5.2 KiB
Kontextual Engine Functional Requirements Specification V0.1
kontextual-engine
1. System Overview
kontextual-engine is a headless knowledge system that enables persistent storage, transformation, retrieval, and AI-driven operation of structured and semi-structured knowledge across heterogeneous data sources.
This FRS defines the externally observable functional behavior of the system.
2. Actors and Interfaces
2.1 Primary Actors
- User (Human Operator) via API or service interface
- Automation System (
atm) executing workflows - LLM Agent (
agt) interacting with knowledge and workflows - External Systems integrating via APIs
2.2 System Interfaces
- Service API (HTTP, RPC, or equivalent)
- Programmatic API (SDK/library interface)
- Storage interface (abstracted from implementation)
3. Functional Requirements
3.1 Knowledge Persistence
FR-001: Store Knowledge Artifacts
Description: The system must allow storage of knowledge artifacts.
Input:
- Structured or semi-structured data
Output:
- Persisted knowledge artifact with identifier
FR-002: Retrieve Knowledge Artifacts
The system must allow retrieval of stored knowledge artifacts by identifier or query.
FR-003: Update Knowledge Artifacts
The system must allow modification of existing knowledge artifacts.
FR-004: Delete Knowledge Artifacts
The system must allow removal of stored knowledge artifacts.
3.2 Knowledge Organization
FR-010: Group Knowledge into Collections
The system must allow grouping knowledge artifacts into collections or domains.
FR-011: Maintain Relationships
The system must allow defining and retrieving relationships between knowledge artifacts.
3.3 Ingestion and Normalization
FR-020: Ingest Multi-Format Data
The system must accept input from multiple data formats (e.g. markdown, documents, files).
FR-021: Normalize Data
The system must convert ingested data into a structured representation usable by the system.
3.4 Query and Retrieval
FR-030: Query Knowledge
The system must allow querying knowledge artifacts based on:
- Content
- Metadata
- Relationships
FR-031: Return Query Results
The system must return matching knowledge artifacts and associated data.
3.5 Transformation and Composition
FR-040: Transform Knowledge Artifacts
The system must allow applying transformations to knowledge artifacts.
FR-041: Compose Knowledge
The system must allow combining multiple knowledge artifacts into derived outputs.
3.6 Workflow Orchestration
FR-050: Execute Workflows
The system must allow execution of multi-step workflows on knowledge artifacts.
FR-051: Manage Workflow Dependencies
The system must handle dependencies between workflow steps.
FR-052: Provide Workflow Results
The system must return results of workflow execution.
3.7 AI Interaction
FR-060: Support AI-Driven Operations
The system must allow AI agents to:
- Access knowledge
- Trigger transformations
- Participate in workflows
FR-061: Maintain Context for AI Interaction
The system must provide contextual information to support AI-driven operations.
3.8 Integration with External Tools
FR-070: Integrate with Tooling
The system must allow integration with external tooling (e.g. markitect-tool).
FR-071: Accept External Processing Results
The system must accept outputs from external tools and incorporate them into knowledge.
3.9 API Interaction
FR-080: Provide API Access
The system must expose its capabilities through a programmatic interface.
FR-081: Support External Invocation
The system must allow external systems to invoke operations on knowledge.
3.10 Error Handling
FR-090: Provide Structured Errors
The system must return structured error information for invalid operations.
FR-091: Avoid Silent Failures
The system must not silently ignore errors affecting correctness.
4. Functional Constraints
- Functions must be accessible through service interfaces
- System must support heterogeneous data formats
- AI-related functions must operate independently of specific providers
- System must not require CLI-based interaction
5. Traceability
| PRD Concept | FRS Coverage |
|---|---|
| Knowledge persistence | FR-001–FR-004 |
| Organization & relationships | FR-010–FR-011 |
| Ingestion & normalization | FR-020–FR-021 |
| Query & retrieval | FR-030–FR-031 |
| Transformation & composition | FR-040–FR-041 |
| Workflow orchestration | FR-050–FR-052 |
| AI interaction | FR-060–FR-061 |
| Integration | FR-070–FR-071 |
| API access | FR-080–FR-081 |
6. Acceptance Perspective
The system satisfies this FRS when:
- Knowledge can be stored, retrieved, and manipulated via API
- Queries return expected results
- Workflows execute and produce observable outputs
- AI agents can interact with knowledge meaningfully
- Errors are explicit and traceable