Files
semantica/docs/reference/core.md
T
Mohd Kaif 5d70d0c10d docs: replace Exported Classes import blocks with summary tables (all 25 modules) (#567)
* docs: replace Exported Classes import blocks with summary tables across all 25 modules

* docs: add method/parameter tables to parse, ingest, ontology, normalize, triplet_store, change_management, conflicts, export, graph_store, provenance, and semantic_extract modules
2026-05-24 15:49:58 +05:30

211 lines
6.3 KiB
Markdown

---
title: "Core Module"
description: "Framework orchestration, lifecycle management, configuration, and plugin system."
icon: "gear"
---
`semantica.core` is the coordination layer for the framework. For most tasks you should use individual modules directly (`semantica.ingest`, `semantica.kg`, etc.). Reach for Core when you need application-level lifecycle management, centralized configuration, or a plugin registry.
## Exported Classes
| Class | Role |
| --- | --- |
| `Semantica` | Orchestration entry point — coordinates the full KG construction pipeline |
| `ConfigManager` | YAML config loading, deep-merge, validation, and env var overrides |
| `LifecycleManager` | Startup/shutdown state machine with health monitoring and lifecycle hooks |
| `PluginRegistry` | Dynamic plugin discovery, registration, and loading |
| `method_registry` | Global `MethodRegistry` instance — register and dispatch custom orchestration methods |
<Tip>
**Use individual modules directly** for the vast majority of use cases. Use the `Semantica` orchestration class only when you need application-level lifecycle management or a plugin system.
</Tip>
## Semantica (Orchestration)
High-level entry point that coordinates the full KG construction pipeline:
```python
from semantica.core import Semantica, ConfigManager
config_manager = ConfigManager()
config = config_manager.load_from_file("config.yaml")
framework = Semantica(config=config)
framework.initialize()
try:
result = framework.build_knowledge_base(
sources=["doc1.pdf", "doc2.docx"],
embeddings=True,
graph=True,
)
status = framework.get_status()
print(f"State: {status['state']}")
finally:
framework.shutdown(graceful=True)
```
### Core Methods
| Method | Description |
| ------ | ----------- |
| `initialize()` | Initialize all framework components |
| `build_knowledge_base(sources, **kwargs)` | Orchestrate full KG construction pipeline |
| `run_pipeline(pipeline, data)` | Execute an existing `Pipeline` instance |
| `get_status()` | Return system health and current state |
| `shutdown(graceful=True)` | Graceful shutdown — waits for in-flight operations |
## ConfigManager
Centralized config loading with deep-merge and environment variable overrides:
```python
from semantica.core import ConfigManager
manager = ConfigManager()
config = manager.load_from_file("config.yaml")
# Merge base config with environment-specific overrides
merged = manager.merge_configs(
manager.load_from_file("base.yaml"),
manager.load_from_file("prod.yaml"),
)
# Nested key access with dot notation
batch_size = config.get("processing.batch_size", default=16)
config.set("processing.batch_size", 64)
config.validate()
```
### YAML Configuration
```yaml
llm_provider:
name: openai
model: gpt-4o
api_key: ${OPENAI_API_KEY}
processing:
batch_size: 32
max_workers: 4
quality:
min_confidence: 0.7
logging:
level: INFO
```
Environment variable overrides (prefix `SEMANTICA_`):
```bash
export SEMANTICA_PROCESSING_BATCH_SIZE=64
export SEMANTICA_LOG_LEVEL=DEBUG
```
## LifecycleManager
Manages framework state with a defined state machine and ordered startup/shutdown hooks:
**State machine:** `UNINITIALIZED``INITIALIZING``READY``RUNNING``STOPPING``STOPPED`
```python
from semantica.core import LifecycleManager
manager = LifecycleManager()
def init_db():
print("Initializing database...")
def cleanup_db():
print("Closing database connections...")
# Lower priority values run first during startup
# Higher priority values run first during shutdown
manager.register_startup_hook(init_db, priority=10)
manager.register_shutdown_hook(cleanup_db, priority=10)
manager.startup()
# Component health monitoring
class DatabaseComponent:
def health_check(self):
return {"healthy": True, "message": "Connected"}
manager.register_component("database", DatabaseComponent())
summary = manager.get_health_summary()
# → {"database": {"healthy": True, "message": "Connected"}, ...}
manager.shutdown(graceful=True)
```
## PluginRegistry
Register custom components that participate in the full pipeline — provenance tracking, retry policies, and parallel execution included:
```python
from semantica.core import PluginRegistry
class MyPlugin:
def initialize(self):
print("Plugin initialized")
def execute(self, data):
return {"processed": True}
registry = PluginRegistry(plugin_paths=["./plugins"])
registry.register_plugin("my_plugin", MyPlugin, version="1.0.0")
plugin = registry.load_plugin("my_plugin", api_key="xxx")
result = plugin.execute("sample data")
for info in registry.list_plugins():
print(f"{info['name']}: {info['version']}")
```
## MethodRegistry
Register custom orchestration methods and dispatch them by name:
```python
from semantica.core import method_registry
from semantica.core.methods import build_knowledge_base
def fast_kb_builder(sources, **kwargs):
# Custom logic — skip embeddings for speed
...
method_registry.register("knowledge_base", "fast", fast_kb_builder)
result = build_knowledge_base(sources=["doc.pdf"], method="fast")
```
## When to Use Core vs. Individual Modules
| Scenario | Recommended Approach |
| -------- | -------------------- |
| Single extraction task | `from semantica.semantic_extract import NERExtractor` |
| Build a knowledge graph | `from semantica.kg import GraphBuilder` |
| Multi-step pipeline | `from semantica.pipeline import Pipeline` |
| App-level lifecycle + config | `from semantica.core import Semantica, ConfigManager` |
| Custom dispatch / plugins | `from semantica.core import method_registry, PluginRegistry` |
<Tip>
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.
</Tip>
<CardGroup cols={2}>
<Card title="Pipeline" icon="arrows-turn-to-dots" href="pipeline">
Pipeline execution and step orchestration.
</Card>
<Card title="Utils" icon="wrench" href="utils">
Shared utilities used by Core internally.
</Card>
<Card title="Getting Started" icon="play" href="../getting-started">
Learn the basics before using Core.
</Card>
<Card title="LLMs" icon="microchip" href="llms">
Configure LLM providers via ConfigManager.
</Card>
</CardGroup>