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SearchMuse Functional Documentation

Welcome to SearchMuse's comprehensive functional documentation. This collection provides complete specification and guidance for understanding, using, and extending SearchMuse.

Documentation Overview

1. Vision and Goals

Scope: Strategic overview and philosophy - Vision statement and core mission - Problems solved by SearchMuse - Design principles and goals - Non-goals and out-of-scope features - Success criteria

For: Anyone new to SearchMuse, stakeholders, contributors understanding project direction

2. Use Cases

Scope: Real-world usage scenarios and user stories - Primary user persona (Research-Focused Developer) - 5 detailed use cases: - Quick fact-finding - Deep research - Technology comparison - Literature review - Trend analysis - User stories with acceptance criteria - Quality metrics and success criteria

For: Product managers, UX designers, understanding user needs, feature planning

3. Feature Specifications

Scope: Detailed technical specifications for core features - Architecture overview (Mermaid diagram) - 6 major features with detailed specs: 1. Iterative Search 2. Source Citation 3. Content Extraction 4. LLM Integration 5. Multi-Strategy Scraping 6. Result Synthesis - Configuration examples - Output examples

For: Developers, technical leads, implementation planning

4. Search Refinement Algorithm

Scope: Detailed algorithm specification with step-by-step processes - Algorithm flowchart (Mermaid diagram) - 10 detailed algorithm steps: 1. Query parsing 2. Strategy generation 3. Search execution 4. Content scraping 5. Content extraction 6. Relevance assessment 7. Coverage assessment 8. Convergence decision 9. Strategy refinement 10. Iteration loop - Quality score calculation - Configuration reference - Performance characteristics

For: Core developers, algorithm designers, research quality analysis

5. Source Citation

Scope: Citation philosophy, data models, and formats - Citation philosophy and importance - Citation data model - 3 supported citation formats: - Markdown (default) - HTML - APA-style - Citation extraction process - Quality assurance and hallucination detection - Best practices

For: Researchers, academic users, output designers

6. Supported Websites

Scope: Website categories, support levels, and scraping strategies - 3 support levels: - Level 1: Full support (static HTML) - Level 2: Partial support (JavaScript-rendered) - Level 3: Limited support (anti-bot protection) - Website categories: - News & media - Technical documentation - Academic sources - Blogs & articles - Forums & communities - Government sources - robots.txt compliance - Adapter pattern for adding support - Known limitations per category - Performance metrics

For: Users understanding site support, developers adding site adapters

7. LLM Requirements

Scope: Local LLM setup, model selection, and configuration - Ollama installation (Docker and native) - 3 recommended models: - Mistral (default, balanced) - Llama 3 (large, better reasoning) - Phi 3 (lightweight, fastest) - Hardware requirements by model - Temperature and parameter settings - Prompt templates for each task - Custom model configuration - Performance optimization - Troubleshooting guide - Configuration template

For: DevOps engineers, system administrators, power users

8. Input/Output Formats

Scope: API and user interaction formats - Input formats: - Simple string query - JSON query object with optional parameters - Output formats: - Markdown (default, human-readable) - JSON (structured, programmatic) - Plain text (simple) - HTML (web publishing) - Error output format - Streaming output (progress updates) - Format examples for each use case

For: API users, integration developers, tool builders

9. Limitations

Scope: Transparent assessment of what SearchMuse cannot do - Scope limitations: - Not real-time - Not for login-required sites - Not multimedia-focused - Not a database query system - Quality limitations: - Depends on LLM quality - Limited by source availability - Limited by source quality - Content extraction limitations - Technical limitations: - robots.txt compliance - Rate limiting - JavaScript-heavy sites slower - Memory constraints - Network issues - Site-specific limitations: - Paywalls - CAPTCHA/bot detection - Geo-restrictions - Dynamic content - Comparison with alternatives - Mitigation strategies

For: Users assessing fit for use case, product planning, setting expectations

10. Roadmap

Scope: Future development direction and versioned release plan - Version 0.1.0 (MVP): Core search functionality - Version 0.2.0 (Iterative): Multi-iteration search with coverage assessment - Version 0.3.0 (Polish): Multiple scraping strategies and output formats - Version 1.0.0 (Release): Plugin system, API server, Docker support - Version 1.1.0 (Advanced): Advanced research features and integrations - Version 2.0.0 (Expansion): Web UI, multi-language, collaborative features - Feature priority matrix - Community contribution areas - Success metrics by version - Known technical debt

For: Project planning, community contributions, feature requests

Quick Navigation

By Role

For Researchers/End Users: 1. Start with Vision and Goals to understand what SearchMuse does 2. Read Use Cases to find scenarios matching your needs 3. Check Supported Websites to see if your sources work 4. Refer to Input/Output Formats for usage examples 5. Review Limitations to understand constraints

For Developers/Contributors: 1. Read Vision and Goals for project philosophy 2. Study Feature Specifications for architecture 3. Deep dive Search Refinement Algorithm for core logic 4. Check LLM Requirements for setup 5. Review Roadmap for contribution opportunities

For DevOps/System Administrators: 1. Start with Feature Specifications overview 2. Focus on LLM Requirements for infrastructure planning 3. Check Input/Output Formats for API integration 4. Review Limitations for capacity planning

For Product Managers: 1. Read Vision and Goals for product direction 2. Study Use Cases for market opportunities 3. Review Limitations for positioning 4. Check Roadmap for release planning

By Task

Understanding the System: - Vision and Goals - Feature Specifications - Search Refinement Algorithm

Using SearchMuse: - Use Cases - Supported Websites - Input/Output Formats - Limitations

Setting Up SearchMuse: - LLM Requirements - Feature Specifications

Extending SearchMuse: - Supported Websites (site adapters) - Feature Specifications (plugin points) - Roadmap (contribution areas)

Troubleshooting: - Limitations (known issues) - LLM Requirements (troubleshooting section) - Supported Websites (error handling)

Document Statistics

Document Lines Topics Focus
Vision and Goals 100 8 Strategy
Use Cases 240 5 Requirements
Feature Specifications 260 6 Architecture
Search Algorithm 380 10 Implementation
Source Citation 340 4 Data Model
Supported Websites 350 8 Integration
LLM Requirements 380 8 Configuration
Input/Output Formats 380 8 API Design
Limitations 320 10 Constraints
Roadmap 340 6 Planning

Total: ~3,000 lines of documentation covering all aspects of SearchMuse

Key Concepts

Core Algorithm

SearchMuse implements an iterative search refinement algorithm: 1. Generate search strategy (LLM) 2. Execute search (DuckDuckGo) 3. Extract content (trafilatura/readability) 4. Assess relevance (LLM) 5. Assess coverage (LLM) 6. If not converged, refine strategy and repeat

Privacy-First Architecture

  • All processing local (via Ollama)
  • No external API calls for research
  • Open-source for transparency
  • Users control all data

Always-Cited Sources

  • Every claim traced to source
  • Multiple citation formats available
  • Hallucination detection
  • Citation validation

Extensible Design

  • Adapter pattern for scrapers
  • Plugin system for LLM providers
  • Multiple output formats
  • Custom configuration

Getting Started

Quick Start Path

  1. Read Vision and Goals (5 min)
  2. Check Use Cases (10 min)
  3. Review LLM Requirements (10 min)
  4. Try Input/Output Formats (10 min)
  5. Install and test locally (30 min)

Deep Dive Path

  1. Read all documentation in order
  2. Study architecture diagrams
  3. Review source code with docs
  4. Contribute to roadmap items
  5. Suggest improvements

Contributing to Documentation

SearchMuse documentation is open to community improvements:

  • Suggest additions or clarifications via GitHub Issues
  • Submit pull requests for documentation improvements
  • Share feedback on clarity and completeness
  • Contribute examples and use cases

All documentation follows these principles: - Clear, accessible language - Concrete examples - Comprehensive coverage - Regular updates - Version-specific guidance

Questions and Feedback

If anything in this documentation: - Is unclear - Is incomplete - Has errors - Needs examples - Could be better organized

Please open a GitHub Issue or Discussion with your feedback.

Documentation quality directly impacts user success!

Version History

v0.1.0 (Initial Documentation): - Created 10 comprehensive functional documentation files - Covers vision, use cases, features, algorithms, deployment - Includes roadmap and limitations - Suitable for MVP through v1.0 releases

Last Updated: February 28, 2024 Next Review: After v0.1.0 release