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Configuration System Migration - Changelog

Date: December 26, 2025

Summary

Migrated all hardcoded configuration values from palefire-cli.py to a centralized configuration system in config.py. This improves maintainability, flexibility, and follows best practices for production applications.

Changes Made

1. New Files Created

config.py

  • Purpose: Centralized configuration management
  • Features:
    • Loads all settings from environment variables
    • Provides sensible defaults for all values
    • Validates configuration on import
    • Helper functions: get_llm_config(), get_embedder_config(), print_config(), validate_config()
  • Configuration Categories:
    • Neo4j connection settings
    • LLM provider configuration (Ollama/OpenAI)
    • Embedder configuration
    • Search parameters (method, limits, top-k)
    • Ranking weights (connection, temporal, query match, entity type)
    • NER settings
    • Logging configuration
    • Application settings

env.example

  • Purpose: Template for environment variables
  • Contents: All configurable settings with descriptions and defaults
  • Usage: cp env.example .env and customize

CONFIGURATION.md

  • Purpose: Comprehensive configuration documentation
  • Contents:
    • Complete list of all environment variables
    • Configuration functions reference
    • Setup instructions
    • Best practices for production/development/research
    • Troubleshooting guide
    • Advanced configuration topics

CHANGELOG_CONFIG.md

  • Purpose: Document this migration
  • Contents: This file

2. Modified Files

palefire-cli.py

Removed hardcoded values:

  • neo4j_uri = "bolt://10.147.18.253:7687"
  • neo4j_user = "neo4j"
  • neo4j_password = "password"
  • openai_api_key checks
  • llm_config hardcoded parameters
  • embedder hardcoded parameters
  • node_search_config.limit = 20
  • node_search_config.limit = 5
  • connection_weight=0.3 default
  • Method default 'question-aware'

Added:

  • Import of config module
  • Use of config.NEO4J_URI, config.NEO4J_USER, config.NEO4J_PASSWORD
  • Use of config.get_llm_config() and config.get_embedder_config()
  • Use of config.SEARCH_RESULT_LIMIT and config.SEARCH_TOP_K
  • Use of config.WEIGHT_CONNECTION for default weights
  • Use of config.DEFAULT_SEARCH_METHOD
  • Use of config.print_config() for config command
  • Configuration validation via config.validate_config()

Function signature changes:

  • search_episodes_with_custom_ranking(): connection_weight=0.3 → connection_weight=None (uses config.WEIGHT_CONNECTION if None)
  • CLI parser: --method default changed from 'question-aware' to None (uses config.DEFAULT_SEARCH_METHOD if None)

PALEFIRE_SETUP.md

Updated:

  • Configuration section to reference env.example and config.py
  • Added step to view configuration with python palefire-cli.py config
  • Updated environment variable examples
  • Added note about centralized configuration

README.md

Updated:

  • Quick start section to include configuration viewing
  • Configuration section with complete examples
  • Added reference to CONFIGURATION.md
  • Updated .env.example references to env.example

3. Configuration Values Migrated

Neo4j Settings

  • NEO4J_URI (default: bolt://10.147.18.253:7687)
  • NEO4J_USER (default: neo4j)
  • NEO4J_PASSWORD (default: password)

LLM Settings

  • LLM_PROVIDER (default: ollama)
  • OPENAI_API_KEY (required)
  • OLLAMA_BASE_URL (default: http://10.147.18.253:11434/v1)
  • OLLAMA_MODEL (default: deepseek-r1:7b)
  • OLLAMA_SMALL_MODEL (default: deepseek-r1:7b)
  • OLLAMA_API_KEY (default: ollama)
  • OPENAI_BASE_URL (default: None)
  • OPENAI_MODEL (default: gpt-4)
  • OPENAI_SMALL_MODEL (default: gpt-3.5-turbo)

Embedder Settings

  • EMBEDDER_PROVIDER (default: ollama)
  • OLLAMA_EMBEDDING_MODEL (default: nomic-embed-text)
  • OLLAMA_EMBEDDING_DIM (default: 768)
  • OLLAMA_EMBEDDING_BASE_URL (default: http://10.147.18.253:11434/v1)
  • OPENAI_EMBEDDING_MODEL (default: text-embedding-ada-002)
  • OPENAI_EMBEDDING_DIM (default: 1536)

Search Settings

  • DEFAULT_SEARCH_METHOD (default: question-aware)
  • SEARCH_RESULT_LIMIT (default: 20)
  • SEARCH_TOP_K (default: 5)

Ranking Weights

  • WEIGHT_CONNECTION (default: 0.15)
  • WEIGHT_TEMPORAL (default: 0.20)
  • WEIGHT_QUERY_MATCH (default: 0.20)
  • WEIGHT_ENTITY_TYPE (default: 0.15)
  • Semantic weight: calculated as 1.0 - sum(other weights) = 0.30

NER Settings

  • NER_ENABLED (default: true)
  • NER_USE_SPACY (default: true)
  • SPACY_MODEL (default: en_core_web_sm)

Logging Settings

  • LOG_LEVEL (default: INFO)
  • LOG_FORMAT (default: %(asctime)s - %(name)s - %(levelname)s - %(message)s)
  • LOG_DATE_FORMAT (default: %Y-%m-%d %H:%M:%S)

Application Settings

  • EPISODE_NAME_PREFIX (default: Episode)
  • USE_CURRENT_TIME (default: true)

Benefits

1. Maintainability

  • All configuration in one place
  • Easy to find and modify settings
  • Clear separation of code and configuration

2. Flexibility

  • Environment-specific configurations (dev/prod/test)
  • Override any setting via environment variables
  • No code changes needed for deployment

3. Validation

  • Automatic validation on startup
  • Clear error messages for missing/invalid settings
  • Prevents runtime errors due to misconfiguration

4. Documentation

  • Self-documenting via config.py comments
  • Comprehensive CONFIGURATION.md guide
  • Example file (env.example) with all options

5. Best Practices

  • Follows 12-factor app methodology
  • Secrets not hardcoded in source
  • Easy to integrate with deployment tools

Migration Guide

For Existing Users

  1. Copy example configuration:

    cd /path/to/palefire
cp env.example .env

  2. Update .env with your settings:

    nano .env  # or your preferred editor

  3. Verify configuration:

    python palefire-cli.py config

  4. Test with a query:

    python palefire-cli.py query "Test question?"

For New Users

Just follow the Quick Start in README.md - the configuration system is already integrated.

Backward Compatibility

Breaking Changes

  • None for users who set environment variables via .env file
  • Hardcoded values in palefire-cli.py are removed, but defaults in config.py match the previous hardcoded values

Non-Breaking Changes

  • All default values match previous hardcoded values
  • CLI interface unchanged
  • Function signatures backward compatible (optional parameters)

Testing

Verification Steps

  1. ✅ Configuration loads correctly

    python3 -c "import config; config.print_config()"

  2. ✅ Files compile without errors

    python3 -m py_compile palefire-cli.py config.py

  3. ✅ CLI help works

    python palefire-cli.py --help

  4. ✅ Config command works

    python palefire-cli.py config

Test Results

All tests passed successfully:

  • Configuration module loads and validates
  • All files compile without syntax errors
  • CLI commands work as expected
  • Configuration display shows correct values

Future Enhancements

Potential Improvements

  1. Configuration Profiles

    • Support for named profiles (dev, prod, test)
    • Switch between profiles via CLI flag

  2. Runtime Configuration

    • CLI flags to override config values
    • Example: --search-limit 50 --top-k 10

  3. Configuration Validation

    • More sophisticated validation rules
    • Warnings for suboptimal settings

  4. Configuration Export

    • Export current config to file
    • Share configurations between environments

  5. Configuration UI

    • Interactive configuration wizard
    • Web-based configuration editor

References

Credits

Migration performed on December 26, 2025, as part of the Pale Fire project modernization effort.

Support

For issues related to configuration:

  1. Check CONFIGURATION.md for detailed documentation
  2. Verify .env file exists and has correct values
  3. Run python palefire-cli.py config to see current settings
  4. Check logs for configuration validation errors

Configuration System v1.0 - Centralized, Validated, Documented 🎯