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README.md

@@ -5,8 +5,8 @@ MuleSoft Documentation Embeddings for RAG Applications
 ## Dataset Information
 
 - **Version**: 1.0.0
-- **Created**: 2025-09-16T02:31:46.176390
-- **Source**: Weaviate Vector Database
+- **Created**: 2025-09-16T02:37:51.960450
+- **Source**: Vector Database
 - **License**: MIT
 - **Language**: en
 
@@ -23,26 +23,6 @@ question-answering, retrieval, knowledge-base
 - **Knowledge Sources**: mulesoft, user_defined_docs
 - **Average Content Length**: 5079 characters
 
-## RAG Configuration
-
-This dataset was created using the following RAG (Retrieval-Augmented Generation) configuration:
-
-### Embedding Model
-- **Model Type**: OpenAI
-- **Model ID**: text-embedding-3-large
-- **Embedding Dimensions**: 3072
-- **Provider**: OpenAI
-
-### Chunking Configuration
-- **Chunk Size**: 2048 characters
-- **Chunk Overlap**: 256 characters
-
-### Technical Details
-- **Vector Database**: Weaviate
-- **Collection**: SkillPilotDataSet_v11
-- **Total Vectors**: 6430
-- **Vector Distance**: Cosine similarity
-
 ## Usage
 
 This dataset can be used for:
@@ -52,42 +32,22 @@ This dataset can be used for:
 - Technical interview preparation
 - AI assistant training
 
-## Dataset Schema
-
-The dataset preserves the original Weaviate structure with the following columns:
-
-- **weaviate_id**: Unique identifier from Weaviate
-- **collection**: Source collection name (SkillPilotDataSet_v11)
-- **extracted_at**: Timestamp of extraction
-- **properties**: Nested object containing all original Weaviate properties:
-  - `author`: Document author
-  - `chunk_id`: Unique chunk identifier
-  - `chunk_index`: Position of chunk in document
-  - `document_id`: Source document identifier
-  - `entities`: Extracted entities
-  - `keywords`: Document keywords
-  - `knowledge_source`: Source of knowledge (mulesoft, user_defined_docs)
-  - `page_content`: Main text content
-  - `relationships`: Entity relationships
-  - `source_url`: Original document URL
-  - `tags`: Document tags
-  - `title`: Document title
-  - `total_chunks`: Total number of chunks in document
-
 ## Files
 
+- `dataset.json`: Complete dataset in JSON format
+- `dataset.csv`: Dataset in CSV format
 - `dataset.parquet`: Dataset in Parquet format (recommended for large datasets)
-- `README.md`: This documentation file
+- `dataset_metadata.json`: Detailed metadata and statistics
 
 ## Citation
 
 If you use this dataset, please cite:
 
 ```bibtex
-@dataset{{mulesoft_documentation_embeddings,
-  title={{MuleSoft Documentation Embeddings}},
-  author={{Bassem Elsodany}},
+@dataset{{skillpilot_knowledge_base,
+  title={{SkillPilot Knowledge Base}},
+  author={{SkillPilot Team}},
   year={{2025}},
-  url={{https://huggingface.co/datasets/BassemE/mulesoft-documentation-embeddings}}
+  url={{https://huggingface.co/datasets/skillpilot/knowledge-base}}
 }}
 ```