Create LLM Content Context Builder #102

New Issue

tegwick · 2025-10-03T22:26:35Z

tegwick commented

2025-10-03 22:26:35 +00:00

Priority: HIGH | Effort: 3 days | Dependencies: OpenRouter Client Infrastructure

User Story

As a user, I want the LLM to have relevant context from my MarkiTect content when answering questions so that responses are accurate and cite my actual documents.

Description

Build a smart context builder that extracts relevant content from the MarkiTect database, uses FTS search for content discovery, and constructs context within token limits while maintaining source citations.

Technical Implementation

New Files: markitect/llm/context_builder.py, markitect/llm/content_selector.py, tests/test_context_builder.py

Acceptance Criteria

ContextBuilder class with intelligent content selection
Integration with existing FTS search capabilities
Token-aware context truncation and optimization
Source tracking and citation generation
Relevance scoring for content ranking
Support for different context strategies (recent, relevant, comprehensive)
Performance optimization for large content repositories
Unit tests with mock database content

Core component for Issue #98 (OpenRoute Integration).

**Priority**: HIGH | **Effort**: 3 days | **Dependencies**: OpenRouter Client Infrastructure ## User Story As a user, I want the LLM to have relevant context from my MarkiTect content when answering questions so that responses are accurate and cite my actual documents. ## Description Build a smart context builder that extracts relevant content from the MarkiTect database, uses FTS search for content discovery, and constructs context within token limits while maintaining source citations. ## Technical Implementation - **New Files**: markitect/llm/context_builder.py, markitect/llm/content_selector.py, tests/test_context_builder.py ## Acceptance Criteria - [ ] ContextBuilder class with intelligent content selection - [ ] Integration with existing FTS search capabilities - [ ] Token-aware context truncation and optimization - [ ] Source tracking and citation generation - [ ] Relevance scoring for content ranking - [ ] Support for different context strategies (recent, relevant, comprehensive) - [ ] Performance optimization for large content repositories - [ ] Unit tests with mock database content ## Related Issues Core component for Issue #98 (OpenRoute Integration).

tegwick added the type:feature priority:high labels 2025-10-03 22:26:35 +00:00

tegwick added this to the LLM Chat and Agent Assistance project 2025-10-03 22:28:30 +00:00

Sign in to join this conversation.

1 Participants

Notifications

Due Date

No due date set.

Dependencies

No dependencies set.

Reference: coulomb/markitect-main#102