Prompts - Allocated Requirements¶
This document outlines the requirements allocated to the Prompts component within the AgentHeaven architecture.
1. Overview¶
The Prompts component manages prompt templates and their versioning within the system.
2. Allocated Requirements¶
2.1 Functional Requirements¶
ID |
Requirement |
Implementation Details |
Priority |
|---|---|---|---|
FR-05 |
Prompt Templating |
Manages jinja templates and versions |
High |
FR-09 |
Multi-lingual Prompt Engine |
Supports multiple languages in prompts |
High |
FR-43 |
Prompt Resource Management |
Organizes prompts in resources directory with structured hierarchy |
High |
FR-44 |
Prompt Versioning |
Supports version control and inheritance for prompt templates |
High |
FR-45 |
Context-Aware Prompts |
Enables retrieval of relevant context for prompt execution |
Medium |
FR-46 |
Prompt Caching |
Caches compiled prompt templates for performance |
Medium |
FR-47 |
Prompt Validation |
Validates template syntax and variable substitution |
Medium |
2.2 Non-Functional Requirements¶
ID |
Requirement |
Implementation Details |
Priority |
|---|---|---|---|
NFR-04 |
Documentation |
Documents prompt templates and versions |
Medium |
NFR-18 |
Template Performance |
Optimizes template rendering speed |
High |
NFR-19 |
Template Security |
Prevents template injection attacks |
High |
NFR-20 |
Internationalization |
Supports proper localization and multi-language handling |
Medium |
2.3 Cross-Component Dependencies¶
Component |
Description |
|---|---|
BaseUKF |
For storing prompt templates |
LLM |
For executing prompts |
KLBase |
For retrieving context-aware prompts |
3. Implementation Notes¶
[Add implementation notes here]
4. Open Issues¶
[List any open issues or questions]
Further Exploration¶
Tip: For more information about prompts and templates in AgentHeaven, see:
Main Guide (Python) - Jinja Utils - Template processing and Jinja integration
Configuration - Core - Core configuration concepts
Main Guide (Python) - Configuration Utils - Configuration management utilities
Tip: For more information about AgentHeaven architecture, see:
LLM Component - LLM integration and interface
Agent Component - Agent implementation and architecture
CLI Guide - LLM Inference - Command-line LLM inference tools