# Step 1: Check if API is running
docker ps | grep api

# Step 2: Verify port 5055 is accessible
curl http://localhost:5055/health

# Expected output: {"status":"ok"}

# If that doesn't work:
# Step 3: Restart services
docker compose restart

# Step 4: Try again
# Open http://localhost:8502 in browser

1. Go to Settings → API Keys
2. If no credential exists, click "Add Credential" and add one
3. If a credential exists, click "Test Connection"
4. If test fails, delete and re-create with correct key
5. After test passes, click "Discover Models" → "Register Models"
6. Go to Settings → Models to verify models appear

# Option 1: Stop the other service
# Find what's using port 8502
lsof -i :8502
# Kill it or close the app

# Option 2: Use different port
# Edit docker-compose.yml
# Change: - "8502:8502"
# To:     - "8503:8502"

# Then restart
docker compose restart
# Access at: http://localhost:8503

# Check if file format is supported:
# ✓ PDF, DOCX, PPTX, XLSX (documents)
# ✓ MP3, WAV, M4A (audio)
# ✓ MP4, AVI, MOV (video)
# ✓ URLs/web links

# ✗ Pure images (.jpg without OCR)
# ✗ Files > 100MB

# Try these:
# - Convert to PDF if possible
# - Split large files
# - Try uploading again

# Step 1: Check which model you're using
# Settings → Models
# Note the model name

# Step 2: Try a cheaper/faster model
# OpenAI: Switch to gpt-4o-mini (10x cheaper, slightly faster)
# Anthropic: Switch to claude-3-5-haiku (fastest)
# Groq: Use any model (ultra-fast)

# Step 3: Reduce context
# Chat: Select fewer sources
# Use "Summary Only" instead of "Full Content"

# Step 4: Check if API is overloaded
docker stats
# Look at CPU/memory usage

# Step 1: Make sure sources are in context
# Click "Select Sources" in Chat
# Verify relevant sources are checked and set to "Full Content"

# Step 2: Ask a specific question
# Bad: "What do you think?"
# Good: "Based on the paper's methodology section, what are the 3 main limitations?"

# Step 3: Try a more powerful model
# OpenAI: Use gpt-4o (better reasoning)
# Anthropic: Use claude-3-5-sonnet (best reasoning)

# Step 4: Check citations
# Click citations to verify AI actually saw those sources

# Try a different search type:

# If you searched with KEYWORDS:
# Try VECTOR SEARCH instead
# (Concept-based, not keyword-based)

# If you searched for CONCEPTS:
# Try TEXT SEARCH instead
# (Look for specific words in your query)

# Try simpler search:
# Instead of: "How do transformers work in neural networks?"
# Try: "transformers" or "neural networks"

# Check sources are processed:
# Go to notebook
# All sources should show green "Ready" status

# Step 1: Make sure you have content
# Select at least 1-2 sources
# Avoid single-sentence sources

# Step 2: Try again
# Sometimes it's a temporary API issue
# Wait 30 seconds and retry

# Step 3: Check your TTS provider has quota
# OpenAI: Check account has credits
# ElevenLabs: Check monthly quota
# Google: Check API quota

# Step 4: Try different TTS provider
# In podcast generation, choose "Google" or "Local"
# instead of "ElevenLabs"

# Step 1: Check logs
docker compose logs

# Step 2: Try restart
docker compose restart

# Step 3: If that fails, rebuild
docker compose down
docker compose up --build

# Step 4: Check disk space
df -h
# Need at least 5GB free

# Step 5: Check Docker has enough memory
# Docker settings → Resources → Memory: 4GB+

# In .env, reduce concurrency:
SURREAL_COMMANDS_MAX_TASKS=2

# Then restart:
docker compose restart

# This makes it slower but more stable

# In docker-compose.yml environment:
environment:
  - UV_HTTP_TIMEOUT=600  # 10 minutes (default is 30s)

environment:
  - UV_HTTP_TIMEOUT=600
  - UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
  - PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple

docker compose down -v
docker compose up --build

# Backup your .env first!
cp .env .env.backup

# Reset to example
cp .env.example .env

# Edit with your API keys
# Restart
docker compose up