Open Issues Need Help
View All on GitHubAI Summary: This issue proposes the development of an official Claude Code Plugin for Semantica, a comprehensive knowledge graph and agent intelligence library. The plugin aims to expose Semantica's core functionalities as Claude Code skills and agents, enabling seamless interaction with a live knowledge graph directly within the IDE.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request aims to implement named graph support within the Semantica RDF store. This will allow for logical partitioning of data (e.g., by environment, tenant, or trust tier) using graph URIs, enabling targeted queries and integrations with existing change management and versioning systems.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request proposes the creation of an interactive, browser-based dashboard called the 'Knowledge Explorer' for the Semantica platform. This tool aims to allow users, particularly domain experts, to visually explore, query, filter, and enrich knowledge graphs without needing to write code, addressing a current bottleneck in knowledge graph interaction and validation. The solution involves an optional installable add-on that launches a local FastAPI server with a React dashboard.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature aims to automatically generate SHACL validation rules from existing OWL ontologies. The generated SHACL shapes will be derived from OWL classes and properties, and will be accessible through the existing ontology and export APIs. This will reduce manual effort in defining data quality constraints and make Semantica more suitable for enterprise data validation workflows.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request proposes the implementation of reusable SPARQL CONSTRUCT templates within Semantica. These templates will allow users to define parameterized graph transformations that can be executed by the existing query and pipeline engines, enabling automated reasoning and knowledge graph enrichment.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request aims to integrate SKOS (Simple Knowledge Organization System) vocabulary management into the existing Semantica platform. It involves extending the current ontology and RDF infrastructure to store, search, browse, and utilize SKOS concepts and collections, enhancing semantic search and centralizing enterprise vocabularies without introducing new Python packages.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: The `create_position_class` function in the Ontology module incorrectly passes the `name` argument twice when a custom name is provided. This leads to a `TypeError` because the underlying `create_associative_class` method receives the `name` argument multiple times. The fix involves ensuring the `name` argument is not duplicated when unpacking `**options`.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request proposes adding a native Snowflake connector to Semantica's ingestion module. This will allow users to seamlessly integrate data from Snowflake, a popular cloud data warehouse, without manual Python connector setup. The implementation will involve creating a `SnowflakeIngestor` class with support for various authentication methods, query execution, and data streaming.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This issue proposes adding support for exporting data in Apache Arrow format. The goal is to enable high-performance, in-memory data exchange by implementing an `ArrowExporter` that converts entities and relationships into Arrow Tables with explicit schema definitions. This will improve compatibility with downstream tools like pandas and DuckDB.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request aims to implement audit-grade provenance tracking for Semantica, enabling full traceability from source documents to query responses. This is crucial for high-stakes domains like finance, healthcare, and legal, requiring W3C PROV-O compliance and detailed lineage for every claim.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This feature request aims to significantly enhance Semantica's version management by introducing persistent storage for snapshots, detailed change tracking (beyond simple counts), and standardized metadata. The goal is to enable audit trails, compliance, and data governance for enterprise adoption, particularly in regulated industries.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This issue proposes enhancing the CSV file ingestion process by adding features like automatic delimiter and encoding detection, improved header and quote handling, support for large files through streaming, and more robust error handling. The goal is to make CSV ingestion more flexible and resilient to various file formats and potential issues.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This issue requests the addition of unit tests for the ingestion module, specifically for file, web, and feed ingestors. The goal is to improve code coverage and reliability by testing edge cases and error handling, making it a good opportunity for new contributors to learn the codebase.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This issue requests the addition of comprehensive unit tests for the `TextNormalizer` class. The goal is to improve test coverage, ensure reliability, document expected behavior, and prevent regressions by creating a new test file and covering various scenarios including basic text, special characters, and different normalization options.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: The user is encountering an incomplete output when processing earnings call data in step 5 of the '03_Earnings_Call' module. This is due to a `max_tokens` length limit in the LLM call, which was not resolved by increasing the limit to 128k.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: The user reports a bug where the `semantica.kg.KnowledgeGraph` class, referenced in the `ontology.md` documentation for schema-first knowledge graph creation, is not available in the installed Semantica version (0.1.1). This prevents users from following the documented workflow for initializing and populating a knowledge graph.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: This issue addresses three distinct problems: a missing export in `DoclingParser`, a `UnicodeEncodeError` occurring on Windows during progress tracking, and an outdated earnings call analysis notebook that needs to be updated with current financial data.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.
AI Summary: On Windows, importing the Groq LLM provider fails due to a PyTorch DLL error. This occurs because PyTorch is imported at the top level of the semantica library, even when not needed by Groq, blocking all API-based LLM providers on Windows.
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision intelligence systems with explainability and provenance.