open-notebook/docs/6-TROUBLESHOOTING/ai-chat-issues.md
Luis Novo 47c513edfd
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fix: improve error logging for chat model configuration issues (#458)
* docs: update CHANGELOG for v1.6.0 release

* fix: improve error logging for chat model configuration issues (#358)

- Add detailed error logging in provision.py when model lookup fails
- Add warning logging in models.py when default model is not configured
- Add traceback logging in chat router exception handler
- Update Ollama docs with model name configuration guidance
- Update troubleshooting docs with "Failed to send message" solutions
- Bump version to 1.6.1

* chore: uvlock
2026-01-23 16:45:13 -03:00

8.9 KiB

AI & Chat Issues - Model Configuration & Quality

Problems with AI models, chat, and response quality.


"Failed to send message" Error

Symptom: Chat shows "Failed to send message" toast. Logs show:

Error executing chat: Model is not a LanguageModel: None

Cause: No valid language model configured for chat

Solutions:

Solution 1: Check Default Model Configuration

1. Go to Settings → Models
2. Scroll to "Default Models" section
3. Verify "Default Chat Model" has a model selected
4. If empty, select an available language model
5. Click Save

Solution 2: Verify Model Names (Ollama Users)

# Get exact model names
ollama list

# Example output:
# NAME                   SIZE      MODIFIED
# gemma3:12b            8.1 GB    2 months ago

# The model name in Open Notebook must be EXACTLY "gemma3:12b"
# NOT "gemma3" or "gemma3-12b"

Solution 3: Re-add Missing Models

1. Note the exact model names from your provider
2. Go to Settings → Models
3. Delete any misconfigured models
4. Add models with exact names
5. Set new defaults

Solution 4: Check Model Still Exists

# For Ollama: verify model is installed
ollama list

# For cloud providers: verify API key is valid
# and you have access to the model

Tip: This error often occurs when you delete a model from Ollama but forget to update the default models in Open Notebook. Always re-configure defaults after removing models.


"Models not available" or "Models not showing"

Symptom: Settings → Models shows empty, or "No models configured"

Cause: Missing or invalid API key

Solutions:

Solution 1: Add API Key

# Check .env has your API key:
cat .env | grep -i "OPENAI\|ANTHROPIC\|GOOGLE"

# Should see something like:
# OPENAI_API_KEY=sk-proj-...

# If missing, add it:
OPENAI_API_KEY=sk-proj-your-key-here

# Save and restart:
docker compose restart api

# Wait 10 seconds, then refresh browser

Solution 2: Check Key is Valid

# Test API key directly:
curl https://api.openai.com/v1/models \
  -H "Authorization: Bearer sk-proj-..."

# Should return list of models
# If error: key is invalid

Solution 3: Switch Provider

# Try a different provider:
# Remove: OPENAI_API_KEY
# Add: ANTHROPIC_API_KEY=sk-ant-...

# Restart and check Settings → Models

"Invalid API key" or "Unauthorized"

Symptom: Error when trying to chat: "Invalid API key"

Cause: API key wrong, expired, or revoked

Solutions:

Step 1: Verify Key Format

# OpenAI: Should start with sk-proj-
# Anthropic: Should start with sk-ant-
# Google: Should be AIzaSy...

# Check in .env:
cat .env | grep OPENAI_API_KEY

Step 2: Get Fresh Key

# Go to provider's dashboard:
# - OpenAI: https://platform.openai.com/api-keys
# - Anthropic: https://console.anthropic.com/
# - Google: https://aistudio.google.com/app/apikey

# Generate new key
# Copy exactly (no extra spaces)

Step 3: Update .env

# Edit .env:
OPENAI_API_KEY=sk-proj-new-key-here
# No quotes needed, no spaces

# Save and restart:
docker compose restart api

Step 4: Verify in UI

1. Open Open Notebook
2. Go to Settings → Models
3. Select your provider
4. Should show available models

Chat Returns Generic/Bad Responses

Symptom: AI responses are shallow, generic, or wrong

Cause: Bad context, vague question, or wrong model

Solutions:

Solution 1: Check Context

1. In Chat, click "Select Sources"
2. Verify sources you want are CHECKED
3. Set them to "Full Content" (not "Summary Only")
4. Click "Save"
5. Try chat again

Solution 2: Ask Better Question

Bad:     "What do you think?"
Good:    "Based on the paper's methodology, what are 3 limitations?"

Bad:     "Tell me about X"
Good:    "Summarize X in 3 bullet points with page citations"

Solution 3: Use Stronger Model

OpenAI:
  Current: gpt-4o-mini → Switch to: gpt-4o

Anthropic:
  Current: claude-3-5-haiku → Switch to: claude-3-5-sonnet

To change:
1. Settings → Models
2. Select model
3. Try chat again

Solution 4: Add More Sources

If:  "Response seems incomplete"
Try: Add more relevant sources to provide context

Chat is Very Slow

Symptom: Chat responses take minutes

Cause: Large context, slow model, or overloaded API

Solutions:

Solution 1: Use Faster Model

Fastest: Groq (any model)
Fast: OpenAI gpt-4o-mini
Medium: Anthropic claude-3-5-haiku
Slow: Anthropic claude-3-5-sonnet

Switch in: Settings → Models

Solution 2: Reduce Context

1. Chat → Select Sources
2. Uncheck sources you don't need
3. Or switch to "Summary Only" for background sources
4. Save and try again

Solution 3: Increase Timeout

# In .env:
API_CLIENT_TIMEOUT=600  # 10 minutes

# Restart:
docker compose restart

Solution 4: Check System Load

# See if API is overloaded:
docker stats

# If CPU >80% or memory >90%:
# Reduce: SURREAL_COMMANDS_MAX_TASKS=2
# Restart: docker compose restart

Chat Doesn't Remember History

Symptom: Each message treated as separate, no context between questions

Cause: Chat history not saved or new chat started

Solution:

1. Make sure you're in same Chat (not new Chat)
2. Check Chat title at top
3. If it's blank, start new Chat with a title
4. Each named Chat keeps its history
5. If you start new Chat, history is separate

"Rate limit exceeded"

Symptom: Error: "Rate limit exceeded" or "Too many requests"

Cause: Hit provider's API rate limit

Solutions:

For Cloud Providers (OpenAI, Anthropic, etc.)

Immediate:

  • Wait 1-2 minutes
  • Try again

Short term:

  • Use cheaper/smaller model
  • Reduce concurrent operations
  • Space out requests

Long term:

  • Upgrade your account
  • Switch to different provider
  • Use Ollama (local, no limits)

Check Account Status

OpenAI: https://platform.openai.com/account/usage/overview
Anthropic: https://console.anthropic.com/account/billing/overview
Google: Google Cloud Console

For Ollama (Local)

  • No rate limits
  • Use ollama pull mistral for best model
  • Restart if hitting resource limits

"Context length exceeded" or "Token limit"

Symptom: Error about too many tokens

Cause: Sources too large for model

Solutions:

Solution 1: Use Model with Longer Context

Current: GPT-4o (128K tokens) → Switch to: Claude (200K tokens)
Current: Claude Haiku (200K) → Switch to: Gemini (1M tokens)

To change: Settings → Models

Solution 2: Reduce Context

1. Select fewer sources
2. Or use "Summary Only" instead of "Full Content"
3. Or split large documents into smaller pieces

Solution 3: For Ollama (Local)

# Use smaller model:
ollama pull phi  # Very small
# Instead of: ollama pull neural-chat  # Large

"API call failed" or Timeout

Symptom: Generic API error, response times out

Cause: Provider API down, network issue, or slow service

Solutions:

Check Provider Status

OpenAI: https://status.openai.com/
Anthropic: Check website
Google: Google Cloud Status
Groq: Check website

Retry Operation

1. Wait 30 seconds
2. Try again

Use Different Model/Provider

1. Settings → Models
2. Try different provider
3. If OpenAI down, use Anthropic

Check Network

# Verify internet working:
ping google.com

# Test API endpoint directly:
curl https://api.openai.com/v1/models \
  -H "Authorization: Bearer YOUR_KEY"

Responses Include Hallucinations

Symptom: AI makes up facts that aren't in sources

Cause: Sources not in context, or model guessing

Solutions:

Solution 1: Verify Context

1. Click citation in response
2. Check source actually says that
3. If not, sources weren't in context
4. Add source to context and try again

Solution 2: Request Citations

Ask: "Answer this with citations to specific pages"

The AI will be more careful if asked for citations

Solution 3: Use Stronger Model

Weaker models hallucinate more
Switch to: GPT-4o or Claude Sonnet

High API Costs

Symptom: API bills are higher than expected

Cause: Using expensive model, large context, many requests

Solutions:

Use Cheaper Model

Expensive: gpt-4o
Cheaper: gpt-4o-mini (10x cheaper)

Expensive: Claude Sonnet
Cheaper: Claude Haiku (5x cheaper)

Groq: Ultra cheap but fewer models

Reduce Context

In Chat:
1. Select fewer sources
2. Use "Summary Only" for background
3. Ask more specific questions

Switch to Ollama (Free)

# Install Ollama
# Run: ollama serve
# Download: ollama pull mistral
# Set: OLLAMA_API_BASE=http://localhost:11434
# Cost: Free!

Still Having Chat Issues?