.env

# =============================================================================
# Research AI Assistant API - Environment Configuration
# =============================================================================
# Copy this content to a file named .env and fill in your actual values
# Never commit .env to version control!

# =============================================================================
# Novita AI Configuration (REQUIRED)
# =============================================================================
# Get your API key from: https://novita.ai
NOVITA_API_KEY=sk_gaMaeJaUy-qQxms1NIgJuov_RotL_NZXMoQbJlNhS6M


# Dedicated endpoint base URL (default for dedicated endpoints)
NOVITA_BASE_URL=https://api.novita.ai/dedicated/v1/openai

# Your dedicated endpoint model ID
# Format: model-name:endpoint-id
NOVITA_MODEL=deepseek-ai/DeepSeek-R1-Distill-Qwen-7B:de-1a706eeafbf3ebc2

# =============================================================================
# DeepSeek-R1 Optimized Settings
# =============================================================================
# Temperature: 0.5-0.7 range (0.6 recommended for DeepSeek-R1)
DEEPSEEK_R1_TEMPERATURE=0.6

# Force reasoning trigger: Enable to ensure DeepSeek-R1 uses reasoning pattern
# Set to True to add `<think>` prefix for reasoning tasks
DEEPSEEK_R1_FORCE_REASONING=True

# =============================================================================
# Token Allocation Configuration
# =============================================================================
# Maximum tokens dedicated for user input (prioritized over context)
# Recommended: 32000 tokens for DeepSeek R1 (128K context window)
USER_INPUT_MAX_TOKENS=32000

# Maximum tokens for context preparation (includes user input + context)
# Recommended: 115000 tokens for DeepSeek R1 (leaves ~13K for output)
CONTEXT_PREPARATION_BUDGET=115000

# Context pruning threshold (should match context_preparation_budget)
CONTEXT_PRUNING_THRESHOLD=115000

# Always prioritize user input over historical context
PRIORITIZE_USER_INPUT=True

# Model context window (actual limit for your deployed model)
# Default: 128000 tokens for DeepSeek R1 (128K context window)
# This is the maximum total tokens (input + output) the model can handle
# Take full advantage of DeepSeek R1's 128K capability
NOVITA_MODEL_CONTEXT_WINDOW=128000

# =============================================================================
# Database Configuration
# =============================================================================
# SQLite database path (default: sessions.db)
# Use /tmp/ for Docker/containerized environments
DB_PATH=sessions.db

# FAISS index path for embeddings (default: embeddings.faiss)
FAISS_INDEX_PATH=embeddings.faiss

# =============================================================================
# Cache Configuration
# =============================================================================
# HuggingFace cache directory (for any remaining model downloads)
HF_HOME=~/.cache/huggingface
TRANSFORMERS_CACHE=~/.cache/huggingface

# HuggingFace token (optional - only needed if using gated models)
HF_TOKEN=

# Cache TTL in seconds (default: 3600 = 1 hour)
CACHE_TTL=3600

# =============================================================================
# Session Configuration
# =============================================================================
# Session timeout in seconds (default: 3600 = 1 hour)
SESSION_TIMEOUT=3600

# Maximum session size in megabytes (default: 10 MB)
MAX_SESSION_SIZE_MB=10

# =============================================================================
# Performance Configuration
# =============================================================================
# Maximum worker threads for parallel processing (default: 4)
MAX_WORKERS=4

# =============================================================================
# Mobile Optimization
# =============================================================================
# Maximum tokens for mobile responses (default: 1200)
# Increased from 800 to allow better responses on mobile
MOBILE_MAX_TOKENS=1200

# Mobile request timeout in milliseconds (default: 15000)
MOBILE_TIMEOUT=15000

# =============================================================================
# API Configuration
# =============================================================================
# Flask/Gradio server port (default: 7860)
GRADIO_PORT=7860

# Server host (default: 0.0.0.0 for all interfaces)
GRADIO_HOST=0.0.0.0

# =============================================================================
# Logging Configuration
# =============================================================================
# Logging level: DEBUG, INFO, WARNING, ERROR, CRITICAL (default: INFO)
LOG_LEVEL=INFO

# Log format: json or text (default: json)
LOG_FORMAT=json

# Log directory (default: /tmp/logs)
LOG_DIR=/tmp/logs

# =============================================================================
# Context Configuration
# =============================================================================
# Maximum context tokens (default: 4000)
# Note: This is overridden by CONTEXT_PREPARATION_BUDGET if set
MAX_CONTEXT_TOKENS=4000

# Cache TTL for context in seconds (default: 300 = 5 minutes)
CACHE_TTL_SECONDS=300

# Maximum cache size (default: 100)
MAX_CACHE_SIZE=100

# Enable parallel processing (default: True)
PARALLEL_PROCESSING=True

# Context decay factor (default: 0.8)
CONTEXT_DECAY_FACTOR=0.8

# Maximum interactions to keep in context (default: 10)
MAX_INTERACTIONS_TO_KEEP=10

# Enable metrics collection (default: True)
ENABLE_METRICS=True

# Enable context compression (default: True)
COMPRESSION_ENABLED=True

# Summarization threshold in tokens (default: 2000)
SUMMARIZATION_THRESHOLD=2000

# =============================================================================
# Model Selection (for context operations - if still using local models)
# =============================================================================
# These are optional and only used if local models are still needed
# for context summarization or other operations
CONTEXT_SUMMARIZATION_MODEL=Qwen/Qwen2.5-7B-Instruct
CONTEXT_INTENT_MODEL=Qwen/Qwen2.5-7B-Instruct
CONTEXT_SYNTHESIS_MODEL=Qwen/Qwen2.5-7B-Instruct

# =============================================================================
# Security Notes
# =============================================================================
# - Never commit .env file to version control
# - Keep API keys secret and rotate them regularly
# - Use environment variables in production (not .env files)
# - Set proper file permissions: chmod 600 .env