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Complete Local Development Setup and Critical Fixes#32

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aaron-seq merged 3 commits intomainfrom
fix/comprehensive-local-setup-and-deployment
Feb 10, 2026
Merged

Complete Local Development Setup and Critical Fixes#32
aaron-seq merged 3 commits intomainfrom
fix/comprehensive-local-setup-and-deployment

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@aaron-seq aaron-seq commented Feb 7, 2026

Summary

This PR provides a comprehensive solution for local development setup and resolves multiple critical issues blocking deployment and local testing.

Issues Resolved

Fully Resolved

Partial Resolution

Changes Made

1. Configuration Files Added

Redis Configuration (config/redis.conf)

  • Production-ready Redis settings with security optimizations
  • Append-only file (AOF) persistence enabled
  • Memory management with LRU eviction policy (256MB limit)
  • Optimized for Docker container deployment
  • Security settings ready for production hardening

PostgreSQL Schema (database/init/01_init_schema.sql)

  • Complete database schema with all required tables
  • Proper indexes for performance optimization
  • Foreign key constraints and data integrity rules
  • Custom types for lead classification and processing status
  • Automated triggers for timestamp updates
  • Sample data for testing
  • Full-text search capabilities

Tables created:

  • audio_files: Audio file metadata
  • analysis_results: Complete analysis data
  • lead_scoring_details: Detailed lead scoring
  • processing_logs: System logs
  • user_sessions: Session management

Environment Template (.env.example)

  • Complete list of all required environment variables
  • Clear documentation for each setting
  • Separate configurations for development and production
  • AWS, database, Redis, and ML model settings
  • Security and monitoring options
  • Docker-specific configurations

ML Model Installation Script (backend/scripts/install_models.py)

  • Automated spaCy model download and installation
  • Fallback to smaller models if primary fails
  • Verification mode to check installation
  • Force reinstall option
  • Clear error messages and logging
  • Command-line interface for flexibility

Usage:

python scripts/install_models.py              # Install all models
python scripts/install_models.py --verify      # Check installation
python scripts/install_models.py --force       # Force reinstall

2. Backend Improvements (backend/main.py)

Pagination Boundary Validation

Before (Issue #28):

# No validation - silently returns empty results for out-of-bounds pages
start_index = (page_number - 1) * items_per_page
end_index = start_index + items_per_page
page_files = analysis_files[start_index:end_index]

After:

# Validate page number is within bounds
if page_number < 1:
    raise HTTPException(
        status_code=status.HTTP_400_BAD_REQUEST,
        detail="Page number must be greater than or equal to 1"
    )

if total_page_count > 0 and page_number > total_page_count:
    raise HTTPException(
        status_code=status.HTTP_400_BAD_REQUEST,
        detail=f"Page {page_number} is out of bounds. Valid range: 1-{total_page_count}"
    )

Benefits:

  • Clear error messages indicating valid page range
  • HTTP 400 status for client errors
  • Prevents silent failures and confusion
  • Improves API usability

AWS S3 Exception Handling

Before (Issues #22, #25):

except aws_connector.s3_client.exceptions.NoSuchKey:
    # This fails because s3_client doesn't have 'exceptions' attribute
    raise HTTPException(...)

After:

from botocore.exceptions import ClientError

except ClientError as e:
    error_code = e.response.get('Error', {}).get('Code', '')
    if error_code == 'NoSuchKey':
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail=f"Analysis results for '{file_name}' not found"
        )
    elif error_code == 'AccessDenied':
        raise HTTPException(
            status_code=status.HTTP_403_FORBIDDEN,
            detail="Access denied to analysis file"
        )

Benefits:

  • Proper exception handling using botocore.exceptions
  • Differentiated error responses (404, 403, 500)
  • Better error messages for debugging
  • Follows AWS SDK best practices

3. Comprehensive Setup Guide (SETUP_GUIDE.md)

Added detailed documentation covering:

Setup Options

  • Docker Compose (recommended)
  • Manual setup with native services
  • Step-by-step instructions for both approaches

Configuration

  • Environment variable explanations
  • AWS setup (with disable option for local dev)
  • Database configuration
  • Redis setup
  • ML model installation

Troubleshooting

  • Common issues and solutions
  • Docker problems
  • Database connectivity
  • Redis connection issues
  • ML model errors
  • AWS credential problems
  • Debug mode instructions

Production Deployment

  • Pre-deployment checklist
  • Security configuration
  • Cloud platform guides
  • SSL setup
  • Monitoring recommendations

Technical Implementation Details

Database Schema Highlights

-- Custom enums for type safety
CREATE TYPE lead_classification AS ENUM ('Hot', 'Warm', 'Cold', 'Unknown');
CREATE TYPE processing_status AS ENUM ('pending', 'processing', 'completed', 'failed');

-- Automated timestamp management
CREATE TRIGGER update_analysis_results_updated_at
    BEFORE UPDATE ON analysis_results
    FOR EACH ROW
    EXECUTE FUNCTION update_updated_at_column();

-- Full-text search
CREATE INDEX idx_analysis_results_transcript_fts 
    ON analysis_results USING gin(to_tsvector('english', transcript_text));

Redis Configuration Highlights

# Persistence
appendonly yes
appendfsync everysec

# Memory management
maxmemory 256mb
maxmemory-policy allkeys-lru

# Performance
io-threads 4
auto-aof-rewrite-percentage 100

Testing Performed

Configuration Files

  • Validated Redis config syntax
  • Tested PostgreSQL schema execution
  • Verified all environment variables are documented

Backend Changes

  • Pagination validation returns correct HTTP status codes
  • AWS exception handling works with proper error codes
  • Testing mode bypasses AWS requirements successfully

Documentation

  • All setup steps verified for accuracy
  • Commands tested for correctness
  • Troubleshooting steps validated

Local Development Quick Start

# 1. Clone and navigate
git clone https://github.com/aaron-seq/ML-voice-lead-analysis.git
cd ML-voice-lead-analysis

# 2. Configure environment
cp .env.example .env
# Edit .env and set DISABLE_AWS_CHECKS=true for local dev

# 3. Start services
docker-compose up --build

# 4. Access application
# Frontend: http://localhost:3000
# Backend: http://localhost:8000
# API Docs: http://localhost:8000/v1/docs

Breaking Changes

None. All changes are additive or fix existing bugs.

Migration Notes

For existing deployments:

  1. Copy .env.example to .env and configure
  2. Run database initialization script: 
    psql -U voice_user -d voice_analysis -f database/init/01_init_schema.sql
  3. Restart services to pick up new configuration

Dependencies

No new dependencies added. All requirements already in requirements.txt:

  • boto3: Already included for AWS
  • botocore: Included as boto3 dependency
  • spacy: Already included for NLP

Remaining Work

This PR does not address:

These are tracked in their respective issues and will be addressed in future PRs.

Checklist

  • Configuration files added and tested
  • Database schema complete with indexes
  • Environment variables documented
  • ML model installation script created
  • Pagination validation implemented
  • AWS exception handling fixed
  • Comprehensive setup guide written
  • All changes follow project conventions
  • No breaking changes introduced
  • Documentation is clear and complete

Related Issues

Screenshots

N/A - Backend and configuration changes only.

Additional Context

This PR is critical for enabling:

  1. Local development without AWS dependencies
  2. Proper testing in CI/CD pipelines
  3. Production deployment with complete configuration
  4. Developer onboarding with clear documentation

The changes are production-ready and follow best practices for:

  • Security (proper exception handling, validation)
  • Performance (database indexes, Redis optimization)
  • Maintainability (clear documentation, automated scripts)
  • Scalability (proper schema design, efficient queries)

@aaron-seq
feat: add comprehensive local development configuration files
206df30 
- Add Redis configuration file with production-ready settings
- Add PostgreSQL initialization script with database schema
- Add .env.example with all required environment variables
- Add backend post-install script for spaCy model download
- Fix pagination boundary validation in main.py
- Add comprehensive documentation

Resolves: #10, #20, #21, #28
Partial resolution for: #11, #17
@aaron-seq
fix: add pagination boundary validation and improve error handling
b1a578f 
- Add pagination boundary validation to prevent out-of-bounds requests
- Return 400 Bad Request for invalid page numbers with clear error messages
- Improve AWS S3 exception handling with proper error code checking
- Add comprehensive setup guide documentation
- Add requirements clarification comment about spaCy models

Fixes: #28
Related to: #22, #25
@aaron-seq
Merge branch 'main' into fix/comprehensive-local-setup-and-deployment
72eab74
@aaron-seq aaron-seq merged commit 61f64bc into main Feb 10, 2026
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