mirror of
https://github.com/semantica-agi/semantica.git
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docs: replace all CardGroup/Card blocks with animated bullet points across all 50 docs pages (#648)
- Fix What's new → link in Info banner (now a proper <a> tag, always clickable) - Replace 4-stat CardGroup on index with inline premium stats row - Convert every <CardGroup>/<Card> block site-wide to markdown bullet lists: content sections → bold-title bullets with sub-bullets, nav cards → [Title](href) — description - Add cursor-animated list item hover effects to custom.css: green inset left border, subtle background tint, marker color change on hover - Affects index, getting-started, quickstart, concepts, modules, faq, architecture, installation, cookbook, glossary, learning-more, explorer-setup, cli-setup, community, contributing-guide, governance, citation, project-license, all integrations pages, and all 20+ reference module pages
This commit is contained in:
Mohd Kaif
@@ -30,26 +30,12 @@ icon: "clock-rotate-left"
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## What You Get
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<CardGroup cols={2}>
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<Card title="TemporalVersionManager" icon="code-branch">
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Snapshot, diff, rollback, and per-entity audit trail for knowledge graphs.
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</Card>
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<Card title="OntologyVersionManager" icon="sitemap">
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Version control for OWL ontologies with diff and schema migration support.
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</Card>
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<Card title="VersionStorage" icon="database">
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Pluggable backends: `InMemoryVersionStorage` for tests, `SQLiteVersionStorage` for production.
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</Card>
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<Card title="Integrity Verification" icon="shield-check">
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SHA-256 checksums on every snapshot to detect any unauthorised modification.
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</Card>
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<Card title="ChangeLogEntry" icon="list-check">
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Internal metadata validated on every snapshot: ISO 8601 timestamp, email author, and description (max 500 chars).
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</Card>
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<Card title="Version History" icon="file-shield">
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Full tamper-evident version history via `list_versions()` and `diff()` for regulatory review.
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</Card>
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</CardGroup>
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- **TemporalVersionManager** — Snapshot, diff, rollback, and per-entity audit trail for knowledge graphs.
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- **OntologyVersionManager** — Version control for OWL ontologies with diff and schema migration support.
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- **VersionStorage** — Pluggable backends: `InMemoryVersionStorage` for tests, `SQLiteVersionStorage` for production.
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- **Integrity Verification** — SHA-256 checksums on every snapshot to detect any unauthorised modification.
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- **ChangeLogEntry** — Internal metadata validated on every snapshot: ISO 8601 timestamp, email author, and description (max 500 chars).
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- **Version History** — Full tamper-evident version history via `list_versions()` and `diff()` for regulatory review.
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## Typical Workflow
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@@ -364,17 +350,7 @@ for record in history:
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</Accordion>
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</AccordionGroup>
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<CardGroup cols={2}>
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<Card title="Provenance" icon="link" href="provenance">
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W3C PROV-O lineage tracking.
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</Card>
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<Card title="Knowledge Graph" icon="diagram-project" href="kg">
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The graph being versioned.
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</Card>
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<Card title="Export" icon="file-export" href="export">
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Export versioned snapshots.
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</Card>
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<Card title="Conflicts" icon="triangle-exclamation" href="conflicts">
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Detect conflicts introduced between versions.
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</Card>
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</CardGroup>
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- [Provenance](provenance) — W3C PROV-O lineage tracking.
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- [Knowledge Graph](kg) — The graph being versioned.
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- [Export](export) — Export versioned snapshots.
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- [Conflicts](conflicts) — Detect conflicts introduced between versions.
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+10
-34
@@ -45,26 +45,12 @@ Semantica's conflict detection makes disagreements explicit and actionable:
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## What You Get
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<CardGroup cols={2}>
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<Card title="ConflictDetector" icon="magnifying-glass">
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Value, type, and relationship conflict detection across entity and relationship lists.
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</Card>
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<Card title="ConflictResolver" icon="check">
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7 resolution strategies including voting, credibility-weighted, and temporal preference.
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</Card>
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<Card title="SourceTracker" icon="link">
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Track which source each conflicting fact came from, with per-source credibility scores.
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</Card>
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<Card title="ConflictAnalyzer" icon="chart-line">
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Pattern analysis, severity grouping, source-level statistics, and trend identification.
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</Card>
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<Card title="InvestigationGuideGenerator" icon="list-check">
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Auto-generate step-by-step investigation checklists for human and expert review.
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</Card>
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<Card title="Convenience Functions" icon="bolt">
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`detect_conflicts()` and `resolve_conflicts()` for one-call workflows.
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</Card>
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</CardGroup>
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- **ConflictDetector** — Value, type, and relationship conflict detection across entity and relationship lists.
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- **ConflictResolver** — 7 resolution strategies including voting, credibility-weighted, and temporal preference.
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- **SourceTracker** — Track which source each conflicting fact came from, with per-source credibility scores.
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- **ConflictAnalyzer** — Pattern analysis, severity grouping, source-level statistics, and trend identification.
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- **InvestigationGuideGenerator** — Auto-generate step-by-step investigation checklists for human and expert review.
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- **Convenience Functions** — `detect_conflicts()` and `resolve_conflicts()` for one-call workflows.
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## Quick Start
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@@ -464,17 +450,7 @@ class InvestigationStep:
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</Accordion>
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</AccordionGroup>
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<CardGroup cols={2}>
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<Card title="Deduplication" icon="copy" href="deduplication">
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Resolve duplicate entities before conflict detection.
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</Card>
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<Card title="Ontology" icon="sitemap" href="ontology">
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Logical conflicts use SHACL shapes and ontology axioms.
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</Card>
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<Card title="Provenance" icon="link" href="provenance">
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Track which source each conflicting fact came from.
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</Card>
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<Card title="Knowledge Graph" icon="diagram-project" href="kg">
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The graph being checked for conflicts.
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</Card>
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</CardGroup>
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- [Deduplication](deduplication) — Resolve duplicate entities before conflict detection.
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- [Ontology](ontology) — Logical conflicts use SHACL shapes and ontology axioms.
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- [Provenance](provenance) — Track which source each conflicting fact came from.
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- [Knowledge Graph](kg) — The graph being checked for conflicts.
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+30
-64
@@ -29,48 +29,30 @@ icon: "brain"
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## What You Get
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<CardGroup cols={2}>
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<Card title="AgentContext" icon="brain">
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- Memory, decision tracking, and graph-backed retrieval behind one API
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- Conversation history and checkpoint diffing
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- Persist and restore full context state to disk
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</Card>
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<Card title="ContextGraph" icon="diagram-project">
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- Thread-safe in-memory knowledge graph
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- PageRank, centrality, community detection, temporal validity
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- Cross-graph navigation and link traversal
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</Card>
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<Card title="AgentMemory" icon="database">
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- Embedding-backed memory with retention policy
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- LRU eviction at configurable `max_memory_size`
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- Per-conversation history isolation
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</Card>
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<Card title="DecisionRecorder" icon="list-check">
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- Records decisions with causal chains and confidence scores
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- Temporal validity windows (`valid_from` / `valid_until`)
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- Cross-system context capture on every decision
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</Card>
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<Card title="PolicyEngine" icon="shield-check">
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- Versioned policy storage in the knowledge graph
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- Compliance checking against recorded decisions
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- Policy exception tracking with approver audit trail
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</Card>
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<Card title="EntityLinker" icon="link">
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- Maps entity text to stable URIs
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- Creates typed links between entity IDs
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- Prevents "Apple", "Apple Inc.", "AAPL" becoming separate nodes
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</Card>
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<Card title="ContextRetriever" icon="magnifying-glass">
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- Fuses vector similarity, graph traversal, and agent memory
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- Richer context than pure vector search
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- Configurable `hybrid_alpha` and expansion hops
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</Card>
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<Card title="CausalChainAnalyzer" icon="arrow-trend-up">
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- Traces upstream causes and downstream effects of any decision
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- Explainability paths with relationship types
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- Configurable depth and direction
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</Card>
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</CardGroup>
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- **AgentContext** — Memory, decision tracking, and graph-backed retrieval behind one API
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- Conversation history and checkpoint diffing
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- Persist and restore full context state to disk
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- **ContextGraph** — Thread-safe in-memory knowledge graph
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- PageRank, centrality, community detection, temporal validity
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- Cross-graph navigation and link traversal
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- **AgentMemory** — Embedding-backed memory with retention policy
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- LRU eviction at configurable `max_memory_size`
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- Per-conversation history isolation
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- **DecisionRecorder** — Records decisions with causal chains and confidence scores
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- Temporal validity windows (`valid_from` / `valid_until`)
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- Cross-system context capture on every decision
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- **PolicyEngine** — Versioned policy storage in the knowledge graph
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- Compliance checking against recorded decisions
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- Policy exception tracking with approver audit trail
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- **EntityLinker** — Maps entity text to stable URIs
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- Creates typed links between entity IDs
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- Prevents "Apple", "Apple Inc.", "AAPL" becoming separate nodes
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- **ContextRetriever** — Fuses vector similarity, graph traversal, and agent memory
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- Richer context than pure vector search
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- Configurable `hybrid_alpha` and expansion hops
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- **CausalChainAnalyzer** — Traces upstream causes and downstream effects of any decision
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- Explainability paths with relationship types
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- Configurable depth and direction
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## Quick Start
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@@ -889,26 +871,10 @@ class EntityLink:
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</Tab>
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</Tabs>
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<CardGroup cols={2}>
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<Card title="Vector Store" icon="database" href="vector_store">
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Embedding storage backend for memory retrieval.
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</Card>
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<Card title="Knowledge Graph" icon="diagram-project" href="kg">
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Graph algorithms and analytics used inside ContextGraph.
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</Card>
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<Card title="Reasoning" icon="microchip" href="reasoning">
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Logical inference layered on top of context.
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</Card>
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<Card title="Provenance" icon="link" href="provenance">
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W3C PROV-O lineage for every stored fact.
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</Card>
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</CardGroup>
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- [Vector Store](vector_store) — Embedding storage backend for memory retrieval.
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- [Knowledge Graph](kg) — Graph algorithms and analytics used inside ContextGraph.
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- [Reasoning](reasoning) — Logical inference layered on top of context.
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- [Provenance](provenance) — W3C PROV-O lineage for every stored fact.
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<CardGroup cols={2}>
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<Card title="Context Module" icon="book-open" href="https://github.com/semantica-agi/semantica/blob/main/cookbook/introduction/19_Context_Module.ipynb">
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Memory and decision tracking · Intermediate
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</Card>
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<Card title="Advanced Context Engineering" icon="flask" href="https://github.com/semantica-agi/semantica/blob/main/cookbook/advanced/11_Advanced_Context_Engineering.ipynb">
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Production FAISS + Neo4j setup · Advanced
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</Card>
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</CardGroup>
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- [Context Module](https://github.com/semantica-agi/semantica/blob/main/cookbook/introduction/19_Context_Module.ipynb) — Memory and decision tracking · Intermediate
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- [Advanced Context Engineering](https://github.com/semantica-agi/semantica/blob/main/cookbook/advanced/11_Advanced_Context_Engineering.ipynb) — Production FAISS + Neo4j setup · Advanced
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+8
-28
@@ -18,20 +18,10 @@ icon: "gear"
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## What You Get
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<CardGroup cols={2}>
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<Card title="Semantica" icon="arrows-turn-to-dots">
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High-level orchestrator: coordinates the full KG construction pipeline from a single `config.yaml`. Entry point for application-level deployments.
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</Card>
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<Card title="ConfigManager" icon="sliders">
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YAML config with deep-merge, `SEMANTICA_` env var overrides, and dot-notation nested key access. Keeps secrets out of source files.
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</Card>
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<Card title="LifecycleManager" icon="circle-play">
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Ordered startup/shutdown hooks, health monitoring, and a 6-state machine. Essential for long-running services like FastAPI apps.
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</Card>
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<Card title="PluginRegistry" icon="plug">
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Register custom ingestors, parsers, exporters, or any component. Load them by name at runtime: no imports required.
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</Card>
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</CardGroup>
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- **Semantica** — High-level orchestrator: coordinates the full KG construction pipeline from a single `config.yaml`. Entry point for application-level deployments.
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- **ConfigManager** — YAML config with deep-merge, `SEMANTICA_` env var overrides, and dot-notation nested key access. Keeps secrets out of source files.
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||||
- **LifecycleManager** — Ordered startup/shutdown hooks, health monitoring, and a 6-state machine. Essential for long-running services like FastAPI apps.
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- **PluginRegistry** — Register custom ingestors, parsers, exporters, or any component. Load them by name at runtime: no imports required.
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## Exported Classes
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@@ -236,17 +226,7 @@ result = build_knowledge_base(sources=["doc.pdf"], method="fast")
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Use `Semantica` and `LifecycleManager` only when building a long-running application (e.g. a FastAPI service) that needs ordered startup, health checks, and graceful shutdown. For scripts and notebooks, use individual modules directly.
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</Tip>
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<CardGroup cols={2}>
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<Card title="Pipeline" icon="arrows-turn-to-dots" href="pipeline">
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Pipeline execution and step orchestration.
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</Card>
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<Card title="Utils" icon="wrench" href="utils">
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Shared utilities used by Core internally.
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</Card>
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<Card title="Getting Started" icon="play" href="../getting-started">
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Learn the basics before using Core.
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</Card>
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<Card title="LLMs" icon="microchip" href="llms">
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Configure LLM providers via ConfigManager.
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</Card>
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</CardGroup>
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- [Pipeline](pipeline) — Pipeline execution and step orchestration.
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- [Utils](utils) — Shared utilities used by Core internally.
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- [Getting Started](../getting-started) — Learn the basics before using Core.
|
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- [LLMs](llms) — Configure LLM providers via ConfigManager.
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|
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@@ -30,26 +30,12 @@ icon: "copy"
|
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|
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## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="DuplicateDetector" icon="copy">
|
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Pairwise, batch, incremental, and group detection modes. Returns scored candidates with reasons.
|
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</Card>
|
||||
<Card title="EntityMerger" icon="code-merge">
|
||||
Five merge strategies: keep first, last, most complete, highest confidence, or merge all fields.
|
||||
</Card>
|
||||
<Card title="SimilarityCalculator" icon="equals">
|
||||
Multi-factor scoring across string edit distance, property overlap, relationship overlap, and embeddings.
|
||||
</Card>
|
||||
<Card title="ClusterBuilder" icon="diagram-project">
|
||||
Union-Find and hierarchical clustering for batch deduplication at scale: handles 100k+ entity sets.
|
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</Card>
|
||||
<Card title="MergeStrategyManager" icon="sliders">
|
||||
Per-property merge rules with conflict resolution priorities. Apply different strategies to different fields.
|
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</Card>
|
||||
<Card title="v2 Strategies" icon="bolt">
|
||||
`blocking_v2`, `hybrid_v2`, `semantic_v2`: up to 7× faster than v1 for large entity sets.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **DuplicateDetector** — Pairwise, batch, incremental, and group detection modes. Returns scored candidates with reasons.
|
||||
- **EntityMerger** — Five merge strategies: keep first, last, most complete, highest confidence, or merge all fields.
|
||||
- **SimilarityCalculator** — Multi-factor scoring across string edit distance, property overlap, relationship overlap, and embeddings.
|
||||
- **ClusterBuilder** — Union-Find and hierarchical clustering for batch deduplication at scale: handles 100k+ entity sets.
|
||||
- **MergeStrategyManager** — Per-property merge rules with conflict resolution priorities. Apply different strategies to different fields.
|
||||
- **v2 Strategies** — `blocking_v2`, `hybrid_v2`, `semantic_v2`: up to 7× faster than v1 for large entity sets.
|
||||
|
||||
|
||||
## Getting Started
|
||||
@@ -451,17 +437,7 @@ result = calculate_similarity(entity_a, entity_b, method="drug_name")
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Conflicts" icon="triangle-exclamation" href="conflicts">
|
||||
Detect value conflicts between non-duplicate entities.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
GraphBuilder uses deduplication during construction.
|
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</Card>
|
||||
<Card title="Normalize" icon="broom" href="normalize">
|
||||
Normalize entity names before deduplication.
|
||||
</Card>
|
||||
<Card title="Provenance" icon="link" href="provenance">
|
||||
Track merged entity lineage.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Conflicts](conflicts) — Detect value conflicts between non-duplicate entities.
|
||||
- [Knowledge Graph](kg) — GraphBuilder uses deduplication during construction.
|
||||
- [Normalize](normalize) — Normalize entity names before deduplication.
|
||||
- [Provenance](provenance) — Track merged entity lineage.
|
||||
|
||||
@@ -41,26 +41,12 @@ Semantica uses embeddings for:
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="EmbeddingGenerator" icon="vector-square">
|
||||
Main entry point: provider-agnostic, handles batching automatically across all backends.
|
||||
</Card>
|
||||
<Card title="TextEmbedder" icon="text-size">
|
||||
Text-specific with automatic batching and progress tracking. Default method is FastEmbed.
|
||||
</Card>
|
||||
<Card title="GraphEmbeddingManager" icon="diagram-project">
|
||||
Node and edge embeddings for graph databases: Neo4j, NetworkX, FalkorDB.
|
||||
</Card>
|
||||
<Card title="VectorEmbeddingManager" icon="database">
|
||||
Prepare, normalize, and format embeddings for FAISS, Weaviate, Qdrant, and Milvus.
|
||||
</Card>
|
||||
<Card title="Provider Stores" icon="plug">
|
||||
`OpenAIStore`, `BGEStore`, `FastEmbedStore`, and `ProviderStoreFactory`.
|
||||
</Card>
|
||||
<Card title="Pooling Strategies" icon="layer-group">
|
||||
Mean, Max, CLS, Attention, and Hierarchical: control token-to-vector aggregation.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **EmbeddingGenerator** — Main entry point: provider-agnostic, handles batching automatically across all backends.
|
||||
- **TextEmbedder** — Text-specific with automatic batching and progress tracking. Default method is FastEmbed.
|
||||
- **GraphEmbeddingManager** — Node and edge embeddings for graph databases: Neo4j, NetworkX, FalkorDB.
|
||||
- **VectorEmbeddingManager** — Prepare, normalize, and format embeddings for FAISS, Weaviate, Qdrant, and Milvus.
|
||||
- **Provider Stores** — `OpenAIStore`, `BGEStore`, `FastEmbedStore`, and `ProviderStoreFactory`.
|
||||
- **Pooling Strategies** — Mean, Max, CLS, Attention, and Hierarchical: control token-to-vector aggregation.
|
||||
|
||||
## Provider Setup
|
||||
|
||||
@@ -633,17 +619,7 @@ providers = check_available_providers()
|
||||
# → {"sentence_transformers": True, "fastembed": True, "openai": False}
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Vector Store" icon="database" href="vector_store">
|
||||
Store and search the generated embeddings.
|
||||
</Card>
|
||||
<Card title="Split" icon="scissors" href="split">
|
||||
Chunk text before embedding for better retrieval quality.
|
||||
</Card>
|
||||
<Card title="KG Module" icon="diagram-project" href="kg">
|
||||
Distance Intelligence uses graph embeddings for semantic neighbourhoods.
|
||||
</Card>
|
||||
<Card title="Deduplication" icon="copy" href="deduplication">
|
||||
Semantic deduplication uses embedding distance for entity resolution.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Vector Store](vector_store) — Store and search the generated embeddings.
|
||||
- [Split](split) — Chunk text before embedding for better retrieval quality.
|
||||
- [KG Module](kg) — Distance Intelligence uses graph embeddings for semantic neighbourhoods.
|
||||
- [Deduplication](deduplication) — Semantic deduplication uses embedding distance for entity resolution.
|
||||
|
||||
+4
-14
@@ -58,17 +58,7 @@ print("Relation coverage: ", report["relation_completeness"]["relation_coverage"
|
||||
| `suggestions` | `List[str]` | Improvement suggestions |
|
||||
| `metrics` | `dict` | Detailed sub-metrics |
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Extraction module.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
Graph quality assessment.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Pipeline performance metrics.
|
||||
</Card>
|
||||
<Card title="Ontology Evaluator" icon="sitemap" href="ontology">
|
||||
Available now for ontology quality metrics.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Semantic Extract](semantic_extract) — Extraction module.
|
||||
- [Knowledge Graph](kg) — Graph quality assessment.
|
||||
- [Pipeline](pipeline) — Pipeline performance metrics.
|
||||
- [Ontology Evaluator](ontology) — Available now for ontology quality metrics.
|
||||
|
||||
+10
-34
@@ -115,26 +115,12 @@ EXPLORER_CORS_ORIGINS="http://myapp.example.com" \
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Graph Explorer" icon="diagram-project">
|
||||
Interactive node/edge search, path finding, and neighborhood expansion. Indexed search at 0.004ms on 118k-node graphs.
|
||||
</Card>
|
||||
<Card title="Ontology Hub" icon="sitemap">
|
||||
SKOS vocabulary management, SHACL shape generation and validation, ontology alignment, health dashboard, and versioning.
|
||||
</Card>
|
||||
<Card title="Analytics" icon="chart-line">
|
||||
Degree centrality, community detection, connectivity analysis, graph validation, and distance matrices.
|
||||
</Card>
|
||||
<Card title="REST API" icon="code">
|
||||
All features available as a REST API: fully documented at `/docs`.
|
||||
</Card>
|
||||
<Card title="WebSocket Updates" icon="bolt">
|
||||
Real-time graph mutation events streamed over WebSocket at `/ws/graph-updates`.
|
||||
</Card>
|
||||
<Card title="CLI Launcher" icon="terminal">
|
||||
`semantica-explorer --graph my_graph.json` for instant local startup.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **Graph Explorer** — Interactive node/edge search, path finding, and neighborhood expansion. Indexed search at 0.004ms on 118k-node graphs.
|
||||
- **Ontology Hub** — SKOS vocabulary management, SHACL shape generation and validation, ontology alignment, health dashboard, and versioning.
|
||||
- **Analytics** — Degree centrality, community detection, connectivity analysis, graph validation, and distance matrices.
|
||||
- **REST API** — All features available as a REST API: fully documented at `/docs`.
|
||||
- **WebSocket Updates** — Real-time graph mutation events streamed over WebSocket at `/ws/graph-updates`.
|
||||
- **CLI Launcher** — `semantica-explorer --graph my_graph.json` for instant local startup.
|
||||
|
||||
## Features
|
||||
|
||||
@@ -412,17 +398,7 @@ Semantic neighborhood requires node embeddings stored in node properties (keys `
|
||||
**Session state lost after restart**
|
||||
Session state is in-memory only. Use `POST /api/export` to save a JSON snapshot before shutting down.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
Build and save the ContextGraph that Explorer loads.
|
||||
</Card>
|
||||
<Card title="Ontology" icon="sitemap" href="ontology">
|
||||
Programmatic ontology management and SHACL generation.
|
||||
</Card>
|
||||
<Card title="Visualization" icon="chart-bar" href="visualization">
|
||||
Programmatic graph rendering without the Explorer server.
|
||||
</Card>
|
||||
<Card title="Export" icon="file-export" href="export">
|
||||
Export to RDF, Parquet, and other formats without launching a server.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Context](context) — Build and save the ContextGraph that Explorer loads.
|
||||
- [Ontology](ontology) — Programmatic ontology management and SHACL generation.
|
||||
- [Visualization](visualization) — Programmatic graph rendering without the Explorer server.
|
||||
- [Export](export) — Export to RDF, Parquet, and other formats without launching a server.
|
||||
|
||||
@@ -381,17 +381,7 @@ The `export_csv` convenience function delegates to `CSVExporter.export()`. For p
|
||||
**Match your export format to your consumer.** Neo4j → `cypher`; ArangoDB → `aql`; Gephi/yEd → `graphml` or `gexf`; semantic web tools → `turtle` or `json-ld`; analytics pipelines → `parquet`; zero-copy IPC → `arrow`.
|
||||
</Tip>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Triplet Store" icon="table" href="triplet_store">
|
||||
Store RDF exports in a SPARQL-queryable backend.
|
||||
</Card>
|
||||
<Card title="Ontology" icon="sitemap" href="ontology">
|
||||
Export OWL ontologies.
|
||||
</Card>
|
||||
<Card title="Provenance" icon="link" href="provenance">
|
||||
Include provenance metadata in RDF exports.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Add export as a final pipeline step.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Triplet Store](triplet_store) — Store RDF exports in a SPARQL-queryable backend.
|
||||
- [Ontology](ontology) — Export OWL ontologies.
|
||||
- [Provenance](provenance) — Include provenance metadata in RDF exports.
|
||||
- [Pipeline](pipeline) — Add export as a final pipeline step.
|
||||
|
||||
@@ -28,38 +28,24 @@ icon: "server"
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="GraphStore" icon="server">
|
||||
- Unified API across Neo4j, FalkorDB, Apache AGE, Amazon Neptune
|
||||
- Context manager support for automatic connection cleanup
|
||||
- `create_nodes()` for bulk loading: faster than individual calls
|
||||
</Card>
|
||||
<Card title="QueryEngine" icon="magnifying-glass">
|
||||
- Parameterized Cypher construction prevents injection attacks
|
||||
- Optional in-process result caching with `use_cache=True`
|
||||
- `clear_cache()` on writes, toggle with `enable_cache()` / `disable_cache()`
|
||||
</Card>
|
||||
<Card title="GraphAnalytics" icon="chart-line">
|
||||
- Degree centrality ordered by degree DESC
|
||||
- Connected component assignment
|
||||
- Shortest path between nodes, neighbor traversal up to N hops
|
||||
</Card>
|
||||
<Card title="Bulk Operations" icon="layer-group">
|
||||
- `create_nodes(list)`: one round-trip for many nodes
|
||||
- `create_relationship()` with typed properties
|
||||
- `delete_node(detach=True)` removes all connected relationships
|
||||
</Card>
|
||||
<Card title="Schema Management" icon="table">
|
||||
- `create_index(label, property_name=)`: makes MATCH queries orders-of-magnitude faster
|
||||
- `get_stats()`: node counts, edge counts, type breakdown
|
||||
- Create indexes before bulk loading for best performance
|
||||
</Card>
|
||||
<Card title="Path Traversal" icon="route">
|
||||
- `shortest_path()` returns `length`, `nodes`, `relationships`
|
||||
- `get_neighbors()` with direction and depth control
|
||||
- Cross-backend path traversal via the unified API
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **GraphStore** — Unified API across Neo4j, FalkorDB, Apache AGE, Amazon Neptune
|
||||
- Context manager support for automatic connection cleanup
|
||||
- `create_nodes()` for bulk loading: faster than individual calls
|
||||
- **QueryEngine** — Parameterized Cypher construction prevents injection attacks
|
||||
- Optional in-process result caching with `use_cache=True`
|
||||
- `clear_cache()` on writes, toggle with `enable_cache()` / `disable_cache()`
|
||||
- **GraphAnalytics** — Degree centrality ordered by degree DESC
|
||||
- Connected component assignment
|
||||
- Shortest path between nodes, neighbor traversal up to N hops
|
||||
- **Bulk Operations** — `create_nodes(list)`: one round-trip for many nodes
|
||||
- `create_relationship()` with typed properties
|
||||
- `delete_node(detach=True)` removes all connected relationships
|
||||
- **Schema Management** — `create_index(label, property_name=)`: makes MATCH queries orders-of-magnitude faster
|
||||
- `get_stats()`: node counts, edge counts, type breakdown
|
||||
- Create indexes before bulk loading for best performance
|
||||
- **Path Traversal** — `shortest_path()` returns `length`, `nodes`, `relationships`
|
||||
- `get_neighbors()` with direction and depth control
|
||||
- Cross-backend path traversal via the unified API
|
||||
|
||||
|
||||
## Getting Started
|
||||
@@ -517,17 +503,7 @@ stats = store.get_stats()
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="KG Module" icon="diagram-project" href="kg">
|
||||
Build the graph before persisting it.
|
||||
</Card>
|
||||
<Card title="Triplet Store" icon="table" href="triplet_store">
|
||||
RDF triple store for semantic web and SPARQL queries.
|
||||
</Card>
|
||||
<Card title="Visualization" icon="chart-bar" href="visualization">
|
||||
Visualize graphs stored in any backend.
|
||||
</Card>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
AgentContext uses GraphStore for memory retrieval.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [KG Module](kg) — Build the graph before persisting it.
|
||||
- [Triplet Store](triplet_store) — RDF triple store for semantic web and SPARQL queries.
|
||||
- [Visualization](visualization) — Visualize graphs stored in any backend.
|
||||
- [Context](context) — AgentContext uses GraphStore for memory retrieval.
|
||||
|
||||
@@ -625,17 +625,7 @@ from semantica.ingest import ingest_file
|
||||
result = ingest_file("source_path", method="my_format")
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Parse" icon="file-lines" href="parse">
|
||||
Parse raw sources into structured text and tables.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Orchestrate ingest as the first pipeline step.
|
||||
</Card>
|
||||
<Card title="Snowflake Integration" icon="snowflake" href="../integrations/snowflake">
|
||||
Snowflake-specific setup and authentication guide.
|
||||
</Card>
|
||||
<Card title="Provenance" icon="link" href="provenance">
|
||||
Track lineage from ingest through to inference.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Parse](parse) — Parse raw sources into structured text and tables.
|
||||
- [Pipeline](pipeline) — Orchestrate ingest as the first pipeline step.
|
||||
- [Snowflake Integration](../integrations/snowflake) — Snowflake-specific setup and authentication guide.
|
||||
- [Provenance](provenance) — Track lineage from ingest through to inference.
|
||||
|
||||
+4
-14
@@ -316,20 +316,10 @@ kg:
|
||||
default_validity: infinite
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Graph Store" icon="server" href="graph_store">
|
||||
Persist graphs in Neo4j, FalkorDB, or Apache AGE.
|
||||
</Card>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Source of entities and relationships fed to GraphBuilder.
|
||||
</Card>
|
||||
<Card title="Visualization" icon="chart-bar" href="visualization">
|
||||
Visualize knowledge graphs interactively.
|
||||
</Card>
|
||||
<Card title="Conflicts" icon="triangle-exclamation" href="conflicts">
|
||||
Conflict detection and resolution.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Graph Store](graph_store) — Persist graphs in Neo4j, FalkorDB, or Apache AGE.
|
||||
- [Semantic Extract](semantic_extract) — Source of entities and relationships fed to GraphBuilder.
|
||||
- [Visualization](visualization) — Visualize knowledge graphs interactively.
|
||||
- [Conflicts](conflicts) — Conflict detection and resolution.
|
||||
|
||||
### Cookbooks
|
||||
|
||||
|
||||
+4
-14
@@ -439,17 +439,7 @@ extractor = NERExtractor(
|
||||
)
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Use LLMs for NER and relation extraction.
|
||||
</Card>
|
||||
<Card title="Agno Integration" icon="robot" href="../integrations/agno">
|
||||
LLM providers in Agno multi-agent teams.
|
||||
</Card>
|
||||
<Card title="Reasoning" icon="brain" href="reasoning">
|
||||
LLM-backed deductive and abductive reasoning.
|
||||
</Card>
|
||||
<Card title="Context" icon="diagram-project" href="context">
|
||||
GraphRAG uses LLMs for reasoning over knowledge graphs.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Semantic Extract](semantic_extract) — Use LLMs for NER and relation extraction.
|
||||
- [Agno Integration](../integrations/agno) — LLM providers in Agno multi-agent teams.
|
||||
- [Reasoning](reasoning) — LLM-backed deductive and abductive reasoning.
|
||||
- [Context](context) — GraphRAG uses LLMs for reasoning over knowledge graphs.
|
||||
|
||||
@@ -40,26 +40,12 @@ python -m semantica.mcp_server
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="12 MCP Tools" icon="wrench">
|
||||
Extract entities, extract relations, record decisions, query decisions, find precedents, trace causal chains, add entities, add relationships, run analytics, summarise graph, run reasoning, export graph.
|
||||
</Card>
|
||||
<Card title="3 Readable Resources" icon="book-open">
|
||||
Live graph JSON (`semantica://graph/summary`), decision list, and schema/version info: readable by any MCP client.
|
||||
</Card>
|
||||
<Card title="Zero Infrastructure" icon="bolt">
|
||||
Runs over stdio: no server, no port, no Docker required. One config block to activate in any MCP client.
|
||||
</Card>
|
||||
<Card title="Persistent Graphs" icon="database">
|
||||
Point `SEMANTICA_KG_PATH` at a saved graph file to reload it automatically on every server startup.
|
||||
</Card>
|
||||
<Card title="Decision Intelligence" icon="brain">
|
||||
Record decisions, find precedents via hybrid similarity search, and trace causal chains across agent runs.
|
||||
</Card>
|
||||
<Card title="REST Alternative" icon="globe">
|
||||
The [Explorer](explorer) module offers a full HTTP API and browser dashboard if you prefer programmatic access.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **12 MCP Tools** — Extract entities, extract relations, record decisions, query decisions, find precedents, trace causal chains, add entities, add relationships, run analytics, summarise graph, run reasoning, export graph.
|
||||
- **3 Readable Resources** — Live graph JSON (`semantica://graph/summary`), decision list, and schema/version info: readable by any MCP client.
|
||||
- **Zero Infrastructure** — Runs over stdio: no server, no port, no Docker required. One config block to activate in any MCP client.
|
||||
- **Persistent Graphs** — Point `SEMANTICA_KG_PATH` at a saved graph file to reload it automatically on every server startup.
|
||||
- **Decision Intelligence** — Record decisions, find precedents via hybrid similarity search, and trace causal chains across agent runs.
|
||||
- **REST Alternative** — The [Explorer](explorer) module offers a full HTTP API and browser dashboard if you prefer programmatic access.
|
||||
|
||||
## Installation
|
||||
|
||||
@@ -459,17 +445,7 @@ The MCP server exposes three readable resources:
|
||||
| `semantica://decisions/list` | All recorded decisions (up to 50) |
|
||||
| `semantica://schema/info` | Server version and available tools |
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
The ContextGraph that the MCP server operates on.
|
||||
</Card>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
NER and relation extraction powering the MCP tools.
|
||||
</Card>
|
||||
<Card title="Reasoning" icon="microchip" href="reasoning">
|
||||
Forward-chaining engine behind run_reasoning.
|
||||
</Card>
|
||||
<Card title="Agno Integration" icon="robot" href="../integrations/agno">
|
||||
Use Semantica inside Agno multi-agent teams.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Context](context) — The ContextGraph that the MCP server operates on.
|
||||
- [Semantic Extract](semantic_extract) — NER and relation extraction powering the MCP tools.
|
||||
- [Reasoning](reasoning) — Forward-chaining engine behind run_reasoning.
|
||||
- [Agno Integration](../integrations/agno) — Use Semantica inside Agno multi-agent teams.
|
||||
|
||||
@@ -584,17 +584,7 @@ normalized = normalize_text("Apple Inc.", method="expand_suffixes")
|
||||
# → "Apple Incorporated"
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Parse" icon="file-lines" href="parse">
|
||||
Parse documents before normalization.
|
||||
</Card>
|
||||
<Card title="Split" icon="scissors" href="split">
|
||||
Chunk normalized text for embedding.
|
||||
</Card>
|
||||
<Card title="Deduplication" icon="copy" href="deduplication">
|
||||
Resolve duplicate entities after normalization.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Include normalization as a named pipeline step.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Parse](parse) — Parse documents before normalization.
|
||||
- [Split](split) — Chunk normalized text for embedding.
|
||||
- [Deduplication](deduplication) — Resolve duplicate entities after normalization.
|
||||
- [Pipeline](pipeline) — Include normalization as a named pipeline step.
|
||||
|
||||
@@ -286,17 +286,7 @@ ontology_data = ingest_ontology("schema.jsonld") # JSON-LD
|
||||
Ontology versioning (`VersionManager`, `OntologyVersion`) has moved to `semantica.change_management`. Import from there: `from semantica.change_management import VersionManager`.
|
||||
</Note>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Reasoning" icon="microchip" href="reasoning">
|
||||
Apply inference rules over ontology axioms.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
The graph being modeled by the ontology.
|
||||
</Card>
|
||||
<Card title="Export" icon="file-export" href="export">
|
||||
Export ontologies as RDF, OWL, or JSON-LD.
|
||||
</Card>
|
||||
<Card title="Conflicts" icon="triangle-exclamation" href="conflicts">
|
||||
Detect ontology constraint violations.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Reasoning](reasoning) — Apply inference rules over ontology axioms.
|
||||
- [Knowledge Graph](kg) — The graph being modeled by the ontology.
|
||||
- [Export](export) — Export ontologies as RDF, OWL, or JSON-LD.
|
||||
- [Conflicts](conflicts) — Detect ontology constraint violations.
|
||||
|
||||
+4
-14
@@ -297,17 +297,7 @@ for source in sources:
|
||||
Docling is an optional dependency. If `docling` is not installed, `DoclingParser` raises an `ImportError` with installation instructions: `pip install docling`. `DocumentParser` is always available and requires no extras.
|
||||
</Note>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Ingest" icon="database" href="ingest">
|
||||
Load files before parsing.
|
||||
</Card>
|
||||
<Card title="Split" icon="scissors" href="split">
|
||||
Chunk parsed text for embedding and extraction.
|
||||
</Card>
|
||||
<Card title="Docling Integration" icon="file-pdf" href="../integrations/docling">
|
||||
Full Docling integration setup guide.
|
||||
</Card>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Extract entities and relations from parsed text.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Ingest](ingest) — Load files before parsing.
|
||||
- [Split](split) — Chunk parsed text for embedding and extraction.
|
||||
- [Docling Integration](../integrations/docling) — Full Docling integration setup guide.
|
||||
- [Semantic Extract](semantic_extract) — Extract entities and relations from parsed text.
|
||||
|
||||
+30
-69
@@ -29,26 +29,12 @@ icon: "gear"
|
||||
|
||||
You could wire Semantica modules together with plain Python code. Pipelines add:
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Retry and failure handling" icon="arrow-rotate-right">
|
||||
A single bad document doesn't crash a 10,000-document run.
|
||||
</Card>
|
||||
<Card title="Parallelism" icon="bolt">
|
||||
Run extraction across multiple workers with one parameter.
|
||||
</Card>
|
||||
<Card title="Progress tracking" icon="chart-line">
|
||||
tqdm console bar or WebSocket streaming to Explorer.
|
||||
</Card>
|
||||
<Card title="Reproducibility" icon="floppy-disk">
|
||||
Save the exact pipeline configuration to YAML and replay on any machine.
|
||||
</Card>
|
||||
<Card title="Delta mode" icon="code-compare">
|
||||
On re-runs, only process documents that changed since the last run.
|
||||
</Card>
|
||||
<Card title="Validation" icon="shield-check">
|
||||
Catch misconfigured steps and dependency cycles before they fail mid-run.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **Retry and failure handling** — A single bad document doesn't crash a 10,000-document run.
|
||||
- **Parallelism** — Run extraction across multiple workers with one parameter.
|
||||
- **Progress tracking** — tqdm console bar or WebSocket streaming to Explorer.
|
||||
- **Reproducibility** — Save the exact pipeline configuration to YAML and replay on any machine.
|
||||
- **Delta mode** — On re-runs, only process documents that changed since the last run.
|
||||
- **Validation** — Catch misconfigured steps and dependency cycles before they fail mid-run.
|
||||
|
||||
<Note>
|
||||
Use plain module calls for quick scripts and notebooks. Use pipelines for anything you run repeatedly, at scale, or in production.
|
||||
@@ -322,48 +308,33 @@ manager = PipelineTemplateManager()
|
||||
|
||||
The `create_pipeline_from_template(name)` method returns a configured `PipelineBuilder`. Call `.build(pipeline_name)` on it to produce a runnable `Pipeline`.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="document_processing" icon="diagram-project">
|
||||
**Ingest → Parse → Normalize → Extract → Embed → Build KG**
|
||||
- **document_processing** — **Ingest → Parse → Normalize → Extract → Embed → Build KG** — Complete document processing from ingestion to knowledge graph.
|
||||
|
||||
Complete document processing from ingestion to knowledge graph.
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("document_processing")
|
||||
pipeline = builder.build("doc_pipeline")
|
||||
```
|
||||
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("document_processing")
|
||||
pipeline = builder.build("doc_pipeline")
|
||||
```
|
||||
</Card>
|
||||
<Card title="rag_pipeline" icon="magnifying-glass">
|
||||
**Ingest → Chunk → Embed → Store Vectors**
|
||||
- **rag_pipeline** — **Ingest → Chunk → Embed → Store Vectors** — RAG pipeline for question answering: builds a vector-indexed store.
|
||||
|
||||
RAG pipeline for question answering: builds a vector-indexed store.
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("rag_pipeline")
|
||||
pipeline = builder.build("rag_pipeline")
|
||||
```
|
||||
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("rag_pipeline")
|
||||
pipeline = builder.build("rag_pipeline")
|
||||
```
|
||||
</Card>
|
||||
<Card title="kg_construction" icon="chart-bar">
|
||||
**Ingest → Extract Entities → Extract Relations → Dedup → Resolve → Build Graph**
|
||||
- **kg_construction** — **Ingest → Extract Entities → Extract Relations → Dedup → Resolve → Build Graph** — Knowledge graph construction from multiple sources.
|
||||
|
||||
Knowledge graph construction from multiple sources.
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("kg_construction")
|
||||
pipeline = builder.build("kg_pipeline")
|
||||
```
|
||||
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("kg_construction")
|
||||
pipeline = builder.build("kg_pipeline")
|
||||
```
|
||||
</Card>
|
||||
<Card title="ontology_generation" icon="shield-check">
|
||||
**Extract Concepts → Infer Classes → Infer Properties → Generate OWL → Validate**
|
||||
- **ontology_generation** — **Extract Concepts → Infer Classes → Infer Properties → Generate OWL → Validate** — Ontology generation from extracted data.
|
||||
|
||||
Ontology generation from extracted data.
|
||||
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("ontology_generation")
|
||||
pipeline = builder.build("ontology_pipeline")
|
||||
```
|
||||
</Card>
|
||||
</CardGroup>
|
||||
```python
|
||||
builder = manager.create_pipeline_from_template("ontology_generation")
|
||||
pipeline = builder.build("ontology_pipeline")
|
||||
```
|
||||
|
||||
<Tip>
|
||||
**Use templates from `PipelineTemplateManager` for common patterns.** `create_pipeline_from_template("kg_construction")` wires normalization, deduplication, conflict detection, and graph construction in the correct order: saving you from common mistakes like deduplicating before normalizing.
|
||||
@@ -583,17 +554,7 @@ StepStatus.SKIPPED # Skipped due to FailureHandler "skip" strategy
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Ingest" icon="database" href="ingest">
|
||||
First step in most pipelines.
|
||||
</Card>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Core extraction step.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
Graph construction step.
|
||||
</Card>
|
||||
<Card title="Export" icon="file-export" href="export">
|
||||
Final output step.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Ingest](ingest) — First step in most pipelines.
|
||||
- [Semantic Extract](semantic_extract) — Core extraction step.
|
||||
- [Knowledge Graph](kg) — Graph construction step.
|
||||
- [Export](export) — Final output step.
|
||||
|
||||
@@ -517,17 +517,7 @@ Provenance tracking in Semantica produces the following audit artifacts:
|
||||
`ProvenanceManager` does not include built-in Turtle or JSON-LD serialization. Use `entry.to_dict()` and `get_lineage()` to retrieve provenance data, then serialize with your preferred RDF library if W3C PROV-O RDF output is required.
|
||||
</Note>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Change Management" icon="clock-rotate-left" href="change_management">
|
||||
Version control and snapshot audit trails.
|
||||
</Card>
|
||||
<Card title="Ingest" icon="database" href="ingest">
|
||||
Provenance begins at the ingestion stage.
|
||||
</Card>
|
||||
<Card title="Export" icon="file-export" href="export">
|
||||
Include provenance metadata in RDF exports.
|
||||
</Card>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
Decision provenance via AgentContext.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Change Management](change_management) — Version control and snapshot audit trails.
|
||||
- [Ingest](ingest) — Provenance begins at the ingestion stage.
|
||||
- [Export](export) — Include provenance metadata in RDF exports.
|
||||
- [Context](context) — Decision provenance via AgentContext.
|
||||
|
||||
+10
-34
@@ -31,26 +31,12 @@ icon: "microchip"
|
||||
|
||||
## Which Engine Should I Use?
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Reasoner" icon="arrow-right-arrow-left" href="#reasoner-forwardbackward-chaining">
|
||||
IF/THEN rules, forward and backward chaining. **Start here**: covers 90% of use cases. No query language required.
|
||||
</Card>
|
||||
<Card title="GraphReasoner" icon="robot" href="#graphreasoner">
|
||||
Natural language queries over a knowledge graph via LLM. No SPARQL or rules: just ask a question.
|
||||
</Card>
|
||||
<Card title="DatalogReasoner" icon="code" href="#datalogreasoner">
|
||||
Recursive Horn clause rules with guaranteed termination. Use for complex multi-hop transitive rules.
|
||||
</Card>
|
||||
<Card title="ReteEngine" icon="bolt" href="#reteengine">
|
||||
Rete pattern matching for high-frequency inference. Use when you need to match many facts against many rules simultaneously.
|
||||
</Card>
|
||||
<Card title="SPARQLReasoner" icon="database" href="#sparqlreasoner">
|
||||
SPARQL query expansion and rule-based inference. Use when you're working with RDF/OWL data.
|
||||
</Card>
|
||||
<Card title="TemporalReasoningEngine" icon="clock" href="#temporalreasoningengine">
|
||||
All 13 Allen interval algebra relations. Use for time-aware reasoning: overlaps, before/after, during, contains.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Reasoner](#reasoner-forwardbackward-chaining) — IF/THEN rules, forward and backward chaining. **Start here**: covers 90% of use cases. No query language required.
|
||||
- [GraphReasoner](#graphreasoner) — Natural language queries over a knowledge graph via LLM. No SPARQL or rules: just ask a question.
|
||||
- [DatalogReasoner](#datalogreasoner) — Recursive Horn clause rules with guaranteed termination. Use for complex multi-hop transitive rules.
|
||||
- [ReteEngine](#reteengine) — Rete pattern matching for high-frequency inference. Use when you need to match many facts against many rules simultaneously.
|
||||
- [SPARQLReasoner](#sparqlreasoner) — SPARQL query expansion and rule-based inference. Use when you're working with RDF/OWL data.
|
||||
- [TemporalReasoningEngine](#temporalreasoningengine) — All 13 Allen interval algebra relations. Use for time-aware reasoning: overlaps, before/after, during, contains.
|
||||
|
||||
|
||||
## Getting Started
|
||||
@@ -479,17 +465,7 @@ step.confidence # float
|
||||
`GraphReasoner` requires a configured LLM provider. If the provider fails to initialize, `reason()` returns an error string instead of raising. Check `reasoner.provider is not None` before calling if you need to surface failures explicitly.
|
||||
</Warning>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
The knowledge graph being reasoned over.
|
||||
</Card>
|
||||
<Card title="Ontology" icon="sitemap" href="ontology">
|
||||
Ontology axioms and SHACL constraints for logical reasoning.
|
||||
</Card>
|
||||
<Card title="Triplet Store" icon="table" href="triplet_store">
|
||||
RDF backend for SPARQL-based reasoning.
|
||||
</Card>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
Reasoning integrated into agent decision intelligence.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Knowledge Graph](kg) — The knowledge graph being reasoned over.
|
||||
- [Ontology](ontology) — Ontology axioms and SHACL constraints for logical reasoning.
|
||||
- [Triplet Store](triplet_store) — RDF backend for SPARQL-based reasoning.
|
||||
- [Context](context) — Reasoning integrated into agent decision intelligence.
|
||||
|
||||
+10
-34
@@ -23,26 +23,12 @@ icon: "database"
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="SeedDataManager" icon="database">
|
||||
Register sources, build a foundation graph, validate quality, and merge with extracted data.
|
||||
</Card>
|
||||
<Card title="SeedDataSource" icon="file-code">
|
||||
Typed source definition supporting CSV, JSON, SQL, and API with format-specific config.
|
||||
</Card>
|
||||
<Card title="Foundation Graph" icon="circle-plus">
|
||||
Build a foundation graph from all registered sources in one pass, ready to merge with extracted data.
|
||||
</Card>
|
||||
<Card title="Merge Strategies" icon="arrows-merge">
|
||||
`seed_first`, `extracted_first`, and `merge` with property-level conflict detection.
|
||||
</Card>
|
||||
<Card title="Validation" icon="shield-check">
|
||||
Required field checks, ID uniqueness, type consistency, reference integrity, and encoding validation before loading.
|
||||
</Card>
|
||||
<Card title="Versioning" icon="clock-rotate-left">
|
||||
Track seed data versions across pipeline runs and diff changes between versions.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **SeedDataManager** — Register sources, build a foundation graph, validate quality, and merge with extracted data.
|
||||
- **SeedDataSource** — Typed source definition supporting CSV, JSON, SQL, and API with format-specific config.
|
||||
- **Foundation Graph** — Build a foundation graph from all registered sources in one pass, ready to merge with extracted data.
|
||||
- **Merge Strategies** — `seed_first`, `extracted_first`, and `merge` with property-level conflict detection.
|
||||
- **Validation** — Required field checks, ID uniqueness, type consistency, reference integrity, and encoding validation before loading.
|
||||
- **Versioning** — Track seed data versions across pipeline runs and diff changes between versions.
|
||||
|
||||
<Tip>
|
||||
**When to use the Seed Module:** Bootstrapping with structured reference data (taxonomies, user lists, product catalogs), loading immutable facts (ISO country codes, standard ontology terms) that extracted data should not override, ensuring test reproducibility with deterministic datasets, and anchoring entity disambiguation with canonical forms.
|
||||
@@ -335,17 +321,7 @@ export SEMANTICA_SEED_MERGE_STRATEGY=seed_first
|
||||
**Use YAML configuration for production deployments.** Hard-coding source paths in Python scripts makes environment-switching (dev → staging → prod) fragile. Declare sources in `config.yaml` under the `seed:` key and override paths with `SEMANTICA_SEED_DATA_DIR`. This way, the same code runs in every environment.
|
||||
</Tip>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Ingest" icon="file-import" href="ingest">
|
||||
Load unstructured data alongside seed data.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
The target graph that seed data populates.
|
||||
</Card>
|
||||
<Card title="Deduplication" icon="copy" href="deduplication">
|
||||
Handle duplicates during seed-extracted merge.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Incorporate seed loading as a named pipeline step.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Ingest](ingest) — Load unstructured data alongside seed data.
|
||||
- [Knowledge Graph](kg) — The target graph that seed data populates.
|
||||
- [Deduplication](deduplication) — Handle duplicates during seed-extracted merge.
|
||||
- [Pipeline](pipeline) — Incorporate seed loading as a named pipeline step.
|
||||
|
||||
@@ -410,17 +410,7 @@ triplets = trip.extract(text)
|
||||
| `ml` | Fast | Free | High | Limited |
|
||||
| `llm` | Medium | API cost | Highest | Yes (schema) |
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="LLM Providers" icon="microchip" href="llms">
|
||||
Configure which LLM is used for extraction.
|
||||
</Card>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
Build graphs from extracted entities and relationships.
|
||||
</Card>
|
||||
<Card title="Parse Module" icon="file-lines" href="parse">
|
||||
Parse documents before extraction.
|
||||
</Card>
|
||||
<Card title="Deduplication" icon="copy" href="deduplication">
|
||||
Resolve duplicate entities after extraction.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [LLM Providers](llms) — Configure which LLM is used for extraction.
|
||||
- [Knowledge Graph](kg) — Build graphs from extracted entities and relationships.
|
||||
- [Parse Module](parse) — Parse documents before extraction.
|
||||
- [Deduplication](deduplication) — Resolve duplicate entities after extraction.
|
||||
|
||||
+9
-31
@@ -51,23 +51,11 @@ Semantica's chunking methods are designed to avoid these failure modes.
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="TextSplitter" icon="scissors">
|
||||
Unified interface for 11 chunking strategies: swap methods without changing downstream code.
|
||||
</Card>
|
||||
<Card title="Semantic Chunking" icon="brain">
|
||||
Embedding-based topic shift detection: splits only when the topic actually changes.
|
||||
</Card>
|
||||
<Card title="Entity-Aware Chunking" icon="user">
|
||||
Entity spans never cross chunk boundaries: guaranteed by boundary adjustment.
|
||||
</Card>
|
||||
<Card title="Relation-Aware Chunking" icon="arrows-left-right">
|
||||
Subject–predicate–object triplets kept within a single chunk for KG pipelines.
|
||||
</Card>
|
||||
<Card title="Chunk Object" icon="box">
|
||||
Output dataclass with text, character offsets, optional id, and method-specific metadata.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **TextSplitter** — Unified interface for 11 chunking strategies: swap methods without changing downstream code.
|
||||
- **Semantic Chunking** — Embedding-based topic shift detection: splits only when the topic actually changes.
|
||||
- **Entity-Aware Chunking** — Entity spans never cross chunk boundaries: guaranteed by boundary adjustment.
|
||||
- **Relation-Aware Chunking** — Subject–predicate–object triplets kept within a single chunk for KG pipelines.
|
||||
- **Chunk Object** — Output dataclass with text, character offsets, optional id, and method-specific metadata.
|
||||
|
||||
## Quick Start
|
||||
|
||||
@@ -385,17 +373,7 @@ for chunk in chunks:
|
||||
|
||||
For the full pipeline orchestration API, see the [Pipeline reference](pipeline).
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Parse" icon="file-lines" href="parse">
|
||||
Parse documents before chunking: produces sections and metadata.
|
||||
</Card>
|
||||
<Card title="Embeddings" icon="vector-square" href="embeddings">
|
||||
Embed chunks for vector search and semantic chunking.
|
||||
</Card>
|
||||
<Card title="Semantic Extract" icon="magnifying-glass" href="semantic_extract">
|
||||
Extract entities and relations from individual chunks.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="gear" href="pipeline">
|
||||
Integrate splitting as a named pipeline step.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Parse](parse) — Parse documents before chunking: produces sections and metadata.
|
||||
- [Embeddings](embeddings) — Embed chunks for vector search and semantic chunking.
|
||||
- [Semantic Extract](semantic_extract) — Extract entities and relations from individual chunks.
|
||||
- [Pipeline](pipeline) — Integrate splitting as a named pipeline step.
|
||||
|
||||
@@ -19,26 +19,12 @@ icon: "table"
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="TripletStore" icon="server">
|
||||
Unified interface across Blazegraph, Apache Jena, and RDF4J: swap backends with one parameter.
|
||||
</Card>
|
||||
<Card title="SPARQL" icon="magnifying-glass">
|
||||
Full SPARQL SELECT, ASK, CONSTRUCT, and UPDATE query support via `execute_query()`.
|
||||
</Card>
|
||||
<Card title="Bulk Loading" icon="layer-group">
|
||||
`add_triplets()` batches writes with configurable batch size, retry logic, and progress tracking.
|
||||
</Card>
|
||||
<Card title="SKOS Vocabulary" icon="diagram-project">
|
||||
Built-in helpers: `add_skos_concept()` and `get_skos_concepts()` for controlled vocabulary management.
|
||||
</Card>
|
||||
<Card title="Named Graphs" icon="folder-tree">
|
||||
Blazegraph and RDF4J support named graph scoping via `graph=` on `execute_query()`.
|
||||
</Card>
|
||||
<Card title="Delta Computation" icon="code-compare">
|
||||
`compute_delta(old_graph_uri, new_graph_uri)` returns added and removed triples between two named graph snapshots.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **TripletStore** — Unified interface across Blazegraph, Apache Jena, and RDF4J: swap backends with one parameter.
|
||||
- **SPARQL** — Full SPARQL SELECT, ASK, CONSTRUCT, and UPDATE query support via `execute_query()`.
|
||||
- **Bulk Loading** — `add_triplets()` batches writes with configurable batch size, retry logic, and progress tracking.
|
||||
- **SKOS Vocabulary** — Built-in helpers: `add_skos_concept()` and `get_skos_concepts()` for controlled vocabulary management.
|
||||
- **Named Graphs** — Blazegraph and RDF4J support named graph scoping via `graph=` on `execute_query()`.
|
||||
- **Delta Computation** — `compute_delta(old_graph_uri, new_graph_uri)` returns added and removed triples between two named graph snapshots.
|
||||
|
||||
## Getting Started
|
||||
|
||||
@@ -490,17 +476,7 @@ for row in result.bindings:
|
||||
print(row)
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Export" icon="file-export" href="export">
|
||||
Export knowledge graphs to RDF formats.
|
||||
</Card>
|
||||
<Card title="Ontology" icon="sitemap" href="ontology">
|
||||
Load OWL ontologies and store as RDF triples.
|
||||
</Card>
|
||||
<Card title="Reasoning" icon="microchip" href="reasoning">
|
||||
SPARQL-based property chain inference.
|
||||
</Card>
|
||||
<Card title="Graph Store" icon="server" href="graph_store">
|
||||
Property graph alternative for Cypher queries.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Export](export) — Export knowledge graphs to RDF formats.
|
||||
- [Ontology](ontology) — Load OWL ontologies and store as RDF triples.
|
||||
- [Reasoning](reasoning) — SPARQL-based property chain inference.
|
||||
- [Graph Store](graph_store) — Property graph alternative for Cypher queries.
|
||||
|
||||
+8
-28
@@ -36,26 +36,12 @@ Most users won't call utils directly: it's the **shared foundation** for all mod
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Logging" icon="scroll">
|
||||
Structured logging with `@log_execution_time` decorator and quality metrics via environment variables.
|
||||
</Card>
|
||||
<Card title="Validation" icon="shield-check">
|
||||
`validate_entity` and `validate_config` with a typed `ValidationError` carrying field and value context.
|
||||
</Card>
|
||||
<Card title="Progress Tracking" icon="bars-progress">
|
||||
`track_progress` wraps any iterable: auto-detects console vs Jupyter for the right renderer.
|
||||
</Card>
|
||||
<Card title="Helper Functions" icon="wrench">
|
||||
`clean_text`, `hash_data`, `safe_filename`, and nested dict utilities used throughout the framework.
|
||||
</Card>
|
||||
<Card title="Exception Hierarchy" icon="triangle-exclamation">
|
||||
`SemanticaError` → `ValidationError`, `ProcessingError`: typed exceptions for targeted recovery.
|
||||
</Card>
|
||||
<Card title="File Utilities" icon="file">
|
||||
`read_json_file` raises `FileNotFoundError` or `json.JSONDecodeError` on failure: no boilerplate try/except around JSON I/O.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **Logging** — Structured logging with `@log_execution_time` decorator and quality metrics via environment variables.
|
||||
- **Validation** — `validate_entity` and `validate_config` with a typed `ValidationError` carrying field and value context.
|
||||
- **Progress Tracking** — `track_progress` wraps any iterable: auto-detects console vs Jupyter for the right renderer.
|
||||
- **Helper Functions** — `clean_text`, `hash_data`, `safe_filename`, and nested dict utilities used throughout the framework.
|
||||
- **Exception Hierarchy** — `SemanticaError` → `ValidationError`, `ProcessingError`: typed exceptions for targeted recovery.
|
||||
- **File Utilities** — `read_json_file` raises `FileNotFoundError` or `json.JSONDecodeError` on failure: no boilerplate try/except around JSON I/O.
|
||||
|
||||
## Logging
|
||||
|
||||
@@ -226,11 +212,5 @@ from semantica.utils import read_json_file
|
||||
config = read_json_file("config.json")
|
||||
```
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Core" icon="gear" href="core">
|
||||
Framework orchestration that uses Utils internally.
|
||||
</Card>
|
||||
<Card title="Pipeline" icon="arrows-turn-to-dots" href="pipeline">
|
||||
Uses ProgressTracker for per-step tracking.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Core](core) — Framework orchestration that uses Utils internally.
|
||||
- [Pipeline](pipeline) — Uses ProgressTracker for per-step tracking.
|
||||
|
||||
@@ -32,38 +32,24 @@ icon: "database"
|
||||
|
||||
## What You Get
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="VectorStore" icon="database">
|
||||
- Unified interface across FAISS, Pinecone, Weaviate, Qdrant, Milvus, PgVector
|
||||
- One-line backend swap: no application code changes
|
||||
- `add_documents()` auto-embeds; `store_vectors()` for pre-computed embeddings
|
||||
</Card>
|
||||
<Card title="HybridSearch" icon="magnifying-glass">
|
||||
- Dense vector similarity with metadata filtering
|
||||
- RRF or weighted-average fusion strategies
|
||||
- Multi-source fusion across separate collections
|
||||
</Card>
|
||||
<Card title="MetadataStore" icon="table">
|
||||
- Rich metadata indexing by field values
|
||||
- Update metadata fields without re-embedding
|
||||
- OR and AND query operators
|
||||
</Card>
|
||||
<Card title="NamespaceManager" icon="folder-tree">
|
||||
- Structural per-tenant namespace isolation
|
||||
- Faster queries (smaller search space per tenant)
|
||||
- Safer than metadata-filter-only separation
|
||||
</Card>
|
||||
<Card title="Batch Operations" icon="layer-group">
|
||||
- Bulk add, delete, and metadata updates
|
||||
- Parallel embedding with configurable `batch_size` and `workers`
|
||||
- In-place vector updates without full re-indexing
|
||||
</Card>
|
||||
<Card title="FAISS Index Types" icon="chart-scatter">
|
||||
- flat, ivf, hnsw, and pq index types
|
||||
- Full configuration control via `FAISSStore.create_index()`
|
||||
- `save()` / `load()` for disk persistence
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- **VectorStore** — Unified interface across FAISS, Pinecone, Weaviate, Qdrant, Milvus, PgVector
|
||||
- One-line backend swap: no application code changes
|
||||
- `add_documents()` auto-embeds; `store_vectors()` for pre-computed embeddings
|
||||
- **HybridSearch** — Dense vector similarity with metadata filtering
|
||||
- RRF or weighted-average fusion strategies
|
||||
- Multi-source fusion across separate collections
|
||||
- **MetadataStore** — Rich metadata indexing by field values
|
||||
- Update metadata fields without re-embedding
|
||||
- OR and AND query operators
|
||||
- **NamespaceManager** — Structural per-tenant namespace isolation
|
||||
- Faster queries (smaller search space per tenant)
|
||||
- Safer than metadata-filter-only separation
|
||||
- **Batch Operations** — Bulk add, delete, and metadata updates
|
||||
- Parallel embedding with configurable `batch_size` and `workers`
|
||||
- In-place vector updates without full re-indexing
|
||||
- **FAISS Index Types** — flat, ivf, hnsw, and pq index types
|
||||
- Full configuration control via `FAISSStore.create_index()`
|
||||
- `save()` / `load()` for disk persistence
|
||||
|
||||
|
||||
## Getting Started
|
||||
@@ -602,17 +588,7 @@ store.create_index(index_type="pq", metric="L2", m=8)
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Embeddings" icon="vector-square" href="embeddings">
|
||||
Generate the vectors stored here.
|
||||
</Card>
|
||||
<Card title="Context" icon="brain" href="context">
|
||||
AgentContext uses VectorStore for memory retrieval.
|
||||
</Card>
|
||||
<Card title="Split" icon="scissors" href="split">
|
||||
Chunk documents before embedding and storing.
|
||||
</Card>
|
||||
<Card title="Ingest" icon="download" href="ingest">
|
||||
Ingest documents before embedding and storing.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Embeddings](embeddings) — Generate the vectors stored here.
|
||||
- [Context](context) — AgentContext uses VectorStore for memory retrieval.
|
||||
- [Split](split) — Chunk documents before embedding and storing.
|
||||
- [Ingest](ingest) — Ingest documents before embedding and storing.
|
||||
|
||||
@@ -290,17 +290,7 @@ semantica-explorer --graph my_graph.json
|
||||
|
||||
See the [Explorer reference](explorer) for the full feature set and REST API.
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Knowledge Graph" icon="diagram-project" href="kg">
|
||||
The graph being visualized.
|
||||
</Card>
|
||||
<Card title="Ontology" icon="sitemap" href="ontology">
|
||||
Visualize ontology class structure.
|
||||
</Card>
|
||||
<Card title="Embeddings" icon="vector-square" href="embeddings">
|
||||
Generate the embeddings visualized here.
|
||||
</Card>
|
||||
<Card title="Explorer" icon="globe" href="explorer">
|
||||
Full interactive Knowledge Explorer UI.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
- [Knowledge Graph](kg) — The graph being visualized.
|
||||
- [Ontology](ontology) — Visualize ontology class structure.
|
||||
- [Embeddings](embeddings) — Generate the embeddings visualized here.
|
||||
- [Explorer](explorer) — Full interactive Knowledge Explorer UI.
|
||||
|
||||
Reference in New Issue
Block a user