inquid-gpt/.env.example at main · inquid/inquid-gpt · GitHub

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APP_NAME=Laravel
APP_ENV=local
APP_KEY=
APP_DEBUG=true
APP_URL=http://localhost

APP_LOCALE=en
APP_FALLBACK_LOCALE=en
APP_FAKER_LOCALE=en_US

APP_MAINTENANCE_DRIVER=file
# APP_MAINTENANCE_STORE=database

# PHP_CLI_SERVER_WORKERS=4

BCRYPT_ROUNDS=12

LOG_CHANNEL=stack
LOG_STACK=single
LOG_DEPRECATIONS_CHANNEL=null
LOG_LEVEL=debug

DB_CONNECTION=sqlite
# DB_HOST=127.0.0.1
# DB_PORT=3306
# DB_DATABASE=laravel
# DB_USERNAME=root
# DB_PASSWORD=

SESSION_DRIVER=database
SESSION_LIFETIME=120
SESSION_ENCRYPT=false
SESSION_PATH=/
SESSION_DOMAIN=null

BROADCAST_CONNECTION=log
FILESYSTEM_DISK=local
QUEUE_CONNECTION=database

CACHE_STORE=database
# CACHE_PREFIX=

MEMCACHED_HOST=127.0.0.1

REDIS_CLIENT=phpredis
REDIS_HOST=127.0.0.1
REDIS_PASSWORD=null
REDIS_PORT=6379

MAIL_MAILER=log
MAIL_SCHEME=null
MAIL_HOST=127.0.0.1
MAIL_PORT=2525
MAIL_USERNAME=null
MAIL_PASSWORD=null
MAIL_FROM_ADDRESS="hello@example.com"
MAIL_FROM_NAME="${APP_NAME}"

AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_DEFAULT_REGION=us-east-1
AWS_BUCKET=
AWS_USE_PATH_STYLE_ENDPOINT=false

VITE_APP_NAME="${APP_NAME}"

# ============================================================================
# Ollama Configuration
# ============================================================================
# Local LLM API settings for code Q&A and embeddings
#
# Setup Instructions:
# 1. Install Ollama from https://ollama.ai
# 2. Pull required models:
#    - ollama pull gemma3:4b (or your preferred chat model)
#    - ollama pull nomic-embed-text (required for embeddings)
# 3. Ensure Ollama is running: ollama serve
# ============================================================================

# Ollama API URL (default: http://127.0.0.1:11434)
OLLAMA_URL=http://127.0.0.1:11434

# Connection timeout in seconds for API requests
OLLAMA_CONNECTION_TIMEOUT=300

# Default system prompt for general Ollama interactions
OLLAMA_DEFAULT_PROMPT="You are a senior Laravel/PHP assistant."

# Chat/completion model for answering questions
# Options: gemma3:4b, llama3:8b, codellama:7b, mistral:7b, etc.
OLLAMA_MODEL=gemma3:4b

# Embedding model for code indexing (MUST be consistent!)
# WARNING: Changing this after indexing will break queries
# Recommended: nomic-embed-text (384 dimensions, fast)
OLLAMA_EMBED_MODEL=nomic-embed-text

# ============================================================================
# Code Q&A Configuration
# ============================================================================
# Fine-tune the code indexing and question-answering behavior
# ============================================================================

# Number of top similar code chunks to retrieve as context
OLLAMA_CODE_QA_TOP_K=8

# Temperature for code Q&A responses (0.0-1.0, lower = more focused)
OLLAMA_CODE_QA_TEMPERATURE=0.2

# System prompt for code Q&A (optional override)
# OLLAMA_CODE_QA_PROMPT="You are a senior Laravel/PHP assistant. Answer ONLY using the provided code context when relevant. If something is not in the context, say you are not sure."