mirror of https://github.com/semantica-agi/semantica.git synced 2026-08-29 04:26:20 +00:00

Files

T

Mohd KaifandClaude Sonnet 4.6 e8d0d7a2cf feat: add 105 real-world context graph tests + update Discord link (#365 )

- Add tests/test_030_context_graph_realworld_extended.py (105 tests, 0 failed)
  - ContextGraph advanced methods: analyze_decision_influence,
    get_decision_insights, trace_decision_causality,
    enforce_decision_policy, find_precedents_by_scenario
  - Research paper citation KG (arXiv provenance: Transformer, BERT,
    GPT-3, GPT-4, LLaMA, PaLM — source URLs as entity provenance)
  - E-commerce KG with pricing / supply-chain causal decision chains
  - GraphBuilderWithProvenance with GitHub + arXiv web-sourced data
  - AlgorithmTrackerWithProvenance: all 10 methods incl. 9 domain-specific
    ones added in 0.3.0-alpha (track_cross_domain_similarity, etc.)
  - Parquet export: entities, relationships, full KG, all codecs (PR #343)
  - ArangoDB AQL export: INSERT content, custom collections (PR #342)
  - Deduplication v2: two-stage prefilter, phonetic blocking, hybrid_v2,
    budget limiting (PR #339); semantic rel dedup v2 (PR #340)
  - AgentMemory: store, retrieve, statistics, conversation history
  - Full E2E workflow: build → decisions → influence → export → dedup
  - Multi-domain precedent search (SEC EDGAR, AMA, M&A news sources)
  - Graph serialization round-trips (research, ecommerce, GitHub domains)
  - Incremental/delta processing simulation (PR #349)
  - All 190 tests (85 existing + 105 new) pass, 0 failed

- Fix Discord invite link — replace expiring links with permanent invite
  across all docs and GitHub files:
  Old: discord.gg/N7WmAuDH, discord.gg/ggb7vWeP
  New: discord.gg/sV34vps5hH (never-expire, unlimited invites)
  Files: README.md, CONTRIBUTING.md, CONTRIBUTORS.md, SUPPORT.md,
         .github/SUPPORT.md, docs/index.md, docs/getting-started.md,
         docs/CodeExamples.md, docs/reference/provenance.md,
         semantica/change_management/change_management_usage.md

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-03-10 00:00:44 +05:30

3.0 KiB

Raw Blame History

Getting Started

Overview

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.

What You Can Build

GraphRAG Systems - Enhanced retrieval with semantic reasoning
AI Agents - Trustworthy agents with explainable memory
Knowledge Graphs - Production-ready semantic databases
Compliance-Ready AI - Auditable systems with full provenance

Installation

pip install semantica

Or with all features:

pip install semantica[all]

Verify installation:

import semantica
print(f"Semantica {semantica.__version__} installed!")

Quick Start

from semantica.semantic_extract import NERExtractor
from semantica.kg import GraphBuilder

# Extract entities
ner = NERExtractor(method="ml", model="en_core_web_sm")
entities = ner.extract("Apple Inc. was founded by Steve Jobs in 1976.")

# Build knowledge graph
kg = GraphBuilder().build({"entities": entities, "relationships": []})
print(f"Built KG with {len(kg.get('entities', []))} entities")

What this does:

Extracts entities (people, organizations, dates) from text
Builds a knowledge graph from extracted entities
Outputs the number of entities found

Core Architecture

Semantica uses a modular architecture - use only what you need:

1️⃣ Input Layer - Data Ingestion

from semantica.ingest import FileIngestor
documents = FileIngestor().ingest_directory("docs/")

2️⃣ Semantic Layer - Intelligence Engine

from semantica.semantic_extract import NERExtractor, RelationExtractor
entities = NERExtractor().extract(text)
relationships = RelationExtractor().extract(text, entities)

3️⃣ Output Layer - Knowledge Assets

from semantica.kg import GraphBuilder
kg = GraphBuilder().build_graph(entities, relationships)

Next Steps

🍳 Interactive Tutorials

Welcome to Semantica - Complete framework overview
Your First Knowledge Graph - Hands-on graph building
GraphRAG Complete - Production-ready RAG

📚 Learn More

Core Concepts - Deep dive into knowledge graphs & ontologies
Cookbook - 14 domain-specific tutorials
API Reference - Complete technical documentation

Need Help?

💬 Discord Community - Get help from the community
🐛 Issues - Report bugs or request features
📖 Documentation - Full documentation site

3.0 KiB Raw Blame History