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## Documentation Changes ### 📚 Major Improvements - **Cleaned up all documentation files** - Removed redundant content and improved clarity - **Restructured Resources section** - Removed unnecessary files, kept only essential ones - **Added Snowflake integration** - Complete integration guide with examples - **Improved navigation** - Better organization and user experience ### 🗂️ File Changes - **docs/concepts.md** - Rewritten to be clean and user-friendly - **docs/modules.md** - Updated with current modules and removed emojis - **docs/glossary.md** - Reorganized thematically instead of alphabetically - **docs/getting-started.md** - Made more concise and practical - **docs/community.md** - Clean, focused community guide - **docs/contributing.md** - Clear contribution guidelines - **docs/faq.md** - Comprehensive FAQ with practical answers - **docs/license.md** - Clean license explanation - **docs/css/custom.css** - Fixed CSS syntax and organization ### 🔧 Technical Changes - **mkdocs.yml** - Updated navigation, removed redundant files - **docs/integrations/snowflake.md** - New comprehensive Snowflake guide - **docs/reference/ingest.md** - Added Snowflake references - **Removed files**: changelog.md, release-guide.md, change_management_usage.md, community-projects.md, architecture.md, governance.md, citation.md ### 🎯 Benefits - **Better user experience** - Clean, easy to navigate documentation - **Reduced redundancy** - No duplicate or unnecessary content - **Professional quality** - Enterprise-ready documentation - **Consistent style** - Uniform formatting across all files This commit includes all documentation improvements while maintaining the main branch's stability.
102 lines
3.0 KiB
Markdown
102 lines
3.0 KiB
Markdown
# Getting Started
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## Overview
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**Semantica** is a semantic intelligence layer that bridges the gap between raw data and trustworthy AI. It transforms unstructured data into explainable, auditable knowledge graphs perfect for high-stakes domains.
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### What You Can Build
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- **GraphRAG Systems** - Enhanced retrieval with semantic reasoning
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- **AI Agents** - Trustworthy agents with explainable memory
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- **Knowledge Graphs** - Production-ready semantic databases
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- **Compliance-Ready AI** - Auditable systems with full provenance
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---
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## Installation
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```bash
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pip install semantica
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```
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Or with all features:
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```bash
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pip install semantica[all]
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```
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Verify installation:
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```python
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import semantica
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print(f"Semantica {semantica.__version__} installed!")
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```
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---
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## Quick Start
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```python
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from semantica.semantic_extract import NERExtractor
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from semantica.kg import GraphBuilder
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# Extract entities
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ner = NERExtractor(method="ml", model="en_core_web_sm")
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entities = ner.extract("Apple Inc. was founded by Steve Jobs in 1976.")
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# Build knowledge graph
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kg = GraphBuilder().build({"entities": entities, "relationships": []})
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print(f"Built KG with {len(kg.get('entities', []))} entities")
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```
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**What this does:**
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- Extracts entities (people, organizations, dates) from text
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- Builds a knowledge graph from extracted entities
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- Outputs the number of entities found
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---
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## Core Architecture
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Semantica uses a **modular architecture** - use only what you need:
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### 1️⃣ Input Layer - Data Ingestion
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```python
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from semantica.ingest import FileIngestor
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documents = FileIngestor().ingest_directory("docs/")
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```
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### 2️⃣ Semantic Layer - Intelligence Engine
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```python
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from semantica.semantic_extract import NERExtractor, RelationExtractor
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entities = NERExtractor().extract(text)
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relationships = RelationExtractor().extract(text, entities)
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```
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### 3️⃣ Output Layer - Knowledge Assets
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```python
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from semantica.kg import GraphBuilder
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kg = GraphBuilder().build_graph(entities, relationships)
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```
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---
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## Next Steps
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### 🍳 Interactive Tutorials
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1. **[Welcome to Semantica](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/01_Welcome_to_Semantica.ipynb)** - Complete framework overview
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2. **[Your First Knowledge Graph](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/08_Your_First_Knowledge_Graph.ipynb)** - Hands-on graph building
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3. **[GraphRAG Complete](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/use_cases/advanced_rag/01_GraphRAG_Complete.ipynb)** - Production-ready RAG
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### 📚 Learn More
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- **[Core Concepts](concepts.md)** - Deep dive into knowledge graphs & ontologies
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- **[Cookbook](cookbook.md)** - 14 domain-specific tutorials
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- **[API Reference](reference/core.md)** - Complete technical documentation
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---
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## Need Help?
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- **[💬 Discord Community](https://discord.gg/ggb7vWeP)** - Get help from the community
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- **[🐛 Issues](https://github.com/Hawksight-AI/semantica/issues)** - Report bugs or request features
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- **[📖 Documentation](https://semantica.readthedocs.io/)** - Full documentation site
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