

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+    {
+      "category": "chunk_records",
+      "language": "lua",
+      "relative_path": "chunk_records/r0_00000.parquet",
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+    {
+      "category": "chunk_records",
+      "language": "lua",
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+      "language": "lua",
+      "relative_path": "question_metadata/r0_00000.parquet",
+      "rows": 22950
+    }
+  ],
+  "language": "lua",
+  "qdrant_snapshot": {
+    "artifact_files": [
+      "part_000.tar.zst"
+    ],
+    "artifact_format": "tar.zst",
+    "collection_name": "stackoverflow_lua_vector",
+    "manifest_path": "/var/stackoverflow_data/vector_dataset_archives/hf_upload_folder/lua/qdrant_snapshots/collections_manifest.json",
+    "points_count": 28209,
+    "snapshot_file": "snapshots/stackoverflow_lua_vector.snapshot"
+  },
+  "source": "vector_dataset_language_folder",
+  "total_rows": 51159
+}

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qdrant_snapshots/collections_manifest.json

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+  "max_archive_parts": 1000,
+  "qdrant_url": "http://localhost:6333",
+  "snapshot_dir": "snapshots",
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