DocMind

DocMind is an intelligent document analysis and question-answering system built with Golang and LangChain. It allows users to upload documents, process them, and perform intelligent queries to extract relevant information.

Features

• Document Upload: Supports multiple document formats including PDF, Word, and Markdown.
• Intelligent Analysis: Utilizes AI to analyze and vectorize document content.
• Question-Answering: Provides accurate answers to user queries based on document content.
• RESTful API: Offers a robust API for integration with other applications.

Tech Stack

• Backend: Golang
• AI Integration: LangChain
• Database: PostgreSQL for metadata, Milvus/Weaviate for vector storage
• Framework: Gin for HTTP server
• Document Processing: Apache Tika or native parsers

Getting Started

Prerequisites

• Go 1.18 or higher
• Docker (for containerization)
• PostgreSQL
• Milvus/Weaviate (for vector storage)

DocMind Project Milestones

Overview

This document outlines the key milestones for the DocMind project, an intelligent document analysis and question-answering system. Each milestone represents a significant phase in the project's development lifecycle.

Database Setup

The project uses PostgreSQL running in Docker. To start the database:

# Build and start the PostgreSQL container
docker-compose up -d postgres

Milestone 1: Infrastructure Setup

Target Completion: [Date]

Core infrastructure and project foundation setup.

Objectives for Milestone 1

• Initialize project structure
  • Set up directory hierarchy
  • Configure Go modules
  • Implement basic dependency management
• Establish core configuration system
  • Environment variable management
  • Configuration file handling
  • Secret management
• Set up basic Gin web server
  • HTTP router configuration
  • Middleware integration
  • Basic endpoint structure
• Implement logging system
  • Structured logging
  • Log rotation
  • Log level management
• Create error handling framework
  • Custom error types
  • Error middleware
  • Error response standardization

Milestone 2: Document Management System

Target Completion: [Date]

Implementation of core document handling capabilities.

Objectives for Milestone 2

• Document upload system
  • Multipart file upload handling
  • File type validation
  • Size limit management
• Database integration
  • Document metadata models
  • Database migrations
  • CRUD operations
• Storage system
  • File storage implementation
  • Document versioning
  • Storage optimization
• Document processing pipeline
  • Queue system integration
  • Parser implementation (PDF, TXT)
  • Processing status tracking

Milestone 3: Vectorization System

Target Completion: [Date]

Implementation of document vectorization and storage capabilities.

Objectives for Milestone 3

• Vector database setup
  • Milvus/Weaviate integration
  • Index configuration
  • Connection management
• Document processing
  • Content chunking
  • Text preprocessing
  • Metadata extraction
• Vector operations
  • OpenAI embeddings integration
  • Batch processing
  • Vector storage optimization
• Search functionality
  • Similarity search implementation
  • Result ranking
  • Search optimization

Milestone 4: LangChain Integration & QA System

Target Completion: [Date]

Integration of LangChain and implementation of question-answering capabilities.

Objectives for Milestone 4

• LangChain setup
  • Framework integration
  • Model configuration
  • Chain management
• QA system implementation
  • Question processing
  • Context management
  • Answer generation
• Response optimization
  • Answer quality improvements
  • Source attribution
  • Confidence scoring
• Conversation handling
  • Multi-turn dialogue support
  • Context preservation
  • History management

Milestone 5: API Enhancement & Performance

Target Completion: [Date]

API refinement and system performance optimization.

Objectives for Milestone 5

• API development
  • RESTful endpoint implementation
  • Authentication/Authorization
  • Rate limiting
• Performance optimization
  • Response time improvement
  • Resource utilization
  • Caching implementation
• Documentation
  • Swagger integration
  • API documentation
  • Usage examples

Milestone 6: Monitoring & Operations

Target Completion: [Date]

Implementation of monitoring and operational capabilities.

Objectives for Milestone 6

• Health monitoring
  • Health check endpoints
  • System metrics collection
  • Alert system
• Operational tools
  • Performance monitoring
  • Log aggregation
  • Trace analysis
• System reliability
  • Graceful shutdown
  • Error recovery
  • Backup systems

Milestone 7: Testing & Documentation

Target Completion: [Date]

Comprehensive testing and documentation implementation.

Objectives for Milestone 7

• Testing implementation
  • Unit tests
  • Integration tests
  • End-to-end tests
• Documentation
  • Technical documentation
  • API guides
  • Code examples
• Quality assurance
  • Code review process
  • Performance testing
  • Security audit

Milestone 8: Deployment & Release

Target Completion: [Date]

System deployment and release preparation.

Objectives for Milestone 8

• Deployment setup
  • Docker configuration
  • CI/CD pipeline
  • Environment configuration
• Release preparation
  • Version management
  • Release documentation
  • Migration guides
• Production readiness
  • Performance verification
  • Security validation
  • Scalability testing

Success Criteria for Milestones

Each milestone will be considered complete when:

1. All objectives have been implemented and tested
2. Documentation has been updated
3. Code review has been completed
4. Tests are passing
5. Stakeholder approval has been obtained

Notes

• Milestone dates should be adjusted based on team capacity and project priorities
• Regular progress reviews will be conducted
• Milestones may be updated as project requirements evolve